The Evolution Of Supply Chain Management Business Essay - Free Essay Example

Sample details Pages: 10 Words: 2889 Downloads: 2 Date added: 2017/06/26 Category Business Essay Type Analytical essay Did you like this example? Despite the increased attention paid to supply chain management in recent years, including university courses solely devoted to the topic, it is not a new business discipline. Supply chain management is as old as trade itself. We view the purpose of supply chain operations as getting the right resources and products to the right places at the right times, while yielding the highest possible profits. Don’t waste time! Our writers will create an original "The Evolution Of Supply Chain Management Business Essay" essay for you Create order The evolution of supply chain management practices can be partitioned into four periods: the industrial revolution (1776-1900), the mass production era (1901-1974), the lean production/quality control era (1975-1995), and the mass customization era (1996-2010). During the industrial revolution, many businesses arose from the division and specialization of labor and from expanded markets and opportunities arising from the development of electricity, railroads, transportation, and communications. In the mass production era, businesses adopted and utilized capital equipment to improve production operations, focusing their efforts on defining and improving specialized tasks through the methods of scientific management, operations research techniques, and mass-production moving assembly lines. In the lean production/quality control era, businesses focused on improving internal processes, particularly by monitoring production methods and implementing lean production ideas such as just-in-t ime inventory systems, total quality management (TQM) programs, and enterprise resource planning (ERP) systems. Finally, during the mass customization era, firms began to develop and implement e-business technologies, such as the Internet and e-commerce systems, and started to improve service and delivery processes by integrating internal systems with external partners. While earlier supply chain operations improvements centered mostly on internal processes, more recent enhancements are on production and distribution channels. Improved inventory management, streamlined logistics systems, and various information-sharing technologies such as global position satellites (GPS), radio freqency identification devices (RFID), the Internet, and other wireless telecommunications platforms all greatly improved supply chain operations. In the mass customization era, information replaces inventory. The collection, analysis, and distribution of information through improved e-business technologies have become more accurate and far less expensive. As a result, lower inventory levels can be maintained throughout the supply chain, while still allowing producers and suppliers to meet anticipated demand. Some authors have identified these improvements and proclaimed a New Economy (Shapiro and Varian, 1999; Baily, 2001; and DeLong and Summers, 2001), where the old rules no longer apply and where productivity advancements brought on by new e-business information technologies have permanently changed the way goods and services are delivered. We agree with this assessment. The New Economy, which is perhaps more accurately termed the Real-Time Economy, allows firms to make better decisions as information flow can be separated from the product flow, thereby enabling better real-time analysis of business conditions. The Impact of E-Business Technologies on Operations of Supply Chain In order to analyze the impact of e-business technologies on supply chain operations, we break down the supply chain into three distinct components: the business channel, the transportation/distribution channel, and the payments channel. All three channels have been transformed and have become more tightly interconnected by e-business technologies that bring more accurate information to decision-makers in real time. Information can be stripped from products/services and analyzed separately to make better decisions regarding production, distribution, marketing, sales, etc. The business channel of supply chain operations concerns what goods or services a business should focus on producing and at what levels. This involves knowing your customer and satisfying their needs and desires. Information needed to make these decisions comes from the market as it sends out its many signals. Producing this information entails consumer and market research, and is often very data intensive to most accurately understand changing preferences, tastes, styles, etc. The transportation/distribution channel of supply chain operations addresses what is the best way to move products to customers, essentially answering the question, How goods and services should be moved and stored? This involves understanding the entire supply chain, from the raw materials to the end consumer, and then taking advantage of the most efficient and effective logistics and inventory systems. Again, information at all points along the supply chain can be integrated using new e-business technologies, enabling better decisions regarding necessary inventory levels and efficient movement of products. The payments channel of supply chains pertain to the best way to move money in exchange for delivered goods and services. The essential question addressed here is, How (and when) suppliers should be paid? Knowing and understanding the supply chain operations of all the firms involved is crucial to making the payme nts system flow smoothly and accurately. ERP systems that communicate and share information in real time can lead to competitive advantages. All three of these channels have been transformed by new e-business technologies. The effective implementation of new information technologies allows firms to quickly collect and analyze important information throughout the supply chain, including monitoring demand in real-time. In short, information flows within and between businesses can be reorganized through e-business technologies, resulting in better and more timely decisions across all channels of the supply chain (Lee and Wang, 2001). Information is Everything The supply chain is pervaded by the need to gather and analyze important information. Firms must spend time and resources to find and acquire suppliers, to enforce contracts, to maintain appropriate inventory levels, to transport products to the next production process, and to attract and retain customers, among many other activities. All of these activities entail obtaining information that can be made available in real time thorough the Internet and other e-business technologies. If easier information availability results in better management of the supply chain, then we can detect noticeable improvements at various points along the supply chain. We empirically examine several time series indicators to see if such improvements have arisen. First, with respect to demand management, real-time monitoring of sales should help producers more closely match production output with sales. Second, average inventory levels should remain lower as e-business systems help move the right things to the right places at the right times. Third, logistical costs as a percentage of total output should be lower as goods are shipped more efficiently through the supply chain. And finally, procurement costs should be lower as firms utilize e-business systems to eliminate paperwork and streamline payments. Production and Sales Volatility With almost real-time monitoring of sales, shipments, quality and output, along with more reliable performance measures of lead times, forecast errors, etc., we expect less volatility in output when utilizing e-business systems. Information that can be shared along all points of the supply chain allows decision makers to better manage their specialized tasks. Without being able to share this information quickly and accurately, information distortions often compound when traveling further up the supply chain from customers to suppliers. Chart 1 shows the 10-year moving average of the volatility of durable goods production growth and the 10-year moving average of the volatility of durable goods sales growth. Ten-year sales growth volatility averaged about 8 percent during the 1960s, gradually rising to an average of around 12 percent during the 1970s and 1980s, and then fell back to the 8 percent range in the 1990s. In contrast, 10-year production growth volatility averaged between a bout 15 and 18 percent during the 1960s, 70s and 80s, but then fell sharply during the 1990s, finally settling in near an average 8 percent in the mid-1990s. This dramatic improvement in production growth volatility occurred as improved manufacturing and quality control processes and e-business technologies brought significant improvements to supply chain operations. Indeed, information distortions in supply chains today appear to be far less of a problem. The traditional bullwhip effect, where information distortions accumulate and compound as one travels further up the supply chain (Lee, 1997), appears to have been tamed. In more recent years, the marriage of better production and logistics methodologies with e-business technologies that supply real-time information to all points along the supply chain is plausibly at least partly responsible for the improvement. Inventory Unused and unsold inventory can carry burdensome costs. There are holding costs, including warehouse and production-line storage costs, insurance costs, and costs due to obsolescence and spoilage. At the same time, however, sufficient inventory must be maintained to meet demand and keep the production operations flowing as smoothly and efficiently as possible. Better information about product demand, potential bottlenecks, change orders, and the like should allow less inventory to be needed throughout the supply chain, thereby increasing returns to shareholders as these costs are minimized and yet, at the same time, product orders are fulfilled. In essence, e-business technologies should allow firms to replace inventory with information and then use the information more productively. peaked at the start of the recession and did not grow worse. Again, better and more timely information helps to explain this change in cyclic inventory levels. It appears that during the 2001 recess ion, producers of durable goods had better foresight of demand prior to the beginning of the downturn and took the necessary steps earlier in the business cycle to ensure that inventory levels did not get too