Biomedical subjects

Robert C Rizzo

Publications and source records attributed to Robert C Rizzo.

6 recordsLinked to original sources

PubMed2006

Development and validation of a modular, extensible docking program: DOCK 5.

We report on the development and validation of a new version of DOCK. The algorithm has been rewritten in a modular format, which allows for easy implementation of new scoring functions, sampling methods and analysis tools. We validated the sampling algorithm with a test set of 114 protein-ligand complexes. Using an optimized parameter set, we are able to reproduce the crystal ligand pose to within 2 A of the crystal structure for 79% of the test cases using our rigid ligand docking algorithm with an average run time of 1 min per complex and for 72% of the test cases using our flexible ligand docking algorithm with an average run time of 5 min per complex. Finally, we perform an analysis of the docking failures in the test set and determine that the sampling algorithm is generally sufficient for the binding pose prediction problem for up to 7 rotatable bonds; i.e. 99% of the rigid ligand docking cases and 95% of the flexible ligand docking cases are sampled successfully. We point out that success rates could be improved through more advanced modeling of the receptor prior to docking and through improvement of the force field parameters, particularly for structures containing metal-based cofactors.

Algorithms↗

PubMed2006

HIV-1 protease flaps spontaneously close to the correct structure in simulations following manual placement of an inhibitor into the open state.

We report unrestrained, all-atom molecular dynamics simulations of HIV-1 protease (HIV-PR) with a continuum solvent model that reproducibly sample closing of the active site flaps following manual placement of a cyclic urea inhibitor into the substrate binding site of the open protease. The open form was obtained from the unbound, semi-open HIV-PR crystal structure, which we recently reported (Hornak, V.; et al. Proc. Natl. Acad. Sci. U.S.A. 2006, 103, 915-920.) to have spontaneously opened during unrestrained dynamics. In those simulations, the transiently open flaps always returned to the semi-open form that is observed in all crystal structures of the free protease. Here, we show that manual docking of the inhibitor reproducibly induces spontaneous conversion to the closed form as seen in all inhibitor-bound HIV-PR crystal structures. These simulations reproduced not only the greater degree of flap closure, but also the striking difference in flap "handedness" between bound and free enzyme. In most of the simulations, the final structures were highly accurate. Root-mean-square deviations (RMSD) from the crystal structure of the complex were approximately 1.5 A (averaged over the last 100 ps) for the inhibitor and each flap despite initial RMSD of 2-5 A for the inhibitors and 6-11 A for the flaps. Key hydrogen bonds were formed between the flap tips and between flaps and inhibitor that match those seen in the crystal structure. The results demonstrate that all-atom simulations have the ability to significantly improve poorly docked ligand conformations and reproduce large-scale receptor conformational changes that occur upon binding.

Azepines↗

PubMed2006

HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations.

We report unrestrained, all-atom molecular dynamics simulations of HIV-1 protease that sample large conformational changes of the active site flaps. In particular, the unliganded protease undergoes multiple conversions between the "closed" and "semiopen" forms observed in crystal structures of inhibitor-bound and unliganded protease, respectively, including reversal of flap "handedness." Simulations in the presence of a cyclic urea inhibitor yield stable closed flaps. Furthermore, we observe several events in which the flaps of the unliganded protease open to a much greater degree than observed in crystal structures and subsequently return to the semiopen state. Our data strongly support the hypothesis that the unliganded protease predominantly populates the semiopen conformation, with closed and fully open structures being a minor component of the overall ensemble. The results also provide a model for the flap opening and closing that is considered to be essential to enzyme function.

Acquired Immunodeficiency Syndrome↗

PubMed2004

A molecular basis for the selectivity of thiadiazole urea inhibitors with stromelysin-1 and gelatinase-A from generalized born molecular dynamics simulations.

Matrix metalloproteinases (MMPs) represent a potentially important class of therapeutic targets for the treatment of diseases such as cancer. Selective inhibition of MMPs will be required given the high sequence identity across the family and the discovery that individual MMPs also regulate the natural angiogenesis inhibitor angiostatin. In this study, we have used computational methods to model the selectivity for six thiadiazole urea inhibitors with stromelysin-1 and gelatinase-A, two homologous MMPs that have been implicated in breast cancer. From continuum Generalized Born molecular dynamics (GB-MD) and MM-GBSA analysis, we estimated ligand free energies of binding using 200 snapshots obtained from a short 40 ps simulation of the relevant protein-ligand complex. The MM-GBSA free energies, computed from the continuum GB-MD trajectories, show strong correlation with the experimental affinities (r(2) = 0.74); prior studies have employed explicit water MD simulations. Including estimates for changes in solute entropy in the binding calculations slightly diminishes the overall correlation with experiment (r2 = 0.71). Notably, in every case, the simulation results correctly predict that a given ligand will bind selectively to stromelysin-1 over gelatinase-A which is gratifying given the high degree of structural homology between the two proteins. The increased selectivity for stromelysin-1 appears to be driven by (1) increased favorable van der Waals interactions, (2) increased favorable Coulombic interactions, and (3) decreased unfavorable total electrostatic energies (Coulombic plus desolvation).

