To explain drug resistance by computer simulations at the molecular level, we first have to assess the accuracy of theoretical predictions. Herein we report an application of the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) technique to the ranking of binding affinities of the inhibitor saquinavir with the wild type (WT) and three resistant mutants of HIV-1 protease: L90M, G48V, and G48V/L90M. For each ligand-protein complex we report 10 ns of fully unrestrained molecular dynamics (MD) simulations with explicit solvent. We investigate convergence, internal consistency, and model dependency of MM/PBSA ligand binding energies. Converged enthalpy and entropy estimates produce ligand binding affinities within 1.5 kcal/mol of experimental values, with a remarkable level of correlation to the experimentally observed ranking of resistance levels. A detailed analysis of the enthalpic/entropic balance of drug-protease interactions explains resistance in L90M in terms of a higher vibrational entropy than in the WT complex, while G48V disrupts critical hydrogen bonds at the inhibitor's binding site and produces an altered, more unfavorable balance of Coulomb and polar desolvation energies.

A considerable number of approved drugs show non-equilibrium binding characteristics, emphasizing the potential role of drug residence times for in vivo efficacy. Therefore, a detailed understanding of the kinetics of association and dissociation of a target-ligand complex might provide crucial insight into the molecular mechanism-of-action of a compound. This deeper understanding will help to improve decision making in drug discovery, thus leading to a better selection of interesting compounds to be profiled further. In this review, we highlight the contributions of the Kinetics for Drug Discovery (K4DD) Consortium, which targets major open questions related to binding kinetics in an industry-driven public-private partnership.

Accurate calculation of important thermodynamic properties, such as macromolecular binding free energies, is one of the principal goals of molecular dynamics simulations. However, single long simulation frequently produces incorrectly converged quantitative results due to inadequate sampling of conformational space in a feasible wall-clock time. Multiple short (ensemble) simulations have been shown to explore conformational space more effectively than single long simulations, but the two methods have not yet been thermodynamically compared. Here we show that, for end-state binding free energy determination methods, ensemble simulations exhibit significantly enhanced thermodynamic sampling over single long simulations and result in accurate and converged relative binding free energies that are reproducible to within 0.5 kcal/mol. Completely correct ranking is obtained for six HIV-1 protease variants bound to lopinavir with a correlation coefficient of 0.89 and a mean relative deviation from experiment of 0.9 kcal/mol. Multidrug resistance to lopinavir is enthalpically driven and increases through a decrease in the protein-ligand van der Waals interaction, principally due to the V82A/I84V mutation, and an increase in net electrostatic repulsion due to water-mediated disruption of protein-ligand interactions in the catalytic region. Furthermore, we correctly rank, to within 1 kcal/mol of experiment, the substantially increased chemical potency of lopinavir binding to the wild-type protease compared to saquinavir and show that lopinavir takes advantage of a decreased net electrostatic repulsion to confer enhanced binding. Our approach is dependent on the combined use of petascale computing resources and on an automated simulation workflow to attain the required level of sampling and turn around time to obtain the results, which can be as little as three days. This level of performance promotes integration of such methodology with clinical decision support systems for the optimization of patient-specific therapy.

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HIV maturation requires multiple cleavage of long polyprotein chains into functional proteins that include the viral protease itself. Initial cleavage by the protease dimer occurs from within these precursors, and yet only a single protease monomer is embedded in each polyprotein chain. Self-activation has been proposed to start from a partially dimerized protease formed from monomers of different chains binding its own N termini by self-association to the active site, but a complete structural understanding of this critical step in HIV maturation is missing. Here, we captured the critical self-association of immature HIV-1 protease to its extended aminoterminal recognition motif using large-scale molecular dynamics simulations, thus confirming the postulated intramolecular mechanism in atomic detail. We show that self-association to a catalytically viable state requires structural cooperativity of the flexible β-hairpin "flap" regions of the enzyme and that the major transition pathway is first via self-association in the semiopen/open enzyme states, followed by enzyme conformational transition into a catalytically viable closed state. Furthermore, partial N-terminal threading can play a role in self-association, whereas wide opening of the flaps in concert with self-association is not observed. We estimate the association rate constant (k on ) to be on the order of ∼1 × 10 4 s −1 , suggesting that N-terminal self-association is not the rate-limiting step in the process. The shown mechanism also provides an interesting example of molecular conformational transitions along the association pathway.conformational kinetics | Markov state model | high-throughput molecular dynamics H IV, along with all retroviruses, achieves infectious maturation of nascent virus particles through cleavage of polyprotein precursors by the viral protease. In particular, the GagPol chains contain several covalently linked proteins including the protease itself (Fig. 1A). Thus, maturation of the virus is initiated by autocatalysis of viral protease initially embedded in GagPol precursors. HIV-1 protease is functional only in dimeric form (1, 2) because activity of monomeric protease precursor is three orders of magnitude less than the mature dimer (3), and yet only a single monomer is embedded within each precursor. Two individual monomers in different GagPol chains must, therefore, come together to form an embedded dimeric protease, which ultimately cleaves itself into a mature form (Fig. 1B).Experiments indicate initial cleavage by a precursor protease still embedded in the GagPol chain occurs through an intramolecular, concentration-independent mechanism with the precursor protease cleaving its own terminus (4) and critically modulated by the N-terminal region (5-8). Mutations that block N-terminal cleavage result in severe loss of efficiency in catalytic activity. Cleavage at the protease (PR), reverse transcriptase (RT) junction at the C-terminal end of the protease by the precursor protease occurs via an intermolecular, concentrat...

