A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands.

To alleviate the problems in the receptor-based design of metalloprotein ligands due to inadequacies in the force-field description of coordination bonds, a four-tier approach was devised. Representative ligand-metalloprotein interaction energies are obtained by subsequent application of (1) docking with metal-binding-guided selection of modes, (2) optimization of the ligand-metalloprotein complex geometry by combined quantum mechanics and molecular mechanics (QM/MM) methods, (3) conformational sampling of the complex with constrained metal bonds by force-field-based molecular dynamics (MD), and (4) a single point QM/MM energy calculation for the time-averaged structures. The QM/MM interaction energies are, in a linear combination with the desolvation-characterizing changes in the solvent-accessible surface areas, correlated with experimental data. The approach was applied to structural correlation of published binding free energies of a diverse set of 28 hydroxamate inhibitors to zinc-dependent matrix metalloproteinase 9 (MMP-9). Inclusion of steps 3 and 4 significantly improved both correlation and prediction. The two descriptors explained 90% of variance in inhibition constants of all 28 inhibitors, ranging from 0.08 to 349 nM, with the average unassigned error of 0.318 log units. The structural and energetic information obtained from the time-averaged MD simulation results helped understand the differences in binding modes of related compounds.

[1]  R. S. Mulliken Electronic Population Analysis on LCAO–MO Molecular Wave Functions. I , 1955 .

[2]  Martin Karplus,et al.  Calculation of ground and excited state potential surfaces of conjugated molecules. I. Formulation and parametrization , 1972 .

[3]  M. Levitt,et al.  Theoretical studies of enzymic reactions: dielectric, electrostatic and steric stabilization of the carbonium ion in the reaction of lysozyme. , 1976, Journal of molecular biology.

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

[5]  W. R. Wadt,et al.  Ab initio effective core potentials for molecular calculations , 1984 .

[6]  W. R. Wadt,et al.  Ab initio effective core potentials for molecular calculations. Potentials for main group elements Na to Bi , 1985 .

[7]  U. Singh,et al.  A combined ab initio quantum mechanical and molecular mechanical method for carrying out simulations on complex molecular systems: Applications to the CH3Cl + Cl− exchange reaction and gas phase protonation of polyethers , 1986 .

[8]  A. D. McLachlan,et al.  Solvation energy in protein folding and binding , 1986, Nature.

[9]  Angelo Vedani,et al.  YETI: An interactive molecular mechanics program for small‐molecule protein complexes , 1988 .

[10]  Theoretical study of solvation effects on chemical reactions. A combined quantum chemical/Monte Carlo study of the Meyer-Schuster reaction mechanism in water , 1989 .

[11]  R. Cramer,et al.  Validation of the general purpose tripos 5.2 force field , 1989 .

[12]  Angelo Vedani,et al.  A new force field for modeling metalloproteins , 1990 .

[13]  M. Karplus,et al.  A combined quantum mechanical and molecular mechanical potential for molecular dynamics simulations , 1990 .

[14]  W. C. Still,et al.  Semianalytical treatment of solvation for molecular mechanics and dynamics , 1990 .

[15]  Kenneth M. Merz,et al.  Force Field Design for Metalloproteins , 1991 .

[16]  Kenneth M. Merz,et al.  Mechanism of the human carbonic anhydrase II-catalyzed hydration of carbon dioxide , 1992 .

[17]  A. Becke Density-functional thermochemistry. III. The role of exact exchange , 1993 .

[18]  Arieh Warshel,et al.  Simulation of enzyme reactions using valence bond force fields and other hybrid quantum/classical approaches , 1993 .

[19]  Peter A. Kollman,et al.  FREE ENERGY CALCULATIONS : APPLICATIONS TO CHEMICAL AND BIOCHEMICAL PHENOMENA , 1993 .

[20]  J. Aqvist,et al.  A new method for predicting binding affinity in computer-aided drug design. , 1994, Protein engineering.

[21]  A. Skalka,et al.  The retroviral enzymes. , 1994, Annual review of biochemistry.

