Accuracy Assessment of Protein-Based Docking Programs against RNA Targets

Ribonucleic acid (RNA) molecules play central roles in a variety of biological processes and, hence, are attractive targets for therapeutic intervention. In recent years, molecular docking techniques have become one of the most popular and successful approaches in drug discovery; however, almost all docking programs are protein based. The adaptability of popular docking programs in RNA world has not been systematically evaluated. This paper describes the comprehensive evaluation of two widely used protein-based docking programs--GOLD and Glide--for their docking and virtual screening accuracies against RNA targets. Using multiple docking strategies, both GOLD 4.0 and Glide 5.0 successfully reproduced most binding modes of the 60 tested RNA complexes. Applying different docking/scoring combinations, significant enrichments from the simulated virtual and fragment screening experiments were achieved against tRNA decoding A site of 16S rRNA (rRNA A-site). Our study demonstrated that current protein-based docking programs can fulfill general docking tasks against RNA, and these programs are very helpful in RNA-based drug discovery and design.

[1]  M. Jacobson,et al.  Virtual screening against highly charged active sites: identifying substrates of alpha-beta barrel enzymes. , 2005, Biochemistry.

[2]  Miklos Feher,et al.  Effect of Input Differences on the Results of Docking Calculations , 2009, J. Chem. Inf. Model..

[3]  Zhi Chen,et al.  An Improved PMF Scoring Function for Universally Predicting the Interactions of a Ligand with Protein, DNA, and RNA , 2008, J. Chem. Inf. Model..

[4]  Gilles Marcou,et al.  Optimizing Fragment and Scaffold Docking by Use of Molecular Interaction Fingerprints , 2007, J. Chem. Inf. Model..

[5]  John E Kerrigan,et al.  Coupling of drug protonation to the specific binding of aminoglycosides to the A site of 16 S rRNA: elucidation of the number of drug amino groups involved and their identities. , 2003, Journal of molecular biology.

[6]  Gabriele Varani,et al.  Validation of automated docking programs for docking and database screening against RNA drug targets. , 2004, Journal of medicinal chemistry.

[7]  Richard D. Taylor,et al.  Improved protein–ligand docking using GOLD , 2003, Proteins.

[8]  D. Rognan,et al.  Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. , 2000, Journal of medicinal chemistry.

[9]  Ajay N. Jain.  Effects of protein conformation in docking: improved pose prediction through protein pocket adaptation , 2009, J. Comput. Aided Mol. Des..

[10]  Andrea Rizzi,et al.  Virtual Screening Using PLS Discriminant Analysis and ROC Curve Approach: An Application Study on PDE4 Inhibitors , 2008, J. Chem. Inf. Model..

[11]  Ecker,et al.  RNA as a small-molecule drug target: doubling the value of genomics. , 1999, Drug discovery today.

[12]  C. E. Peishoff,et al.  A critical assessment of docking programs and scoring functions. , 2006, Journal of medicinal chemistry.

[13]  Ricardo L. Mancera,et al.  Ligand-Protein Docking with Water Molecules , 2008, J. Chem. Inf. Model..

[14]  Anthony Nicholls,et al.  What do we know and when do we know it? , 2008, J. Comput. Aided Mol. Des..

[15]  Stephen Hanessian,et al.  Docking of aminoglycosides to hydrated and flexible RNA. , 2006, Journal of medicinal chemistry.

[16]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[17]  Jin Li,et al.  On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors , 2006, J. Chem. Inf. Model..

[18]  Thierry Langer,et al.  The discovery of new 11beta-hydroxysteroid dehydrogenase type 1 inhibitors by common feature pharmacophore modeling and virtual screening. , 2006, Journal of medicinal chemistry.

[19]  Gabriele Varani,et al.  Rational design of inhibitors of HIV-1 TAR RNA through the stabilisation of electrostatic "hot spots". , 2004, Journal of molecular biology.

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

[21]  Brian K Shoichet,et al.  Prediction of protein-ligand interactions. Docking and scoring: successes and gaps. , 2006, Journal of medicinal chemistry.

[22]  Liping Yu,et al.  Discovery of aminoglycoside mimetics by NMR-based screening of Escherichia coli A-site RNA. , 2003, Journal of the American Chemical Society.

[23]  S. Mahmood,et al.  3D-QSAR and molecular docking studies of 1,3,5-triazene-2,4-diamine derivatives against r-RNA: novel bacterial translation inhibitors. , 2008, Journal of molecular graphics & modelling.

[24]  Didier Rognan,et al.  Comparative evaluation of eight docking tools for docking and virtual screening accuracy , 2004, Proteins.

[25]  W D Wilson,et al.  Targeting RNA with small molecules. , 2000, Current medicinal chemistry.

[26]  Thomas Hermann,et al.  Structure-Guided Discovery of Novel Aminoglycoside Mimetics as Antibacterial Translation Inhibitors , 2005, Antimicrobial Agents and Chemotherapy.

[27]  E. Jaeger,et al.  Comparison of automated docking programs as virtual screening tools. , 2005, Journal of Medicinal Chemistry.

[28]  Thomas Hermann,et al.  Synthesis and SAR of 3,5-diamino-piperidine derivatives: novel antibacterial translation inhibitors as aminoglycoside mimetics. , 2007, Bioorganic & medicinal chemistry letters.

[29]  F. Aboul-Ela,et al.  Design and implementation of an ribonucleic acid (RNA) directed fragment library. , 2009, Journal of medicinal chemistry.

[30]  T. Hermann,et al.  Strategies for the Design of Drugs Targeting RNA and RNA-Protein Complexes. , 2000, Angewandte Chemie.

[31]  I. Kuntz,et al.  DOCK 6: combining techniques to model RNA-small molecule complexes. , 2009, RNA.

