Bioinformatics and Drug Discovery

New Strategies in Drug Discovery Eliot H. Ohlstein, Anthony G. Johnson, John D. Elliot, and Anne M. Romanic Basic Microarray Analysis: Strategies for Successful Experiments Scott A. Ness From Microarray to Biological Networks: Analysis of Gene Expression Profiles Xiwei Wu and T. Gregory Dewey Microarray Analysis in Drug Discovery and Clinical Applications Siqun Wang and Qiong Cheng Ontology-Driven Approaches to Analyzing Data in Functional Genomics Francisco Azuaje, Fatima Al-Shahrour, and Joaquin Dopazo Gene Evolution and Drug Discovery James O. McInerney, Caroline S. Finnerty, Jennifer M. Commins, and Gayle K. Philip Standardization of Microarray and Pharmacogenomics Data Casey S. Husser, Jeffrey R. Buchhalter, O. Scott Raffo, Amnon Shabo, Steven H. Brown, Karen E. Lee, and Peter L. Elkin Clinical Applications of Bioinformatics, Genomics, and Pharmacogenomics Omer Iqbal and Jawed Fareed Protein Interactions Probed With Mass Spectrometry Suma Kaveti and John R. Engen Discovering New Drug Targeting Sites on Flexible Multidomain Protein Kinases: Combining Segmental Isotopic and Site-Directed Spin Labeling for Nuclear Magnetic Resonance Dectection of Interfacial Clefts Thomas K. Harris Nuclear Magnetic Resonance-Based Screening Methods for Drug Discovery Laurel O. Sillerud and Richard S. Larson Receptor-Binding Sites: Bioinformatic Approaches Darren R. Flower In Silico Protein Design: Fitting Sequence Onto Structure Bassil I. Dahiyat Chemical Database Preparation for Compound Acquisition or Virtual Screening Cristian G. Bologna, Marius M. Olah, and Tudor I. Oprea Bioinformatics Platform Development: From Gene to Lead Compound Alexis S. Ivanov, Alexander V. Veselovsky, Alexander V. Dubanov, and Vladlen S. Skvortsov Index

[1]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[2]  R. Nussinov,et al.  Relationship between ion pair geometries and electrostatic strengths in proteins. , 2002, Biophysical journal.

[3]  G. Klebe,et al.  A new method to detect related function among proteins independent of sequence and fold homology. , 2002, Journal of molecular biology.

[4]  Weida Tong,et al.  Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models , 2003, J. Chem. Inf. Comput. Sci..

[5]  A Joshua Wand,et al.  Improved side‐chain prediction accuracy using an ab initio potential energy function and a very large rotamer library , 2004, Protein science : a publication of the Protein Society.

[6]  T. Klabunde Chemogenomic approaches to drug discovery: similar receptors bind similar ligands , 2007, British journal of pharmacology.

[7]  M. DePristo,et al.  Ab initio construction of polypeptide fragments: Accuracy of loop decoy discrimination by an all‐atom statistical potential and the AMBER force field with the Generalized Born solvation model , 2003, Proteins.

[8]  Jill E. Gready,et al.  Identification and energetic ranking of possible docking sites for pterin on dihydrofolate reductase , 1998, J. Comput. Aided Mol. Des..

[9]  Robin Taylor,et al.  SuperStar: a knowledge-based approach for identifying interaction sites in proteins. , 1999, Journal of molecular biology.

[10]  B. Honig,et al.  A rapid finite difference algorithm, utilizing successive over‐relaxation to solve the Poisson–Boltzmann equation , 1991 .

[11]  D. Scott Linthicum,et al.  PROGEN: An automated modelling algorithm for the generation of complete protein structures from the α-carbon atomic coordinates , 1993, J. Comput. Aided Mol. Des..

[12]  Shunzhou Wan,et al.  Large‐scale molecular dynamics simulations of HLA‐A*0201 complexed with a tumor‐specific antigenic peptide: Can the α3 and β2m domains be neglected? , 2004, J. Comput. Chem..

[13]  A. Petros,et al.  Three-dimensional structure of the FK506 binding protein/ascomycin complex in solution by heteronuclear three- and four-dimensional NMR. , 1993, Biochemistry.

[14]  P. Christen,et al.  Empirical calculation of the relative free energies of peptide binding to the molecular chaperone DnaK , 2000, Proteins.

[15]  Gennady M Verkhivker,et al.  Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming. , 1995, Chemistry & biology.

[16]  C. Breneman,et al.  Prediction of protein retention in ion-exchange systems using molecular descriptors obtained from crystal structure. , 2001, Analytical chemistry.

[17]  K. P. Murphy,et al.  Variability in the pKa of histidine side‐chains correlates with burial within proteins , 2002, Proteins.

[18]  Kuo-Chen Chou,et al.  Support vector machines for predicting HIV protease cleavage sites in protein , 2002, J. Comput. Chem..

[19]  E. Jacoby,et al.  Chemogenomics: an emerging strategy for rapid target and drug discovery , 2004, Nature Reviews Genetics.

[20]  Rajarshi Guha,et al.  Structure—Activity Landscape Index: Identifying and Quantifying Activity Cliffs. , 2008 .

[21]  P. C. Viswanathan,et al.  A sodium-channel mutation causes isolated cardiac conduction disease , 2001, Nature.

[22]  Z. Xiang,et al.  Extending the accuracy limits of prediction for side-chain conformations. , 2001, Journal of molecular biology.

[23]  Roland L. Dunbrack,et al.  Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool. , 1997, Journal of molecular biology.

[24]  B. Shoichet,et al.  Flexible ligand docking using conformational ensembles , 1998, Protein science : a publication of the Protein Society.

[25]  John P. Overington,et al.  An assessment of COMPOSER: a rule-based approach to modelling protein structure. , 1990, Biochemical Society symposium.

[26]  David S. Wishart,et al.  DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..

[27]  G Schneider,et al.  The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: de novo design of an idealized leader peptidase cleavage site. , 1994, Biophysical journal.

[28]  A Caflisch,et al.  Monte Carlo docking of oligopeptides to proteins , 1992, Proteins.

[29]  M Rarey,et al.  Detailed analysis of scoring functions for virtual screening. , 2001, Journal of medicinal chemistry.

[30]  Giuseppina C. Gini,et al.  The Importance of Scaling in Data Mining for Toxicity Prediction , 2002, J. Chem. Inf. Comput. Sci..

[31]  Bin Chen,et al.  PubChem BioAssays as a data source for predictive models. , 2010, Journal of molecular graphics & modelling.

[32]  A W Munro,et al.  The TB structural genomics consortium: a resource for Mycobacterium tuberculosis biology. , 2003, Tuberculosis.

[33]  David Weininger,et al.  SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules , 1988, J. Chem. Inf. Comput. Sci..

[34]  D. Lipman,et al.  Rapid similarity searches of nucleic acid and protein data banks. , 1983, Proceedings of the National Academy of Sciences of the United States of America.

[35]  Mika A. Kastenholz,et al.  GRID/CPCA: a new computational tool to design selective ligands. , 2000, Journal of medicinal chemistry.

[36]  S. Miyamoto,et al.  An efficient method for reconstructing protein backbones from alpha-carbon coordinates. , 2001, Journal of molecular graphics & modelling.

[37]  H Buerger,et al.  Demystified … Tissue microarray technology , 2003, Molecular pathology : MP.

[38]  S. Wodak,et al.  Deviations from standard atomic volumes as a quality measure for protein crystal structures. , 1996, Journal of molecular biology.

[39]  C. Frömmel,et al.  The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. , 1996, Journal of molecular biology.

[40]  M. Karplus,et al.  pKa's of ionizable groups in proteins: atomic detail from a continuum electrostatic model. , 1990, Biochemistry.

[41]  D R Flower,et al.  SERF: a program for accessible surface area calculations. , 1997, Journal of molecular graphics & modelling.

[42]  T Lengauer,et al.  Two-stage method for protein-ligand docking. , 1999, Journal of medicinal chemistry.