[22]  R. Huber,et al.  X-ray structures of human neutrophil collagenase complexed with peptide hydroxamate and peptide thiol inhibitors. Implications for substrate binding and rational drug design. , 1995, European journal of biochemistry.

[23]  Simulating solvent effects in organic chemistry: combining quantum and molecular mechanics , 1995 .

[24]  Robert J. Deeth,et al.  Molecular Mechanics for Coordination Complexes: The Impact of Adding d-Electron Stabilization Energies , 1995 .

[25]  W. Bode,et al.  Structure determination and analysis of human neutrophil collagenase complexed with a hydroxamate inhibitor. , 1995, Biochemistry.

[26]  T. Hansson,et al.  Estimation of binding free energies for HIV proteinase inhibitors by molecular dynamics simulations. , 1995, Protein engineering.

[27]  M Karplus,et al.  Zinc binding in proteins and solution: A simple but accurate nonbonded representation , 1995, Proteins.

[28]  M. Browner,et al.  Matrilysin-inhibitor complexes: common themes among metalloproteases. , 1996, Biochemistry.

[29]  W. L. Jorgensen,et al.  AN EXTENDED LINEAR RESPONSE METHOD FOR DETERMINING FREE ENERGIES OF HYDRATION , 1995 .

[30]  R. Wade,et al.  Prediction of drug binding affinities by comparative binding energy analysis , 1995 .

[31]  William N. Lipscomb,et al.  Recent Advances in Zinc Enzymology. , 1996, Chemical reviews.

[32]  J. Åqvist,et al.  Calculation of absolute binding free energies for charged ligands and effects of long‐range electrostatic interactions , 1996 .

[33]  W. L. Jorgensen,et al.  Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids , 1996 .

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

[35]  Garland R. Marshall,et al.  VALIDATE: A New Method for the Receptor-Based Prediction of Binding Affinities of Novel Ligands , 1996 .

[36]  G. V. Paolini,et al.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes , 1997, J. Comput. Aided Mol. Des..

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

[38]  W. L. Jorgensen,et al.  Binding affinities for sulfonamide inhibitors with human thrombin using Monte Carlo simulations with a linear response method. , 1997, Journal of medicinal chemistry.

[39]  Peter A. Kollman,et al.  Free energy calculation methods: A theoretical and empirical comparison of numerical errors and a new method qualitative estimates of free energy changes , 1997, J. Comput. Chem..

[40]  Anton J. Hopfinger,et al.  Prediction of Ligand-Receptor Binding Thermodynamics by Free Energy Force Field (FEFF) 3D-QSAR Analysis: Application to a Set of Peptidometic Renin Inhibitors , 1997, J. Chem. Inf. Comput. Sci..

[41]  P. Kollman,et al.  Continuum Solvent Studies of the Stability of DNA, RNA, and Phosphoramidate−DNA Helices , 1998 .

[42]  M Karplus,et al.  Improving the accuracy of protein pKa calculations: Conformational averaging versus the average structure , 1998, Proteins.

[43]  K. D. Hardman,et al.  Structure-based design and synthesis of a series of hydroxamic acids with a quaternary-hydroxy group in P1 as inhibitors of matrix metalloproteinases. , 1998, Bioorganic & medicinal chemistry letters.

[44]  H. Tsuzuki,et al.  Highly selective and orally active inhibitors of type IV collagenase (MMP-9 and MMP-2): N-sulfonylamino acid derivatives. , 1998, Journal of medicinal chemistry.

[45]  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..

[46]  Johan Åqvist,et al.  Ligand binding affinity prediction by linear interaction energy methods , 1998, J. Comput. Aided Mol. Des..

[47]  K V Damodaran,et al.  Binding preferences of hydroxamate inhibitors of the matrix metalloproteinase human fibroblast collagenase. , 1999, Journal of medicinal chemistry.

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

[49]  Thomas Lengauer,et al.  Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking , 1999, Proteins.

[50]  U. Ryde,et al.  Carboxylate binding modes in zinc proteins: a theoretical study. , 1999, Biophysical journal.

