Prediction of Protein Secondary Structure

315 Pages·2017·12.1 MB·English

by  Yaoqi Zhou

Methods in
Molecular Biology 1484
Yaoqi Zhou
Andrzej Kloczkowski
Eshel Faraggi
Yuedong Yang Editors
Prediction of
Protein Secondary
Structure
M M B
ETHODS IN OLECULAR IOLOGY
Series Editor
John M. Walker
School of Life and Medical Sciences
University of Hertfordshire
Hatfield, Hertfordshire , AL10 9AB, UK
For further volumes:
http://www.springer.com/series/7651
Prediction of Protein Secondary
Structure
Edited by
Yaoqi Zhou
Institute for Glycomics and School of Information and Communication Technology,
Griffith University, Southport, QLD, Australia
Andrzej Kloczkowski
Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH, USA;
Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH, USA
Eshel Faraggi
Department of Biochemistry and Molecular Biology, Indiana University School of Medicine,
Indianapolis, IN, USA; Research and Information Systems, LLC, Indianapolis, IN, USA
Yuedong Yang
Institute for Glycomics and School of Information and Communication Technology,
Griffith University, Southport, QLD, Australia
Editors
Yaoqi Zhou Andrzej Kloczkowski
Institute for Glycomics and School of Information Battelle Center for Mathematical Medicine
and Communication Technology Nationwide Children’s Hospital
Griffith University Columbus , OH , USA
Southport, QLD, Australia
Department of Pediatrics
The Ohio State University College of Medicine
Eshel Faraggi
Columbus, OH, USA
Department of Biochemistry
and Molecular Biology
Yuedong Yang
Indiana University School of Medicine
Institute for Glycomics and School of Information
Indianapolis, IN , USA
and Communication Technology
Research and Information Systems, LLC Griffith University
Indianapolis, IN, USA Southport, QLD, Australia
ISSN 1064-3745 ISSN 1940-6029 (electronic)
Methods in Molecular Biology
ISBN 978-1-4939-6404-8 ISBN 978-1-4939-6406-2 (eBook)
DOI 10.1007/978-1-4939-6406-2
Library of Congress Control Number: 2016949704
© Springer Science+Business Media New York 2 017
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Prefa ce
One of the most important challenges in molecular biology is to fi gure out how the
one- dimensional (1D) sequence of amino acid residues in a protein at a physiological con-
dition specifi es its unique, functional three-dimensional (3D) structure. Despite more than
50 years of effort, reliable computational protein models with experimental resolution
remain out of reach, except for homology models that are based on the structures of highly
similar sequences. To overcome the challenge of prediction from 1D to 3D, many 1D to
1D methods have been developed as an intermediate step or a substitute for 1D to 3D
prediction. These 1D quantities can be either structural or functional properties character-
ized by a one-dimensional vector along the protein sequence. One prominent example is
protein secondary structure where protein backbone structure is annotated by a few states
such as helices, sheets, or coils. Protein backbone structure can also be characterized by
torsion angles. In addition to backbone structural properties, protein structures can be
characterized by global structural properties: Properties that depend on interactions
between multiple residues that are far apart in the sequence. One such example is the sol-
vent accessible surface area, relevant to tertiary packing and function of proteins. More
recently, predicting one-dimensional functional properties (functional sites in particular)
from protein sequences has received increasing attention.
This book starts from secondary structure prediction based on sequence only (GOR,
Chapters 1 and 2 and single helix prediction, Chapter 3 ) , followed by secondary structure
prediction based on evolution information (CDM, Chapter 4 , SPINE-X, Chapter 5 , and
SPIDER2, Chapter 6 ) . In addition to secondary structure, SPINE-X and SPIDER2 also
predict solvent accessible surface areas and backbone torsion angles. The latter is reviewed
in Chapter 7 . Predicted secondary structures are utilized in model building (Chapters 8 and
9 ) . Next, a few chapters focus on global structural properties (solvent accessibility in
Chapter 10 ; intrinsically disordered regions in Chapters 1 1 and 12 ; and protein fl exibility
in Chapter 13 ) . Functional properties are predicted in Chapter 1 4 (DNA/RNA-binding
sites), Chapter 15 (RNA-binding residues), Chapter 1 6 (protein-binding sites), Chapter 1 7
(B-cell epitopes), Chapter 18 (phosphorylation sites), and Chapter 1 9 (post-translation
modifi cations). Chapter 2 0 describes a tool for visualizing interior and protruding regions
in proteins. These chapters represent a fraction of the excellent methods available in the
literature. We hope that this collection will provide a guide to a few current state-of-the-art
techniques that are useful for computational and experimental biologists.
