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ABSTRACT: In this work, a new ansatz is presented that combines molecular dynamics simulations with MM-PBSA (Molecular Mechanics Poisson-Boltzmann/surface area) to rank the binding affinities of 12 TIBO-like HIV-1 RT inhibitors. Encouraging results have been obtained not only for the relative binding free energies, but also for the absolute ones, which have a root-mean-square deviation of 1.0 kcal/mol (the maximum error is 1.89 kcal/mol). Since the root-mean-square error is rather small, this approach can be reliably applied in ranking the ligands from the databases for this important target. Encouraged by the results, we decided to apply MM-PBSA combined with molecular docking to determine the binding mode of efavirenz SUSTIVA(TM) another promising HIV-1 RT inhibitor for which no ligand-protein crystal structure had been published at the time of this work. To proceed, we define the following ansatz: Five hundred picosecond molecular dynamics simulations were first performed for the five binding modes suggested by DOCK 4.0, and then MM-PBSA was carried out for the collected snapshots. MM-PBSA successfully identified the correct binding mode, which has a binding free energy about 7 kcal/mol more favorable than the second best mode. Moreover, the calculated binding free energy (-13.2 kcal/mol) is in reasonable agreement with experiment (-11.6 kcal/mol). In addition, this procedure was also quite successful in modeling the complex and the structure of the last snapshot was quite close to that of the measured 2,3 A resolution crystal (structure the root-mean-square deviation of the 54 C(alpha) around the binding site and the inhibitor is 1.1 A). We want to point out that this result was achieved without prior knowledge of the structure of the efavirenz/RT complex. Therefore, molecular docking combined with MD simulations followed by MM-PBSA analysis is an attractive approach for modeling protein complexes a priori.
Journal of the American Chemical Society 07/2001; 123(22):5221-30. · 9.91 Impact Factor
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ABSTRACT: The Src-homology-3 (SH3) domain of the Caenorhabditis elegans protein Sem-5 binds proline-rich sequences. It is reported that the SH3 domains broadly accept amide N-substituted residues instead of only recognizing prolines on the basis of side chain shape or rigidity. We have studied the interactions between Sem-5 and its ligands using molecular dynamics (MD), free energy calculations, and sequence analysis. Relative binding free energies, estimated by a method called MM/PBSA, between different substitutions at sites -1, 0, and +2 of the peptide are consistent with the experimental data. A new method to calculate atomic partial charges, AM1-BCC method, is also used in the binding free energy calculations for different N-substitutions at site -1. The results are very similar to those obtained from widely used RESP charges in the AMBER force field. AM1-BCC charges can be calculated more rapidly for any organic molecule than can the RESP charges. Therefore, their use can enable a broader and more efficient application of the MM/PBSA method in drug design. Examination of each component of the free energy leads to the construction of van der Waals interaction energy profiles for each ligand as well as for wild-type and mutant Sem-5 proteins. The profiles and free energy calculations indicate that the van der Waals interactions between the ligands and the receptor determine whether an N- or a Calpha-substituted residue is favored at each site. A VC value (defined as a product of the conservation percentage of each residue and its van der Waals interaction energy with the ligand) is used to identify several residues on the receptor that are critical for specificity and binding affinity. This VC value may have a potential use in identifying crucial residues for any ligand-protein or protein-protein system. Mutations at two of those crucial residues, N190 and N206, are examined. One mutation, N190I, is predicted to reduce the selectivity of the N-substituted residue at site -1 of the ligand and is shown to bind similarly with N- and Calpha-substituted residues at that site.
Journal of the American Chemical Society 06/2001; 123(17):3986-94. · 9.91 Impact Factor
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ABSTRACT: A flexible ligand docking protocol based on a divide-and-conquer strategy is investigated. This approach first separates total search space into conformation and orientation space. It uses a grid-based method to sample the conformation of an unbound ligand and to select the low-energy conformers. Rigid docking is then carried out to locate the low-energy binding orientations for these conformers. These docking structures are subsequently subjected to structure refinement including molecular mechanics minimization, conformational scanning at the binding site and a short period of molecular dynamics-based simulated annealing. This approach has been applied to twelve ligand-protein complexes with three to sixteen rotatable bonds. The docked lowest-energy structures have root mean square deviations ranging from 0.64 A to 2.01 A with respect to the corresponding crystal structures. The effect of atomic charges and van der Waals parameters on the docking results, and the role of the dielectric constant in the conformation sampling are discussed in detail. A fragment-based docking approach that takes advantages of the divide-and-conquer strategy has also been explored and the results are compared with those produced by a whole molecule-based approach.
Proteins Structure Function and Bioinformatics 08/1999; 36(1):1-19. · 3.39 Impact Factor
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ABSTRACT: Recently a semiempirical method has been proposed by Aqvist et al. to calculate absolute and relative binding free energies. In this method, the absolute binding free energy of a ligand is estimated as deltaGbind = alpha<Vel(bound) - Vel(free)> + beta<Vvdw(bound) - Vvdw(free)>, where Vel(bound) and Vvdw(bound) are the electrostatic and van der Waals interaction energies between the ligand and the solvated protein from an molecular dynamics (MD) trajectory with ligand bound to protein and Vel(free) and Vel(free) and Vvdw(free) are the electrostatic and van der Waals interaction energies between the ligand and the water from an MD trajectory with the ligand in water. A set of values, alpha = 0.5 and beta = 0.16, was found to give results in good agreement with experimental data. Later, however, different optimal values of beta were found in studies of compounds binding to P450cam and avidin. The present work investigates how the optimal value of beta depends on the nature of binding sites for different protein-ligand interactions. By examining seven ligands interacting with five proteins, we have discovered a linear correlation between the value of beta and the weighted non-polar desolvation ratio (WNDR), with a correlation coefficient of 0.96. We have also examined the ability of this correlation to predict optimal values of beta for different ligands binding to a single protein. We studied twelve neutral compounds bound to avidin. In this case, the WNDR approach gave a better estimate of the absolute binding free energies than results obtained using the fixed value of beta found for biotin-avidin. In terms of reproducing the relative binding free energy to biotin, the fixed-beta value gave better results for compounds similar to biotin, but for compounds less similar to biotin, the WNDR approach led to better relative binding free energies.
Proteins Structure Function and Bioinformatics 03/1999; 34(3):395-402. · 3.39 Impact Factor
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ABSTRACT: The binding of 14 biotin analogues to avidin is examined to evaluate the viability of calculating binding free energy based on molecular dynamics (MD) trajectories. Two approaches were investigated in this work. The first one uses the linear interaction energy approximation, while the other approach utilizes the interaction free energy. The results obtained from these two methods were found to correlate well with the experimental binding free energy data for 10 out of 14 ligands. For the other four ligands, both methods overestimate their binding strength by more than 7 kcal/mol. Free energy calculations using the thermodynamic integration method are employed to understand this overestimation. The effect of protein flexibility on binding free energy calculation and the effect of charged or neutral ligands on the calculated results are discussed. MD simulations are shown to be able to provide insight into the interactions occurring in the active site and the origins of variations in binding free energy.
Proteins Structure Function and Bioinformatics 02/1999; 34(1):69-81. · 3.39 Impact Factor