[32]  Jonathan W. Essex,et al.  A review of protein-small molecule docking methods , 2002, J. Comput. Aided Mol. Des..

[33]  Christophe Guilbert,et al.  Discovery of ligands for a novel target, the human telomerase RNA, based on flexible-target virtual screening and NMR. , 2008, Journal of medicinal chemistry.

[34]  Tudor I. Oprea,et al.  Integrating virtual screening in lead discovery. , 2004, Current opinion in chemical biology.

[35]  Thomas L. James,et al.  Docking to RNA via Root-Mean-Square-Deviation-Driven Energy Minimization with Flexible Ligands and Flexible Targets , 2008, J. Chem. Inf. Model..

[36]  Ruben Abagyan,et al.  Identification of ligands for RNA targets via structure-based virtual screening: HIV-1 TAR , 2000, J. Comput. Aided Mol. Des..

[37]  J. Pin,et al.  Virtual screening workflow development guided by the "receiver operating characteristic" curve approach. Application to high-throughput docking on metabotropic glutamate receptor subtype 4. , 2005, Journal of medicinal chemistry.

[38]  Thomas Hermann,et al.  Structure-activity relationships of novel antibacterial translation inhibitors: 3,5-diamino-piperidinyl triazines. , 2006, Bioorganic & medicinal chemistry letters.

[39]  Nicolas Foloppe,et al.  A structure-based strategy to identify new molecular scaffolds targeting the bacterial ribosomal A-site. , 2004, Bioorganic & medicinal chemistry.

[40]  J. Gready,et al.  Combining docking and molecular dynamic simulations in drug design , 2006, Medicinal research reviews.

[41]  Maria Kontoyianni,et al.  Evaluation of library ranking efficacy in virtual screening , 2005, J. Comput. Chem..

[42]  Richard D. Taylor,et al.  Modeling water molecules in protein-ligand docking using GOLD. , 2005, Journal of medicinal chemistry.

[43]  I D Kuntz,et al.  Structure-based discovery of ligands targeted to the RNA double helix. , 1997, Biochemistry.

[44]  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.

[45]  Thomas Hermann,et al.  Rational design of azepane-glycoside antibiotics targeting the bacterial ribosome. , 2004, Bioorganic & medicinal chemistry letters.

[46]  Caterina Barillari,et al.  Classification of water molecules in protein binding sites. , 2007, Journal of the American Chemical Society.

[47]  S. Mobashery,et al.  Versatility of Aminoglycosides and Prospects for Their Future , 2003, Clinical Microbiology Reviews.

[48]  Stephan Heyse,et al.  From targets to leads: the importance of advanced data analysis for decision support in drug discovery. , 2005, Current opinion in drug discovery & development.

[49]  Renxiao Wang,et al.  Comparative evaluation of 11 scoring functions for molecular docking. , 2003, Journal of medicinal chemistry.

[50]  Thomas E. Exner,et al.  Influence of Protonation, Tautomeric, and Stereoisomeric States on Protein-Ligand Docking Results , 2009, J. Chem. Inf. Model..

[51]  W. L. Jorgensen.  The Many Roles of Computation in Drug Discovery , 2004, Science.

[52]  E Westhof,et al.  Crystal structure of paromomycin docked into the eubacterial ribosomal decoding A site. , 2001, Structure.

[53]  B. Shoichet,et al.  Molecular docking and ligand specificity in fragment-based inhibitor discovery. , 2009, Nature chemical biology.

[54]  Thomas Hermann,et al.  Novel Paromamine Derivatives Exploring Shallow‐Groove Recognition of Ribosomal‐ Decoding‐Site RNA , 2002, Chembiochem : a European journal of chemical biology.

[55]  Nicolas Foloppe,et al.  Towards the discovery of drug-like RNA ligands? , 2006, Drug discovery today.

[56]  G. Varani,et al.  Targeting RNA with small-molecule drugs: therapeutic promise and chemical challenges. , 2001, Accounts of chemical research.

[57]  Hongming Wang,et al.  Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide , 2009, J. Comput. Aided Mol. Des..

[58]  Thomas Hermann,et al.  Novel 2,5-dideoxystreptamine derivatives targeting the ribosomal decoding site RNA. , 2002, Bioorganic & medicinal chemistry letters.

[59]  Lakshmi P Kotra,et al.  Design of novel antibiotics that bind to the ribosomal acyltransfer site. , 2002, Journal of the American Chemical Society.

[60]  S. David Morley,et al.  Validation of an empirical RNA-ligand scoring function for fast flexible docking using RiboDock® , 2004, J. Comput. Aided Mol. Des..

[61]  Matthew P. Repasky,et al.  Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. , 2004, Journal of medicinal chemistry.

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

[63]  Thomas Hermann,et al.  Novel Acyclic Deoxystreptamine Mimetics Targeting the Ribosomal Decoding Site , 2003, Chembiochem : a European journal of chemical biology.

[64]  Zhihua Du,et al.  Structure-based computational database screening, in vitro assay, and NMR assessment of compounds that target TAR RNA. , 2002, Chemistry & biology.

[65]  T. James,et al.  NMR-based characterization of phenothiazines as a RNA binding scaffold. , 2004, Journal of the American Chemical Society.

[66]  Holger Gohlke,et al.  DrugScoreRNAKnowledge-Based Scoring Function To Predict RNA-Ligand Interactions , 2007, J. Chem. Inf. Model..

[67]  Yongbo Hu,et al.  Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy , 2009, J. Chem. Inf. Model..

[68]  J. Puglisi,et al.  Paromomycin binding induces a local conformational change in the A-site of 16 S rRNA. , 1998, Journal of molecular biology.