Does a diol cyclic urea inhibitor of HIV-1 protease bind tighter than its corresponding alcohol form? A study by free energy perturbation and continuum electrostatics calculations

Identification of HIV inhibitors guided by free energy perturbation calculations

Free energy perturbation (FEP) theory coupled to molecular dynamics (MD) or Monte Carlo (MC) statistical mechanics offers a theoretically precise method for determining the free energy differences of related biological inhibitors. Traditionally requiring extensive computational resources and expertise, it is only recently that its impact is being felt in drug discovery. A review of computer-aided anti-HIV efforts employing FEP calculations is provided here that describes early and recent successes in the design of human immunodeficiency virus type 1 (HIV-1) protease and non-nucleoside reverse transcriptase inhibitors. In addition, our ongoing work developing and optimizing leads for small molecule inhibitors of cyclophilin A (CypA) is highlighted as an update on the current capabilities of the field. CypA has been shown to aid HIV-1 replication by catalyzing the cis/trans isomerization of a conserved Gly-Pro motif in the Nterminal domain of HIV-1 capsid (CA) protein. In the absence of a functional CypA, e.g., by the addition of an inhibitor such as cyclosporine A (CsA), HIV-1 has reduced infectivity. Our simulations of acylurea-based and 1-indanylketone-based CypA inhibitors have determined that their nanomolar and micromolar binding affinities, respectively, are tied to their ability to stabilize Arg55 and Asn102. A structurally novel 1-(2,6-dichlorobenzamido) indole core was proposed to maximize these interactions. FEP-guided optimization, experimental synthesis, and biological testing of lead compounds for toxicity and inhibition of wild-type HIV-1 and CA mutants have demonstrated a dose-dependent inhibition of HIV-1 infection in two cell lines. While the inhibition is modest compared to CsA, the results are encouraging.

Structure, dynamics and solvation of HIV-1 protease/saquinavir complex in aqueous solution and their contributions to drug resistance: molecular dynamic simulations

As it is known that the understanding of the basic properties of the enzyme/inhibitor complex leads directly to enhancing the capability in drug designing and drug discovery. Molecular dynamics simulations have been performed to examine detailed information on the structure and dynamical properties of the HIV-1 PR complexed with saquinavir in the three protonated states, monoprotonates at Asp25 (Mono-25) and Asp25'(Mono-25') and diprotonate (Di-Pro) at both Asp25 and Asp25'. The obtained results support clinical data which reveal that Ile84 and Gly48 are two of the most frequent residues where mutation toward a protease inhibitor takes place. In contrast to the Ile84 mutation due to high displacement of Ile84 in the presence of saquinavir, source of the Gly48 mutation was observed to be due to the limited space in the HIV-1 PR pocket. The Gly48 was, on one side, found to form strong hydrogen bonds with saquinavir, while on the other side this residue was repelled by the hydrophobic Phe53 residue. In terms of inhibitor/enzyme binding, interactions between saquinavir and a catalytic triad of the HIV-1 PR were calculated using the ab initio method. The results show an order of the binding energy of Mono25<Di-pro<<Mono-25', suggesting that the active site in the HIV-1 PR complexed with saquinavir is monoprotonated states on Asp25. In contrast to the binding energy, 3, 6 and 12 hydrogen bonds between saquinavir and HIV-1 PR were found for the Mono-25, Mono-25' and Di-pro states, respectively. Discrepancy between the two trends suggests us to conclude that interaction between inhibitor and catalytic residues should be used as a criteria to enhance capability in drug designing and drug screening instead of using the total inhibitor/enzyme interaction which is normally reported in the literature. In addition, the distribution and binding of water molecules, in terms of hydrogen bonding, to the donor atoms of saquinavir were investigated and discussed, referring to that which was reported experimentally.

