On the Engineering of Proteins: Methods and Applications for Carbohydrate-Active Enzymes
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New Methods for the Prediction and Classification of Protein Domains
New Methods for the Prediction and Classi¯cation of Protein Domains Jan Erik Gewehr MÄunchen2007 New Methods for the Prediction and Classi¯cation of Protein Domains Jan Erik Gewehr Dissertation an der FakultÄatfÄurMathematik und Informatik der Ludwig{Maximilians{UniversitÄat MÄunchen vorgelegt von Jan Erik Gewehr aus LÄubeck MÄunchen, den 01.10.2007 Erstgutachter: Prof. Dr. Ralf Zimmer Zweitgutachter: Prof. Dr. Dmitrij Frishman Tag der mÄundlichen PrÄufung:19.12.2007 Contents 1 Motivation and Overview 1 1.1 The Bene¯t of Protein Structure Prediction ................. 1 1.2 Thesis Outline .................................. 3 2 Introduction to Protein Structure Prediction 7 2.1 Protein Structures and Related Databases .................. 7 2.1.1 From Primary to Tertiary Structure .................. 7 2.1.2 Structure-Related Databases ...................... 8 2.2 Assignment of Protein Domains ........................ 10 2.2.1 An Old Problem ............................ 10 2.2.2 Comparison of Domain Assignments . 11 2.3 Structure Prediction Categories ........................ 13 2.3.1 Comparative Modeling ......................... 13 2.3.2 Fold Recognition ............................ 14 2.3.3 Ab Initio ................................. 15 2.4 Community-Wide E®orts ............................ 15 2.4.1 Community-Wide Experiments .................... 15 2.4.2 Structural Genomics and Structure Prediction . 16 2.5 Alignment Methods ............................... 16 2.5.1 Sequence Alignment .......................... 16 2.5.2 Alignment Methods used in this Work . 19 3 Selection of Fold Classes based on Secondary Structure Elements 23 3.1 Introduction ................................... 23 3.2 Material ..................................... 25 3.2.1 Training and Test Data ......................... 25 3.2.2 Quoted Methods ............................ 27 3.3 Preselection of Fold Classes .......................... 28 3.3.1 Secondary Structure Element Alignment (SSEA) . 28 3.3.2 Selection Strategies based on SSEA . -
(12) United States Patent (10) Patent No.: US 8,715,988 B2 Arnold Et Al
US008715988B2 (12) United States Patent (10) Patent No.: US 8,715,988 B2 Arnold et al. (45) Date of Patent: May 6, 2014 (54) ALKANE OXIDATION BY MODIFIED 2003, OO77795 A1 4, 2003 Wilson HYDROXYLASES 2003/OO77796 A1 4/2003 Crotean 2003. O100744 A1 5/2003 Farinas 2005, 0037411 A1 2/2005 Arnold et al. (75) Inventors: Frances Arnold, Pasadena, CA (US); 2005/00591.28 A1 3, 2005 Arnold et al. Peter Meinhold, Pasadena, CA (US); 2005/0202419 A1 9, 2005 Cirino et al. Matthew W. Peters, Pasadena, CA 2008/0293928 A1 11/2008 Farinas et al. (US); Rudi Fasan, Brea, CA (US); Mike M. Y. Chen, Pasadena, CA (US) FOREIGN PATENT DOCUMENTS EP O 505 198 A1 9, 1992 (73) Assignee: California Institute of Technology, EP O 752 008 2, 1997 Pasadena, CA (US) EP O932 670 8, 2000 WO WO 89.03424 A1 4f1989 (*) Notice: Subject to any disclaimer, the term of this WO WO95/22625 A1 8, 1995 patent is extended or adjusted under 35 WO WO97, 16553 A1 5, 1997 WO WO97/20078 A1 6, 1997 U.S.C. 154(b) by 999 days. WO WO 97.35957 A1 Of 1997 WO WO97/35966 A1 10, 1997 (21) Appl. No.: 11/697,404 WO WO 98.27 230 A1 6, 1998 WO WO 98,31837 A1 7, 1998 (22) Filed: Apr. 6, 2007 WO WO98/41653 A1 9, 1998 WO WO 98.42832 A1 10, 1998 Prior Publication Data WO WO99,60096 A2 11/1999 (65) WO WOOOOO632 A1 1, 2000 US 2008/0057577 A1 Mar. -
From Directed Evolution to Computational Enzyme Engineering—A Review
Received: 19 August 2019 Revised: 14 October 2019 Accepted: 19 October 2019 DOI: 10.1002/aic.16847 TRIBUTE TO FOUNDERS: FRANCES ARNOLD. BIOMOLECULAR ENGINEERING, BIOENGINEERING, BIOCHEMICALS, BIOFUELS, AND FOOD From directed evolution to computational enzyme engineering—A review Ratul Chowdhury | Costas D. Maranas Department of Chemical Engineering, The Pennsylvania State University, University Park, Abstract Pennsylvania Nature relies on a wide range of enzymes with specific biocatalytic roles to carry out Correspondence much of the chemistry needed to sustain life. Enzymes catalyze the interconversion of a Costas D. Maranas, Department of Chemical vast array of molecules with high specificity—from molecular nitrogen fixation to the syn- Engineering, The Pennsylvania State University, University Park, PA 16802. thesis of highly specialized hormones and quorum-sensing