Tailored Parameterization of the LIE Method for Calculating the Binding Free Energy of Vps34–Inhibitor Complexes
Ontology highlight
ABSTRACT:
SUBMITTER: Valdes-Tresanco M
PROVIDER: S-EPMC8582068 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:A simple and robust formulation of the path-independent confinement method for the calculation of free energies is presented. The simplified confinement method (SCM) does not require matrix diagonalization or switching off the molecular force field, and has a simple convergence criterion. The method can be readily implemented in molecular dynamics programs with minimal or no code modifications. Because the confinement method is a special case of thermodynamic integration, it is trivially parallel over the integration variable. The accuracy of the method is demonstrated using a model diatomic molecule, for which exact results can be computed analytically. The method is then applied to the alanine dipeptide in vacuum, and to the ?-helix ? ?-sheet transition in a 16-residue peptide modeled in implicit solvent. The SCM requires less effort for the calculation of free energy differences than previous formulations because it does not require computing normal modes. The SCM has a diminished advantage for determining absolute free energy values, because it requires decreasing the MD integration step to obtain accurate results. An approximate confinement procedure is introduced, which can be used to estimate directly the configurational entropy difference between two macrostates, without the need for additional computation of the difference in the free energy or enthalpy. The approximation has convergence properties similar to those of the standard confinement method for the calculation of free energies. The use of the approximation requires about 5 times less wall-clock simulation time than that needed to compute enthalpy differences to similar precision from an MD trajectory. For the biomolecular systems considered in this study, the errors in the entropy approximation are under 10%. Practical applications of the methods to proteins are currently limited to implicit solvent simulations.
| S-EPMC3569517 | biostudies-literature
Project description:Protein-protein binding is fundamental to most biological processes. It is important to be able to use computation to accurately estimate the change in protein-protein binding free energy due to mutations in order to answer biological questions that would be experimentally challenging, laborious, or time-consuming. Although nonrigorous free-energy methods are faster, rigorous alchemical molecular dynamics-based methods are considerably more accurate and are becoming more feasible with the advancement of computer hardware and molecular simulation software. Even with sufficient computational resources, there are still major challenges to using alchemical free-energy methods for protein-protein complexes, such as generating hybrid structures and topologies, maintaining a neutral net charge of the system when there is a charge-changing mutation, and setting up the simulation. In the current study, we have used the pmx package to generate hybrid structures and topologies, and a double-system/single-box approach to maintain the net charge of the system. To test the approach, we predicted relative binding affinities for two protein-protein complexes using a nonequilibrium alchemical method based on the Crooks fluctuation theorem and compared the results with experimental values. The method correctly identified stabilizing from destabilizing mutations for a small protein-protein complex, and a larger, more challenging antibody complex. Strong correlations were obtained between predicted and experimental relative binding affinities for both protein-protein systems.
| S-EPMC8044032 | biostudies-literature
Project description:The interface between protein receptor-ligand complexes has been studied with respect to their binary interatomic interactions. Crystal structure data have been used to catalogue surfaces buried by atoms from each member of a bound complex and determine a statistical preference for pairs of amino-acid atoms. A simple free energy model of the receptor-ligand system is constructed from these atom-atom preferences and used to assess the energetic importance of interfacial interactions. The free energy approximation of binding strength in this model has a reliability of about +/- 1.5 kcal/mol, despite limited knowledge of the unbound states. The main utility of such a scheme lies in the identification of important stabilizing atomic interactions across the receptor-ligand interface. Thus, apart from an overall hydrophobic attraction (Young L, Jernigan RL, Covell DG, 1994, Protein Sci 3:717-729), a rich variety of specific interactions is observed. An analysis of 10 HIV-1 protease inhibitor complexes is presented that reveals a common binding motif comprised of energetically important contacts with a rather limited set of atoms. Design improvements to existing HIV-1 protease inhibitors are explored based on a detailed analysis of this binding motif.