Southport, QLD, Australia Yaoqi Zhou
Columbus, OH, USA Andrzej Kloczkowski
Indianapolis, IN, USA Eshel Faraggi
Southport, QLD, Australia Yuedong Yang
v
Contents
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Contributors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i x
1 W here the Name “GOR” Originates: A Story. . . . . . . . . . . . . . . . . . . . . . . . . 1
Jean Garnier
2 T he GOR Method of Protein Secondary Structure Prediction
and Its Application as a Protein Aggregation Prediction Tool . . . . . . . . . . . . . 7
Maksim Kouza , E shel Faraggi , A ndrzej Kolinski ,
and Andrzej Kloczkowski
3 C onsensus Prediction of Charged Single Alpha-Helices with CSAHserver. . . . 2 5
Dániel Dudola , G ábor Tóth , L ászló Nyitray , and Zoltán Gáspári
4 P redicting Protein Secondary Structure Using Consensus
Data Mining (CDM) Based on Empirical Statistics and Evolutionary
Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 5
Gaurav Kandoi , S umudu P. Leelananda , R obert L. Jernigan ,
and Taner Z . Sen
5 A ccurate Prediction of One-Dimensional Protein Structure Features
Using SPINE-X . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 5
Eshel Faraggi and Andrzej Kloczkowski
6 S PIDER2: A Package to Predict Secondary Structure,
Accessible Surface Area, and Main-Chain Torsional Angles
by Deep Neural Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
Yuedong Yang , R hys Heffernan , K uldip Paliwal , J ames Lyons ,
Abdollah Dehzangi , A lok Sharma , J ihua Wang , A bdul Sattar ,
and Yaoqi Zhou
7 B ackbone Dihedral Angle Prediction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Olav Zimmermann
8 O ne-Dimensional Structural Properties of Proteins in the Coarse-Grained
CABS Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3
Sebastian Kmiecik and Andrzej Kolinski
9 A ssessing Predicted Contacts for Building Protein
Three-D imensional Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Badri Adhikari , D ebswapna Bhattacharya , R enzhi Cao ,
and Jianlin Cheng
10 F ast and Accurate Accessible Surface Area Prediction Without
a Sequence Profile. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Eshel Faraggi, Maksim Kouza, Yaoqi Zhou, and Andrzej Kloczkowski
11 H ow to Predict Disorder in a Protein of Interest. . . . . . . . . . . . . . . . . . . . . . . 1 37
Vladimir N. Uversky
vii
viii Contents
12 I ntrinsic Disorder and Semi-disorder Prediction by SPINE-D . . . . . . . . . . . . . 1 59
Tuo Zhang , E shel Faraggi , Z hixiu Li , and Yaoqi Zhou
13 P redicting Real-Valued Protein Residue Fluctuation Using FlexPred. . . . . . . . 1 75
Lenna Peterson , M ichal Jamroz , A ndrzej Kolinski , and Daisuke Kihara
14 P rediction of Disordered RNA, DNA, and Protein Binding
Regions Using DisoRDPbind . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 87
Zhenling Peng , C hen Wang , V ladimir N. Uversky , and Lukasz Kurgan
15 S equence-Based Prediction of RNA-Binding Residues in Proteins. . . . . . . . . . 2 05
Rasna R. Walia , Y asser EL-Manzalawy , V asant G. Honavar ,
and Drena Dobbs
16 C omputational Approaches for Predicting Binding Partners,
Interface Residues, and Binding Affinity of Protein–Protein Complexes. . . . . . 237
K. Yugandhar and M. Michael Gromiha
17 I n Silico Prediction of Linear B-Cell Epitopes on Proteins. . . . . . . . . . . . . . . . 2 55
Yasser EL-Manzalawy , D rena Dobbs , and Vasant G. Honavar
18 P rediction of Protein Phosphorylation Sites by Integrating Secondary
Structure Information and Other One-D imensional Structural Properties . . . . 265
Yongchao Dou , B o Yao , and Chi Zhang
19 P redicting Post-Translational Modifications from Local Sequence
Fragments Using Machine Learning Algorithms: Overview
and Best Practices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