[51]  P Venkatarangan,et al.  Prediction of ligand-receptor binding thermodynamics by free energy force field three-dimensional quantitative structure-activity relationship analysis: applications to a set of glucose analogue inhibitors of glycogen phosphorylase. , 1999, Journal of medicinal chemistry.

[52]  M L Lamb,et al.  Estimation of the binding affinities of FKBP12 inhibitors using a linear response method. , 1999, Bioorganic & medicinal chemistry.

[53]  Yuan-Ping Pang,et al.  Novel Zinc Protein Molecular Dynamics Simulations: Steps Toward Antiangiogenesis for Cancer Treatment , 1999 .

[54]  A. Gearing,et al.  Design and therapeutic application of matrix metalloproteinase inhibitors. , 1999, Chemical reviews.

[55]  P A Kollman,et al.  What determines the van der Waals coefficient β in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations? , 1999, Proteins.

[56]  Y. Pang,et al.  Novel Stable Configurations and Tautomers of the Neutral and Deprotonated Hydroxamic Acids Predicted from High-Level ab Initio Calculations , 1999 .

[57]  W. L. Jorgensen,et al.  Prediction of Properties from Simulations: Free Energies of Solvation in Hexadecane, Octanol, and Water , 2000 .

[58]  Richard A. Friesner,et al.  A mixed quantum mechanics/molecular mechanics (QM/MM) method for large‐scale modeling of chemistry in protein environments , 2000, J. Comput. Chem..

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

[60]  Z. Havlas,et al.  Theoretical Studies of Metal Ion Selectivity. 1. DFT Calculations of Interaction Energies of Amino Acid Side Chains with Selected Transition Metal Ions (Co2+, Ni2+, Cu2+, Zn2+, Cd2+, and Hg2+) , 2000 .

[61]  P. Kollman,et al.  Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. , 2000, Accounts of chemical research.

[62]  Yuan-Ping Pang,et al.  Proton Dissociation Energies of Zinc-Coordinated Hydroxamic Acids and Their Relative Affinities for Zinc: Insight into Design of Inhibitors of Zinc-Containing Proteinases , 2000 .

[63]  C. Lim,et al.  Metal Binding in Proteins: The Effect of the Dielectric Medium , 2000 .

[64]  P A Kollman,et al.  Calculation and prediction of binding free energies for the matrix metalloproteinases. , 2000, Journal of medicinal chemistry.

[65]  D. Hupe,et al.  A Rationalization of the Acidic pH Dependence for Stromelysin-1 (Matrix Metalloproteinase-3) Catalysis and Inhibition* , 2000, The Journal of Biological Chemistry.

[66]  A. Warshel,et al.  Examining methods for calculations of binding free energies: LRA, LIE, PDLD‐LRA, and PDLD/S‐LRA calculations of ligands binding to an HIV protease , 2000, Proteins.

[67]  G. Klebe,et al.  Knowledge-based scoring function to predict protein-ligand interactions. , 2000, Journal of molecular biology.

[68]  Nohad Gresh,et al.  Interaction of neutral and zwitterionic glycine with Zn2+ in gas phase: ab initio and SIBFA molecular mechanics calculations , 2000 .

[69]  Y. Pang,et al.  Successful molecular dynamics simulation of the zinc-bound farnesyltransferase using the cationic dummy atom approach. , 2000, Protein science : a publication of the Protein Society.

[70]  L. Johnson,et al.  Structure-activity relationships and pharmacokinetic analysis for a series of potent, systemically available biphenylsulfonamide matrix metalloproteinase inhibitors. , 2000, Journal of medicinal chemistry.

[71]  Lee G. Pedersen,et al.  Models for protein–zinc ion binding sites. II. The catalytic sites* , 2001 .

[72]  Michael Bräuer,et al.  Molecular mechanics for zinc complexes with fluctuating atomic charges , 2001 .