high. Additional evidence that firms have managed inventories better is provided by Koenig, Siems, and Wynne (2002), who follow the work of Mr. McConnell and Mr. Perez-Quiros. Examining time series data from 1959 to 2001, the authors find that GDP growth volatility is about half as volatile in the post-1983 period and that 41 percent of the reduction was from inventory investment. While cause and effect are difficult to disentangle, new e-business technologies and better business practices in the supply chain have plausibly contributed to the economys increased stability. Logistics Improved supply chain operations should also result in lower relative logistics costs. Just about everything that is consumed is taken from one place and transported to another. For tangible goods, this movement often involves freight transportation of some kind as raw materials are pulled from the ground, sent to facilities that convert and transform the materials into useable goods, which are then delivered as final goods to consumers. In the past, these logistics systems focused on stored inventory. That is, the goal was to get goods shipped from point A to point B, and there was an expectation that inventory would need to be stored at each delivery endpoint. But now, with e-business technologies that manage information flow separately from the flow of goods by connecting critical points along the supply chain, logistics are focused more on managing in-transit inventory. In other words, now the goal is to get the right goods shipped to the right places at just the right times , without storing much inventory at intermediate stages. As a result, the role of transportation providers is changing. Today, the transportation of goods often involves great distances and requires careful coordination. According to Wilson (2004), business logistics costs in the United States were $936 billion in 2003, roughly 8.5 percent of GDP. Chart 3 shows that reengineering logistics systems to be more efficient is a worthwhile effort. Logistics costs as a percentage of GDP has fallen steadily from 14.5 percent in 1982, with the percentage devoted to both transportation costs and inventory carrying costs contributing to the improvement. Transportation costs have declined by 20 percent since 1982 and inventory carrying costs have declined by an even more impressive 60 percent. Wilson (2004) concludes that logistics costs have declined primarily because inventories are managed more efficiently, warehousing expenses have been reduced, and risks have been minimized. 3PLs that furn ish specialized and customized end-to-end solutions are becoming more common and are better able to respond to shifts and changes in our global economy. In short, this sort of specialization and trade helps make industry supply chains more efficient because these specialists can provide expertise, reach, reliability and flexibility. This is consistent with Gupta and Basu (1989) who argue that IT-induced reductions in transactions costs will motivate companies to parcel out or outsource, many economic activities currently done within firms. Procurement As technology costs continue to fall and electronic connections between companies increase, more firms are adopting digital technologies and eliminating paper transactions and human contact. Automatic order placement, billing, and payment can all be triggered and performed by a computer without requiring human intervention and/or a trail of paperwork. And such electronic transactions can now be accomplished faster and cheaper, thereby enhancing the efficiency of the supply chain.All of these improvements in the supply chain production volatility, inventory, logistics, and procurement have this common characteristic: they use better methodologies and new e-business technologies to use information more efficiently and effectively. Improved information management and better information engineering help lower transactions costs, whether in procurement, production, logistics, or inventory. The bottom line is that new information technologies make more and better information available in real-time at lower costs to those who need it. And the end result is that consumers benefit from lower prices, higher quality products and services, and an improved variety and selection of goods. Macroeconomic Evidence One place where we can identify macroeconomic benefits from the impact of new e-business technologies on supply chain operations is on prices. In a competitive economic environment, supply chain improvements should help lower prices by reducing production volatility, inventory levels, and logistics costs, and by introducing more efficient procurement methods as described above. While better monetary policy, globalization of industries and markets, and other factors have also resulted in lower prices, Chart 4 shows that consumer price inflation for core commodities and services has generally declined the past two decades, when supply chain improvements were more widely adopted, particularly those using newer e-business technologies. Moreover, prices for core commodities have actually fallen since 2001, with the annual percent change less than 2 percent per year since the early 1990s. In fact, core commodity prices have risen only 3.4 percent since 1993, averaging less than 0.3 perce nt per year. In contrast, core services prices have continued to rise over the past decade at between 2.5 to 4 percent annually. Another macroeconomic variable where we would expect to see improvement from streamlined supply chain operations is the growth of productivity, measured as output per hour. As e-business technologies help firms to move quickly and inexpensively collect, analyze and process information, industry supply chains become more efficient. That is, supply chains become more productive. Chart 5 shows that the 5-year moving average of productivity growth has surged in recent years to an average level experienced only briefly in the mid-1960s. Additionally, the 2001 recession is the only recession on record since World War II where productivity growth continued to grow by at least 2 percent annually. In other words, productivity growth continued throughout the 2001 recession as firms quickly adjusted labor hours to the lower output levels. Clearly, this can have a neg ative impact on employment, and perhaps that should also be expected as new e-business technologies often provide labor-saving solutions to supply chain problems. New technology solutions frequently eliminate the need for labor, whether it is counting inventory, processing orders, streamlining production operations, or moving stuff from one location to another. Moreover, as information is collected and processed in real-time, businesses have a better understanding of the demand for their products and can take necessary actions quicker to reduce production output (and labor resources). And there are signs that these benefits are spreading to the service sector, whose productivity growth has recently picked up, particularly in retail and wholesale trade (Alm, Cox, and Duca, 2004). Chart 6 shows that employment growth was very slow to recover following the 2001 recession. However, as shown in Chart 7, GDP growth is much more stable today than 20 or 30 years ago, and this increased stab ility is at least partially attributable to better management (Siems, 2004). The good news is that, in the end, stronger productivity growth directly translates into higher standards of living for an economys citizens. Many factors can influence macroeconomic variables such as inflation, employment, output, and the like. Higher productivity growth, more stable economic output, and lower inflation might result from good monetary policies, better fiscal policies, or luck (fewer external shocks). We believe, however, that the impact of e-business technologies on supply chain operations should not be overlooked. The macroeconomic benefits highlighted above might also partly stem from better management of technology, supply chain operations, and risk. Moreover, the effective implementation of e-business technologies in a competitive environment that demands economic efficiency in order to maximize shareholder wealth should lead to stronger productivity growth. Conclusion While improved supply chain management principles combined with new information (e-business) technologies may not have been given much macroeconomic attention in the past, its effective implementation can help firms reduce costs, increase revenues, boost efficiencies, and expand market opportunities. We find evidence that these improvements have resulted in a reduced bullwhip effect (production volatility that more closely resembles sales volatility), lower inventory levels, reduced logistical costs, and streamlined procurement processes. Taken one step further, we show evidence that strongly suggests that these improvements are linked to macroeconomic benefits such as lower inflation, more stable economic output, higher productivity growth, and better standards of living. Furthermore, these improvements have occurred even in the face of powerful economic shocks, including the post-Y2K stock market bubble and IT investment bust, the 2001 recession, the September 11 terrorist attack s, corporate governance scandals, and rising energy costs, among other developments. 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Section : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Subject Name : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Subject Code : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Topic of assignment (Project) : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Faculty Name : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Date of submission of assignment : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Signature of Student ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Receipt Assignment Submission Form Enrollment No. : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Name : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Course : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Batch : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Section : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Subject Name : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Subject Code : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Topic of assignment (Project) : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Faculty Name : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ Date of submission of assignment : ÃÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦ÃƒÆ' ¢Ãƒ ¢Ã¢â‚¬Å¡Ã‚ ¬Ãƒâ€šÃ‚ ¦. Signature of receiver Stamp(office)