[43]  M. Murcko,et al.  Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. , 1999, Journal of medicinal chemistry.

[44]  David J. States,et al.  Conformational model for binding site recognition by the E.coli MetJ transcription factor , 2001, Bioinform..

[45]  Valentin A. Ilyin,et al.  LigBase: a database of families of aligned ligand binding sites in known protein sequences and structures , 2002, Bioinform..

[46]  Collin M. Stultz,et al.  Dynamic ligand design and combinatorial optimization: Designing inhibitors to endothiapepsin , 2000, Proteins.

[47]  H. Kröger,et al.  [Protein synthesis]. , 1974, Fortschritte der Medizin.

[48]  Satoru Miyano,et al.  Extensive feature detection of N-terminal protein sorting signals , 2002, Bioinform..

[49]  M. Levitt Accurate modeling of protein conformation by automatic segment matching. , 1992, Journal of molecular biology.

[50]  D. Phillips,et al.  A possible three-dimensional structure of bovine alpha-lactalbumin based on that of hen's egg-white lysozyme. , 1969, Journal of molecular biology.

[51]  D Rognan,et al.  A pseudo-particle approach for studying protein-ligand models truncated to their active sites. , 1998, Biopolymers.

[52]  Dragos Horvath,et al.  Predicting ADME properties and side effects: the BioPrint approach. , 2003, Current opinion in drug discovery & development.

[53]  M. L. Connolly Solvent-accessible surfaces of proteins and nucleic acids. , 1983, Science.

[54]  R Samudrala,et al.  Constructing side chains on near-native main chains for ab initio protein structure prediction. , 2000, Protein engineering.

[55]  Brian K Shoichet,et al.  Protein–protein docking with multiple residue conformations and residue substitutions , 2002, Protein science : a publication of the Protein Society.

[56]  A. Kidera,et al.  Determinants of protein side‐chain packing , 1994, Protein science : a publication of the Protein Society.

[57]  I Lasters,et al.  Enhanced dead-end elimination in the search for the global minimum energy conformation of a collection of protein side chains. , 1995, Protein engineering.

[58]  Hans-Joachim Böhm,et al.  Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo design or 3D database search programs , 1998, J. Comput. Aided Mol. Des..

[59]  J. Bajorath,et al.  SAR index: quantifying the nature of structure-activity relationships. , 2007, Journal of medicinal chemistry.

[60]  I. Muchnik,et al.  Prediction of protein folding class using global description of amino acid sequence. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[61]  T Lengauer,et al.  The particle concept: placing discrete water molecules during protein‐ligand docking predictions , 1999, Proteins.

[62]  A. Vedani,et al.  Pseudo-receptor modeling: a new concept for the three-dimensional construction of receptor binding sites. , 1993, Journal of receptor research.

[63]  Robert P. Sheridan,et al.  Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling , 2003, J. Chem. Inf. Comput. Sci..

[64]  T. Blundell,et al.  Incorporating knowledge-based biases into an energy-based side-chain modeling method: application to comparative modeling of protein structure. , 2001, Biopolymers.

[65]  Erik Johansson,et al.  Megavariate analysis of environmental QSAR data. Part I – A basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD) , 2006, Molecular Diversity.

[66]  R E Hubbard,et al.  Locating interaction sites on proteins: The crystal structure of thermolysin soaked in 2% to 100% isopropanol , 1999, Proteins.

[67]  Meir Glick,et al.  Docking of flexible molecules using multiscale ligand representations. , 2002, Journal of medicinal chemistry.

[68]  Igor V. Tetko,et al.  Data modelling with neural networks: Advantages and limitations , 1997, J. Comput. Aided Mol. Des..

[69]  I. Muchnik,et al.  Recognition of a protein fold in the context of the Structural Classification of Proteins (SCOP) classification. , 1999, Proteins.

[70]  Jonas Boström,et al.  Conformational energy penalties of protein-bound ligands , 1998, J. Comput. Aided Mol. Des..

[71]  Pieter F. W. Stouten,et al.  Fast prediction and visualization of protein binding pockets with PASS , 2000, J. Comput. Aided Mol. Des..

[72]  Paul W Finn,et al.  Ultrafast shape recognition: evaluating a new ligand-based virtual screening technology. , 2009, Journal of molecular graphics & modelling.

[73]  J. Richardson,et al.  Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. , 1999, Journal of molecular biology.

[74]  W. Graham Richards,et al.  Ultrafast shape recognition to search compound databases for similar molecular shapes , 2007, J. Comput. Chem..

[75]  Z. Weng,et al.  Toward a predictive understanding of molecular recognition , 1998, Immunological reviews.

[76]  Defining topological equivalences in macromolecules. , 1991, Protein engineering.

[77]  Alan J. Robinson,et al.  XEMBL: distributing EMBL data in XML format , 2002, Bioinform..

[78]  Jason E. Stewart,et al.  Design and implementation of microarray gene expression markup language (MAGE-ML) , 2002, Genome Biology.

[79]  A. Liwo,et al.  Addition of side chains to a known backbone with defined side-chain centroids. , 2002, Biophysical chemistry.

[80]  N. Nikolova,et al.  International Union of Pure and Applied Chemistry, LUMO energy ± The Lowest Unoccupied Molecular Orbital (LUMO) , 2022 .

[81]  W. Roberts,et al.  Quantitative Analysis of the Distribution of Cardiac Muscle Cell Disorganization in the Left Ventricular Wall of Patients with Hypertrophic Cardiomyopathy , 1981, Circulation.

[82]  Tohru Koike,et al.  Computer-aided design of a factor Xa inhibitor by using MCSS functionality maps and a CAVEAT linker search. , 2003, Journal of molecular graphics & modelling.

[83]  H. Macfie,et al.  An application of unsupervised neural network methodology Kohonen topology-Preserving mapping) to QSAR analysis , 1991 .

[84]  M. Randic,et al.  The connectivity index 25 years after. , 2001, Journal of molecular graphics & modelling.

[85]  R. Czerminski,et al.  Use of Support Vector Machine in Pattern Classification: Application to QSAR Studies , 2001 .

[86]  D. Stephan,et al.  Identification of mutations in the cardiac ryanodine receptor gene in families affected with arrhythmogenic right ventricular cardiomyopathy type 2 (ARVD2). , 2001, Human molecular genetics.

[87]  D. Rognan Chemogenomic approaches to rational drug design , 2007, British journal of pharmacology.

[88]  ROY MARKHAM,et al.  Structure of Ribonucleic Acid , 1951, Nature.

[89]  J A Swets,et al.  Better decisions through science. , 2000, Scientific American.

[90]  G. Breithardt,et al.  Genetic basis and molecular mechanism for idiopathic ventricular fibrillation , 1998, Nature.

[91]  R. Wade,et al.  New hydrogen-bond potentials for use in determining energetically favorable binding sites on molecules of known structure. , 1989, Journal of medicinal chemistry.

[92]  P Tufféry,et al.  Prediction of protein side chain conformations: a study on the influence of backbone accuracy on conformation stability in the rotamer space. , 1997, Protein engineering.

[93]  Irini A. Doytchinova,et al.  JenPep: a database of quantitative functional peptide data for immunology , 2002, Bioinform..

[94]  T. Koch,et al.  Solving Steiner Tree Problems in Graphs to Optimality , 1998 .

[95]  Shinn-Ying Ho,et al.  POPI: predicting immunogenicity of MHC class I binding peptides by mining informative physicochemical properties , 2007, Bioinform..

[96]  Lei Xie,et al.  Detecting evolutionary relationships across existing fold space, using sequence order-independent profile–profile alignments , 2008, Proceedings of the National Academy of Sciences.

[97]  J. Taskinen,et al.  Neural network modeling for estimation of the aqueous solubility of structurally related drugs. , 1997, Journal of pharmaceutical sciences.

[98]  G. Klebe,et al.  Statistical potentials and scoring functions applied to protein-ligand binding. , 2001, Current opinion in structural biology.