Evaluation of a neural networks QSAR method based on ligand representation using substituent descriptors. Application to HIV-1 protease inhibitors

We present here a neural networks method designed to predict biological activity based on a local representation of the ligand. The compounds of the series are represented by a vector mapping for each of four substituent properties: volume, log P, dipole moment and a simple 'steric' parameter relating to its shape. This ligand representation was tested using neural networks on a set of 42 cyclic-urea derivatives, inhibiting HIV-1 protease. The leave-one-out cross-validation using all descriptors in the input gave a correlation factor between prediction and experiment of 0.76 for the overall set and 0.88 when three outliers were left out. To rank the significance of the four descriptors, we further tested all combinations of two and three parameters for each substituent, using two disjunctive testing sets of five inhibitors. In these sets, vectors with extreme descriptor values were used either in the training or the testing set (sets A and B, respectively). The method is a very good interpolator (set A, 95+/-2% accuracy) but a less effective extrapolator (set B, 85+/-2% accuracy). Generally, the combinations including the 'steric' parameter predict better than average, while those containing the volume are less effective. The best prediction, 98.8+/-1.2%, was obtained when log P, the dipole and the steric parameter were used on set A. At the opposite end, the lowest ranked descriptor set was obtained when replacing log P with the volume, giving 92.3+/-6.7% accuracy over the set A.

Molecular docking and 3D QSAR studies on 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes based on the structural modeling of human CCR5 receptor

In the present study, we have used an approach combining protein structure modeling, molecular dynamics (MD) simulation, automated docking, and 3D QSAR analyses to investigate the detailed interactions of CCR5 with their antagonists. Homology modeling and MD simulation were used to build the 3D model of CCR5 receptor based on the high-resolution X-ray structure of bovine rhodopsin. A series of 64 CCR5 antagonists, 1-amino-2-phenyl-4-(piperidin-1-yl)-butanes, were docked into the putative binding site of the 3D model of CCR5 using the docking method, and the probable interaction model between CCR5 and the antagonists were obtained. The predicted binding affinities of the antagonists to CCR5 correlate well with the antagonist activities, and the interaction model could be used to explain many mutagenesis results. All these indicate that the 3D model of antagonist-CCR5 interaction is reliable. Based on the binding conformations and their alignment inside the binding pocket of CCR5, three-dimensional structure-activity relationship (3D QSAR) analyses were performed on these antagonists using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) methods. Both CoMFA and CoMSIA provide statistically valid models with good correlation and predictive power. The q(2)(r(cross)(2)) values are 0.568 and 0.587 for CoMFA and CoMSIA, respectively. The predictive ability of these models was validated by six compounds that were not included in the training set. Mapping these models back to the topology of the active site of CCR5 leads to a better understanding of antagonist-CCR5 interaction. These results suggest that the 3D model of CCR5 can be used in structure-based drug design and the 3D QSAR models provide clear guidelines and accurate activity predictions for novel antagonist design.

Comparing the conformational behavior of a series of diastereomeric cyclic urea HIV-1 inhibitors using the low mode:monte carlo conformational search method

The conformational flexibility of a series of diastereomeric cyclic urea HIV-1 protease inhibitors has been examined using the Low Mode:Monte Carlo conformational search method. Force fields were validated by a comparison of the energetic ordering of the minimum energy structures on the AMBER/GBSA(water), OPLSAA/GBSA(water) and HF/6-311G/SCRF(water) surfaces. The energetic ordering of the minima on the OPLSAA /GBSA(water) surface was in better agreement with the quantum calculations than the ordering on the AMBER/GBSA(water) surface. An ensemble of low energy structures was generated using OPLSAA/GBSA(water) and used to compare the molecular shape and flexibility of each diastereomer to the experimentally determined binding affinities and crystal structures of closely related systems. The results indicate that diastereomeric solution-phase energetic stability, conformational rigidity and ability to adopt a chair conformation correlate strongly with experimental binding affinities. Rigid body docking suggests that all of the diastereomers adopt solution-phase conformations suitable for alignment with the HIV-1 protease; however, these results indicate that the binding affinities are dependent upon subtle differences in the P1/P1' and P2/P2' substituent orientations.