Essay about A Gender Debate - 606 Words

Gender refers to the psychological, social, and cultural differences between males and females. Gender also means the physiological and anatomical differences between the male and female bodies. Most socio-biologists believe differences in sex are a result of differences in the thinking and behavior of men and women. They argue gender identity is formed through socialization. Gender structures every aspect of an individuals life through social relationships and all forms of interaction with society including work. Marxist writers note that pre-capitalism depended on a working relationship. Men dominated the public sphere while a womans place was in the private sphere. John Stuart Mill (1869) wrote one of the first political†¦show more content†¦Women who do not conform to these ideals, such as lesbians, single women, unmarried mothers, and childfree women are viewed as deviants. Women are also choosing to have children without the support of a husband-father figure (Warren et al 2002). In the same way as women are expected to be the `angel of the hearth (Walsh 1997), men are socially expected to be hunter gatherers, providers, and breadwinners because men are viewed as being physically and mentally stronger. Men have different expectations...aspirations... needs. ...My wife needs nurturing, friendship, faithfulness and clothes that fit, whereas I need food, sex...(www.newmanmag.com/article.php 29/03/03). However, men are now taking nurturing roles in the family while women more are now more prominent in the workplace. One may see this as a positive advance for women, however: men and women of equivalent training and employment do not receive equal pay (www.eironline.com/gender/pay/disparities 26/03/03). Furthermore, since the 1970s the wage gap has widened. Women who started their careers in the 1970s would expect to find a 15% wage gap; in comparison women in the 1990s found a gap of 22% (eironline). The reason is in the types of jobs that women h eld. For example, there has always been a gap between part time and full time wages. However, that argument does not account for wageShow MoreRelatedThe Gender Marker Debate : Is Gender Needed On Government Issued Id?1029 Words   |  5 PagesProfessor Hall ENC1102 April 12,2017 Final Assignment The gender marker debate: is gender needed on government-issued ID? Should Non-binary join male and female options for state IDs? As of 2017 the Gender Recognition Act would add â€Å"non-binary† to male and female gender boxes on official state documents making it easier for transgender people to change the gender in which they identify with. As of now, the federal government does not offer a third gender option for official documents such as passports.Read MoreNature Nurture Debate in Gender Development Essay839 Words   |  4 Pagesfeminine or androgynous behavior, then what determines this? The two main arguments are either gender is innate or it has been learnt. 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Enzyme Biocatalysis Free Essays

string(56) " Redox Biotransformations Catalyzed by Dehydrogenases \." Enzyme Biocatalysis Andr? s Illanes e Editor Enzyme Biocatalysis Principles and Applications 123 Prof. Dr. Andr? s Illanes e School of Biochemical Engineering Ponti? cia Universidad Cat? lica o de Valpara? so ? Chile aillanes@ucv. We will write a custom essay sample on Enzyme Biocatalysis or any similar topic only for you Order Now cl ISBN 978-1-4020-8360-0 e-ISBN 978-1-4020-8361-7 Library of Congress Control Number: 2008924855 c 2008 Springer Science + Business Media B. V. No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, micro? ming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied speci? cally for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper. 9 8 7 6 5 4 3 2 1 springer. com Contents Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andr? s Illanes e 1. 1 Catalysis and Biocatalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. 2 Enzymes as Catalysts. Structure–Functionality Relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. 3 The Concept and Determination of Enzyme Activity . . . . . . . . . . . . . . 1. 4 Enzyme Classes. Properties and Technological Signi? cance . . . . . . . 1. 5 Applications of Enzymes. Enzyme as Process Catalysts . . . . . . . . . . . 1. 6 Enzyme Processes: the Evolution from Degradation to Synthesis. Biocatalysis in Aqueous and Non-conventional Media . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Enzyme Production . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Andr? s Illanes e 2. 1 Enzyme Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2 Production of Enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2. 1 Enzyme Synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2. 2 Enzyme Recovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2. 3 Enzyme Puri? cation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. 2. 4 Enzyme Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1 4 8 16 19 31 39 57 57 60 61 65 74 84 89 2 3 Homogeneous Enzyme Kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Andr? s Illanes, Claudia Altamirano, and Lorena Wilson e 3. 1 General Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 3. 2 Hypothesis of Enzyme Kinetics. Determination of Kinetic Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 3. 2. 1 Rapid Equilibrium and Steady-State Hypothesis . . . . . . . . . . . 108 v vi Contents Determination of Kinetic Parameters for Irreversible and Reversible One-Substrate Reactions . . . . . . . . . . . . . . . . . . . . . 112 3. 3 Kinetics of Enzyme Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 3. 3. 1 Types of Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 3. 3. Development of a Generalized Kinetic Model for One-Substrate Reactions Under Inhibition . . . . . . . . . . . . . . . . 117 3. 3. 3 Determination of Kinetic Parameters for One-Substrate Reactions Under Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 3. 4 Reactions with More than One Substrate . . . . . . . . . . . . . . . . . . . . . . . . 124 3. 4. 1 Mechanisms of Reaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 3. 4. 2 Development of Kinetic Models . . . . . . . . . . . . . . . . . . . . . . . . 125 3. 4. 3 Determination of Kinetic Parameters . . . . . . . . . . . . . . . . . . . 131 3. 5 Environmental Variables in Enzyme Kinetics . . . . . . . . . . . . . . . . . . . . 133 3. 5. 1 Effect of pH: Hypothesis of Michaelis and Davidsohn. Effect on Enzyme Af? nity and Reactivity . . . . . . . . . . . . . . . . 134 3. 5. 2 Effect of Temperature: Effect on Enzyme Af? nity, Reactivity and Stability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 3. 5. 3 Effect of Ionic Strength . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 4 Heterogeneous Enzyme Kinetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Andr? s Illanes, Roberto Fern? ndez-Lafuente, Jos? M. Guis? n, e a e a and Lorena Wilson 4. 1 Enzyme Immobilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 4. 1. 1 Methods of Immobilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 4. 1. 2 Evaluation of Immobilization . . . . . . . . . . . . . . . . . . . . . . . . . . 166 4. 2 Heterogeneous Kinetics: Apparent, Inherent and Intrinsic Kinetics; Mass Transfer Effects in Heterogeneous Biocatalysis . . . . . . . . . . . . . 169 4. 3 Partition Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 4. 4 Diffusional Restrictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 4. 4. 1 External Diffusional Restrictions . . . . . . . . . . . . . . . . . . . . . . . 173 4. 4. 2 Internal Diffusional Restrictions . . . . . . . . . . . . . . . . . . . . . . . . 181 4. 4. 3 Combined Effect of External and Internal Diffusional Restrictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Enzy me Reactors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Andr? s Illanes and Claudia Altamirano e 5. 1 Types of Reactors, Modes of Operation . . . . . . . . . . . . . . . . . . . . . . . . . 205 5. 2 Basic Design of Enzyme Reactors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 5. 2. 1 Design Fundamentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 5. 2. 2 Basic Design of Enzyme Reactors Under Ideal Conditions. Batch Reactor; Continuous Stirred Tank Reactor Under Complete Mixing; Continuous Packed-Bed Reactor Under Plug Flow Regime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 3. 2. 2 5 Contents vii Effect of Diffusional Restrictions on Enzyme Reactor Design and Performance in Heterogeneous Systems. Determination of Effectiveness Factors. Batch Reactor; Continuous Stirred Tank Reactor Under Complete Mixing; Continuous Packed-Bed Reactor Under Plug Flow Regime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 5. 4 Effect of Thermal Inactivation on Enzyme Reactor Design and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224 5. 4. 1 Complex Mechanisms of Enzyme Inactivation . . . . . . . . . . . 225 5. 4. 2 Effects of Modulation on Thermal Inactivation . . . . . . . . . . . . 231 5. 4. 3 Enzyme Reactor Design and Performance Under Non-Modulated and Modulated Enzyme Thermal Inactivation . . . . . . . . . . . . . . . . . . . . . . . . . . 234 5. 4. 4 Operation of Enzyme Reactors Under Inactivation and Thermal Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 5. 4. 5 Enzyme Reactor Design and Performance Under Thermal Inactivation and Mass Transfer Limitations . . . . . . . . . . . . . . . 245 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248 6 Study Cases of Enzymatic Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253 6. 1 Proteases as Catalysts for Peptide Synthesis . . . . . . . . . . . . . . . . . . . . . 253 Sonia Barberis, Fanny Guzm? n, Andr? s Illanes, and a e Joseph L? pez-Sant? n o ? 6. 1. 1 Chemical Synthesis of Peptides . . . . . . . . . . . . . . . . . . . . . . . . . 254 6. 1. 2 Proteases as Catalysts for Peptide Synthesis . . . . . . . . . . . . . . 257 6. 1. 3 Enzymatic Synthesis of Peptides . . . . . . . . . . . . . . . . . . . . . . . . 258 6. 1. 4 Process Considerations for the Synthesis of Peptides . . . . . . . 263 6. 1. Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 268 6. 2 Synthesis of ? -Lactam Antibiotics with Penicillin Acylases . . . . . . . 273 Andr? s Illanes and Lorena Wilson e 6. 2. 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 6. 2. 2 Chemical Versus Enzymatic Synthesis of Semi-Synthetic ? -Lactam Antibiotics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 274 6. 2. 3 Strategies of Enzymatic Synthesis . . . . . . . . . . . . . . . . . . . . . . 276 6. 2. 4 Penicillin Acylase Biocatalysts . . . . . . . . . . . . . . . . . . . . . . . . . 