[99]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[100]  J. Mendes,et al.  Improved modeling of side‐chains in proteins with rotamer‐based methods: A flexible rotamer model , 1999, Proteins.

[101]  Hans-Joachim Böhm,et al.  The computer program LUDI: A new method for the de novo design of enzyme inhibitors , 1992, J. Comput. Aided Mol. Des..

[102]  X. Chen,et al.  SVM-Prot: web-based support vector machine software for functional classification of a protein from its primary sequence , 2003, Nucleic Acids Res..

[103]  M Karplus,et al.  Use of the multiple copy simultaneous search (MCSS) method to design a new class of picornavirus capsid binding drugs , 1997, Proteins.

[104]  G. Klebe,et al.  Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials. , 2003, Journal of molecular biology.

[105]  P E Correa,et al.  The building of protein structures from alpha-carbon coordinates. , 1990, Proteins.

[106]  W. Pitt,et al.  New methods for the analysis of the protein-solvent interface , 1995 .

[107]  M. Aida,et al.  An ab initio molecular orbital study on the sequence-dependency of DNA conformation: an evaluation of intra- and inter-strand stacking interaction energy. , 1988, Journal of theoretical biology.

[108]  Philip E. Bourne,et al.  SMAP-WS: a parallel web service for structural proteome-wide ligand-binding site comparison , 2010, Nucleic Acids Res..

[109]  Jeffrey J. Popma,et al.  Lack of Neointimal Proliferation After Implantation of Sirolimus-Coated Stents in Human Coronary Arteries: A Quantitative Coronary Angiography and Three-Dimensional Intravascular Ultrasound Study , 2001, Circulation.

[110]  C. Napoli,et al.  Microarray analysis: a novel research tool for cardiovascular scientists and physicians , 2003, Heart.

[111]  Janet M. Thornton,et al.  Evaluation of a knowledge‐based potential of mean force for scoring docked protein–ligand complexes , 2001, J. Comput. Chem..

[112]  H Oschkinat,et al.  Receptor binding properties of four‐helix‐bundle growth factors deduced from electrostatic analysis , 1994, Protein science : a publication of the Protein Society.

[113]  P. Roy,et al.  Exploring the impact of size of training sets for the development of predictive QSAR models , 2008 .

[114]  D. Rognan,et al.  Structure-based design of nonnatural ligands for the HLA-B27 protein. , 1999, Journal of receptor and signal transduction research.

[115]  Marvin Johnson,et al.  Concepts and applications of molecular similarity , 1990 .

[116]  Jill E. Gready,et al.  Simple method for locating possible ligand binding sites on protein surfaces , 1999, J. Comput. Chem..

[117]  M. Lawrence,et al.  CLIX: A search algorithm for finding novel ligands capable of binding proteins of known three‐dimensional structure , 1992, Proteins.

[118]  F Guarnieri,et al.  A self-consistent, microenvironment modulated screened coulomb potential approximation to calculate pH-dependent electrostatic effects in proteins. , 1999, Biophysical journal.

[119]  Kristin P. Bennett,et al.  Support vector machines: hype or hallelujah? , 2000, SKDD.

[120]  Gisbert Schneider,et al.  Kernel Approach to Molecular Similarity Based on Iterative Graph Similarity , 2007, J. Chem. Inf. Model..

[121]  Philip M Dean,et al.  Efficient conformational sampling of local side-chain flexibility. , 2003, Journal of molecular biology.

[122]  R M Stroud,et al.  Approaches to solving the rigid receptor problem by identifying a minimal set of flexible residues during ligand docking. , 2001, Chemistry & biology.

[123]  Sorel Muresan,et al.  Quantitative assessment of the expanding complementarity between public and commercial databases of bioactive compounds , 2009, J. Cheminformatics.

[124]  I. Kuntz,et al.  Inclusion of Solvation in Ligand Binding Free Energy Calculations Using the Generalized-Born Model , 1999 .

[125]  T. Peng,et al.  Development of Heart Failure and Congenital Septal Defects in Mice Lacking Endothelial Nitric Oxide Synthase , 2002, Circulation.

[126]  L. Pauling,et al.  The structure of hair, muscle, and related proteins. , 1951, Proceedings of the National Academy of Sciences of the United States of America.

[127]  William R. Pitt,et al.  AQUARIUS2: Knowledge‐based modeling of solvent sites around proteins , 1993, J. Comput. Chem..

[128]  Arun Krishnan,et al.  pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties , 2005, BMC Bioinformatics.

[129]  Tim J. P. Hubbard,et al.  SCOP database in 2004: refinements integrate structure and sequence family data , 2004, Nucleic Acids Res..

[130]  Amos Bairoch,et al.  PROSITE: A Documented Database Using Patterns and Profiles as Motif Descriptors , 2002, Briefings Bioinform..

[131]  M Gerstein,et al.  DNA recognition code of transcription factors. , 1995, Protein engineering.

[132]  J. Aqvist,et al.  A new method for predicting binding affinity in computer-aided drug design. , 1994, Protein engineering.

[133]  Timothy Clark,et al.  New Molecular Descriptors Based on Local Properties at the Molecular Surface and a Boiling-Point Model Derived from Them , 2004, J. Chem. Inf. Model..

[134]  D. Levitt,et al.  POCKET: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. , 1992, Journal of molecular graphics.

[135]  Xi Chen,et al.  The Binding Database: data management and interface design , 2002, Bioinform..

[136]  D Rognan,et al.  Molecular dynamics study of a complex between the human histocompatibility antigen HLA-A2 and the IMP58-66 nonapeptide from influenza virus matrix protein. , 1992, European journal of biochemistry.

[137]  Curt M. Breneman,et al.  QTAIM in Drug Discovery and Protein Modeling , 2007 .

[138]  Ayhan Demiriz,et al.  Semi-Supervised Clustering Using Genetic Algorithms , 1999 .

[139]  Colin McMartin,et al.  Flexible matching of test ligands to a 3D pharmacophore using a molecular superposition force field: Comparison of predicted and experimental conformations of inhibitors of three enzymes , 1995, J. Comput. Aided Mol. Des..

[140]  Rajarshi Guha,et al.  On the interpretation and interpretability of quantitative structure–activity relationship models , 2008, J. Comput. Aided Mol. Des..

[141]  D S Goodsell,et al.  Automated docking of flexible ligands: Applications of autodock , 1996, Journal of molecular recognition : JMR.

[142]  J. Thornton,et al.  PROCHECK: a program to check the stereochemical quality of protein structures , 1993 .

[143]  Irwin D Kuntz,et al.  Free energy calculations for theophylline binding to an RNA aptamer: Comparison of MM-PBSA and thermodynamic integration methods. , 2003, Biopolymers.

[144]  M Karplus,et al.  An automated method for dynamic ligand design , 1995, Proteins.

[145]  Philip E. Bourne,et al.  The distribution and query systems of the RCSB Protein Data Bank , 2004, Nucleic Acids Res..

[146]  L. Gallo Cardiovascular Disease , 1995, GWUMC Department of Biochemistry Annual Spring Symposia.

[147]  C. Sander,et al.  Database algorithm for generating protein backbone and side-chain co-ordinates from a C alpha trace application to model building and detection of co-ordinate errors. , 1991, Journal of molecular biology.

[148]  D Horvath,et al.  A virtual screening approach applied to the search for trypanothione reductase inhibitors. , 1997, Journal of medicinal chemistry.

[149]  David S. Wishart,et al.  HMDB: a knowledgebase for the human metabolome , 2008, Nucleic Acids Res..

[150]  Gerhard Klebe,et al.  Ligand-supported homology modeling of g-protein-coupled receptor sites: models sufficient for successful virtual screening. , 2004, Angewandte Chemie.

[151]  Bernard F. Buxton,et al.  Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis , 2001, Comput. Chem..

[152]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[153]  Chris Sander,et al.  Objectively judging the quality of a protein structure from a Ramachandran plot , 1997, Comput. Appl. Biosci..