Amino Acid Sequence↗

PubMed2003

Molecular modeling calculations of HIV-1 reverse transcriptase nonnucleoside inhibitors: correlation of binding energy with biological activity for novel 2-aryl-substituted benzimidazole analogues.

The energies and physical descriptors for the binding of 20 novel 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)benzimidazole analogues (BPBIs) to HIV-1 reverse transcriptase (RT) have been determined using Monte Carlo (MC) simulations. The crystallographic structure of the lead compound, 1-(2,6-difluorobenzyl)-2-(2,6-difluorophenyl)-4-methylbenzimidazole, was used as a starting point to model the inhibitors in both the bound and the unbound states. The energy terms and physical descriptors obtained from the calculations were correlated with their respective experimental EC(50) values, resulting in an r(2) value of 0.70 and a root-mean-square deviation (rms) of 0.53 kcal/mol. The terms in the correlation include the change in total Coulombic energy and solvent-accessible surface area. Structural analysis of the data files from the BPBI calculations reveals that all of the analogues with good biological activity show the formation of a hydrogen bond between the ligand and the backbone nitrogen atom of lysine 103. By use of the structural results, two novel BPBI inhibitors have been designed and calculations have been carried out. The results show the formation of the desired hydrogen bonds, and the DeltaG(binding) values predict the compounds to be excellent RT inhibitors. Subsequent synthesis and biological activity testing of these analogues have shown the validity of the predictive calculations. If the BPBIs are modeled in a site constructed from the crystal coordinates of a member of another class of nonnucleoside inhibitors (the 4,5,6,7-tetrahydroimidazo[4,5,1-jk][1,4]benzodiazepine-2(1H)-thione and -one (TIBO) compounds), the correlation with the same terms drops slightly, giving an r(2) value of 0.61 with an associated root-mean-square value of 0.53 kcal/mol. Conversely, if the TIBO compounds are modeled in a site constructed from the BPBI complex crystal coordinates, a correlation can be obtained using the drug-protein interaction energy and change in the total number of hydrogen bonds, giving an r(2) value of 0.63. These are the same descriptors that were used for the TIBO compounds modeled in their own sites, where the r(2) value was 0.72. These data suggest that it may be possible, in some cases, to design novel inhibitors utilizing structural data from related, but not identical, inhibitors.

Benzimidazoles↗

PubMed2002

Prediction of activity for nonnucleoside inhibitors with HIV-1 reverse transcriptase based on Monte Carlo simulations.

Results of Monte Carlo (MC) simulations for more than 200 nonnucleoside inhibitors of HIV-1 reverse transcriptase (NNRTIs) representing eight diverse chemotypes have been correlated with their anti-HIV activities in an effort to establish simulation protocols and methods that can be used in the development of more effective drugs. Each inhibitor was modeled in a complex with the protein and by itself in water, and potentially useful descriptors of binding affinity were collected during the MC simulations. A viable regression equation was obtained for each data set using an extended linear response approach, which yielded r(2) values between 0.54 and 0.85 and an average unsigned error of only 0.50 kcal/mol. The most common descriptors confirm that a good geometrical match between the inhibitor and the protein is important and that the net loss of hydrogen bonds with the inhibitor upon binding is unfavorable. Other physically reasonable descriptors of binding are needed on a chemotype case-by-case basis. By including descriptors in common from the individual fits, combination regressions that include multiple data sets were also developed. This procedure led to a refined "master" regression for 210 NNRTIs with an r(2) of 0.60 and a cross-validated q(2) of 0.55. The computed activities show an rms error of 0.86 kcal/mol in comparison with experiment and an average unsigned error of 0.69 kcal/mol. Encouraging results were obtained for the predictions of 27 NNRTIs, representing a new chemotype not included in the development of the regression model. Predictions for this test set using the master regression yielded a q(2) value of 0.51 and an average unsigned error of 0.67 kcal/mol. Finally, additional regression analysis reveals that use of ligand-only descriptors leads to models with much diminished predictive ability.

Alkynes↗