277 6. 2. 5 Synthesis of ? -Lactam Antibiotics in Homogeneous and Heterogeneous Aqueous and Organic Media . . . . . . . . . . . . . . 279 6. 2. 6 Model of Reactor Performance for the Production of Semi-Synthetic ? -Lactam Antibiotics . . . . . . . . . . . . . . . . . . . 282 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 6. 3 Chimioselective Esteri? cation of Wood Sterols with Lipases . . . . . . . 292 ? Gregorio Alvaro and Andr? Illanes e 6. 3. 1 Sources and Production of Lipases . . . . . . . . . . . . . . . . . . . . . . 293 6. 3. 2 Structure and Functionality of L ipases . . . . . . . . . . . . . . . . . . . 296 5. 3 viii Contents Improvement of Lipases by Medium and Biocatalyst Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 299 6. 3. 4 Applications of Lipases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304 6. 3. 5 Development of a Process for the Selective Transesteri? cation of the Stanol Fraction of Wood Sterols with Immobilized Lipases . . . . . . . . . . . . . . . . . . . . . . 308 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 6. 4 Oxidoreductases as Powerful Biocatalysts for Green Chemistry . . . . 323 Jos? M. Guis? n, Roberto Fern? ndez-Lafuente, Lorena Wilson, and e a a C? sar Mateo e 6. 4. 1 Mild and Selective Oxidations Catalyzed by Oxidases . . . . . . 324 6. 4. 2 Redox Biotransformations Catalyzed by Dehydrogenases . You read "Enzyme Biocatalysis" in category "Essay examples" . . 326 6. 4. 3 I mmobilization-Stabilization of Dehydrogenases . . . . . . . . . . 329 6. 4. 4 Reactor Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330 6. 4. Production of Long-Chain Fatty Acids with Dehydrogenases 331 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 332 6. 5 Use of Aldolases for Asymmetric Synthesis . . . . . . . . . . . . . . . . . . . . . 333 ? Josep L? pez-Sant? n, Gregorio Alvaro, and Pere Clap? s o ? e 6. 5. 1 Aldolases: De? nitions and Classi? cation . . . . . . . . . . . . . . . . . 334 6. 5. 2 Preparation of Aldolase Biocatalysts . . . . . . . . . . . . . . . . . . . . 335 6. 5. 3 Reaction Performance: Medium Engineering and Kinetics . . 339 6. 5. 4 Synthetic Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346 6. 5. 5 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352 6. 6 Application of Enzymatic Reactors for the Degradation of Highly and Poorly Soluble Recalcitrant Compounds . . . . . . . . . . . . . . . . . . . . 355 o Juan M. Lema, Gemma Eibes, Carmen L? pez, M. Teresa Moreira, and Gumersindo Feijoo 6. 6. 1 Potential Application of Oxidative Enzymes for Environmental Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 6. 6. 2 Requirements for an Ef? cient Catalytic Cycle . . . . . . . . . . . . . 357 6. 6. 3 Enzymatic Reactor Con? gurations . . . . . . . . . . . . . . . . . . . . . . 358 6. 6. 4 Modeling of Enzymatic Reactors . . . . . . . . . . . . . . . . . . . . . . . 364 6. 6. 5 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365 6. 6. 6 Conclusions and Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . 374 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 6. 3. 3 Foreword This book was written with the purpose of providing a sound basis for the design of enzymatic reactions based on kinetic principles, but also to give an updated vision of the potentials and limitations of biocatalysis, especially with respect to recent applications in processes of organic synthesis. The ? rst ? ve chapters are structured in the form of a textbook, going from the basic principles of enzyme structure and function to reactor design for homogeneous systems with soluble enzymes and heterogeneous systems with immobilized enzymes. The last chapter of the book is divided into six sections that represent illustrative case studies of biocatalytic processes of industrial relevance or potential, written by experts in the respective ? elds. We sincerely hope that this book will represent an element in the toolbox of graduate students in applied biology and chemical and biochemical engineering and also of undergraduate students with formal training in organic chemistry, biochemistry, thermodynamics and chemical reaction kinetics. Beyond that, the book pretends also to illustrate the potential of biocatalytic processes with case studies in the ? ld of organic synthesis, which we hope will be of interest for the academia and professionals involved in RDI. If some of our young readers are encouraged to engage or persevere in their work in biocatalysis this will certainly be our more precious reward. ? a Too much has been written about writing. Nobel laureate Gabriel Garc? a M? rquez wrote one of its most inspired books by writing about writing (Living to Tell the Tale). There he wrote â€Å"life is not what one lived, but what one remembers and how one remembers it in order to recount it†. This hardly applies to a scienti? book, but certainly highlights what is applicable to any book: its symbiosis with life. Writing about biocatalysis has given me that privileged feeling, even more so because enzymes are truly the catalysts of life. Biocatalysis is hardly separable from my life and writing this book has been certainly more an ecstasy than an agony. A book is an object of love so who better than friends to build it. Eleven distinguished professors and researchers have contributed to this endeavor with their knowledge, their commitment and their encouragement. Beyond our common language, I share with all of them a view and a life-lasting friendship. That is what lies behind this book and made its construction an exciting and rewarding experience. ix x Foreword Chapters 3 to 5 were written with the invaluable collaboration of Claudia Altamirano and Lorena Wilson, two of my former students, now my colleagues, and my bosses I am afraid. Chapter 4 also included the experience of Jos? Manuel Guis? n, e a Roberto Fern? ndez-Lafuente and C? sar Mateo, all of them very good friends who a e were kind enough to join this project and enrich the book with their world known expertise in heterogeneous biocatalysis. Section 6. is the result of a cooperation sustained by a CYTED project that brought together Sonia Barberis, also a former graduate student, now a successful professor and permanent collaborator and, beyond that, a dear friend, Fanny Guzm? n, a reputed scientist in the ? eld of peptide a synthesis who is my partner, support and inspiration, and Josep L? pez, a well-known o scientist and engineer but, above all, a friend at heart an d a warm host. Section 6. 3 was the result of a joint project with Gregorio Alvaro, a dedicated researcher who has been a permanent collaborator with our group and also a very special friend and kind host. Section 6. is the result of a collaboration, in a very challenging ? eld of applied biocatalysis, of Dr. Guisan’s group with which we have a long-lasting academic connection and strong personal ties. Section 6. 5 represents a very challengo e ing project in which Josep L? pez and Gregorio Alvaro have joined Pere Clap? s, a prominent researcher in organic synthesis and a friend through the years, to build up an updated review on a very provocative ? eld of enzyme biocatalysis. Finally, section 6. 6 is a collaboration of a dear friend and outstanding teacher, Juan Lema, and his research group that widens the scope of biocatalysis to the ? ld of environmental engineering adding a particular ? avor to this ? nal chapter. A substantial part of this book was written in Spain whil e doing a sabbatical in the o Universitat Aut` noma de Barcelona, where I was warmly hosted by the Chemical Engineering Department, as I also was during short stays at the Institute of Catalysis and Petroleum Chemistry in Madrid and at the Department of Chemical Engineering in the Universidad de Santiago de Compostela. My recognition to the persons in my institution, the Ponti? cia Universidad Cat? lica de Valpara? so, that supported and encouraged this project, particularly to o ? the rector Prof. Alfonso Muga, and professors Atilio Bustos and Graciela Mu? oz. n Last but not least, my deepest appreciation to the persons at Springer: Marie Johnson, Meran Owen, Tanja van Gaans and Padmaja Sudhakher, who were always delicate, diligent and encouraging. Dear reader, the judgment about the product is yours, but beyond the product there is a process whose beauty I hope to have been able to transmit. I count on your indulgence with language that, despite the effort of our editor, may still reveal our condition of non-native English speakers. Andr? s Illanes e Valpara? so, May 15, 2008 ? Chapter 1 Introduction Andr? s Illanes e . 1 Catalysis and Biocatalysis Many chemical reactions can occur spontaneously; others require to be catalyzed to proceed at a signi? cant rate. Catalysts are molecules that reduce the magnitude of the energy barrier required to be overcame for a substance to be converted chemically into another. Thermodynamically, the magnitude of this energy barrier can be con veniently expressed in terms of the free-energy change. As depicted in Fig. 1. 1, catalysts reduce the magnitude of this barrier by virtue of its interaction with the substrate to form an activated transition complex that delivers the product and frees the catalyst. The catalyst is not consumed or altered during the reaction so, in principle, it can be used inde? nitely to convert the substrate into product; in practice, however, this is limited by the stability of the catalyst, that is, its capacity to retain its active structure through time at the conditions of reaction. Biochemical reactions, this is, the chemical reactions that comprise the metabolism of all living cells, need to be catalyzed to proceed at the pace required to sustain life. Such life catalysts are the enzymes. Each one of the biochemical reactions of the cell metabolism requires to be catalyzed by one speci? enzyme. Enzymes are protein molecules that have evolved to perform ef? ciently under the mild conditions required to preserve the functionality and integrity of the biological systems. Enzymes can be considered then as catalysts that have been optimized through evolution to perform their physiological task upon which all forms of life depend. No wonder why enzymes are c apable of performing a wide range of chemical reactions, many of which extremely complex to perform by chemical synthesis. It is not presumptuous to state that any chemical reaction already described might have an enzyme able to catalyze it. In fact, the possible primary structures of an enzyme protein composed of n amino acid residues is 20n so that for a rather small protein molecule containing 100 amino acid residues, there are 20100 or 10130 possible School of Biochemical Engineering, Ponti? cia Universidad Cat? lica de Valpara? so, Avenida Brasil o ? 