BSP‐SLIM: A blind low‐resolution ligand‐protein docking approach using predicted protein structures

We developed BSP‐SLIM, a new method for ligand–protein blind docking using low‐resolution protein structures. For a given sequence, protein structures are first predicted by I‐TASSER; putative ligand binding sites are transferred from holo‐template structures which are analogous to the I‐TASSER models; ligand–protein docking conformations are then constructed by shape and chemical match of ligand with the negative image of binding pockets. BSP‐SLIM was tested on 71 ligand–protein complexes from the Astex diverse set where the protein structures were predicted by I‐TASSER with an average RMSD 2.92 Å on the binding residues. Using I‐TASSER models, the median ligand RMSD of BSP‐SLIM docking is 3.99 Å which is 5.94 Å lower than that by AutoDock; the median binding‐site error by BSP‐SLIM is 1.77 Å which is 6.23 Å lower than that by AutoDock and 3.43 Å lower than that by LIGSITECSC. Compared to the models using crystal protein structures, the median ligand RMSD by BSP‐SLIM using I‐TASSER models increases by 0.87 Å, while that by AutoDock increases by 8.41 Å; the median binding‐site error by BSP‐SLIM increase by 0.69Å while that by AutoDock and LIGSITECSC increases by 7.31 Å and 1.41 Å, respectively. As case studies, BSP‐SLIM was used in virtual screening for six target proteins, which prioritized actives of 25% and 50% in the top 9.2% and 17% of the library on average, respectively. These results demonstrate the usefulness of the template‐based coarse‐grained algorithms in the low‐resolution ligand–protein docking and drug‐screening. An on‐line BSP‐SLIM server is freely available at http://zhanglab.ccmb.med.umich.edu/BSP‐SLIM. Proteins 2012. © 2011 Wiley Periodicals, Inc.

[1]  Carlton A Taft,et al.  Current topics in computer-aided drug design. , 2008, Journal of pharmaceutical sciences.

[2]  J. Skolnick,et al.  A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation , 2008, Proceedings of the National Academy of Sciences.

[3]  Paul N. Mortenson,et al.  Diverse, high-quality test set for the validation of protein-ligand docking performance. , 2007, Journal of medicinal chemistry.

[4]  B. Shoichet,et al.  Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes. , 2003, Journal of medicinal chemistry.

[5]  Sitao Wu,et al.  LOMETS: A local meta-threading-server for protein structure prediction , 2007, Nucleic acids research.

[6]  R. Wade,et al.  Computational approaches to identifying and characterizing protein binding sites for ligand design , 2009, Journal of molecular recognition : JMR.

[7]  Hui Sun Lee,et al.  Improving Virtual Screening Performance against Conformational Variations of Receptors by Shape Matching with Ligand Binding Pocket , 2009, J. Chem. Inf. Model..

[8]  J. Skolnick,et al.  Local energy landscape flattening: Parallel hyperbolic Monte Carlo sampling of protein folding , 2002, Proteins.

[9]  Herbert Köppen Virtual screening - what does it give us? , 2009, Current opinion in drug discovery & development.

[10]  Michal Vieth,et al.  Lessons in Molecular Recognition, 2. Assessing and Improving Cross-Docking Accuracy , 2007, J. Chem. Inf. Model..

[11]  Yang Zhang,et al.  I-TASSER: a unified platform for automated protein structure and function prediction , 2010, Nature Protocols.

[12]  J. Irwin,et al.  Docking and chemoinformatic screens for new ligands and targets. , 2009, Current opinion in biotechnology.

[13]  G. Klebe Virtual ligand screening: strategies, perspectives and limitations , 2006, Drug Discovery Today.

[14]  Irwin D. Kuntz,et al.  Development and validation of a modular, extensible docking program: DOCK 5 , 2006, J. Comput. Aided Mol. Des..

[15]  M. Swindells,et al.  Protein clefts in molecular recognition and function. , 1996, Protein science : a publication of the Protein Society.