| S-EPMC2143230 | biostudies-other
Project description:A quantum mechanical/molecular mechanical minimum free energy path (QM/MM-MFEP) method was developed to calculate the redox free energies of large systems in solution with greatly enhanced efficiency for conformation sampling. The QM/MM-MFEP method describes the thermodynamics of a system on the potential of mean force surface of the solute degrees of freedom. The molecular dynamics (MD) sampling is only carried out with the QM subsystem fixed. It thus avoids "on-the-fly" QM calculations and thus overcomes the high computational cost in the direct QM/MM MD sampling. In the applications to two metal complexes in aqueous solution, the new QM/MM-MFEP method yielded redox free energies in good agreement with those calculated from the direct QM/MM MD method. Two larger biologically important redox molecules, lumichrome and riboflavin, were further investigated to demonstrate the efficiency of the method. The enhanced efficiency and uncompromised accuracy are especially significant for biochemical systems. The QM/MM-MFEP method thus provides an efficient approach to free energy simulation of complex electron transfer reactions.
| S-EPMC2736613 | biostudies-other
Project description:A large number of experimental studies have been devoted to quantifying the interaction between transmembrane (TM) helices in detergent micelles and, more recently, in bilayers. Theoretical calculation of association free energy of TM helices would be useful for predicting the propensity of given sequences to oligomerize and for understanding the difference between association in micelles and in bilayers. In this article, the theoretical foundation for calculating the standard association free energy of TM helices is laid out and is applied to glycophorin A in both micelles and bilayers. The standard association free energy is decomposed into the effective energy, translational, rotational, and conformational entropy terms. The effective energy of association is obtained by molecular dynamics simulations in an implicit membrane model. The translational and rotational entropy of association is calculated from the probability distribution of the translational and rotational degrees of freedom obtained from the molecular dynamics simulations. The side-chain conformational entropy of association is estimated from the probability distribution obtained by rigid rotation of all side-chain dihedral angles. The calculated standard association free energy of glycophorin A in N-dodecylphosphocholine micelles is in good agreement with the experimental value. The translational entropy cost is larger, whereas the rotational entropy cost is smaller in bilayers than in micelles. The standard association free energy in 1,2-dimyristoyl-sn-glycero-3-phosphocholine bilayers is calculated to be approximately 1.3 kcal/mol more favorable than in N-dodecylphosphocholine micelles, consistent with available experimental data.
| S-EPMC1544303 | biostudies-literature
Project description:The free energy of a process is the fundamental quantity that determines its spontaneity or propensity at a given temperature. In particular, the binding free energy of a drug candidate to its biomolecular target is used as an objective quantity in drug design. Recently, binding kinetics-rates of association (k on) and dissociation (k off)-have also demonstrated utility for their ability to predict efficacy and in some cases have been shown to be more predictive than the binding free energy alone. Some methods exist to calculate binding kinetics from molecular simulations, although these are typically more difficult to calculate than the binding affinity as they depend on details of the transition path ensemble. Assessing these rate constants can be difficult, due to uncertainty in the definition of the bound and unbound states, large error bars and the lack of experimental data. As an additional consistency check, rate constants from simulation can be used to calculate free energies (using the log of their ratio) which can then be compared to free energies obtained experimentally or using alchemical free energy perturbation. However, in this calculation it is not straightforward to account for common, practical details such as the finite simulation volume or the particular definition of the "bound" and "unbound" states. Here we derive a set of correction terms that can be applied to calculations of binding free energies using full reactive trajectories. We apply these correction terms to revisit the calculation of binding free energies from rate constants for a host-guest system that was part of a blind prediction challenge, where significant deviations were observed between free energies calculated with rate ratios and those calculated from alchemical perturbation. The correction terms combine to significantly decrease the error with respect to computational benchmarks, from 3.4 to 0.76 kcal/mol. Although these terms were derived with weighted ensemble simulations in mind, some of the correction terms are generally applicable to free energies calculated using physical pathways via methods such as Markov state modeling, metadynamics, milestoning, or umbrella sampling.
| S-EPMC7291376 | biostudies-literature
Project description:Modern drug discovery increasingly focuses on the drug-target binding kinetics which depend on drug (un)binding pathways. The conventional molecular dynamics simulation can observe only a few binding events even using the fastest supercomputer. Here, we develop 2D gREST/REUS simulation with enhanced flexibility of the ligand and the protein binding site. Simulation (43 ?s in total) applied to an inhibitor binding to c-Src kinase covers 100 binding and unbinding events. On the statistically converged free-energy landscapes, we succeed in predicting the X-ray binding structure, including water positions. Furthermore, we characterize hidden semibound poses and transient encounter complexes on the free-energy landscapes. Regulatory residues distant from the catalytic core are responsible for the initial inhibitor uptake and regulation of subsequent bindings, which was unresolved by experiments. Stabilizing/blocking of either the semibound poses or the encounter complexes can be an effective strategy to optimize drug-target residence time.