[154]  R C Wade,et al.  Further development of hydrogen bond functions for use in determining energetically favorable binding sites on molecules of known structure. 2. Ligand probe groups with the ability to form more than two hydrogen bonds. , 1993, Journal of medicinal chemistry.

[155]  Graham Cameron,et al.  One-stop shop for microarray data , 2000, Nature.

[156]  G. Nussdorfer,et al.  Reciprocal regulation of endothelin-1 and nitric oxide: relevance in the physiology and pathology of the cardiovascular system. , 2001, International review of cytology.

[157]  Rebecca C. Wade,et al.  Prediction of water binding sites on proteins by neural networks , 1992 .

[158]  Bernhard Schölkopf,et al.  New Support Vector Algorithms , 2000, Neural Computation.

[159]  S. Pickett,et al.  GRid-INdependent descriptors (GRIND): a novel class of alignment-independent three-dimensional molecular descriptors. , 2000, Journal of medicinal chemistry.

[160]  Johann Gasteiger,et al.  Hash codes for the identification and classification of molecular structure elements , 1994, J. Comput. Chem..

[161]  David A. Fenstermacher,et al.  Introduction to bioinformatics , 2005, J. Assoc. Inf. Sci. Technol..

[162]  Anton J. Hopfinger,et al.  Constructing Protein Models for Ligand-Receptor Binding Thermodynamic Simulations: An Application to a Set of Peptidometic Renin Inhibitors , 1997, J. Chem. Inf. Comput. Sci..

[163]  J. Jukema,et al.  Progression and regression of coronary atherosclerosis. , 1993, Indian heart journal.

[164]  Harold A. Scheraga,et al.  Prodock: Software package for protein modeling and docking , 1999, J. Comput. Chem..

[165]  I. Kuntz,et al.  Automated docking with grid‐based energy evaluation , 1992 .

[166]  Ajay N. Jain,et al.  Automatic identification and representation of protein binding sites for molecular docking , 1997, Protein science : a publication of the Protein Society.

[167]  Akinori Sarai,et al.  ProTherm, version 4.0: thermodynamic database for proteins and mutants , 2004, Nucleic Acids Res..

[168]  J. Topliss,et al.  Chance factors in studies of quantitative structure-activity relationships. , 1979, Journal of medicinal chemistry.

[169]  Curt M. Breneman,et al.  Transferable atom equivalent multicentered multipole expansion method , 2003, J. Comput. Chem..

[170]  Glen Eugene Kellogg,et al.  HINT: A new method of empirical hydrophobic field calculation for CoMFA , 1991, J. Comput. Aided Mol. Des..

[171]  A. Hopkins Network pharmacology: the next paradigm in drug discovery. , 2008, Nature chemical biology.

[172]  M. Foster,et al.  Mapping the surface of Escherichia coli peptide deformylase by NMR with organic solvents , 2002, Protein science : a publication of the Protein Society.

[173]  R. Wade,et al.  Further development of hydrogen bond functions for use in determining energetically favorable binding sites on molecules of known structure. 1. Ligand probe groups with the ability to form two hydrogen bonds. , 1993, Journal of medicinal chemistry.

[174]  Richard H. Lathrop,et al.  DNA sequence and structure: direct and indirect recognition in protein-DNA binding , 2002, ISMB.

[175]  M. Levitt,et al.  Accuracy of side‐chain prediction upon near‐native protein backbones generated by ab initio folding methods , 1998, Proteins.

[176]  Jason E. Stewart,et al.  Minimum information about a microarray experiment (MIAME)—toward standards for microarray data , 2001, Nature Genetics.

[177]  R. Cramer,et al.  Recent advances in comparative molecular field analysis (CoMFA). , 1989, Progress in clinical and biological research.

[178]  Tingjun Hou,et al.  ADME evaluation in drug discovery , 2002, Journal of molecular modeling.

[179]  M. Michael Gromiha,et al.  Free-Energy Maps of Base−Amino Acid Interactions for DNA−Protein Recognition , 1999 .

[180]  Chun Yan,et al.  Prediction of protein subcellular location using a combined feature of sequence , 2005, FEBS letters.

[181]  Mathias Wawer,et al.  Navigating structure-activity landscapes. , 2009, Drug discovery today.

[182]  Ricardo L. Mancera,et al.  WaterScore: a novel method for distinguishing between bound and displaceable water molecules in the crystal structure of the binding site of protein-ligand complexes , 2003, Journal of molecular modeling.

[183]  R. Grantham Amino Acid Difference Formula to Help Explain Protein Evolution , 1974, Science.

[184]  R. D. Iii Cramer,et al.  Comparative Molecular Field Analysis (CoMFA). Part 1. Effect of Shape on Binding of Steroids to Carrier Proteins. , 1988 .

[185]  H. Matter,et al.  Structural classification of protein kinases using 3D molecular interaction field analysis of their ligand binding sites: target family landscapes. , 2002, Journal of medicinal chemistry.

[186]  Janet M. Thornton,et al.  The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data , 2004, Nucleic Acids Res..

[187]  R. Agarwala,et al.  Software for constructing and verifying pedigrees within large genealogies and an application to the Old Order Amish of Lancaster County. , 1998, Genome research.

[188]  Tilmann Weber,et al.  Specificity prediction of adenylation domains in nonribosomal peptide synthetases (NRPS) using transductive support vector machines (TSVMs) , 2005, Nucleic acids research.

[189]  Arthur Dalby,et al.  Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited , 1992, J. Chem. Inf. Comput. Sci..

[190]  A. Fedorov,et al.  Comparison of experimental and computational functional group mapping of an RNase A structure: implications for computer-aided drug design. , 1996, Protein engineering.

[191]  Adam J. Smith,et al.  The Database of Interacting Proteins: 2004 update , 2004, Nucleic Acids Res..

[192]  C. Sander,et al.  Positioning hydrogen atoms by optimizing hydrogen‐bond networks in protein structures , 1996, Proteins.

[193]  Gerhard Klebe,et al.  From Structure to Function: A New Approach to Detect Functional Similarity among Proteins Independent from Sequence and Fold Homology. , 2001, Angewandte Chemie.

[194]  W. Punch,et al.  Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm. , 1997, Journal of molecular biology.

[195]  S R Gullans,et al.  DNA microarray analysis of complex biologic processes. , 2001, Journal of the American Society of Nephrology : JASN.

[196]  David M. Rocke,et al.  Predicting ligand binding to proteins by affinity fingerprinting. , 1995, Chemistry & biology.

[197]  Roman Rosipal,et al.  Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space , 2002, J. Mach. Learn. Res..

[198]  Gerhard Klebe,et al.  Subnanomolar Inhibitors from Computer Screening: A Model Study Using Human Carbonic Anhydrase II. , 2001, Angewandte Chemie.

[199]  P. Goodford A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.

[200]  J. Kononen,et al.  Tissue microarrays for high-throughput molecular profiling of tumor specimens , 1998, Nature Medicine.

[201]  M C Nicklaus,et al.  Conformational changes of small molecules binding to proteins. , 1995, Bioorganic & medicinal chemistry.

[202]  D A Agard,et al.  Modeling side-chain conformation for homologous proteins using an energy-based rotamer search. , 1993, Journal of molecular biology.

[203]  Didier Rognan,et al.  Protein‐based virtual screening of chemical databases. II. Are homology models of g‐protein coupled receptors suitable targets? , 2002, Proteins.

[204]  Stewart A. Adcock Peptide backbone reconstruction using dead‐end elimination and a knowledge‐based forcefield , 2004, J. Comput. Chem..

[205]  L. Kedes,et al.  Nomenclature for incompletely specified bases in nucleic acid sequences. Recommendations 1984. Nomenclature Committee of the International Union of Biochemistry (NC-IUB). , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[206]  Kuo-Chen Chou,et al.  Prediction of Membrane Protein Types by Incorporating Amphipathic Effects , 2005, J. Chem. Inf. Model..

[207]  Kristin P. Bennett,et al.  An Optimization Perspective on Kernel Partial Least Squares Regression , 2003 .