2147, Valpara? so, Chile. Phone: 56-32-273642, fax: 56-32-273803; e-mail: aillanes@ucv. cl ? A. Illanes (ed. ), Enzyme Biocatalysis. c Springer Science + Business Media B. V. 2008 1 2 Trasition State A. Illanes Catalyzed Path Uncatalyzed Path Free Energy Ea Ea’ Reactans ? G Products Reaction Progress Fig. 1. 1 Mechanism of catalysis. Ea and Ea are the energies of activation of the uncatalyzed and catalyzed reaction. ?G is the free energy change of the reaction amino acid sequences, which is a fabulous number, higher even than the number of molecules in the whole universe. To get the right enzyme for a certain chemical reaction is then a matter of search and this is certainly challenging and exciting if one realizes that a very small fraction of all living forms have been already isolated. It is even more promising when one considers the possibility of obtaining DNA pools from the environment without requiring to know the organism from which it comes and then expressed it into a suitable host organism (Nield et al. 2002), and the opportunities of genetic remodeling of structural genes by site-directed mutagenesis (Abi? n et al. 2004). a Enzymes have been naturally tailored to perform under physiological conditions. However, biocatalysis refers to the use of enzymes as process catalysts under arti? cial conditions (in vitro), so that a major challenge in biocatalysis is to transform these hysiological catalysts into process catalysts able to perform under the usually tough reaction conditions of an industrial process. Enzyme catalysts (biocatalysts), as any catalyst, act by reducing the energy barrier of the biochemical reactions, without being altered as a consequence of the reaction they promote. However, enzymes display quite distinct properties when compared with ch emical catalysts; most of these properties are a consequence of their complex molecular structure and will be analyzed in section 1. 2. Potentials and drawbacks of enzymes as process catalysts are summarized in Table 1. 1. Enzymes are highly desirable catalysts when the speci? city of the reaction is a major issue (as it occurs in pharmaceutical products and ? ne chemicals), when the catalysts must be active under mild conditions (because of substrate and/or product instability or to avoid unwanted side-reactions, as it occurs in several reactions of organic synthesis), when environmental restrictions are stringent (which is now a 1 Introduction Table 1. 1 Advantages and Drawbacks of Enzymes as Catalysts Advantages High speci? ity High activity under moderate conditions High turnover number Highly biodegradable Generally considered as natural products Drawbacks High molecular complexity High production costs Intrinsic fragility 3 rather general situation that gives biocatalysis a distinct advantage over alternative technologies) or when the label of natural product is an issue (as in the case of food and cosmetic app lications) (Benkovic and Ballesteros 1997; Wegman et al. 2001). However, enzymes are complex molecular structures that are intrinsically labile and costly to produce, which are de? ite disadvantages with respect to chemical catalysts (Bommarius and Broering 2005). While the advantages of biocatalysis are there to stay, most of its present restrictions can be and are being solved through research and development in different areas. In fact, enzyme stabilization under process conditions is a major issue in biocatalysis and several strategies have been developed (Illanes 1999) that include ? chemical modi? cation (Roig and Kennedy 1992; Ozturk et al. 2002; Mislovi? ov? c a et al. 2006), immobilization to solid matrices (Abi? n et al. 2001; Mateo et al. 2005; a Kim et al. 2006; Wilson et al. 006), crystallization (H? ring and Schreier 1999; Roy a and Abraham 2006), aggregation (Cao et al. 2003; Mateo et al. 2004; Schoevaart et al. 2004; Illanes et al. 2006) and the modern techniques of protein engineering (Chen 2001; Declerck et al. 2003; Sylvestre et al. 2006; Leisola and Turunen 2007), namely site-directed mutagenesis (Bhosale et al. 1996; Ogino et al. 2001; Boller et al. 2002; van den Burg and Eijsink 2002; Adamczak and Hari Krishna 2004; Bardy et al. 2005; Morley and Kazlauskas 2005), directed evolution by tandem mutagenesis (Arnold 2001; Brakmann and Johnsson 2002; Alexeeva et al. 003; Boersma et al. 2007) and gene-shuf? ing based on polymerase assisted (Stemmer 1994; Zhao et al. 1998; Shibuya et al. 2000; Kaur and Sharma 2006) and, more recently, ligase assisted recombination (Chodorge et al. 2005). Screening for intrinsically stable enzymes is also a prominent area of research in biocatalysis. Extremophiles, that is, organisms able to survive and thrive in extreme environmental conditions are a promising source for highly stable enzymes and research on those organisms is very active at present (Adams and Kelly 1998; Davis 1998; Demirjian et al. 001; van den Burg 2003; Bommarius and Riebel 2004; Gomes and Steiner 2004). Genes from such extremophiles have been cloned into suitable hosts to develop biological systems more amenable for production (Halld? rsd? ttir et al. 1998; o o Haki and Rakshit 2003; Zeikus et al. 2004). Enzymes are by no means ideal process catalysts, but their extremely high speci? city and activity under moderate conditions are prominent characteristics that are being increasingly appreciated by different production sectors, among which the pharmaceutical and ? ne-chemical industry (Schmid et al. 001; Thomas et al. 2002; Zhao et al. 2002; Bruggink et al. 2003) have added to the more traditional sectors of food (Hultin 1983) and detergents (Maurer 2004). 4 Fig. 1. 2 Scheme of peptide bond formation between two adjacent ? -amino acids R1 + H3N CH C OH O A. Illanes H R2 + H N CH COO? H2O R1 H2O H R2 H3N CH C N CH COO? O + 1. 2 Enzymes as Catalysts. Structure–Functionality Relationships Most of the characteristic s of enzymes as catalysts derive from their molecular structure. Enzymes are proteins composed by a number of amino acid residues that range from 100 to several hundreds. These amino acids are covalently bound through the peptide bond (Fig. 1. 2) that is formed between the carbon atom of the carboxyl group of one amino acid and the nitrogen atom of the ? -amino group of the following. According to the nature of the R group, amino acids can be non-polar (hydrophobic) or polar (charged or uncharged) and their distribution along the protein molecule determines its behavior (Lehninger 1970). Every protein is conditioned by its amino acid sequence, called primary structure, which is genetically determined by the deoxyribonucleotide sequence in the structural gene that codes for it. The DNA sequence is ? rst transcribed into a mRNA molecule which upon reaching the ribosome is translated into an amino acid sequence and ? nally the synthesized polypeptide chain is transformed into a threedimensional structure, called native structure, which is the one endowed with biological functionality. This transformation may include several post-translational reactions, some of which can be quite relevant for its functionality, like proteolytic cleavage, as it occurs, for instance, with Escherichia coli penicillin acylase (Schumacher et al. 986) and glycosylation, as it occurs for several eukaryotic enzymes (Longo et al. 1995). The three-dimensional structure of a protein is then genetically determined, but environmentally conditioned, since the molecule will interact with the surrounding medium. This is particularly relevant for biocatalysis, where the enzyme acts in a medium quite different from the one in which it was synthesized than can alter its native functional struct ure. Secondary three-dimensional structure is the result of interactions of amino acid residues proximate in the primary structure, mainly by hydrogen bonding of the amide groups; for the ase of globular proteins, like enzymes, these interactions dictate a predominantly ribbon-like coiled con? guration termed ? -helix. Tertiary three-dimensional structure is the result of interactions of amino acid residues located apart in the primary structure that produce a compact and twisted con? guration in which the surface is rich in polar amino acid 1 Introduction 5 residues, while the inner part is abundant in hydrophobic amino acid residues. This tertiary structure is essential for the biological functionality of the protein. Some proteins have a quaternary three-dimensional structure, which is common in regulatory proteins, that is the result of the interaction of different polypeptide chains constituting subunits that can display identical or different functions within a protein complex (Dixon and Webb 1979; Creighton 1993). The main types of interactions responsible for the three-dimensional structure of proteins are (Haschemeyer and Haschemeyer 1973): †¢ Hydrogen bonds, resulting from the interaction of a proton linked to an electronegative atom with another electronegative atom. A hydrogen bond has approximately one-tenth of the energy stored in a covalent bond. It is the main determinant of the helical secondary structure of globular proteins and it plays a signi? cant role in tertiary structure as well. †¢ Apolar interactions, as a result of the mutual repulsion of the hydrophobic amino acid residues by a polar solvent, like water. It is a rather weak interaction that does not represent a proper chemical bond (approximation between atoms exceed the van der Waals radius); however, its contribution to the stabilization of the threedimensional structure of a protein is quite signi? ant. †¢ Disulphide bridges, produced by oxidation of cysteine residues. They are especially relevant in the stabilization of the three-dimensional structure of low molecular weight extracellular proteins. †¢ Ionic bonds between charged amino acid residues. They contribute to the stabilization of the three-dimensional structure of a protein, although to a lesser exten t, because the ionic strength of the surrounding medium is usually high so that interaction is produced preferentially between amino acid residues and ions in the medium. Other weak type interactions, like van der Waals forces, whose contribution to three-dimensional structure is not considered signi? cant. Proteins can be conjugated, this is, associated with other molecules (prosthetic groups). In the case of enzymes which are conjugated proteins (holoenzymes), catalysis always occur in the protein portion of the enzyme (apoenzyme). Prosthetic groups may be organic macromolecules, like carbohydrates (in the case of