| S-EPMC6744929 | biostudies-literature
Project description:Hypothetical scanning molecular dynamics (HSMD) is a relatively new method for calculating the absolute free energy and entropy. HSMD is extended here for the first time for calculating the absolute free energy of binding, ?A(0), as applied to the avidin-biotin complex. With HSMD the ligand is built (more accurately reconstructed) from nothing in solvent and in the protein, in contrast to the commonly used methods where the ligand is annihilated (by thermodynamic integration) in these environments. Therefore, the end-point problem encountered with the latter methods does not exist with HSMD and the need for restraints is avoided. Also, the entropy of the ligand and water in both environments is obtained directly as a byproduct of the simulation. The binding mechanism of biotin to avidin involves a mobile loop that is expected to be in an open conformation in unbound avidin, which is changed to a closed one upon binding, that is, the loop moves to cover biotin in the active site. The contribution of the loop's conformational change to the total free energy of binding is calculated here for the first time. Our result, ?A(0) = -24.9 ± 7 covers the experimental value -20.7 kcal/mol within the error bars.
| S-EPMC3042141 | biostudies-literature
Project description:Many studies have provided evidence suggesting that caspases not only contribute to the neurodegeneration associated with Alzheimer's disease (AD) but also play essential roles in promoting the underlying pathology of this disease. Studies regarding the caspase inhibition draw researchers' attention through time due to its therapeutic value in the treatment of AD. In this work, we apply the "Movable Type" (MT) free energy method, a Monte Carlo sampling method extrapolating the binding free energy by simulating the partition functions for both free-state and bound-state protein and ligand configurations, to the caspase-inhibitor binding affinity study. Two test benchmarks are introduced to examine the robustness and sensitivity of the MT method concerning the caspase inhibition complexing. The first benchmark employs a large-scale test set including more than a hundred active inhibitors binding to caspase-3. The second benchmark includes several smaller test sets studying the relative binding free energy differences for minor structural changes at the caspase-inhibitor interaction interfaces. Calculation results show that the RMS errors for all test sets are below 1.5 kcal/mol compared to the experimental binding affinity values, demonstrating good performance in simulating the caspase-inhibitor complexing. For better understanding the protein-ligand interaction mechanism, we then take a closer look at the global minimum binding modes and free-state ligand conformations to study two pairs of caspase-inhibitor complexes with (1) different caspase targets binding to the same inhibitor, and (2) different polypeptide inhibitors targeting the same caspase target. By comparing the contact maps at the binding site of different complexes, we revealed how small structural changes affect the caspase-inhibitor interaction energies. Overall, this work provides a new free energy approach for studying the caspase inhibition, with structural insight revealed for both free-state and bound-state molecular configurations.
| S-EPMC6801467 | biostudies-literature
Project description:VPS34 phosphorylates phosphatidylinositol to produce PtdIns3P and is the progenitor of the phosphoinositide 3-kinase (PI3K) family. VPS34 has a simpler domain organization than class I PI3Ks, which belies the complexity of its quaternary organization, with the enzyme always functioning within larger assemblies. PtdIns3P recruits specific recognition modules that are common in protein-sorting pathways, such as autophagy and endocytic sorting. It is best characterized in two heterotetramers, complexes I and II. Complex I is composed of VPS34, VPS15, Beclin 1, and autophagy-related gene (ATG)14L, whereas complex II replaces ATG14L with UVRAG. Because VPS34 can form a component of several distinct complexes, it enables independent regulation of various pathways that are controlled by PtdIns3P. Complexes I and II are critical for early events in autophagy and endocytic sorting, respectively. Autophagy has a complex association with cancer. In early stages, it inhibits tumorigenesis, but in later stages, it acts as a survival factor for tumors. Recently, various disease-associated somatic mutations were found in genes encoding complex I and II subunits. Lipid kinase activities of the complexes are also influenced by posttranslational modifications (PTMs). Mapping PTMs and somatic mutations on three-dimensional models of the complexes suggests mechanisms for how these affect VPS34 activity.
| S-EPMC6358306 | biostudies-literature