molecules. Ever increasing Email: [email protected] emphasis on renewable sources for energy and waste minimization has turned enzymes Funding information into key industrial workhorses for targeted chemical conversions. Modern enzymology is Division of Chemical, Bioengineering, central to not only food and beverage manufacturing processes but also finds relevance in Environmental, and Transport Systems, Grant/ Award Number: CBET-1703274 countless consumer product formulations such as proteolytic enzymes in detergents, amy- lases for excess bleach removal from textiles, proteases in meat tenderization, and lactoperoxidases in dairy products. Herein, we present an overview of enzyme science and engineering milestones and the emergence of directed evolution of enzymes for which the 2018 Nobel Prize in Chemistry was awarded to Dr. Frances Arnold. KEYWORDS biocatalysis, computational protein design, directed evolution, enzyme engineering, mutagenesis 1 | BACKGROUND O:S to be approximately 1:1.58:0.28:0.3:0.01 (experiments performed by Johannes Mulder)3 and reported that some of the proteins are cat- 1.1 | Background of enzymes, enzymology, and alytic. -
Engineering Enzyme Systems by Recombination
Engineering Enzyme Systems by Recombination Thesis by Devin Lee Trudeau In Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy CALIFORNIA INSTITUTE OF TECHNOLOGY Pasadena, California 2014 (Defended December 11, 2013) 2014 Devin L. Trudeau All Rights Reserved iii ACKNOWLEDGEMENTS I’d like to thank my advisor Frances Arnold for seeing me through four years of failure and success. Frances has continually challenged my ideas and work, which has taught me how to be a better scientist, thinker, and bioengineer. In her lab I’ve had the freedom to pursue many different ideas, and interact with people of diverse personalities and research interests. The Arnold lab has been my home these last few years. I’d like to thank Florence Mingardon and Yousong Ding for being my two mentors as I was learning the art of protein engineering. Toni Lee has been a great collaborator on our endoglucanase project, and I’m happy that our efforts were as synergistic as our enzymes. Matthew Smith and Indira Wu have both been invaluable sources of advice on cellulase engineering. Sabrina Sun was a pleasure to work with over the course of two summers and a fourth-year project. Joseph Meyerowitz was my collaborator on the aldehyde tolerance project. Sabine Bastian kept the lab running smoothly, and has provided excellent advice on directed evolution methodology. Jackson Cahn, Ardemis Boghossian, Phil Romero, Ryan Lauchli, John McIntosh, Martin Engqvist, Chris Farwell, and Jane Wang have been great feedback for my (mostly crazy) ideas— and good friends. I’d like to thank Frank Chang and the rest of my biofuels collaborators in the Ho and Chao labs at Academia Sinica. -
An XML Based Semantic Protein Map
An XML based semantic protein map A. S. Sidhu, T. S. Dillon & H. Setiawan Faculty of Information Technology, University of Technology, Sydney Abstract From the nature of the algorithms for data mining we note that an XML framework can be represented using graph matching algorithms. Various techniques currently exist for graph matching of data structures such as the Adjacency Matrix or Algebraic Representation of Graphs. The Graph Representation can be easily converted to a string representation. Both Graph and String Representations miss semantic relationships that exist in the data. These relationships can be captured by using semi-structured XML as a representation format. We already have an approach to integrate different data formats into a Unified Database. The technique is successfully applied to diverse Protein Databases in a Bioinformatics Domain. An XML representation of this comprehensive database preserving order and semantic relationships is already generated. In this paper we propose an approach to a Semantic Protein Map (PMAP) by building a shared ontology on our structured database model. This ontology can be used by various Bioinformatics researchers from one single site. This site will host mirrors of Protein Databases along with BIODB and have tools on Similarity Searching. Keywords: bioinformatics, protein structures, biomedical ontologies, data integration, data semantics, semantic web. 1 Introduction Bioinformatics is the field of science in which, biology, computer science, and information technology merge to form a single discipline. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology can be discerned.