glycoproteins), lipids (in the case of lipoproteins) and nucleic acids (in the case of nucleoproteins), or simple inorganic entities, like metal ions. Prosthetic groups are tightly bound (usually covalently) to the apoenzyme and do not dissociate during catalysis. A signi? cant number of enzymes from eukaryotes are glycoproteins, in which case the carbohydrate moiety is covalently linked to the apoenzyme, mainly through serine or threonine residues, and even though the carbohydrate does not participate in catalysis it confers relevant properties to the enzyme. Catalysis takes place in a small portion of the enzyme called the active site, which is usually formed by very few amino acid residues, while the rest of the protein acts as a scaffold. Papain, for instance, has a molecular weight of 23,000 Da with 211 amino acid residues of which only cysteine (Cys 25) and histidine (His 159) 6 A. Illanes are directly involved in catalysis (Allen and Lowe 1973). Substrate is bound to the enzyme at the active site and doing so, changes in the distribution of electrons in its chemical bonds are produced that cause the reactions that lead to the formation of products. The products are then released from the enzyme which is ready for the next catalytic cycle. According to the early lock and key model proposed by Emil Fischer in 1894, the active site has a unique geometric shape that is complementary to the geometric shape of the substrate molecule that ? ts into it. Even though recent reports provide evidence in favor of this theory (Sonkaria et al. 2004), this rigid model hardly explains many experimental evidences of enzyme biocatalysis. Later on, the induced-? t theory was proposed (Koshland 1958) according to which he substrate induces a change in the enzyme conformation after binding, that may orient the catalytic groups in a way prone for the subsequent reaction; this theory has been extensively used to explain enzyme catalysis (Youseff et al. 2003). Based on the transition-state theory, enzyme catalysis has been explained according to the hypothesis of enzyme transition state complementariness, which considers the prefc erential binding of the transition state rather than the substrate or product (Benkovi? and Hammes-Schiffer 2003) . Many, but not all, enzymes require small molecules to perform as catalysts. These molecules are termed coenzymes or cofactors. The term coenzyme is used to refer to small molecular weight organic molecules that associate reversibly to the enzyme and are not part of its structure; coenzymes bound to enzymes actually take part in the reaction and, therefore, are sometime called cosubstrates, since they are stoichiometric in nature (Kula 2002). Coenzymes often function as intermediate carriers of electrons (i. e. NAD+ or FAD+ in dehydrogenases), speci? c atoms (i. e. oenzyme Q in H atom transfer) or functional groups (i. e. coenzyme A in acyl group transfer; pyridoxal phosphate in amino group transfer; biotin in CO2 transfer) that are transferred in the reaction. The term cofactor is commonly used to refer to metal ions that also bind reversibly to enzymes but in general are not chemically altered during the reaction; cofactors usually bind strongly to the enzyme structure so that they are not dissociated from the holoenzyme during the reaction (i. e. Ca++ in ? -amylase; Co++ or Mg++ in glucose isomerase; Fe+++ in nitrile hydratase). According to these requirements, enzymes can be classi? ed in three groups as depicted in Fig. 1. 3: (i) those that do not require of an additional molecule to perform biocatalysis, (ii) those that require cofactors that remain unaltered and tightly bound to the enzyme performing in a catalytic fashion, and (iii) those requiring coenzymes that are chemically modi? ed and dissociated during catalysis, performing in a stoichiometric fashion. The requirement of cofactors or coenzymes to perform biocatalysis has profound technological implications, as will be analyzed in section 1. 4. Enzyme activity, this is, the capacity of an enzyme to catalyze a chemical reaction, is strictly dependent on its molecular structure. Enzyme activity relies upon the existence of a proper structure of the active site, which is composed by a reduced number of amino acid residues close in the three-dimensional structure of 1 Introduction Fig. 1. 3 Enzymes according to their cofactor or coenzyme requirements. 1: no requirement; 2: cofactor requiring; 3: coenzyme requiring S 1 7 P E E CoE 2 S E-CoE P E CoE 3 E CoE’ E P S E-CoE the protein but usually far apart in the primary structure. Therefore, any agent that promotes protein unfolding will move apart the residues constituting the active site and will then reduce or destroy its biological activity. Adverse conditions of temperature, pH or solvent and the presence of chaotropic substances, heavy metals and chelating agents can produce this loss of function by distorting the proper active site con? guration. Even though a very small portion of the enzyme molecule participates in catalysis, the remaining of the molecule is by no means irrelevant to its performance. Crucial properties, like enzyme stability, are very much dependent on the enzyme three-dimensional structure. Enzyme stability appears to be determined by unde? ned irreversible processes governed by local unfolding in certain labile regions denoted as weak spots. These regions prone to unfolding are the determinants of enzyme stability and are usually located in or close to the surface of the protein molecule, which explains why the surface structure of the enzyme is so important for its catalytic stability (Eijsink et al. 2004). These regions have been the target of site-speci? c mutations for increasing stability. Though extensively studied, rational engineering of the enzyme molecule for increased stability has been a very complex task. In most cases, these weak spots are not easy to identify so it is not clear to what region of the protein molecule should one be focused on and, even though properly selected, it is not clear what is the right type of mutation to introduce (Gaseidnes et al. 2003). Despite the impressive advances in the ? eld and the existence of some experimentally based rules (Shaw and Bott 1996), rational improvement of the stability is still far from being well established. In fact, the less rational approaches of directed evolution using error-prone PCR and gene shuf? ing have been more successful in obtaining more stable mutant enzymes (Kaur and Sharma 2006). Both strategies can combine using a set of rationally designed mutants that can then be subjected to gene shuf? ing (O’F? g? in 2003). a a A perfectly structured native enzyme expressing its biological activity can lose it by unfolding of its tertiary structure to a random polypeptide chain in which the amino acids located in the active site are no longer aligned closely enough to perform its catalytic function. This phenomenon is termed denaturation and it may be reversible if the denaturing in? uence is removed since no chemical changes 8 A. Illanes have occurred in the protein molecule. The enzyme molecule can also be subjected to chemical changes that produce irreversible loss of activity. This phenomenon is termed inactivation and usually occurs following unfolding, since an unfolded protein is more prone to proteolysis, loss of an essential cofactor and aggregation (O’F? g? in 1997). These phenomena de? e what is called thermodynamic or cona a formational stability, this is the resistance of the folded protein to denaturation, and kinetic or long-term stability, this is the resistance to irreversible inactivation (Eisenthal et al. 2006). The overall process of enzyme inactivation can then be represented by: N U ? I where N represents the native active conformation, U the unfolded conformation and I the irreversibly inactivated enzyme (Klibanov 1983; Bommarius and Broering 2005 ). The ? rst step can be de? ned by the equilibrium constant of unfolding (K), while the second is de? ed in terms of the rate constant for irreversible inactivation (k). Stability is not related to activity and in many cases they have opposite trends. It has been suggested that there is a trade-off between stability and activity based on the fact that stability is clearly related to molecular stiffening while conformational ? exibility is bene? cial for catalysis. This can be clearly appreciated when studying enzyme thermal inactivation: enzyme activity increases with temperature but enzyme stability decreases. These opposite trends make temperature a critical variable in any enzymatic process and make it prone to optimization. This aspect will be thoroughly analyzed in Chapters 3 and 5. Enzyme speci? city is another relevant property of enzymes strictly related to its structure. Enzymes are usually very speci? c with respect to its substrate. This is because the substrate is endowed with the chemical bonds that can be attacked by the functional groups in the active site of the enzyme which posses the functional groups that anchor the substrate properly in the active site for the reaction to take place. Under certain conditions conformational changes may alter substrate speci? city. This has been elegantly proven by site-directed mutagenesis, in which speci? c amino acid residues at or near the active site have been replaced producing an alteration of substrate speci? city (Colby et al. 1998; diSioudi et al. 1999; Parales et al. 2000), and also by chemical modi? cation (Kirk Wright and Viola 2001). K k 1. 3 The Concept and Determination of Enzyme Activity As already mentioned, enzymes act as catalysts by virtue of reducing the magnitude of the barrier that represents the energy of activation required for the formation of a transient active complex that leads to product formation (see Fig. . 1). This thermodynamic de? nition of enzyme activity, although rigorous, is of little practical signi? cance, since it is by no means an easy task to determine free energy changes for molecular structures as unstable as the enzyme–substrate complex. The direct 1 Introduction 9 consequence of such reduction of energy input for the reaction to proceed is the increase in reaction rate, which can be considered as a kinetic de? nition of enzyme activity. Rates of chemical reactions are usually simple to determine so this de? nition is endowed with practicality. Biochemical reactions usually proceed at very low rates in the absence of catalysts so that the magnitude of the reaction rate is a direct and straightforward procedure for assessing the activity of an enzyme. Therefore, for the reaction of conversion of a substrate (S) into a product (P) under the catalytic action of an enzyme (E): S ? P v=? ds dp = dt dt (1. 