Marcin Tatjewski , M arcin Kierczak , and Dariusz Plewczynski
20 C X, DPX, and PCW: Web Servers for the Visualization of Interior
and Protruding Regions of Protein Structures in 3D and 1D. . . . . . . . . . . . . . 301
Balázs Ligeti , R oberto Vera , J ános Juhász , and Sándor Pongor
Index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
Contributors
BADRI A DHIKARI • Computer Science Department, University of Missouri , Columbia,
MO , USA
DEBSWAPNA BHATTACHARYA • Computer Science Department, U niversity of Missouri ,
Columbia, M O, U SA
RENZHI CAO • Computer Science Department, U niversity of Missouri , C olumbia,
MO , U SA
JIANLIN CHENG • Computer Science Department, U niversity of Missouri , C olumbia, M O,
USA
ABDOLLAH DEHZANGI • Department of Psychiatry, Medical Research Center, U niversity of
Iowa , I owa City, I A, U SA
DRENA DOBBS • Genetics, Development and Cell Biology Department, I owa State
University , A mes , I A, U SA
YONGCHAO DOU • School of Biological Sciences, U niversity of Nebraska–Lincoln , L incoln,
NE , U SA
DÁNIEL DUDOLA • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary
YASSER EL-MANZALAWY • College of Information Sciences and Technology, P ennsylvania
State University , U niversity Park, P A, U SA
ESHEL FARAGGI • Department of Biochemistry and Molecular Biology, I ndiana University
School of Medicine , I ndianapolis, I N , U SA; Research and Information Systems, LLC,
Indianapolis, IN, USA
JEAN GARNIER • IUPAB, International Council for Science (ICSU) , P aris , F rance
ZOLTÁN GÁSPÁRI • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary
M. MICHAEL GROMIHA • Department of Biotechnology, Bhupat and Jyoti Mehta School of
Biosciences, I ndian Institute of Technology Madras , C hennai, T amilnadu, I ndia
RHYS HEFFERNAN • Signal Processing Laboratory, School of Engineering, G riffi th University ,
Brisbane, Q LD , A ustralia
VASANT G. HONAVAR • College of Information Sciences and Technology, P ennsylvania State
University , U niversity Park, P A, U SA
MICHAL JAMROZ • Laboratory of Theory of Biopolymers, Faculty of Chemistry , U niversity of
Warsaw , W arsaw, P oland
ROBERT L. JERNIGAN • Bioinformatics and Computational Biology Program, Iowa State
University, Ames, IA, USA; Department of Biochemistry, Biophysics, and Molecular
Biology , I owa State University , A mes , I A, U SA
JÁNOS JUHÁSZ • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary
GAURAV KANDOI • Bioinformatics and Computational Biology Program , I owa State
University , A mes , I A, U SA; Department of Electrical and Computer Engineering,
Iowa State University, Ames, IA, USA
ix
x Contributors
MARCIN KIERCZAK • Science for Life Laboratory, Department of Medical Biochemistry and
Microbiology, U ppsala University , U ppsala , S weden
DAISUKE KIHARA • Department of Biological Sciences, College of Science, P urdue University ,
West Lafayette, I N , U SA; Department of Computer Science, College of Science,
Purdue University, West Lafayette, IN, USA
ANDRZEJ KLOCZKOWSKI • Battelle Center for Mathematical Medicine, N ationwide
Children’s Hospital , C olumbus, O H , U SA; Department of Pediatrics, The Ohio State
University College of Medicine, Columbus, OH, USA
SEBASTIAN KMIECIK • Faculty of Chemistry , U niversity of Warsaw , W arsaw, P oland
ANDRZEJ KOLINSKI • Faculty of Chemistry , U niversity of Warsaw , W arsaw, P oland
MAKSIM KOUZA • Faculty of Chemistry , U niversity of Warsaw , W arsaw, P oland
LUKASZ KURGAN • Department of Computer Science, V irginia Commonwealth University ,
Richmond, V A, U SA
SUMUDU P. LEELANANDA • Battelle Center for Mathematical Medicine, T he Research
Institute at Nationwide Children’s Hospital , C olumbus, O H , U SA
