Searching for bioactive conformations of drug-like ligands with current force fields: how good are we?

Drug-like ligands obtained from protein–ligand complexes deposited in the Protein Databank were subjected to conformational searching using various force fields and solvation settings. For each ligand, the resulting conformer pool was examined for the presence of the bioactive (crystal pose-like) conformation. Similarity of conformers toward the crystal-pose was quantified as the best achievable root mean squared deviation (RMSD, heavy atoms only). Analyzing the conformer pools generated by various force fields revealed only small differences in the likelihood of finding a crystal pose-like conformation. However, employing different solvents in the conformational search was found to be very important for achieving RMSDs below 1.0 Å. The best statistical values of likelihood were observed with a recently released force field covering a large portion of dihedral angles occurring in drug-like compounds in combination with the water as solvent. In order to enable computational chemists and modelers to efficiently use available software tools, we have additionally performed several focused analyses on ligands, grouped according to descriptors most relevant for the rational drug design.

[1]  T. Halgren Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94 , 1996, J. Comput. Chem..

[2]  Andrew J. Tebben,et al.  Macrocycle Conformational Sampling with MacroModel , 2014, J. Chem. Inf. Model..

[3]  Xicheng Wang,et al.  Bioactive conformational generation of small molecules: A comparative analysis between force-field and multiple empirical criteria based methods , 2010, BMC Bioinformatics.

[4]  Amedeo Caflisch,et al.  Library screening by fragment‐based docking , 2009, Journal of molecular recognition : JMR.

[5]  Ting Wang,et al.  Free Energy-Based Conformational Search Algorithm Using the Movable Type Sampling Method. , 2015, Journal of chemical theory and computation.

[6]  Woody Sherman,et al.  Close intramolecular sulfur–oxygen contacts: modified force field parameters for improved conformation generation , 2012, Journal of Computer-Aided Molecular Design.

[7]  Stephen R. Johnson,et al.  Molecular properties that influence the oral bioavailability of drug candidates. , 2002, Journal of medicinal chemistry.

[8]  Christof H. Schwab,et al.  Conformations and 3D pharmacophore searching. , 2010, Drug discovery today. Technologies.

[9]  Benjamin A. Ellingson,et al.  Conformer Generation with OMEGA: Algorithm and Validation Using High Quality Structures from the Protein Databank and Cambridge Structural Database , 2010, J. Chem. Inf. Model..

[10]  Robert P. Sheridan,et al.  FLOG: A system to select ‘quasi-flexible’ ligands complementary to a receptor of known three-dimensional structure , 1994, J. Comput. Aided Mol. Des..

[11]  L. Evangelisti,et al.  Conformational flexibility of mephenesin. , 2014, The journal of physical chemistry. B.

[12]  P. Kollman,et al.  A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules , 1995 .

[13]  Federico D. Sacerdoti,et al.  Scalable Algorithms for Molecular Dynamics Simulations on Commodity Clusters , 2006, ACM/IEEE SC 2006 Conference (SC'06).

[14]  P. Kollman,et al.  An all atom force field for simulations of proteins and nucleic acids , 1986, Journal of computational chemistry.

[15]  W. L. Jorgensen,et al.  The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin. , 1988, Journal of the American Chemical Society.

[16]  Nicolas Foloppe,et al.  Is conformational sampling of drug‐like molecules a solved problem? , 2011 .

[17]  Jennifer L. Knight,et al.  OPLS3: A Force Field Providing Broad Coverage of Drug-like Small Molecules and Proteins. , 2016, Journal of chemical theory and computation.

[18]  H. Nar,et al.  Ligand bioactive conformation plays a critical role in the design of drugs that target the hepatitis C virus NS3 protease. , 2014, Journal of medicinal chemistry.

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

[20]  Olivier Sperandio,et al.  FAF-Drugs2: Free ADME/tox filtering tool to assist drug discovery and chemical biology projects , 2008, BMC Bioinformatics.

[21]  Woody Sherman,et al.  ConfGen: A Conformational Search Method for Efficient Generation of Bioactive Conformers , 2010, J. Chem. Inf. Model..

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

[23]  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..

[24]  Sheng-Yong Yang,et al.  Pharmacophore modeling and applications in drug discovery: challenges and recent advances. , 2010, Drug discovery today.

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

[26]  Matthias Rarey,et al.  Conformational Sampling for Large-Scale Virtual Screening: Accuracy versus Ensemble Size , 2009, J. Chem. Inf. Model..

[27]  Nicolas Foloppe,et al.  Drug-like Bioactive Structures and Conformational Coverage with the LigPrep/ConfGen Suite: Comparison to Programs MOE and Catalyst , 2010, J. Chem. Inf. Model..

[28]  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.

[29]  Rolf Apweiler,et al.  E-MSD: an integrated data resource for bioinformatics. , 2004, Nucleic acids research.

[30]  Chris Morley,et al.  Open Babel: An open chemical toolbox , 2011, J. Cheminformatics.

[31]  Nicolas Foloppe,et al.  Conformational Sampling of Druglike Molecules with MOE and Catalyst: Implications for Pharmacophore Modeling and Virtual Screening , 2008, J. Chem. Inf. Model..

[32]  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.

[33]  M. Mezei,et al.  Molecular docking: a powerful approach for structure-based drug discovery. , 2011, Current computer-aided drug design.

[34]  Matthias Rarey,et al.  Inside Cover: CONFECT: Conformations from an Expert Collection of Torsion Patterns (ChemMedChem 10/2013) , 2013 .

[35]  I. Kuntz,et al.  Conformational analysis of flexible ligands in macromolecular receptor sites , 1992 .

[36]  I. Bruno,et al.  Cambridge Structural Database , 2002 .

[37]  Martin Smiesko DOLINA - Docking Based on a Local Induced-Fit Algorithm: Application toward Small-Molecule Binding to Nuclear Receptors , 2013, J. Chem. Inf. Model..

[38]  Matthias Rarey,et al.  CONFECT: Conformations from an Expert Collection of Torsion Patterns , 2013, ChemMedChem.

[39]  Daniel Cappel,et al.  Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling , 2015, Journal of Computer-Aided Molecular Design.

[40]  Gerhard Klebe,et al.  Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures , 1994, J. Chem. Inf. Comput. Sci..

[41]  Chen Dong,et al.  Performance of four different force fields for simulations of dipeptide conformations: GlyGly, GlyGly−, GlyGly · Cl−, GlyGly · Na+ and GlyGly · (H2O)2 , 2014, Journal of Molecular Modeling.

[42]  Aniko Simon,et al.  eHiTS: a new fast, exhaustive flexible ligand docking system. , 2007, Journal of molecular graphics & modelling.

[43]  Matthew P. Repasky,et al.  WScore: A Flexible and Accurate Treatment of Explicit Water Molecules in Ligand-Receptor Docking. , 2016, Journal of medicinal chemistry.

[44]  Mark S. Johnson,et al.  Generating Conformer Ensembles Using a Multiobjective Genetic Algorithm , 2007, J. Chem. Inf. Model..

[45]  Charlotte M. Deane,et al.  Freely Available Conformer Generation Methods: How Good Are They? , 2012, J. Chem. Inf. Model..

[46]  U. Singh,et al.  A NEW FORCE FIELD FOR MOLECULAR MECHANICAL SIMULATION OF NUCLEIC ACIDS AND PROTEINS , 1984 .