Accurate and efficient description of protein vibrational dynamics: comparing molecular dynamics and Gaussian models

Current all-atom potential based molecular dynamics (MD) allow the identification of a protein's functional motions on a wide-range of time-scales, up to few tens of ns. However, functional large scale motions of proteins may occur on a time-scale currently not accessible by all-atom potential based molecular dynamics. To avoid the massive computational effort required by this approach several simplified schemes have been introduced. One of the most satisfactory is the Gaussian Network approach based on the energy expansion in terms of the deviation of the protein backbone from its native configuration. Here we consider an extension of this model which captures in a more realistic way the distribution of native interactions due to the introduction of effective sidechain centroids. Since their location is entirely determined by the protein backbone, the model is amenable to the same exact and computationally efficient treatment as previous simpler models. The ability of the model to describe the correlated motion of protein residues in thermodynamic equilibrium is established through a series of successful comparisons with an extensive (14 ns) MD simulation based on the AMBER potential of HIV-1 protease in complex with a peptide substrate. Thus, the model presented here emerges as a powerful tool to provide preliminary, fast yet accurate characterizations of proteins near-native motion.Comment: 14 pages 7 figure

Exhaustive Search of Ligand Binding Pathways via Volume-based Metadynamics

Determining the complete set of ligands' binding/unbinding pathways is important for drug discovery and to rationally interpret mutation data. Here we have developed a metadynamics-based technique that addressed this issue and allows estimating affinities in the presence of multiple escape pathways. Our approach is shown on a Lysozyme T4 variant in complex with the benzene molecule. The calculated binding free energy is in agreement with experimental data. Remarkably, not only we were able to find all the previously identified ligand binding pathways, but also we uncovered 3 new ones. This results were obtained at a small computational cost, making this approach valuable for practical applications, such as screening of small compounds libraries

Protein Design is a Key Factor for Subunit-subunit Association

Fundamental questions about the role of the quaternary structures are addressed using a statistical mechanics off-lattice model of a dimer protein. The model, in spite of its simplicity, captures key features of the monomer-monomer interactions revealed by atomic force experiments. Force curves during association and dissociation are characterized by sudden jumps followed by smooth behavior and form hysteresis loops. Furthermore, the process is reversible in a finite range of temperature stabilizing the dimer. It is shown that in the interface between the two monomeric subunits the design procedure naturally favors those amino acids whose mutual interaction is stronger. Furthermore it is shown that the width of the hysteresis loop increases as the design procedure improves, i.e. stabilizes more the dimer.Comment: submitted to "Proceedings of the National Academy of Sciences, USA

Convergent dynamics in the protease enzymatic superfamily

Proteases regulate various aspects of the life cycle in all organisms by cleaving specific peptide bonds. Their action is so central for biochemical processes that at least 2% of any known genome encodes for proteolytic enzymes. Here we show that selected proteases pairs, despite differences in oligomeric state, catalytic residues and fold, share a common structural organization of functionally relevant regions which are further shown to undergo similar concerted movements. The structural and dynamical similarities found pervasively across evolutionarily distant clans point to common mechanisms for peptide hydrolysis.Comment: 13 pages, 6 figure

Molecular Dynamics Studies on HIV-1 Protease: Drug Resistance and Folding Pathways

Drug resistance to HIV-1 Protease involves accumulation of multiple mutations in the protein. Here we investigate the role of these mutations by using molecular dynamics simulations which exploit the influence of the native-state topology in the folding process. Our calculations show that sites contributing to phenotypic resistance of FDA-approved drugs are among the most sensitive positions for the stability of partially folded states and should play a relevant role in the folding process. Furthermore, associations between amino acid sites mutating under drug treatment are shown to be statistically correlated. The striking correlation between clinical data and our calculations suggest a novel approach to the design of drugs tailored to bind regions crucial not only for protein function but also for folding.Comment: Revtex, 14 pages, 7 eps figures. Proteins, Structure Function and Genetics, in press (2001

Open Boundary Simulations of Proteins and Their Hydration Shells by Hamiltonian Adaptive Resolution Scheme

