Identi fic ation of Ligand Binding Site and Protein-Protein Interaction Area FOCUS ON STRUCTURAL BIOLOGY Volume 8 Series Editor ROBERT KAPTEIN Bijvoet Center for Biomolecular Research, Utrecht University, The Netherlands For further volumes: http://www.springer.com/series/5990 Irena Roterman-Konieczna Editor Identi fi cation of Ligand Binding Site and Protein-Protein Interaction Area Editor Irena Roterman-Konieczna Department of Bioinformatics and Telemedicine Jagiellonian University Medical College Cracow, Poland ISSN 1571-4853 ISBN 978-94-007-5284-9 ISBN 978-94-007-5285-6 (eBook) DOI 10.1007/978-94-007-5285-6 Springer Dordrecht Heidelberg New York London Library of Congress Control Number: 2012951181 © Springer Science+Business Media Dordrecht 2013 This work is subject to copyright. 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Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com) Foreword The successful conclusion of the Human Genome Sequencing project, along with rapid progress in the development of analytical methods and high-performance computing solutions, has given rise to numerous biological databases of ever increasing volumes. Huge datasets, which nevertheless remain publicly accessible and affordable, are a crucial element of modern science. On the one hand, the ease with which research can be conducted is a great boon; on the other hand, however, one may feel somewhat overwhelmed by the immense quantity of available data. Such data is usually quite precise and detailed in nature, to the extent that modern scienti fi c equipment and measuring devices allow. Information systems which assist in processing such data appear adequate, and their storage and processing capabilities – suf fi cient to meet the needs of modern researchers. Even so, further scienti fi c breakthroughs are hindered by the relative lack of analysis methods targeted at large-scale datasets. This problem is particularly acute in analytical science, where it manifests itself as a general dearth of broad-scope methods with which to derive information (in the form of generalized models) approximating natural phenomena. The above issue is the principal challenge in systems biology – a discipline which aims to develop comprehensive methods for simulating living organisms, so as to enable i n silico experimentation on such organisms. A suitable system, properly re fl ecting the interactions and interdependencies observed in biological constructs, would support further research on speci fi c anomalies, pathologies and diseases, well known to any clinician. Before such a system can be designed and implemented, a fundamental bio- logical axiom has to be addressed – namely, the relation between genetic information (genome) and the broad spectrum of active proteins, each of which facilitates a biological process, which, together, combine to form the extremely complex structure known as the organism. Achieving this goal requires modeling three-dimensional structures of active proteins on the basis of their aminoacid sequences. The challenge lies not so much in predicting the structure itself, but rather in proposing a mechanism which leads to the generation of such structures. Another important issue, still waiting to v vi Foreword be addressed, is the challenge of determining the biological function of a given protein. We would expect numerical methods (capable of predicting ligand binding sites or catalytic centers, where reaction substrates are processed) to also suggest the means by which such “active” sites are generated. This handbook presents a review of numerical techniques used to identify ligand binding and protein complexation sites. It should be noted that there are many other theoretical studies devoted to predicting the activity of speci fi c proteins and that useful protein data can be found in numerous databases. The aim of advanced computational techniques is to identify the active sites in speci fi c proteins and moreover to suggest a generalized mechanism by which such protein-ligand (or protein-protein) interaction can be effected. The project EFI similar to CASP and CAPRI has been initiated in regard to enzymatic active site recognition (http://enzymefunction.org). Developing such tools is not an easy task – it requires extensive expertise in the area of molecular biology as well as a fi rm grasp of numerical modeling methods. Thus, it is often viewed as a prime candidate for interdisciplinary research. Gatenby R.A. and Maini P.K. (2003) postulate the creation of an entirely new branch of science called “mathematical ontology” (see “Cancer summed up”, Nature , 421, p. 321), which would bring together representatives of both – seemingly unconnected – disciplines. It is hoped that such close collaboration would lead to new systems enabling scientists to better simulate the properties and functioning of living organisms. Cracow, 2012 Irena Roterman-Konieczna Contents 1 SuMo: A Tool for Protein Function Inference Based on 3D Structures Comparisons ..................................................... 