[73]  B. Nordén,et al.  Computational modelling of inhibitor binding to human thrombin. , 2001, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[74]  Robert J. Deeth,et al.  The ligand field molecular mechanics model and the stereoelectronic effects of d and s electrons , 2001 .

[75]  Xiaojie Xu,et al.  Binding Affinities for a Series of Selective Inhibitors of Gelatinase-A Using Molecular Dynamics with a Linear Interaction Energy Approach , 2001 .

[76]  A. Mulholland The QM/MM Approach to Enzymatic Reactions , 2001 .

[77]  J. Åqvist,et al.  The linear interaction energy method for predicting ligand binding free energies. , 2001, Combinatorial chemistry & high throughput screening.

[78]  Hirosato Kondo,et al.  New type of metalloproteinase inhibitor: design and synthesis of new phosphonamide-based hydroxamic acids. , 2002, Journal of medicinal chemistry.

[79]  J. Åqvist,et al.  Ligand binding affinities from MD simulations. , 2002, Accounts of chemical research.

[80]  A. Henney,et al.  Crystal structure of human MMP9 in complex with a reverse hydroxamate inhibitor. , 2002, Journal of molecular biology.

[81]  Xiaojie Xu,et al.  Predictions of Binding of a Diverse Set of Ligands to Gelatinase-A by a Combination of Molecular Dynamics and Continuum Solvent Models , 2002 .

[82]  E. Shakhnovich,et al.  SMall Molecule Growth 2001 (SMoG2001): an improved knowledge-based scoring function for protein-ligand interactions. , 2002, Journal of medicinal chemistry.

[83]  Irene Luque,et al.  Structural parameterization of the binding enthalpy of small ligands , 2002, Proteins.

[84]  Jaroslav Koca,et al.  Coordination number of zinc ions in the phosphotriesterase active site by molecular dynamics and quantum mechanics , 2003, J. Comput. Chem..

[85]  Olivier Michielin,et al.  Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors , 2003, J. Comput. Aided Mol. Des..

[86]  Nohad Gresh,et al.  Inclusion of the ligand field contribution in a polarizable molecular mechanics: SIBFA‐LF , 2003, J. Comput. Chem..

[87]  M. Remko,et al.  Thermodynamics of binding of Zn2+ to carbonic anhydrase inhibitors , 2003 .

[88]  Xin Hu,et al.  Docking studies of matrix metalloproteinase inhibitors: zinc parameter optimization to improve the binding free energy prediction. , 2003, Journal of molecular graphics & modelling.

[89]  M. Remko,et al.  Coordination and Thermodynamics of Stable Zn(II) Complexes in the Gas Phase , 2003, Journal of biomolecular structure & dynamics.

[90]  A Theoretical Study of Imidazole- and Thiol-Based Zinc Binding Groups Relevant to Inhibition of Metzincins , 2004 .

[91]  Johan Åqvist,et al.  Binding affinity prediction with different force fields: Examination of the linear interaction energy method , 2004, J. Comput. Chem..

[92]  Irwin D Kuntz,et al.  A molecular basis for the selectivity of thiadiazole urea inhibitors with stromelysin-1 and gelatinase-A from generalized born molecular dynamics simulations. , 2004, Journal of medicinal chemistry.

[93]  Soumyendu Raha,et al.  Simulation‐Based Predictions of Binding Affinities of Matrix Metalloproteinase Inhibitors , 2004 .

[94]  Amedeo Caflisch,et al.  Efficient evaluation of binding free energy using continuum electrostatics solvation. , 2004, Journal of medicinal chemistry.

[95]  K. Merz,et al.  A quantum mechanics-based scoring function: study of zinc ion-mediated ligand binding. , 2004, Journal of the American Chemical Society.

[96]  Soumyendu Raha,et al.  Similarity of Binding Sites of Human Matrix Metalloproteinases*[boxs] , 2004, Journal of Biological Chemistry.

[97]  S. Balaz,et al.  A practical approach to docking of zinc metalloproteinase inhibitors. , 2004, Journal of molecular graphics & modelling.

[98]  R. Huber,et al.  Handbook of metalloproteins , 2006 .