Validation of Molecular Docking Programs for Virtual Screening against Dihydropteroate Synthase

Dihydropteroate synthase (DHPS) is the target of the sulfonamide class of antibiotics and has been a validated antibacterial drug target for nearly 70 years. The sulfonamides target the p-aminobenzoic acid (pABA) binding site of DHPS and interfere with folate biosynthesis and ultimately prevent bacterial replication. However, widespread bacterial resistance to these drugs has severely limited their effectiveness. This study explores the second and more highly conserved pterin binding site of DHPS as an alternative approach to developing novel antibiotics that avoid resistance. In this study, five commonly used docking programs, FlexX, Surflex, Glide, GOLD, and DOCK, and nine scoring functions, were evaluated for their ability to rank-order potential lead compounds for an extensive virtual screening study of the pterin binding site of B. anthracis DHPS. Their performance in ligand docking and scoring was judged by their ability to reproduce a known inhibitor conformation and to efficiently detect known active compounds seeded into three separate decoy sets. Two other metrics were used to assess performance; enrichment at 1% and 2% and Receiver Operating Characteristic (ROC) curves. The effectiveness of postdocking relaxation prior to rescoring and consensus scoring were also evaluated. Finally, we have developed a straightforward statistical method of including the inhibition constants of the known active compounds when analyzing enrichment results to more accurately assess scoring performance, which we call the 'sum of the sum of log rank' or SSLR. Of the docking and scoring functions evaluated, Surflex with Surflex-Score and Glide with GlideScore were the best overall performers for use in virtual screening against the DHPS target, with neither combination showing statistically significant superiority over the other in enrichment studies or pose selection. Postdocking ligand relaxation and consensus scoring did not improve overall enrichment.

[1]  Li Xing,et al.  Evaluation and application of multiple scoring functions for a virtual screening experiment , 2004, J. Comput. Aided Mol. Des..

[2]  Martin Stahl,et al.  Binding site characteristics in structure-based virtual screening: evaluation of current docking tools , 2003, Journal of molecular modeling.

[3]  W Patrick Walters,et al.  A detailed comparison of current docking and scoring methods on systems of pharmaceutical relevance , 2004, Proteins.

[4]  A. N. Jain,et al.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites. , 1996, Chemistry & biology.

[5]  R. Clark,et al.  Consensus scoring for ligand/protein interactions. , 2002, Journal of molecular graphics & modelling.

[6]  E. Fluder,et al.  Protocols for Bridging the Peptide to Nonpeptide Gap in Topological Similarity Searches. , 2001 .

[7]  Robin Taylor,et al.  Comparing protein–ligand docking programs is difficult , 2005, Proteins.

[8]  D. E. Clark,et al.  Flexible docking using tabu search and an empirical estimate of binding affinity , 1998, Proteins.

[9]  M. Lawrence,et al.  The three-dimensional structure of the bifunctional 6-hydroxymethyl-7,8-dihydropterin pyrophosphokinase/dihydropteroate synthase of Saccharomyces cerevisiae. , 2005, Journal of molecular biology.

[10]  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.

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

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

[13]  W. Mallory,et al.  Pyrimido[4,5-c]pyridazines. 3. Preferential formation of 8-amino-1H-pyrimido[4,5-c]-1,2-diazepin-6(7H)-ones by cyclizations with .alpha.,.gamma.-dioxo esters , 1982 .

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

[15]  B. Shoichet,et al.  Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B. , 2002, Journal of medicinal chemistry.

[16]  Richard A. Lewis,et al.  Lessons in molecular recognition: the effects of ligand and protein flexibility on molecular docking accuracy. , 2004, Journal of medicinal chemistry.

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

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

[19]  R. Ferone,et al.  Inhibitors of dihydropteroate synthase: substituent effects in the side-chain aromatic ring of 6-[[3-(aryloxy)propyl]amino]-5-nitrosoisocytosines and synthesis and inhibitory potency of bridged 5-nitrosoisocytosine-p-aminobenzoic acid analogues. , 1986, Journal of medicinal chemistry.

[20]  J M Blaney,et al.  A geometric approach to macromolecule-ligand interactions. , 1982, Journal of molecular biology.