Correlation between the predicted and the observed biological activity of the symmetric and nonsymmetric cyclic urea derivatives used as HIV-1 protease inhibitors. A 3D-QSAR-CoMFA method for new antiviral drug design

The predicted inhibition constant (Ki) and the predicted inhibitor concentration (IC90) of the HIV-1 protease (HIV- 1 PR) inhibitors: symmetric and nonsymmetric - benzyl, ketone, oxime, pyrazole, imidazole, and triazole cyclic urea derivatives, were obtained by the 3D-CoMFA (Comparative Molecular Field Analysis) method. The CoMFA statistical parameters: cross-validate correlation coefficient (q2), higher than 0.5, and the fitted correlation coefficient (r2), higher than 0.90 validated the predicted biological activities. The best predictions were found for the trifluoromethyl ketoxime derivative (log 1/Ki predict = 8.42), the m-pyridineCH2 pyrazole derivative (log 1/Ki predict = 9.77) and the 1,2,3 triazole derivative (log 1/Ki predict = 7.03). We attempted to design a new potent HIV-1 protease inhibitor by addition of o-benzyl to the (p-HOPhCH2) pyrazole 12f derivative inhibitor. A favorable steric area surrounded the o-benzyl, suggesting a possible new potent HIV-1 protease inhibitor.

Inhibitory mode of 1,5-diarylpyrazole derivatives against cyclooxygenase-2 and cyclooxygenase-1: molecular docking and 3D QSAR analyses

The Lamarckian genetic algorithm of AutoDock 3.0 has been employed to dock 40 1,5-diarylpyrazole class compounds into the active sites of cyclooxygenase-2 (COX-2) and cyclooxygenase-1 (COX-1). The binding models were demonstrated in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding. The data of geometrical parameters and RMSD values compared with the known inhibitor, SC-558 (43), show that these inhibitors interact respectively with COX-2 and COX-1 in a very similar way. The r(2) values of 0.648 for COX-2 and 0.752 for COX-1 indicate that the calculated binding free energies correlate well with the inhibitory activities. The structural and energetic differences in inhibitory potencies of 1,5-diarylpyrazoles were reasonably explored, and the COX-2/COX-1 selectivity was demonstrated by the three-dimensional (3D) interaction models of inhibitors complexing with these two enzymes. Using the binding conformations of 1,5-diarylpyrazoles, consistent and highly predictive 3D quantitative structure-activity relationship (QSAR) models were developed by performing comparative molecular field analyses (CoMFA) and comparative molecular similarity analyses (CoMSIA). The q(2) values are 0.635 and 0.641 for CoMFA and CoMSIA models, respectively. The predictive ability of these models was validated by SC-558 (43) and a set of 10 other compounds that were not included in the training set. Mapping these models back to the topology of the active site of COX-2 leads to a better understanding of vital diarylpyrazole compounds and COX-2 interactions. Structure-based investigations and the final 3D QSAR results provided possible guidelines and accurate activity predictions for novel inhibitor design.

Elucidating the inhibiting mode of AHPBA derivatives against HIV-1 protease and building predictive 3D-QSAR models

The Lamarckian genetic algorithm of AutoDock 3.0 has been used to dock 27 3(S)-amino-2(S)-hydroxyl-4-phenylbutanoic acids (AHPBAs) into the active site of HIV-1 protease (HIVPR). The binding mode was demonstrated in the aspects of the inhibitor's conformation, subsite interaction, and hydrogen bonding. The data of geometrical parameters (tau(1), tau(2), and tau(3) listed in Table 2) and root mean square deviation values as compared with the known inhibitor, kni272,(28) show that both kinds of inhibitors interact with HIVPR in a very similar way. The r(2) value of 0.860 indicates that the calculated binding free energies correlate well with the inhibitory activities. The structural and energetic differences in inhibitory potencies of AHPBAs were reasonably explored. Using the binding conformations of AHPBAs, consistent and highly predictive 3D-QSAR models were developed by performing CoMFA, CoMSIA, and HQSAR analyses. The reasonable r(corss)(2) values were 0.613, 0.530, and 0.717 for CoMFA, CoMSIA, and HQSAR models, respectively. The predictive ability of these models was validated by kni272 and a set of nine compounds that were not included in the training set. Mapping these models back to the topology of the active site of HIVPR leads to a better understanding of vital AHPBA-HIVPR interactions. Structural-based investigations and the final 3D-QSAR results provide clear guidelines and accurate activity predictions for novel HIVPR inhibitors.