The successful application of high throughput molecular simulations to determine biochemical properties would be of great importance to the biomedical community if such simulations could be turned around in a clinically relevant timescale. An important example is the determination of antiretroviral inhibitor efficacy against varying strains of HIV through calculation of drug-protein binding affinities. We describe the Binding Affinity Calculator (BAC), a tool for the automated calculation of HIV-1 protease-ligand binding affinities. The tool employs fully atomistic molecular simulations alongside the well established molecular mechanics Poisson-Boltzmann solvent accessible surface area (MMPBSA) free energy methodology to enable the calculation of the binding free energy of several ligand-protease complexes, including all nine FDA approved inhibitors of HIV-1 protease and seven of the natural substrates cleaved by the protease. This enables the efficacy of these inhibitors to be ranked across several mutant strains of the protease relative to the wildtype. BAC is a tool that utilizes the power provided by a computational grid to automate all of the stages required to compute free energies of binding: model preparation, equilibration, simulation, postprocessing, and data-marshaling around the generally widely distributed compute resources utilized. Such automation enables the molecular dynamics methodology to be used in a high throughput manner not achievable by manual methods. This paper describes the architecture and workflow management of BAC and the function of each of its components. Given adequate compute resources, BAC can yield quantitative information regarding drug resistance at the molecular level within 96 h. Such a timescale is of direct clinical relevance and can assist in decision support for the assessment of patient-specific optimal drug treatment and the subsequent response to therapy for any given genotype.

An accurate description of the conformational dynamics of the β-hairpin flaps of HIV-1 protease is of central importance in elucidating the functional recognition of the enzyme by ligands. Using all-atom molecular dynamics simulations in explicit solvent, with a total of 461 trajectories of ∼50 ns each, we report the closed, semiopen, open, and wide-open flap conformation of the free wild-type protease. The free energy of flap opening and closing from the semiopen state is 0.9 ± 0.2 and 2.4 ± 0.4 kcal/mol, respectively. The mean relaxation time of opening is ∼8 ns, in good agreement with NMR data. The explicit solvent simulations quantitatively confirm the hypothesis that the semiopen state is the dominant population in the free protease whilst fast flap tip fluctuations lead frequently to an open state. More pronounced flap rearrangements lead to a rare wide-open state with the catalytic site completely exposed to the solvent. The structures of the different flap conformations provided herein are of general interest for improved drug design of HIV-1 protease, in particular, the wide-open conformation could be favored by the large Gag and GagPol polyprotein chains. Strategies that take into account multiple flap-gating mechanisms may lead to more effective inhibitors.

Near attack conformations (NACs) are conformations extending from the ground state (GS) that lie on the transition path of a chemical reaction. Here, we develop a method for computing the thermodynamic contribution to catalysis due to NAC formation in bimolecular reactions, within the limit of a classical molecular dynamics force field. We make use of the Bürgi–Dunitz theory applied to large-scale unbiased all-atom ensemble molecular dynamics simulations. We apply this to HIV-1 protease peptide hydrolysis, known to achieve a rate enhancement of ∼1011 (ΔGcat⧧ ∼ 15 kcal/mol) over the uncatalyzed bimolecular reaction (ΔGnon⧧ ∼ 30 kcal/mol). The ground state consists of a nucleophilic water molecule bound to an octapeptide substrate in the active site. We first observe multiple and reversible binding of a nucleophilic water molecule into the active site giving a free energy of binding of ΔG = −1 kcal/mol to form the GS. The free energy barriers for catalyzed and uncatalyzed NAC formation are both equivalent: ΔGNAC⧧ = 4.6 kcal/mol, constituting ∼30% and ∼15% of the overall barriers, respectively. Therefore, not only does adoption of NACs only account for minor progress along the transition path in both catalyzed and uncatalyzed reactions, but there is no preferential formation of them in the catalyzed reaction. Analysis of the catalytic hydrogen bond network reveals interactions that stabilize the GS; however, subsequent NAC formation does not preferentially favor any of the possible hydrogen bond configurations. This supports the view that the catalytic power of HIV-1 protease is not due to NAC formation.