An Anchor-Dependent Molecular Docking Process for Docking Small Flexible Molecules into Rigid Protein Receptors

A molecular docking method designated as ADDock, anchor-dependent molecular docking process for docking small flexible molecules into rigid protein receptors, is presented in this article. ADDock makes the bond connection lists for atoms based on anchors chosen for building molecular structures for docking small flexible molecules or ligands into rigid active sites of protein receptors. ADDock employs an extended version of piecewise linear potential for scoring the docked structures. Since no translational motion for small molecules is implemented during the docking process, ADDock searches the best docking result by systematically changing the anchors chosen, which are usually the single-edge connected nodes or terminal hydrogen atoms of ligands. ADDock takes intact ligand structures generated during the docking process for computing the docked scores; therefore, no energy minimization is required in the evaluation phase of docking. The docking accuracy by ADDock for 92 receptor-ligand complexes docked is 91.3%. All these complexes have been docked by other groups using other docking methods. The receptor-ligand steric interaction energies computed by ADDock for some sets of active and inactive compounds selected and docked into the same receptor active sites are apparently separated. These results show that based on the steric interaction energies computed between the docked structures and receptor active sites, ADDock is able to separate active from inactive compounds for both being docked into the same receptor.

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

[2]  M. Sternberg,et al.  Automated prediction of protein function and detection of functional sites from structure. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[3]  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..

[4]  Haruki Nakamura,et al.  Announcing the worldwide Protein Data Bank , 2003, Nature Structural Biology.

[5]  David Hestenes Proper dynamics of a rigid point particle , 1974 .

[6]  R. Abagyan,et al.  Biased probability Monte Carlo conformational searches and electrostatic calculations for peptides and proteins. , 1994, Journal of molecular biology.

[7]  Fenglou Mao,et al.  Potential of mean force for protein–protein interaction studies , 2002, Proteins.

[8]  T. L. Blundell,et al.  DOCKER, an interactive program for simulating protein receptor and substrate interactions , 1983 .

[9]  Milan Randic,et al.  Graph Theoretical Approach to Recognition of Structural Similarity in Molecules , 1979, J. Chem. Inf. Comput. Sci..

[10]  M. Grütter,et al.  The crystal structures of recombinant glycosylated human renin alone and in complex with a transition state analog inhibitor. , 1991, Journal of structural biology.

[11]  Robert P. Sheridan,et al.  Flexibases: A way to enhance the use of molecular docking methods , 1994, J. Comput. Aided Mol. Des..

[12]  F R Salemme,et al.  An hypothetical structure for an intermolecular electron transfer complex of cytochromes c and b5. , 1976, Journal of molecular biology.

[13]  Jun Tang,et al.  Prediction of Multiple Binding Modes of the CDK2 Inhibitors, Anilinopyrazoles, Using the Automated Docking Programs GOLD, FlexX, and LigandFit: An Evaluation of Performance , 2006, J. Chem. Inf. Model..

[14]  I. Kuntz,et al.  Molecular docking to ensembles of protein structures. , 1997, Journal of molecular biology.

[15]  W. Greenlee,et al.  SAR development of polycyclic guanine derivatives targeted to the discovery of a selective PDE5 inhibitor for treatment of erectile dysfunction. , 2004, Bioorganic & medicinal chemistry letters.

[16]  H A Scheraga,et al.  Reaching the global minimum in docking simulations: a Monte Carlo energy minimization approach using Bezier splines. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Robert P. Sheridan,et al.  Docking Flexible Ligands to Macromolecular Receptors by Molecular Shape. , 1987 .

[18]  Jürgen Bajorath,et al.  New methodologies for ligand-based virtual screening. , 2005, Current pharmaceutical design.

[19]  Yvonne C. Martin,et al.  Use of Structure-Activity Data To Compare Structure-Based Clustering Methods and Descriptors for Use in Compound Selection , 1996, J. Chem. Inf. Comput. Sci..

[20]  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..

[21]  Jean-Claude Latombe,et al.  A Motion Planning Approach to Flexible Ligand Binding , 1999, ISMB.

[22]  D. Koshland Application of a Theory of Enzyme Specificity to Protein Synthesis. , 1958, Proceedings of the National Academy of Sciences of the United States of America.