ZHIXIU LI • Translational Genomics Group, I nstitute of Health and Biomedical
Innovation, Queensland University of Technology at Translational Research Institute ,
QLD , A ustralia
BALÁZS LIGETI • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary
JAMES LYONS • Signal Processing Laboratory, School of Engineering, G riffi th University ,
Brisbane, Q LD , A ustralia
LÁSZLÓ NYITRAY • Department of Biochemistry , E ötvös Loránd University , B udapest,
Hungary
KULDIP PALIWAL • Signal Processing Laboratory, School of Engineering, G riffi th University ,
Brisbane, Q LD , A ustralia
ZHENLING PENG • Center for Applied Mathematics, T ianjin University , T ianjin, C hina
LENNA P ETERSON • Department of Biological Sciences, College of Science, Purdue University ,
West Lafayette, I N , U SA
DARIUSZ PLEWCZYNSKI • Centre of New Technologies, U niversity of Warsaw , W arsaw, P oland
SÁNDOR PONGOR • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary
ABDUL SATTAR • Institute for Integrated and Intelligent Systems, G riffi th University ,
Brisbane, QLD, Australia; National ICT Australia (NICTA), Brisbane, QLD, Australia
TANER Z. SEN • Bioinformatics and Computational Biology Program, Iowa State
University, Ames, IA, USA; Department of Genetics, Development and Cell Biology , I owa
State University , A mes , I A, U SA
ALOK SHARMA • Institute for Integrated and Intelligent Systems, Griffi th University,
Brisbane, QLD, Australia; School of Engineering and Physics, U niversity of the South
Pacifi c , S uva, F iji
MARCIN TATJEWSKI • Institute of Computer Science, P olish Academy of Sciences , W arsaw,
Poland; Centre of New Technologies, University of Warsa, Warsaw, Poland
GÁBOR TÓTH • Department of Medical and Biological Sciences, National Research,
Development and Innovation Offi ce , B udapest, H ungary
VLADIMIR N. UVERSKY • Department of Molecular Medicine and USF Health Byrd
Alzheimer's Research Institute, Morsani College of Medicine, U niversity of South Florida ,
Tampa, F L, U SA; Institute for Biological Instrumentation, Russian Academy of Sciences,
Moscow Region, Russian Federation; Laboratory of Structural Dynamics, Stability and
Contributors xi
Folding of Proteins, Institute of Cytology, Russian Academy of Sciences, Russian
Federation
ROBERTO VERA • Faculty of Information Technology and Bionics, P ázmány Péter Catholic
University , B udapest, H ungary; National Center for Biotechnology Information,
National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
RASNA R. WALIA • USDA-ARS , A mes , I A, U SA
CHEN WANG • Department of Electrical and Computer Engineering, U niversity of Alberta ,
Edmonton, A B , C anada; Department of Computer Science, Virginia Commonwealth
University, Richmond, VA, USA
JIHUA WANG • Shandong Provincial Key Laboratory of Functional
Macromolecular Biophysics, D ezhou University , D ezhou, S handong, C hina
YUEDONG YANG • Institute for Glycomics and School of Information and Communication
Technology, G riffi th University , S outhport, Q LD , A ustralia
BO YAO • School of Biological Sciences, U niversity of Nebraska–Lincoln , L incoln, N E , U SA
K. YUGANDHAR • Department of Biotechnology, Bhupat and Jyoti Mehta School of
Biosciences, I ndian Institute of Technology Madras , C hennai, T amilnadu, I ndia
CHI ZHANG • School of Biological Sciences, U niversity of Nebraska–Lincoln , L incoln,
NE , U SA
TUO ZHANG • Department of Microbiology and Immunology, W eill Cornell Medical
College , N ew York, N Y , U SA
YAOQI ZHOU • Institute for Glycomics and School of Information and Communication
Technology, G riffi th University , S outhport, Q LD , A ustralia
OLAV ZIMMERMANN • Jülich Supercomputing Centre (JSC), I nstitute for Advanced
Simulation (IAS), Forschungszentrum Jülich GmbH , J ülich , G ermany