[16]  A. Sali,et al.  Protein Structure Prediction and Structural Genomics , 2001, Science.

[17]  D. van der Spoel,et al.  Efficient docking of peptides to proteins without prior knowledge of the binding site , 2002, Protein science : a publication of the Protein Society.

[18]  Yang Zhang,et al.  REMO: A new protocol to refine full atomic protein models from C‐alpha traces by optimizing hydrogen‐bonding networks , 2009, Proteins.

[19]  Yang Zhang Progress and challenges in protein structure prediction. , 2008, Current opinion in structural biology.

[20]  Cathy H. Wu,et al.  The Universal Protein Resource (UniProt) , 2004, Nucleic Acids Res..

[21]  Conrad C. Huang,et al.  UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..

[22]  Michal Brylinski,et al.  FINDSITELHM: A Threading-Based Approach to Ligand Homology Modeling , 2009, PLoS Comput. Biol..

[23]  M. Schroeder,et al.  LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation , 2006, BMC Structural Biology.

[24]  Yang Zhang,et al.  Template‐based modeling and free modeling by I‐TASSER in CASP7 , 2007, Proteins.

[25]  J. Skolnick,et al.  Automated structure prediction of weakly homologous proteins on a genomic scale. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Michal Brylinski,et al.  Q‐DockLHM: Low‐resolution refinement for ligand comparative modeling , 2009, J. Comput. Chem..

[27]  D. van der Spoel,et al.  Blind docking of drug‐sized compounds to proteins with up to a thousand residues , 2006, FEBS letters.

[28]  Jaime Prilusky,et al.  Assessment of CASP8 structure predictions for template free targets , 2009, Proteins.

[29]  Burkhard Rost,et al.  Evaluation of template‐based models in CASP8 with standard measures , 2009, Proteins.

[30]  Yang Zhang,et al.  I-TASSER server for protein 3D structure prediction , 2008, BMC Bioinformatics.

[31]  Pedro Alexandrino Fernandes,et al.  Protein–ligand docking: Current status and future challenges , 2006, Proteins.

[32]  Yang Zhang,et al.  I‐TASSER: Fully automated protein structure prediction in CASP8 , 2009, Proteins.

[33]  David S. Goodsell,et al.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility , 2009, J. Comput. Chem..

[34]  Mona Singh,et al.  Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure , 2009, PLoS Comput. Biol..

[35]  J. Irwin,et al.  Benchmarking sets for molecular docking. , 2006, Journal of medicinal chemistry.

[36]  Thomas A. Halgren,et al.  Identifying and Characterizing Binding Sites and Assessing Druggability , 2009, J. Chem. Inf. Model..

[37]  Prasanna R Kolatkar,et al.  Assessment of CASP7 structure predictions for template free targets , 2007, Proteins.

[38]  Yang Zhang Protein structure prediction: when is it useful? , 2009, Current opinion in structural biology.

[39]  Yang Zhang,et al.  SPICKER: A clustering approach to identify near‐native protein folds , 2004, J. Comput. Chem..

[40]  J. Skolnick,et al.  Ab initio modeling of small proteins by iterative TASSER simulations , 2007, BMC Biology.

[41]  Yang Zhang,et al.  How significant is a protein structure similarity with TM-score = 0.5? , 2010, Bioinform..

[42]  Philip M. Dean,et al.  Three-dimensional hydrogen-bond geometry and probability information from a crystal survey , 1996, J. Comput. Aided Mol. Des..

[43]  Yang Zhang,et al.  Scoring function for automated assessment of protein structure template quality , 2004, Proteins.

[44]  J. Skolnick,et al.  TM-align: a protein structure alignment algorithm based on the TM-score , 2005, Nucleic acids research.

[45]  A. Sali,et al.  Comparative protein structure modeling of genes and genomes. , 2000, Annual review of biophysics and biomolecular structure.