[208]  H. Umeyama,et al.  Prediction of protein side-chain conformations by principal component analysis for fixed main-chain atoms. , 1997, Protein engineering.

[209]  Collin M. Stultz,et al.  MCSS functionality maps for a flexible protein , 1999, Proteins.

[210]  A. Wilde,et al.  Cardiac conduction defects associate with mutations in SCN5A , 1999, Nature Genetics.

[211]  R. Bruccoleri,et al.  Application of a directed conformational search for generating 3‐D coordinates for protein structures from α‐carbon coordinates , 1992, Proteins.

[212]  W. Graham Richards,et al.  Virtual screening using grid computing: the screensaver project , 2002, Nature Reviews Drug Discovery.

[213]  David S. Goodsell,et al.  Distributed automated docking of flexible ligands to proteins: Parallel applications of AutoDock 2.4 , 1996, J. Comput. Aided Mol. Des..

[214]  Timothy Clark,et al.  QSAR and QSPR based solely on surface properties? , 2004, Journal of molecular graphics & modelling.

[215]  S. Bryant,et al.  PubChem as a public resource for drug discovery. , 2010, Drug discovery today.

[216]  J M Thornton,et al.  Using the CATH domain database to assign structures and functions to the genome sequences. , 2000, Biochemical Society transactions.

[217]  Hao Chen,et al.  Beyond the rotamer library: Genetic algorithm combined with the disturbing mutation process for upbuilding protein side‐chains , 2003, Proteins.

[218]  Gabriele Cruciani,et al.  Structural differences of matrix metalloproteinases with potential implications for inhibitor selectivity examined by the GRID/CPCA approach. , 2002, Journal of medicinal chemistry.

[219]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[220]  K. Sharp,et al.  Protein folding and association: Insights from the interfacial and thermodynamic properties of hydrocarbons , 1991, Proteins.

[221]  Roland L. Dunbrack,et al.  Bayesian statistical analysis of protein side‐chain rotamer preferences , 1997, Protein science : a publication of the Protein Society.

[222]  Gerhard Klebe,et al.  Predicting binding modes, binding affinities and ‘hot spots’ for protein-ligand complexes using a knowledge-based scoring function , 2000 .

[223]  P Willett,et al.  Development and validation of a genetic algorithm for flexible docking. , 1997, Journal of molecular biology.

[224]  K. Kim,et al.  Selection of peptides that bind to the HLA-A2.1 molecule by molecular modelling. , 1996, Molecular immunology.

[225]  R. Roberts A perspective: the new millennium dawns on a new paradigm for cardiology--molecular genetics. , 2000, Journal of the American College of Cardiology.

[226]  Didier Rognan,et al.  Fine specificity of antigen binding to two class I major histocompatibility proteins (B*2705 and B*2703) differing in a single amino acid residue , 1997, J. Comput. Aided Mol. Des..

[227]  Nikolay A. Kolchanov,et al.  CRASP: a program for analysis of coordinated substitutions in multiple alignments of protein sequences , 2004, Nucleic Acids Res..

[228]  R. Goldstein Efficient rotamer elimination applied to protein side-chains and related spin glasses. , 1994, Biophysical journal.

[229]  T Sasazuki,et al.  Magnitude of structural changes of the T-cell receptor binding regions determine the strength of T-cell antagonism: molecular dynamics simulations of HLA-DR4 (DRB1*0405) complexed with analogue peptide. , 2000, Protein engineering.

[230]  Garland R. Marshall,et al.  VALIDATE: A New Method for the Receptor-Based Prediction of Binding Affinities of Novel Ligands , 1996 .

[231]  Yang Liu,et al.  An introduction to decision tree modeling , 2004 .

[232]  P. Kollman,et al.  Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. , 2000, Accounts of chemical research.

[233]  Mark J. Embrechts,et al.  New developments in PEST shape/property hybrid descriptors , 2003, J. Comput. Aided Mol. Des..

[234]  A. Warshel Calculations of enzymatic reactions: calculations of pKa, proton transfer reactions, and general acid catalysis reactions in enzymes. , 1981, Biochemistry.

[235]  Jordi Mestres,et al.  Computational chemogenomics approaches to systematic knowledge-based drug discovery. , 2004, Current opinion in drug discovery & development.

[236]  T. Blundell,et al.  Comparative protein modelling by satisfaction of spatial restraints. , 1993, Journal of molecular biology.

[237]  R E Hubbard,et al.  Experimental and computational mapping of the binding surface of a crystalline protein. , 2001, Protein engineering.

[238]  K. Kinoshita,et al.  Identification of protein functions from a molecular surface database, eF-site , 2004, Journal of Structural and Functional Genomics.

[239]  Bhaskar D. Kulkarni,et al.  Using pseudo amino acid composition to predict protein subnuclear localization: Approached with PSSM , 2007, Pattern Recognit. Lett..

[240]  Hans-Joachim Böhm,et al.  The development of a simple empirical scoring function to estimate the binding constant for a protein-ligand complex of known three-dimensional structure , 1994, J. Comput. Aided Mol. Des..

[241]  J M Thornton,et al.  X-SITE: use of empirically derived atomic packing preferences to identify favourable interaction regions in the binding sites of proteins. , 1996, Journal of molecular biology.

[242]  A. Fliri,et al.  Biological spectra analysis: Linking biological activity profiles to molecular structure. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[243]  Gabriele Ausiello,et al.  SURFACE: a database of protein surface regions for functional annotation , 2004, Nucleic Acids Res..

[244]  T. Harris,et al.  Structural Basis of Perturbed pKa Values of Catalytic Groups in Enzyme Active Sites , 2002, IUBMB life.

[245]  M. Kanehisa,et al.  Cluster analysis of amino acid indices for prediction of protein structure and function. , 1988, Protein engineering.

[246]  L. R. Scott,et al.  Electrostatics and diffusion of molecules in solution: simulations with the University of Houston Brownian dynamics program , 1995 .

[247]  Irini A. Doytchinova,et al.  JenPep: A Novel Computational Information Resource for Immunobiology and Vaccinology , 2003, J. Chem. Inf. Comput. Sci..

[248]  Y. Martin,et al.  Do structurally similar molecules have similar biological activity? , 2002, Journal of medicinal chemistry.

[249]  L. Ghiadoni,et al.  The T-786C and Glu298Asp polymorphisms of the endothelial nitric oxide gene affect the forearm blood flow responses of Caucasian hypertensive patients. , 2003, Journal of the American College of Cardiology.

[250]  B. Honig,et al.  Classical electrostatics in biology and chemistry. , 1995, Science.

[251]  D. Lipman,et al.  Rapid and sensitive protein similarity searches. , 1985, Science.

[252]  J. Gasteiger,et al.  Autocorrelation of Molecular Surface Properties for Modeling Corticosteroid Binding Globulin and Cytosolic Ah Receptor Activity by Neural Networks , 1995 .

[253]  M. Gilson Multiple‐site titration and molecular modeling: Two rapid methods for computing energies and forces for ionizable groups in proteins , 1993, Proteins.

[254]  Boris Mirkin,et al.  A Measure of Domain of Applicability for QSAR Modelling Based on Intelligent K-Means Clustering , 2007 .

[255]  J. Mendes,et al.  Improvement of side-chain modeling in proteins with the self-consistent mean field theory method based on an analysis of the factors influencing prediction. , 1999, Biopolymers.

[256]  J. Whisstock,et al.  Prediction of protein function from protein sequence and structure , 2003, Quarterly Reviews of Biophysics.

[257]  G. Klebe The use of composite crystal-field environments in molecular recognition and the de novo design of protein ligands. , 1994, Journal of molecular biology.

[258]  P. Willett,et al.  SuperStar: improved knowledge-based interaction fields for protein binding sites. , 2001, Journal of molecular biology.

[259]  J. Thornton,et al.  A study into the effects of protein binding on nucleotide conformation. , 1993, Nucleic acids research.

[260]  R. Michler,et al.  L-arginine prevents xanthoma development and inhibits atherosclerosis in LDL receptor knockout mice. , 1997, Circulation.