[23]  I. Kuntz,et al.  Using shape complementarity as an initial screen in designing ligands for a receptor binding site of known three-dimensional structure. , 1988, Journal of medicinal chemistry.

[24]  H. Wolfson,et al.  Shape complementarity at protein–protein interfaces , 1994, Biopolymers.

[25]  Aurélien Grosdidier,et al.  EADock: Docking of small molecules into protein active sites with a multiobjective evolutionary optimization , 2007, Proteins.

[26]  René Thomsen,et al.  MolDock: a new technique for high-accuracy molecular docking. , 2006, Journal of medicinal chemistry.

[27]  W. Kabsch A discussion of the solution for the best rotation to relate two sets of vectors , 1978 .

[28]  Natasja Brooijmans,et al.  Molecular recognition and docking algorithms. , 2003, Annual review of biophysics and biomolecular structure.

[29]  Hans J. Vogel,et al.  Protein–membrane electrostatic interactions: Application of the Lekner summation technique , 2001 .

[30]  S. Wodak,et al.  Hemoglobin interaction in sickle cell fibers. I: Theoretical approaches to the molecular contacts. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[31]  Yuan-Ping Pang,et al.  EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases , 2001, J. Comput. Chem..

[32]  Thy-Hou Lin,et al.  Modeling Ligand-Receptor Interaction for Some MHC Class II HLA-DR4 Peptide Mimetic Inhibitors Using Several Molecular Docking and 3D QSAR Techniques , 2005, J. Chem. Inf. Model..

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

[34]  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..

[35]  M. Sternberg,et al.  Modelling protein docking using shape complementarity, electrostatics and biochemical information. , 1997, Journal of molecular biology.

[36]  Shaomeng Wang,et al.  MCDOCK: A Monte Carlo simulation approach to the molecular docking problem , 1999, J. Comput. Aided Mol. Des..

[37]  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.

[38]  Ken Shoemake,et al.  Uniform Random Rotations , 1992, Graphics Gems III.

[39]  Thomas E. Moock,et al.  Conformational searching in ISIS/3D databases , 1994, J. Chem. Inf. Comput. Sci..

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

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

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

[43]  Ruben Abagyan,et al.  ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..

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

[45]  A. Párraga,et al.  Molecular structure at 1.8 A of mouse liver class pi glutathione S-transferase complexed with S-(p-nitrobenzyl)glutathione and other inhibitors. , 1994, Journal of molecular biology.

[46]  David B. Fogel,et al.  Docking Conformationally Flexible Small Molecules into a Protein Binding Site through Evolutionary Programming , 1995, Evolutionary Programming.

[47]  Junmei Wang,et al.  Development and testing of a general amber force field , 2004, J. Comput. Chem..

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

[49]  Noriaki Hirayama,et al.  Ph4Dock: pharmacophore-based protein-ligand docking. , 2004, Journal of medicinal chemistry.

[50]  Christopher W. Murray,et al.  The sensitivity of the results of molecular docking to induced fit effects: Application to thrombin, thermolysin and neuraminidase , 1999, J. Comput. Aided Mol. Des..

[51]  Paul A. Rejto,et al.  Fully Automated and Rapic Flexible Docking of Inhibitors Covalently Bound to Serine Proteases , 1998, Evolutionary Programming.

[52]  Thy-Hou Lin,et al.  Supervised Feature Ranking Using a Genetic Algorithm Optimized Artificial Neural Network , 2006, J. Chem. Inf. Model..

[53]  R Abagyan,et al.  Flexible protein–ligand docking by global energy optimization in internal coordinates , 1997, Proteins.

[54]  A. Caflisch,et al.  Fragment-Based Flexible Ligand Docking by Evolutionary Optimization , 2001, Biological chemistry.

[55]  V. Stoll,et al.  Discovery of potent imidazole and cyanophenyl containing farnesyltransferase inhibitors with improved oral bioavailability. , 2003, Bioorganic & medicinal chemistry letters.

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

[57]  Thy-Hou Lin,et al.  Classification of Some Active Compounds and Their Inactive Analogues Using Two Three-Dimensional Molecular Descriptors Derived from Computation of Three-Dimensional Convex Hulls for Structures Theoretically Generated for Them , 2000, J. Chem. Inf. Comput. Sci..

[58]  J. Denavit,et al.  A kinematic notation for lower pair mechanisms based on matrices , 1955 .