1) E If the course of the reaction is followed, a curve like the one depicted in Fig 1. 4 will be obtained. This means that the reaction rate (slope of the p vs t curve) will decrease as the reaction proceeds. Then, the use of Eq. 1. 1 is ambiguous if used for the determination of enzyme activity. To solve this ambiguity, the reasons underlying this behavior must be analyzed. The reduction in reaction rate can be the consequence of desaturation of the enzyme because of substrate transformation into product (at substrate depletion reaction rate drops to zero), enzyme inactivation as a consequence of the exposure of the enzyme to the conditions of reaction, enzyme inhibition caused by the products of the reaction, and equilibrium displacement as a consequence of the law of mass action. Some or all of these phenomena are present in any enzymatic reaction so that the catalytic capacity of the enzyme will vary throughout the course of the reaction. It is customary to identify the enzyme activity with the initial rate of reaction (initial slope of the â€Å"p† versus â€Å"t† curve) where all the above mentioned Product Concentration e e 2 e 4 Time Fig. 1. 4 Time course of an enzyme catalyzed reaction: product concentration versus time of reaction at different enzyme concentrations (e) 10 A. Illanes phenomena are insigni? ant. According to this: a = vt0 = ? ds dt = t0 dp dt (1. 2) t0 This is not only of practical convenience but fundamentally sound, since the enzyme activity so de? ned represents its maximum catalytic potential under a given set of experimental conditions. To what extent is this catalytic potential going to be expressed in a given situation is a different matter and will have to be assessed by modulating it according to the phenomena that cause its reduction. All such phenomena are amenable to quanti? ation as will be presented in Chapter 3, so that the determination of this maximum catalytic potential is fundamental for any study regarding enzyme kinetics. Enzymes should be quanti? ed in terms of its catalytic potential rather than its mass, since enzyme preparations are rather impure mixtures in which the enzyme protein can be a small fraction of the total mass of the preparation; but, even in the unusual case of a completely pure enzyme, the determination of activity is unavoidable since what matters for evaluating the enzyme performance is its catalytic potential and not its mass. Within the context of enzyme kinetics, reaction rates are always considered then as initial rates. It has to be pointed out, however, that there are situations in which the determination of initial reaction rates is a poor predictor of enzyme performance, as it occurs in the determination of degrading enzymes acting on heterogeneous polymeric substrates. This is the case of cellulase (actually an enzyme complex of different activities) (Montenecourt and Eveleigh 1977; Illanes et al. 988; Fowler and Brown 1992), where the more amorphous portions of the cellulose moiety are more easily degraded than the crystalline regions so that a high initial reaction rate over the amorphous portion may give an overestimate of the catalytic potential of the enzyme over the cellulose substrate as a whole. As shown in Fig. 1. 4, the initial slope o the curve (initial rate of reaction) is proportional to the enzyme concentration (it is so in most cases). Therefore, the enzyme sample should be properly diluted to attain a linear product concentration versus time relationship within a reasonable assay time. The experimental determination of enzyme activity is based on the measurement of initial reaction rates. Substrate depletion or product build-up can be used for the evaluation of enzyme activity according to Eq. 1. 2. If the stoichiometry of the reaction is de? ned and well known, one or the other can be used and the choice will depend on the easiness and readiness for their analytical determination. If this is indifferent, one should prefer to measure according to product build-up since in this case one will be determining signi? ant differences between small magnitudes, while in the case of substrate depletion one will be measuring small differences between large magnitudes, which implies more error. If neither of both is readily measurable, enzyme activity can be determined by coupling reactions. In this case the product is transformed (chemically or enzymatically) to a ? nal analyte amenable for analytical determination, as shown: E S P A X B Y C Z 1 Introduction 11 In this case enzyme activity can be determined as: a = vt0 = ? ds dt = t0 dp dt = t0 dz dt (1. 3) t0 rovided that the rate limiting step is the reaction catalyzed by the enzyme, which implies that reagents A, B and C should be added in excess to ensure that all P produced is quantitatively transformed into Z. For those enzymes requiring (stoichiometric) coenzymes: E S CoE CoE P activity can be determined as: a = vt0 = ? dcoe dt = t0 dcoe dt (1. 4) t0 This is actually a very convenient method for determining activity of such class of enzymes, since organic coenzymes (i. e. FAD or NADH) are usually very easy to determine analytically. An example of a coupled system considering coenzyme determination is the assay for lactase (? galactosidase; EC 3. 2. 1. 23). The enzyme catalyzes the hydrolysis of lactose according to: Lactose + H2 O Glucose + Galactose Glucose produced can be coupled to a classical enzymatic glucose kit, that is: hexoquinase (Hx) plus glucose 6 phosphate dehydrogenase (G6PD), in which: Glucose + ATP ? Glucose 6Pi + ADP Glucose 6Pi + NADP+ ? ? ? ? 6PiGluconate + NADPH where the initial rate of NADPH (easily measured in a spectrophotometer; see ahead) can be then stoichiometrically correlated to the initial rate of lactose hydrolysis, provided that the auxiliary enzymes, Hx and G6PD, and co-substrates are added in excess. Enzyme activity can be determined by a continuous or discontinuous assay. If the analytical device is provided with a recorder that register the course of reaction, the initial rate could be easily determined from the initial slope of the product (or substrate, or coupled analyte, or coenzyme) concentration versus time curve. It is not always possible or simple to set up a continuous assay; in that case, the course of reaction should be monitored discontinuously by sampling and assaying at predetermined time intervals and samples should be subjected to inactivation to stop the reaction. This is a drawback, since the enzyme should be rapidly, completely and irreversibly inactivated by subjecting it to harsh conditions that can interfere with the G6PD Hx 12 A. Illanes analytical procedure. Data points should describe a linear â€Å"p† versus â€Å"t† relationship within the time interval for assay to ensure that the initial rate is being measured; if not, enzyme sample should be diluted accordingly. Assay time should be short enough to make the effect of the products on the reaction rate negligible and to produce a negligibly reduction in substrate concentration. A major issue in enzyme activity determination is the de? ition of a control experiment for discriminating the non-enzymatic build-up of product during the assay. There are essentially three options: to remove the enzyme from the reaction mixture by replacing the enzyme sample by water or buffer, to remove the substrate replacing it by water or buffer, or to use an enzyme placebo. The ? rst one discriminates substrate contamination with product or any non-enzymatic transformation of substrate into product, but does not discriminate enzyme contamination with substrate or product; the second one acts exactly the opposite; the third one can in rinciple discriminate both enzyme and substrate contamination with product, but the pitfall in this case is the risk of not having inactivated the enzyme completely. The control of choice depends on the situation. For instance, when one is producing an extracellular enzyme by fermentation, enzyme sample is likely to be contaminated with substrate and or product (that can be constituents of the culture medium or products of metabolism) and may be signi? ant, since the sample probably has a low enzyme protein concentration so that it is not diluted prior to assay; in this case, replacing substrate by water or buffer discriminates such contamination. If, on the other hand, one is assaying a preparation from a stock enzyme concentrate, dilu tion of the sample prior to assay makes unnecessary to blank out enzyme contamination; replacing the enzyme by water or buffer can discriminate substrate contamination that is in this case more relevant. The use of an enzyme placebo as control is advisable when the enzyme is labile enough to be completely inactivated at conditions not affecting the assay. An alternative is to use a double control replacing enzyme in one case and substrate in the other by water or buffer. Once the type of control experiment has been decided, control and enzyme sample are subjected to the same analytical procedure, and enzyme activity is calculated by subtracting the control reading from that of the sample, as illustrated in Fig. . 5. Analytical procedures available for enzyme activity determinations are many and usually several alternatives exist. A proper selection should be based on sensibility, reproducibility, ? exibility, simplicity and availability. Spectrophotometry can be considered as a method that ful? ls most, if not all, such criteria. It is based on the absorption of light of a certain wavelength as described by the Beer–Lambert law: A? = ?  · l  · c where: A? = log I I0 (1. 5) (1. 6) The value of ? an be experimentally obtained through a calibration curve of absorbance versus concentration of analyte, so that the reading of A? will allow the determination of its concentration. Optical path width is usually 1 cm. The method is based on the differential absorption of product (or coupling analyte or modi? ed 1 Introduction 13 Fig. 1. 