[261]  Stephen L Mayo,et al.  Prudent modeling of core polar residues in computational protein design. , 2003, Journal of molecular biology.

[262]  P. Leeson,et al.  A comparison of physiochemical property profiles of development and marketed oral drugs. , 2003, Journal of medicinal chemistry.

[263]  L. Pauling,et al.  The structure of proteins; two hydrogen-bonded helical configurations of the polypeptide chain. , 1951, Proceedings of the National Academy of Sciences of the United States of America.

[264]  R Rein,et al.  Finding the global minimum: a fuzzy end elimination implementation. , 1995, Protein engineering.

[265]  Evan W. Steeg,et al.  Update for users of the Cornell sequence analysis package , 1984, Nucleic Acids Res..

[266]  Jürgen Bajorath,et al.  Rationalizing Three-Dimensional Activity Landscapes and the Influence of Molecular Representations on Landscape Topology and the Formation of Activity Cliffs , 2010, J. Chem. Inf. Model..

[267]  David S. Goodsell,et al.  Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function , 1998, J. Comput. Chem..

[268]  D Rognan,et al.  Molecular dynamics simulation of MHC-peptide complexes as a tool for predicting potential T cell epitopes. , 1994, Biochemistry.

[269]  F. Jørgensen,et al.  A new concept for multidimensional selection of ligand conformations (MultiSelect) and multidimensional scoring (MultiScore) of protein-ligand binding affinities. , 2001, Journal of medicinal chemistry.

[270]  Arthur J Moss,et al.  SCN5A mutations associated with an inherited cardiac arrhythmia, long QT syndrome , 1995, Cell.

[271]  G. Vriend,et al.  The determinants of alpha-amylase pH-activity profiles. , 2001, Protein engineering.

[272]  Yinglin Wang,et al.  Predicting the protein SUMO modification sites based on Properties Sequential Forward Selection (PSFS). , 2007, Biochemical and biophysical research communications.

[273]  J. Antosiewicz,et al.  Empirical relationships between protein structure and carboxyl pKa values in proteins , 2002, Proteins.

[274]  B. Masek,et al.  Molecular shape comparison of angiotensin II receptor antagonists. , 1993, Journal of medicinal chemistry.

[275]  D. Lipman,et al.  Improved tools for biological sequence comparison. , 1988, Proceedings of the National Academy of Sciences of the United States of America.

[276]  Qi Guo,et al.  DNA microarray and cancer. , 2003, Current opinion in oncology.

[277]  C A Floudas,et al.  A predictive method for the evaluation of peptide binding in pocket 1 of HLA‐DRB1 via global minimization of energy interactions , 1997, Proteins.

[278]  C DeLisi,et al.  Computational determination of side chain specificity for pockets in class I MHC molecules. , 1996, Molecular immunology.

[279]  N. Grishin,et al.  Accumulation of dietary cholesterol in sitosterolemia caused by mutations in adjacent ABC transporters. , 2000, Science.

[280]  C. Lipinski Drug-like properties and the causes of poor solubility and poor permeability. , 2000, Journal of pharmacological and toxicological methods.

[281]  D R Flower,et al.  Rotational superposition: a review of methods. , 1999, Journal of molecular graphics & modelling.

[282]  M. Kanehisa,et al.  Analysis of amino acid indices and mutation matrices for sequence comparison and structure prediction of proteins. , 1996, Protein engineering.

[283]  P. Jurs,et al.  Classification of multidrug-resistance reversal agents using structure-based descriptors and linear discriminant analysis. , 2000, Journal of medicinal chemistry.

[284]  I. Lasters,et al.  The fuzzy-end elimination theorem: correctly implementing the side chain placement algorithm based on the dead-end elimination theorem. , 1993, Protein engineering.

[285]  M. Moskowitz,et al.  Hypertension in mice lacking the gene for endothelial nitric oxide synthase , 1995, Nature.

[286]  I. Kuntz,et al.  Structure-based discovery of inhibitors of thymidylate synthase. , 1993, Science.

[287]  S. Roe,et al.  Patterns for prediction of hydration around polar residues in proteins. , 1993, Journal of molecular biology.

[288]  Hans-Joachim Böhm,et al.  LUDI: rule-based automatic design of new substituents for enzyme inhibitor leads , 1992, J. Comput. Aided Mol. Des..

[289]  A. Kurita,et al.  Endothelin-1 enhances vascular cell adhesion molecule-1 expression in tumor necrosis factor alpha-stimulated vascular endothelial cells. , 1999, European journal of pharmacology.

[290]  P. Geladi Notes on the history and nature of partial least squares (PLS) modelling , 1988 .

[291]  Wei Zhang,et al.  Parameters for the generalized Born model consistent with RESP atomic partial charge assignment protocol , 2003 .

[292]  Jonathan D. Hirst,et al.  Similarity by Compression , 2007, J. Chem. Inf. Model..

[293]  Fabio Polticelli,et al.  Structural determinants of trypsin affinity and specificity for cationic inhibitors , 1999, Protein science : a publication of the Protein Society.

[294]  L L Looger,et al.  Generalized dead-end elimination algorithms make large-scale protein side-chain structure prediction tractable: implications for protein design and structural genomics. , 2001, Journal of molecular biology.

[295]  T. Lüscher,et al.  Endothelial dysfunction in coronary artery disease. , 1993, Annual review of medicine.

[296]  A. Schäffer,et al.  Linkage analyses in type I diabetes mellitus using CASPAR, a software and statistical program for conditional analysis of polygenic diseases. , 1997, Human heredity.

[297]  M Hendlich,et al.  LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. , 1997, Journal of molecular graphics & modelling.

[298]  M. Karplus,et al.  Functionality maps of binding sites: A multiple copy simultaneous search method , 1991, Proteins.

[299]  Anand K. Srivastava,et al.  Identification of a gene, ABCG5, important in the regulation of dietary cholesterol absorption , 2001, Nature Genetics.

[300]  S. Greenberg,et al.  DNA microarray gene expression analysis technology and its application to neurological disorders , 2001, Neurology.

[301]  O Nilsson,et al.  Molecular volumes and surfaces of biomacromolecules via GEPOL: a fast and efficient algorithm. , 1990, Journal of molecular graphics.

[302]  B Honig,et al.  On the calculation of binding free energies using continuum methods: Application to MHC class I protein‐peptide interactions , 1997, Protein science : a publication of the Protein Society.

[303]  I. Kuntz,et al.  Matching chemistry and shape in molecular docking. , 1993, Protein engineering.

[304]  D. Rognan,et al.  Customized versus universal scoring functions: application to class I MHC-peptide binding free energy predictions. , 2001, Bioorganic & medicinal chemistry letters.

[305]  Martin Vingron,et al.  IntAct: an open source molecular interaction database , 2004, Nucleic Acids Res..

[306]  B Fristensky,et al.  Portable microcomputer software for nucleotide sequence analysis. , 1982, Nucleic acids research.

[307]  Roger A. Sayle,et al.  Lingos, Finite State Machines, and Fast Similarity Searching , 2006, J. Chem. Inf. Model..

[308]  T. Poulos,et al.  Computer modeling of selective regions in the active site of nitric oxide synthases: implication for the design of isoform-selective inhibitors. , 2003, Journal of medicinal chemistry.

[309]  Guillermo Moyna,et al.  Shape signatures: a new approach to computer-aided ligand- and receptor-based drug design. , 2003, Journal of medicinal chemistry.

[310]  Sung-Sau So,et al.  A comparative study of ligand-receptor complex binding affinity prediction methods based on glycogen phosphorylase inhibitors , 1999, J. Comput. Aided Mol. Des..

[311]  Peter L Elkin,et al.  Primer on medical genomics part V: bioinformatics. , 2003, Mayo Clinic proceedings.

[312]  W R Pitt,et al.  Modelling of solvent positions around polar groups in proteins. , 1991, Protein engineering.

[313]  J. Thornton,et al.  The application of hydrogen bonding analysis in X-ray crystallography to help orientate asparagine, glutamine and histidine side chains. , 1995, Protein engineering.