1 Julie-Anne Chemelle, Emmmanuel Bettler, Christophe Combet, Raphaël Terreux, Christophe Geourjon, and Gilbert Deléage 2 Identification of Pockets on Protein Surface to Predict Protein–Ligand Binding Sites ................................................ 25 Bingding Huang 3 Can the Structure of the Hydrophobic Core Determine the Complexation Site? ............................................................................. 41 Mateusz Banach, Leszek Konieczny, and Irena Roterman-Konieczna 4 Comparative Analysis of Techniques Oriented on the Recognition of Ligand Binding Area in Proteins ........................ 55 Paweł Alejster, Mateusz Banach, Wiktor Jurkowski, Damian Marchewka, and Irena Roterman-Konieczna 5 Docking Predictions of Protein-Protein Interactions and Their Assessment: The CAPRI Experiment ................................... 87 Joël Janin 6 Prediction of Protein-Protein Binding Interfaces .................................. 105 Damian Marchewka, Wiktor Jurkowski, Mateusz Banach, and Irena Roterman-Konieczna 7 Support for Cooperative Experiments in e-Science: From Scienti fi c Work fl ows to Knowledge Sharing ............................... 135 Adam S. Z. Belloum , Reginald Cushing, Spiros Koulouzis, Vladimir Korkhov, Dmitry Vasunin, Victor Guevara-Masis, Zhiming Zhao, and Marian Bubak vii viii Contents Glossary ........................................................................................................... 161 Index ................................................................................................................. 165 Contributors Paweł Alejster Department of Bioinformatics and Telemedicine , Jagiellonian University – Medical College , C racow , Poland Mateusz Banach Department of Bioinformatics and Telemedicine , Jagiellonian University – Medical College , C racow , Poland Adam S. Z. Belloum The Informatics Institue , University of Amsterdam , Amsterdam , The Netherlands Emmmanuel Bettler Université Lyon 1 , CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Marian Bubak AGH University of Science and Technology Krakow, Poland and the Informatics Institute , University of Amsterdam , Amsterdam , The Netherlands Julie-Anne Chemelle Université Lyon 1 , CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Christophe Combet Université Lyon 1 , C NRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Reginald C ushing The Informatics Institute , University of Amsterdam , Amsterdam , The Netherlands Gilbert Deléage Université Lyon 1, CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Christophe Geourjon Université Lyon 1 , CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Victor Guevara-Masis The Informatics Institute , University of Amsterdam , Amsterdam , The Netherlands Bingding Huang Systems Biology Division, Zhejiang-California International NanoSystems Institute , Zhejiang University , Hangzhou , China ix x Contributors Bioinformatics Group, Biotechnology Center , Technical University of Dresden, Dresden , Germany Joël Janin IBBMC , Université Paris-Sud , Orsay , France Wiktor Jurkowski Computational Biology Group, Luxembourg Centre for Systems Biomedicine , University of Luxembourg , Esch-Belval , Luxembourg Leszek Konieczny Department of Bioinformatics and Telemedicine , Jagiellonian University – Medical College , Cracow , P oland Vladimir Korkhov Faculty of Applied Math and Control Processes, St. Petersburg State University , Saint Petersburg , Russia Spiros Koulouzis The Informatics Institute , University of Amsterdam , Amsterdam , The Netherlands Damian Marchewka Department of Bioinformatics and Telemedicine , Jagiellonian University – Medical College , Cracow , P oland Astronomy and Applied Computer Science , Jagiellonian University , Cracow , Poland Irena Roterman-Konieczna Department of Bioinformatics and Telemedicine , Jagiellonian University – Medical College , Cracow , Poland Raphaël Terreux Université Lyon 1 , CNRS, UMR 5086; Bases Moléculaires et Structurales des Systèmes Infectieux , Lyon , France Dmitry Vasunin Faculty of Applied Math and Control Processes, St. Petersburg State University , Saint Petersburg , Russia Zhiming Zhao The Informatics Institute , University of Amsterdam , Amsterdam , The Netherlands