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Exploring the free-energy landscapes of biological systems with steered molecular dynamics.

ABSTRACT: We perform steered molecular dynamics (SMD) simulations and use the Brownian dynamics fluctuation-dissipation-theorem (BD-FDT) to accurately compute the free-energy profiles for several biophysical processes of fundamental importance: hydration of methane and cations, binding of benzene to T4-lysozyme L99A mutant, and permeation of water through aquaglyceroporin. For each system, the center-of-mass of the small molecule (methane, ion, benzene, and water, respectively) is steered (pulled) at a given speed over a period of time, during which the system transitions from one macroscopic state/conformation (State A) to another one (State B). The mechanical work of pulling the system is measured during the process, sampling a forward pulling path. Then the reverse pulling is conducted to sample a reverse path from B back to A. Sampling a small number of forward and reverse paths, we are able to accurately compute the free-energy profiles for all the afore-listed systems that represent various important aspects of biological physics. The numerical results are in excellent agreement with the experimental data and/or other computational studies available in the literature.

SUBMITTER: Chen LY

PROVIDER: S-EPMC3111135 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Exploring the free-energy landscapes of biological systems with steered molecular dynamics.

Chen L Y LY

Physical chemistry chemical physics : PCCP 20110225 13

We perform steered molecular dynamics (SMD) simulations and use the Brownian dynamics fluctuation-dissipation-theorem (BD-FDT) to accurately compute the free-energy profiles for several biophysical processes of fundamental importance: hydration of methane and cations, binding of benzene to T4-lysozyme L99A mutant, and permeation of water through aquaglyceroporin. For each system, the center-of-mass of the small molecule (methane, ion, benzene, and water, respectively) is steered (pulled) at a gi ...[more]

PMID: 21359274

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Project description:The significant work that has been invested toward understanding protein-protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein-protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics and entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein-protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes.

Project description:Computing the free energy of binding a ligand to a protein is a difficult task of essential importance for which purpose various theoretical/computational approaches have been pursued. In this paper, we develop a hybrid steered molecular dynamics (hSMD) method capable of resolving one ligand–protein complex within a few wall-clock days with high enough accuracy to compare with the experimental data. This hSMD approach is based on the relationship between the binding affinity and the potential of mean force (PMF) in the established literature. It involves simultaneously steering n (n = 1, 2, 3, ...) centers of mass of n selected segments of the ligand using n springs of infinite stiffness. Steering the ligand from a single initial state chosen from the bound state ensemble to the corresponding dissociated state, disallowing any fluctuations of the pulling centers along the way, one can determine a 3n-dimensional PMF curve connecting the two states by sampling a small number of forward and reverse pulling paths. This PMF constitutes a large but not the sole contribution to the binding free energy. Two other contributors are (1) the partial partition function containing the equilibrium fluctuations of the ligand at the binding site and the deviation of the initial state from the PMF minimum and (2) the partial partition function containing rotation and fluctuations of the ligand around one of the pulling centers that is fixed at a position far from the protein. We implement this hSMD approach for two ligand–protein complexes whose structures were determined and whose binding affinities were measured experimentally: caprylic acid binding to bovine ?-lactoglobulin and glutathione binding to Schistosoma japonicum glutathione S-transferase tyrosine 7 to phenylalanine mutant. Our computed binding affinities agree with the experimental data within a factor of 1.5. The total time of computation for these two all-atom model systems (consisting of 96K and 114K atoms, respectively) was less than one wall-clock week using 512 cores (32 Xeon E5-2680 processors).

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Exploring the free-energy landscapes of biological systems with steered molecular dynamics.

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Exploring the free-energy landscapes of biological systems with steered molecular dynamics.

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