[314]  Roland L. Dunbrack,et al.  Conformational analysis of the backbone-dependent rotamer preferences of protein sidechains , 1994, Nature Structural Biology.

[315]  A R Leach,et al.  Exploring the conformational space of protein side chains using dead‐end elimination and the A* algorithm , 1998, Proteins.

[316]  H. Edelsbrunner,et al.  Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design , 1998, Protein science : a publication of the Protein Society.

[317]  Roland L. Dunbrack,et al.  Backbone-dependent rotamer library for proteins. Application to side-chain prediction. , 1993, Journal of molecular biology.

[318]  K. Williams,et al.  Atherosclerosis--an inflammatory disease. , 1999, The New England journal of medicine.

[319]  D. Rognan,et al.  Predicting binding affinities of protein ligands from three-dimensional models: application to peptide binding to class I major histocompatibility proteins. , 1999, Journal of medicinal chemistry.

[320]  M. Zalis,et al.  Visualizing and quantifying molecular goodness-of-fit: small-probe contact dots with explicit hydrogen atoms. , 1999, Journal of molecular biology.

[321]  S. Higano,et al.  Long-term follow-up of patients with mild coronary artery disease and endothelial dysfunction. , 2000, Circulation.

[322]  M C Nicklaus,et al.  Internet resources integrating many small-molecule databases1 , 2008, SAR and QSAR in environmental research.

[323]  Sameer Velankar,et al.  E-MSD: the European Bioinformatics Institute Macromolecular Structure Database , 2003, Nucleic Acids Res..

[324]  Jonas Boström,et al.  Assessing the performance of OMEGA with respect to retrieving bioactive conformations. , 2003, Journal of molecular graphics & modelling.

[325]  Deborah R. Carvalho,et al.  A hybrid decision tree/genetic algorithm method for data mining , 2004, Inf. Sci..

[326]  Wolf-Dietrich Ihlenfeldt,et al.  Computation and management of chemical properties in CACTVS: An extensible networked approach toward modularity and compatibility , 1994, J. Chem. Inf. Comput. Sci..

[327]  J. Bell,et al.  Medical implications of understanding complex disease traits. , 1998, Current opinion in biotechnology.

[328]  Vladimir Batagelj,et al.  Comparison of three different approaches to the property prediction problem , 1994, J. Chem. Inf. Comput. Sci..

[329]  Jürgen Brickmann,et al.  A new approach to analysis and display of local lipophilicity/hydrophilicity mapped on molecular surfaces , 1993, J. Comput. Aided Mol. Des..

[330]  P Burkhard,et al.  An example of a protein ligand found by database mining: description of the docking method and its verification by a 2.3 A X-ray structure of a thrombin-ligand complex. , 1998, Journal of molecular biology.

[331]  A J Moss,et al.  Spectrum of Mutations in Long-QT Syndrome Genes: KVLQT1, HERG, SCN5A, KCNE1, and KCNE2 , 2000, Circulation.

[332]  T. Andersson,et al.  Analysis of selective regions in the active sites of human cytochromes P450, 2C8, 2C9, 2C18, and 2C19 homology models using GRID/CPCA. , 2001, Journal of medicinal chemistry.

[333]  D. Cavalieri,et al.  Fundamentals of cDNA microarray data analysis. , 2003, Trends in genetics : TIG.

[334]  I Lasters,et al.  All in one: a highly detailed rotamer library improves both accuracy and speed in the modelling of sidechains by dead-end elimination. , 1997, Folding & design.

[335]  G Klebe,et al.  Improving macromolecular electrostatics calculations. , 1999, Protein engineering.

[336]  W. C. Still,et al.  Semianalytical treatment of solvation for molecular mechanics and dynamics , 1990 .

[337]  P. Charifson,et al.  Improved scoring of ligand-protein interactions using OWFEG free energy grids. , 2001, Journal of medicinal chemistry.

[338]  Thomas Lengauer,et al.  FlexE: efficient molecular docking considering protein structure variations. , 2001, Journal of molecular biology.

[339]  R C Wade,et al.  Prediction of protein hydration sites from sequence by modular neural networks. , 1998, Protein engineering.

[340]  Juan Jesús Pérez,et al.  BUNDLE: A program for building the transmembrane domains of G-protein-coupled receptors , 1998, J. Comput. Aided Mol. Des..

[341]  Peter A. Kollman,et al.  The application of three approximate free energy calculations methods to structure based ligand design: Trypsin and its complex with inhibitors , 1998, J. Comput. Aided Mol. Des..

[342]  D. Benjamin Gordon,et al.  Exact rotamer optimization for protein design , 2003, J. Comput. Chem..

[343]  Todd J. A. Ewing,et al.  DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases , 2001, J. Comput. Aided Mol. Des..

[344]  Lu Huang,et al.  Update of TTD: Therapeutic Target Database , 2009, Nucleic Acids Res..

[345]  Anna Vulpetti,et al.  Predicting Polypharmacology by Binding Site Similarity: From Kinases to the Protein Universe , 2010, J. Chem. Inf. Model..

[346]  Tomasz Arodz,et al.  Computational methods in developing quantitative structure-activity relationships (QSAR): a review. , 2006, Combinatorial chemistry & high throughput screening.

[347]  Adrian A Canutescu,et al.  Access the most recent version at doi: 10.1110/ps.03154503 References , 2003 .

[348]  Tom L Blundell,et al.  Advantages of fine-grained side chain conformer libraries. , 2003, Protein engineering.

[349]  R. Wade,et al.  Classification of protein sequences by homology modeling and quantitative analysis of electrostatic similarity , 1999, Proteins.

[350]  P Herzyk,et al.  Automated method for modeling seven-helix transmembrane receptors from experimental data. , 1995, Biophysical journal.

[351]  N. Grishin,et al.  Side‐chain modeling with an optimized scoring function , 2002, Protein science : a publication of the Protein Society.

[352]  R F Standaert,et al.  Atomic structure of FKBP-FK506, an immunophilin-immunosuppressant complex , 1991, Science.

[353]  M. O. Dayhoff,et al.  Atlas of protein sequence and structure , 1965 .

[354]  D. Rognan,et al.  Long‐range effects in protein–ligand interactions mediate peptide specificity inl the human major histocompatibility antigen HLA‐B27 (B*2701) , 1999, Protein science : a publication of the Protein Society.

[355]  D. Rognan,et al.  Rational design of nonnatural peptides as high-affinity ligands for the HLA-B*2705 human leukocyte antigen. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[356]  Bingcheng Wang,et al.  Chemometrical Classification of Ephrin Ligands and Eph Kinases Using GRID/CPCA Approach , 2003, J. Chem. Inf. Comput. Sci..

[357]  David Weininger,et al.  SMILES. 2. Algorithm for generation of unique SMILES notation , 1989, J. Chem. Inf. Comput. Sci..

[358]  R A Milligan,et al.  Lipid nanotubes as substrates for helical crystallization of macromolecules. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[359]  E Keith Davies,et al.  The potential of Internet computing for drug discovery. , 2002, Drug discovery today.

[360]  Robin Taylor,et al.  IsoStar: A library of information about nonbonded interactions , 1997, J. Comput. Aided Mol. Des..

[361]  B D PETROV,et al.  In Japan … , 1975, Sovetskoe zdravookhranenie.

[362]  H. Margalit,et al.  Quantitative parameters for amino acid-base interaction: implications for prediction of protein-DNA binding sites. , 1998, Nucleic acids research.

[363]  C. DeLisi,et al.  Free energy mapping of class I MHC molecules and structural determination of bound peptides , 1996, Protein science : a publication of the Protein Society.

[364]  A. George,et al.  Molecular mechanism for an inherited cardiac arrhythmia , 1995, Nature.

[365]  A. Leach,et al.  Ligand docking to proteins with discrete side-chain flexibility. , 1994, Journal of molecular biology.

[366]  Li Shao,et al.  Consensus Ranking Approach to Understanding the Underlying Mechanism With QSAR , 2010, J. Chem. Inf. Model..