[21]  K. Binder,et al.  The Monte Carlo Method in Condensed Matter Physics , 1992 .

[22]  Richard D. Taylor,et al.  Virtual Screening Using Protein—Ligand Docking: Avoiding Artificial Enrichment. , 2004 .

[23]  J. Gasteiger,et al.  ITERATIVE PARTIAL EQUALIZATION OF ORBITAL ELECTRONEGATIVITY – A RAPID ACCESS TO ATOMIC CHARGES , 1980 .

[24]  Ola Sköld,et al.  Sulfonamide resistance: mechanisms and trends. , 2000, Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy.

[25]  Maria Kontoyianni,et al.  Evaluation of docking performance: comparative data on docking algorithms. , 2004, Journal of medicinal chemistry.

[26]  Ajay N. Jain,et al.  Parameter estimation for scoring protein-ligand interactions using negative training data. , 2006, Journal of medicinal chemistry.

[27]  M. Page,et al.  Structure and function of the dihydropteroate synthase from Staphylococcus aureus. , 1997, Journal of molecular biology.

[28]  Robert D. Clark,et al.  Managing bias in ROC curves , 2008, J. Comput. Aided Mol. Des..

[29]  Hege S. Beard,et al.  Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. , 2004, Journal of medicinal chemistry.

[30]  Kenji Onodera,et al.  Evaluations of Molecular Docking Programs for Virtual Screening , 2007, J. Chem. Inf. Model..

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

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

[33]  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.

[34]  E. S. Pearson,et al.  On the Problem of the Most Efficient Tests of Statistical Hypotheses , 1933 .

[35]  Jerzy Neyman,et al.  The testing of statistical hypotheses in relation to probabilities a priori , 1933, Mathematical Proceedings of the Cambridge Philosophical Society.

[36]  J. Champness,et al.  Crystal structure of the anti-bacterial sulfonamide drug target dihydropteroate synthase , 1997, Nature Structural Biology.

[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]  Ajay N. Jain.  Surflex: fully automatic flexible molecular docking using a molecular similarity-based search engine. , 2003, Journal of medicinal chemistry.

[39]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

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

[41]  R. Ferone,et al.  Monocyclic pteridine analogues. Inhibition of Escherichia coli dihydropteroate synthase by 6-amino-5-nitrosoisocytosines. , 1985, Journal of medicinal chemistry.

[42]  Luhua Lai,et al.  Further development and validation of empirical scoring functions for structure-based binding affinity prediction , 2002, J. Comput. Aided Mol. Des..

[43]  J. Derrick,et al.  Dihydropteroate synthase from Streptococcus pneumoniae: structure, ligand recognition and mechanism of sulfonamide resistance. , 2008, The Biochemical journal.

[44]  Todd J. A. Ewing,et al.  Critical evaluation of search algorithms for automated molecular docking and database screening , 1997, J. Comput. Chem..

[45]  W. Hol,et al.  Crystal structure of Mycobacterium tuberculosis 7,8-dihydropteroate synthase in complex with pterin monophosphate: new insight into the enzymatic mechanism and sulfa-drug action. , 2000, Journal of molecular biology.

[46]  Thomas Lengauer,et al.  A fast flexible docking method using an incremental construction algorithm. , 1996, Journal of molecular biology.

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

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

[49]  Y. Martin,et al.  A general and fast scoring function for protein-ligand interactions: a simplified potential approach. , 1999, Journal of medicinal chemistry.

[50]  Paul Watson,et al.  Virtual Screening Using Protein-Ligand Docking: Avoiding Artificial Enrichment , 2004, J. Chem. Inf. Model..

[51]  Ruben Abagyan,et al.  Comparative study of several algorithms for flexible ligand docking , 2003, J. Comput. Aided Mol. Des..

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

[53]  Christopher I. Bayly,et al.  Evaluating Virtual Screening Methods: Good and Bad Metrics for the "Early Recognition" Problem , 2007, J. Chem. Inf. Model..

[54]  Ajay N. Jain.  Bias, reporting, and sharing: computational evaluations of docking methods , 2008, J. Comput. Aided Mol. Des..