5 Scheme for the analytical procedure to determine enzyme activity. S: substrate; P: product; P0 : product in control; A, B, C: coupling reagents; Z: analyte; Z0 : analyte in control; s, p, z are the corresponding molar concentrations oenzyme) and substrate (or coenzyme) at a certain wavelength. For instance, the reduced coenzyme NADH (or NADPH) has a strong peak of absorbance at 340 nm while the absorbance of the oxidized coenzyme NAD+ (or NADP+ ) is negligible at that wavelength; therefore, the activity of any enzyme producing or consuming NADH (or NADPH) can be determined by measuring the increase or decline of absorbance at 340 nm in a spectrophotometer. The assay is sensitive, reproducible and simple and equipment is available in any research laboratory. If both substrate and product absorb signi? cantly at a certain wavelength, coupling the detector to an appropriate high performance liquid chromatography (HPLC) column can solve this interference by separating those peaks by differential retardation of the analytes in the column. HPLC systems are increasingly common in research laboratories, so this is a very convenient and ? exible way for assaying enzyme activities. Several other analytical procedures are available for enzyme activity determination. Fluorescence, this is the ability of certain molecules to absorb light at a certain wavelength and emit it at another, is a property than can be used for enzymatic analysis. NADH, but also FAD (? avin adenine dinucleotide) and FMN (? avin mononucleotide) have this property that can be used for those enzyme requiring that molecules as coenzymes (Eschenbrenner et al. 1995). This method shares some of the good properties of spectrophotometry and can also be integrated into an HPLC system, but it is less ? exible and the equipment not so common in a standard research laboratory. Enzymes that produce or consume gases can be assayed by differential manometry by measuring small pressure differences, due to the consumption of the gaseous substrate or the evolution of a gaseous product that can be converted into substrate or product concentrations by using the gas law. Carboxylases and decarboxylases are groups of enzymes that can be conveniently assayed by differential manometry in a respirometer. For instance, the activity of glutamate decarboxylase 14 A. Illanes (EC 4. 1. 1. 15), that catalyzes the decarboxylation of glutamic acid to ? aminobutyric acid and CO2 , has been assayed in a differential respirometer by measuring the increase in pressure caused by the formation of gaseous CO2 (O’Learys and Brummund 1974). Enzymes catalyzing reactions involving optically active compounds can be assayed by polarimetry. A compound is considered to be optically active if polarized light is rotated when passing through it. The magnitude of optical rotation is deter mined by the molecular structure and concentration of the optically active substance which has its own speci? rotation, as de? ned in Biot’s law: ? = ? 0  · l  · c (1. 7) Polarimetry is a simple and accurate method for determining optically active compounds. A polarimeter is a low cost instrument readily available in many research laboratories. The detector can be integrated into an HPLC system if separation of substrates and products of reaction is required. Invertase (? -D-fructofuranoside fructohydrolase; EC 3. 2. 1. 26), a commodity enzyme widely used in the food industry, can be conveniently assayed by polarimetry (Chen et al. 2000), since the speci? optical rotation of the substrate (sucrose) differs from that of the products (fructose plus glucose). Some depolymerizing enzymes can be conveniently assayed by viscometry. The hydrolytic action over a polymeric substrate can produce a signi? cant reduction in kinematic viscosity that can be correlated to the enzyme act ivity. Polygalacturonase activity in pectinase preparations (Gusakov et al. 2002) and endo ? 1–4 glucanase activity in cellulose preparations (Canevascini and Gattlen 1981; Illanes and Schaffeld 1983) have been determined by measuring the reduction in viscosity of the corresponding olymer solutions. A comprehensive review on methods for assaying enzyme activity has been recently published (Bisswanger 2004). Enzyme activity is expressed in units of activity. The Enzyme Commission of the International Union of Biochemistry recommends to express it in international units (IU), de? ning 1 IU as the amount of an enzyme that catalyzes the transformation of 1  µmol of substrate per minute under standard conditions of temperature, optimal pH, and optimal substrate concentration (International Union of Biochemistry). Later on, in 1972, the Commission on Biochemical Nomenclature recommended that, in order to adhere to SI units, reaction rates should be expressed in moles per second and the katal was proposed as the new unit of enzyme activity, de? ning it as the catalytic activity that will raise the rate of reaction by 1 mol/second in a speci? ed assay system (Anonymous 1979). This latter de? nition, although recommended, has some practical drawbacks. The magnitude of the katal is so big that usual enzyme activities expressed in katals are extremely small numbers that are hard to appreciate; the de? ition, on the other hand, is rather vague with respect to the conditions in which the assay should be performed. In practice, even though in some journals the use of the katal is mandatory, there is reluctance to use it and the former IU is still more widely used. 1 Introduction 15 Going back to the de? nition of IU there are some points worthwhile to comment. The magnitude of the IU is appropriate to measure most enzyme preparations, whose activities usually range from a few to a few thousands IU per unit mass or unit volume of preparation. Since enzyme activity is to be considered as the maximum catalytic potential of the enzyme, it is quite appropriate to refer it to optimal pH and optimal substrate concentration. With respect to the latter, optimal is to be considered as that substrate concentration at which the initial rate of reaction is at its maximum; this will imply reaction rate at substrate saturation for an enzyme following typical Michaelis-Menten kinetics or the highest initial reaction rate value in the case of inhibition at high substrate concentrations (see Chapter 3). With respect to pH, it is straightforward to determine the value at which the initial rate of reaction is at its maximum. This value will be the true operational optimum in most cases, since that pH will lie within the region of maximum stability. However, the opposite holds for temperature where enzymes are usually quite unstable at the temperatures in which higher initial reaction rates are obtained; actually the concept of â€Å"optimum† temperature, as the one that maximizes initial reaction rate, is quite misleading since that value usually re? cts nothing more than the departure of the linear â€Å"p† versus â€Å"t† relationship for the time of assay. For the de? nition of IU it is then more appropriate to refer to it as a â€Å"standard† and not as an â€Å"optimal† temperature. Actually, it is quite dif? cult to de? ne the right temperature to assay enzyme activity. Most probably that value will differ from the one at which the enzymatic pr ocess will be conducted; it is advisable then to obtain a mathematical expression for the effect of temperature on the initial rate of reaction to be able to transform the units of activity according to the temperature of operation (Illanes et al. 000). It is not always possible to express enzyme activity in IU; this is the case of enzymes catalyzing reactions that are not chemically well de? ned, as it occurs with depolymerizing enzymes, whose substrates have a varying and often unde? ned molecular weight and whose products are usually a mixture of different chemical compounds. In that case, units of activity can be de? ned in terms of mass rather than moles. These enzymes are usually speci? c for certain types of bonds rather than for a particular chemical structure, so in such cases it is advisable to express activity in terms of equivalents of bonds broken. The choice of the substrate to perform the enzyme assay is by no means trivial. When using an enzyme as process catalyst, the substrate can be different from that employed in its assay that is usually a model substrate or an analogue. One has to be cautious to use an assay that is not only simple, accurate and reproducible, but also signi? cant. An example that illustrates this point is the case of the enzyme glucoamylase (exo-1,4-? -glucosidase; EC 3. 2. 1. 1): this enzyme is widely used in the production of glucose syrups from starch, either as a ? al product or as an intermediate for the production of high-fructose syrups (Carasik and Carroll 1983). The industrial substrate for glucoamylase is a mixture of oligosaccharides produced by the enzymatic liquefaction of starch with ?-amylase (1,4-? -D-glucan glucanohydrolase; EC 3. 2. 1. 1). Several substrates have been used for assaying enzyme activity including high molecular weight starch, small molecular weight oligosaccharides, mal tose and maltose synthetic analogues (Barton et al. 1972; Sabin and Wasserman 16 A. Illanes 1987; Goto et al. 1998). None of them probably re? cts properly the enzyme activity over the real substrate, so it will be a matter of judgment and experience to select the most pertinent assay with respect to the actual use of the enzyme. Hydrolases are currently assayed with respect to their hydrolytic activities; however, the increasing use of hydrolases to perform reactions of synthesis in non-aqueous media make this type of assay not quite adequate to evaluate the synthetic potential of such enzymes. For instance, the protease subtilisin has been used as a catalyst for a transesteri? cation reaction that produces thiophenol as one of the products (Han et al. 004); in this case, a method based on a reaction leading to a ? uorescent adduct of thiophenol is a good system to assess the transesteri? cation potential of such proteases and is to be preferred to a conventional protease assay bas ed on the hydrolysis of a protein (Gupta et al. 1999; Priolo et al. 2000) or a model peptide (Klein et al. 1989). 1. 4 Enzyme Classes. Properties and Technological Signi? cance Enzymes are classi? ed according to the guidelines of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (IUBMB) (Anonymous 1984) into six families, based on the type of chemical reaction catalyzed. A four digit number is assigned to each enzyme by the Enzyme Commission (EC) of the IUBMB: the ? rst one denotes the family, the second denotes the subclass within a family and is related to the type of chemical group upon which it acts, the third denotes a subgroup within a subclass and is related to the particular chemical groups involved in the reaction and the forth is the correlative number of identi? cation within a subgroup. The six families are: 1. Oxidoreductases. Enzymes catalyzing oxidation/reduction reactions that involve the transfer of electrons, hydrogen or oxygen atoms. There are 22 subclasses of oxido-reductases and among them there are several of technological signi? cance, such as the dehydrogenases that oxidize a substrate by transferring hydrogen atoms to a coenzyme (NAD+ , NADP+ , How to cite Enzyme Biocatalysis, Essay examples