[367]  Jinbo Bi,et al.  Prediction of Protein Retention Times in Anion-Exchange Chromatography Systems Using Support Vector Regression. , 2003 .

[368]  F. Javier Luque,et al.  Ligand-induced changes in the binding sites of proteins , 2002, Bioinform..

[369]  D Rognan,et al.  From peptides to peptidomimetics: design of nonpeptide ligands for major histocompatibility proteins. , 1998, Pharmaceutica acta Helvetiae.

[370]  M. DePristo,et al.  Discrete restraint-based protein modeling and the Calpha-trace problem. , 2003, Protein science : a publication of the Protein Society.

[371]  J M Thornton,et al.  Rebuilding flavodoxin from C alpha coordinates: a test study. , 1989, Proteins.

[372]  Nathan A. Baker,et al.  Electrostatics of nanosystems: Application to microtubules and the ribosome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[373]  G. V. Paolini,et al.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes , 1997, J. Comput. Aided Mol. Des..

[374]  Huda Akil,et al.  Microarray technology: a review of new strategies to discover candidate vulnerability genes in psychiatric disorders. , 2003, The American journal of psychiatry.

[375]  H. Kono,et al.  Structure‐based prediction of DNA target sites by regulatory proteins , 1999, Proteins.

[376]  Gerd Folkers,et al.  PrGen: Pseudoreceptor Modeling Using Receptor‐mediated Ligand Alignment and Pharmacophore Equilibration , 1998 .

[377]  S Vajda,et al.  Flexible docking of peptides to class I major-histocompatibility-complex receptors. , 1995, Genetic analysis : biomolecular engineering.

[378]  M. DePristo,et al.  Ab initio construction of polypeptide fragments: Efficient generation of accurate, representative ensembles , 2003, Proteins.

[379]  Pedro J. Ballester,et al.  Ultrafast shape recognition for similarity search in molecular databases , 2007, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[380]  Jonathan D. Hirst,et al.  New approaches to QSAR: Neural networks and machine learning , 1993 .

[381]  G. Klebe,et al.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. , 1994, Journal of medicinal chemistry.

[382]  H. Matter,et al.  Insights into the bile acid transportation system: The human ileal lipid‐binding protein‐cholyltaurine complex and its comparison with homologous structures , 2002, Proteins.

[383]  J L Cornette,et al.  Consistency in structural energetics of protein folding and peptide recognition , 1997, Protein science : a publication of the Protein Society.

[384]  P. Kollman,et al.  Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate−DNA Helices , 1998 .

[385]  Alexander Tropsha,et al.  Chemometric Analysis of Ligand Receptor Complementarity: Identifying Complementary Ligands Based on Receptor Information (CoLiBRI) , 2006, J. Chem. Inf. Model..

[386]  P. Sigler,et al.  Activating mineralocorticoid receptor mutation in hypertension exacerbated by pregnancy. , 2000, Science.

[387]  G. Wagner,et al.  Detection of long-lived bound water molecules in complexes of human dihydrofolate reductase with methotrexate and NADPH. , 1995, Journal of molecular biology.

[388]  D. Flower,et al.  Identifiying Human MHC Supertypes Using Bioinformatic Methods , 2004, The Journal of Immunology.

[389]  H. S. Kim,et al.  Elevated blood pressures in mice lacking endothelial nitric oxide synthase. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[390]  Eric D Wieben,et al.  Primer on medical genomics. Part III: Microarray experiments and data analysis. , 2002, Mayo Clinic proceedings.

[391]  A. Mathiowetz,et al.  Building proteins from Cα coordinates using the dihedral probability grid Monte Carlo method , 1995, Protein science : a publication of the Protein Society.

[392]  D. Ringe,et al.  Analysis of the binding surfaces of proteins , 1999, Medicinal research reviews.

[393]  A Caflisch,et al.  Hydrophobicity at the surface of proteins , 1999, Proteins.

[394]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[395]  Gerhard Klebe,et al.  Utilising structural knowledge in drug design strategies: applications using Relibase. , 2003, Journal of molecular biology.

[396]  R. Ornstein,et al.  A method for determining the positions of polar hydrogens added to a protein structure that maximizes protein hydrogen bonding , 1992, Proteins.

[397]  Jonas Boström,et al.  Reproducing the conformations of protein-bound ligands: A critical evaluation of several popular conformational searching tools , 2001, J. Comput. Aided Mol. Des..

[398]  Manuel C. Peitsch,et al.  SWISS-MODEL: an automated protein homology-modeling server , 2003, Nucleic Acids Res..

[399]  William J. Welsh,et al.  Enrichment of Ligands for the Serotonin Receptor Using the Shape Signatures Approach , 2005, J. Chem. Inf. Model..

[400]  M. Nirenberg,et al.  RNA Codewords and Protein Synthesis , 1964, Science.

[401]  J. A. Grant,et al.  A shape-based 3-D scaffold hopping method and its application to a bacterial protein-protein interaction. , 2005, Journal of medicinal chemistry.

[402]  S. Wodak,et al.  Modelling the polypeptide backbone with 'spare parts' from known protein structures. , 1989, Protein engineering.

[403]  James E. Bray,et al.  The CATH Database provides insights into protein structure/function relationships , 1999, Nucleic Acids Res..

[404]  O. Edholm,et al.  A fast and simple method to calculate protonation states in proteins , 1999, Proteins.

[405]  S. Subbiah,et al.  Prediction of protein side-chain conformation by packing optimization. , 1991, Journal of molecular biology.

[406]  D. Kostrewa,et al.  Novel inhibitors of DNA gyrase: 3D structure based biased needle screening, hit validation by biophysical methods, and 3D guided optimization. A promising alternative to random screening. , 2000, Journal of medicinal chemistry.

[407]  D Rognan,et al.  Molecular modeling of an antigenic complex between a viral peptide and a class I major histocompatibility glycoprotein , 1992, Proteins.

[408]  J. Bajorath,et al.  Structure-activity relationship anatomy by network-like similarity graphs and local structure-activity relationship indices. , 2008, Journal of medicinal chemistry.

[409]  D. Corrado,et al.  Clinical profile of congenital coronary artery anomalies with origin from the wrong aortic sinus leading to sudden death in young competitive athletes. , 2000, Journal of the American College of Cardiology.

[410]  W R Pearson,et al.  Using the FASTA program to search protein and DNA sequence databases. , 1994, Methods in molecular biology.

[411]  W. Richards,et al.  Identification of ligand binding sites on proteins using a multi-scale approach. , 2002, Journal of the American Chemical Society.

[412]  Gerhard Klebe,et al.  Relibase: design and development of a database for comprehensive analysis of protein-ligand interactions. , 2003, Journal of molecular biology.

[413]  John P. Overington,et al.  How many drug targets are there? , 2006, Nature Reviews Drug Discovery.

[414]  Christoph Steinbeck,et al.  Chemical Entities of Biological Interest: an update , 2009, Nucleic Acids Res..

[415]  K. Bennett,et al.  Optimization Approaches to Semi-Supervised Learning , 2001 .

[416]  George W. A. Milne,et al.  Chem-X and CAMBRIDGE. Comparison of computer generated chemical structures with x-ray crystallographic data , 1993, J. Chem. Inf. Comput. Sci..

[417]  Philip E. Bourne,et al.  Drug Discovery Using Chemical Systems Biology: Repositioning the Safe Medicine Comtan to Treat Multi-Drug and Extensively Drug Resistant Tuberculosis , 2009, PLoS Comput. Biol..

[418]  M Suzuki,et al.  A framework for the DNA-protein recognition code of the probe helix in transcription factors: the chemical and stereochemical rules. , 1994, Structure.

[419]  J. Rao New scoring matrix for amino acid residue exchanges based on residue characteristic physical parameters. , 2009 .

[420]  Sourav Das,et al.  Binding Affinity Prediction with Property-Encoded Shape Distribution Signatures , 2010, J. Chem. Inf. Model..