The recently proposed Hamiltonian Adaptive Resolution Scheme (H-AdResS) allows to perform molecular simulations in an open boundary framework. It allows to change on the fly the resolution of specific subset of molecules (usually the solvent), which are free to diffuse between the atomistic region and the coarse-grained reservoir. So far, the method has been successfully applied to pure liquids. Coupling the H-AdResS methodology to hybrid models of proteins, such as the Molecular Mechanics/Coarse-Grained (MM/CG) scheme, is a promising approach for rigorous calculations of ligand binding free energies in low-resolution protein models. Towards this goal, here we apply for the first time H-AdResS to two atomistic proteins in dual-resolution solvent, proving its ability to reproduce structural and dynamic properties of both the proteins and the solvent, as obtained from atomistic simulations.Comment: This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of Chemical Theory and Computation, copyright \c{opyright} American Chemical Society after peer review and technical editing by the publishe

Advanced Computational Methods in Molecular Medicine

The dauntingly complex functioning of human cells is often the outcome of several molecular processes. Understanding such processes is crucial for modern drug discovery, defining interaction cascades, assessing the effects of mutations changes in local concentrations of ligands, and so forth. Computational methods, from systems biology to bioinformatics and molecular simulation, allow to access features difficult or impossible to be measured. Models (if properly validated against experimental data) help understand the intricate molecular mechanisms of life processes. Bolstering the predictive power of these models calls upon the computational biologist to improve algorithms and methods. This issue reports on procedures and on applications facing current challenges in computational biology.Modern biological sciences are becoming more and more multidisciplinary. At the same time, theoretical and computational approaches gain in reliability and their field of application widens. O. Fisette at al. discuss recent advances in the areas of solution nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations that were made possible by the synergistic combination of both methods.Interaction of proteins is of vital importance for many cellular processes and when altered may cause significant health problems, thus the availability of reliable tools to predict and study the determinants of protein-protein interactions is needed. In this regard, X. -Y. Meng et al. present a newly adapted, computationally efficient Brownian Dynamics- (BD-) based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. A shell-based grid force field represents the receptor protein and solvation effects, partially considering protein flexibility.Hybrid quantum mechanics/molecular mechanics (QM/MM) calculations are routinely used to study quantum mechanical processes in biological systems. J. Kang et al. present a review paper describing an UNIX shell-based interface program connecting two widely used QM and MM calculation engines, GAMESS and AMBER. The tool was used to investigate a metalloenzyme, azurin, and PU.1-DNA complex and mechanisms of hydrolysis (editing reaction) in leucyl-tRNA synthetase complexed with the mis-aminoacylated tRNALeu. The authors investigate the influence of environmental effects on the electronic structure.Electron transfer in proteins constitutes key steps in several biological processes, ranging from photosynthesis to aerobic respiration. T. Hayashi and A. Stuchebrukhov investigate electron tunneling in NADH : ubiquinone oxidoreductase (Complex I), a key enzyme in cellular respiration as an entry point of the electron transport chain of mitochondria and bacteria, by evaluating the transition flux between donor and acceptor at atomistic resolution. The study suggests that the diffusion of internal water molecules dynamically controls tunneling efficiency

Molecular Dynamics Simulations of the NGF-TrkA Domain 5 Complex and Comparison with Biological Data

AbstractThe nerve growth factor (NGF) is an important pharmacological target for Alzheimer's and other neurodegenerative diseases. Its action derives partly from its binding to the tyrosine kinase A receptor (TrkA). Here we study energetics and dynamics of the NGF-TrkA complex by carrying out multinanosecond molecular dynamics simulations, accompanied by electrostatic calculations based on the Poisson-Boltzmann equation. Our calculations, which are based on the x-ray structure of the complex, suggest that some of the mutations affecting dramatically the affinity of the complex involve residues that form highly favorable, direct or water-mediated hydrogen bond interactions at the ligand-receptor interface and, in some cases, that also critically participate to the large-scale motions of the complex. Furthermore, our calculations offer a rationale for the small effect on binding affinity observed upon specific mutations involving large changes in electrostatics (i.e., the charged-to-neutral mutations). Finally, these calculations, used along with the mutagenesis data, provide a basis for designing new peptides that mimic NGF in TrkA binding function