To milliseconds and beyond: challenges in the simulation of protein folding.
TL;DR: Recent progress in MD simulation techniques is reviewed and how the vast datasets generated by such techniques present new challenges for analysis is shown, including reaction coordinate and Markov state model methods.
About: This article is published in Current Opinion in Structural Biology.The article was published on 2013-02-01 and is currently open access. It has received 357 citations till now.
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TL;DR: MDTraj is a modern, lightweight, and fast software package for analyzing MD simulations that simplifies the analysis of MD data and connects these datasets with the modern interactive data science software ecosystem in Python.
1,480 citations
Cites background from "To milliseconds and beyond: challen..."
...To use these vast and information-rich datasets to understand biomolecular systems and generate scientific insight, further computation, analysis, and visualization are required (2)....
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TL;DR: The membrane raft hypothesis formalized a physicochemical principle for a subtype of lateral membrane heterogeneity, in which the preferential associations between cholesterol and saturated lipids drive the formation of relatively packed membrane domains that selectively recruit certain lipids and proteins.
Abstract: Cellular plasma membranes are laterally heterogeneous, featuring a variety of distinct subcompartments that differ in their biophysical properties and composition. A large number of studies have focused on understanding the basis for this heterogeneity and its physiological relevance. The membrane raft hypothesis formalized a physicochemical principle for a subtype of such lateral membrane heterogeneity, in which the preferential associations between cholesterol and saturated lipids drive the formation of relatively packed (or ordered) membrane domains that selectively recruit certain lipids and proteins. Recent studies have yielded new insights into this mechanism and its relevance in vivo, owing primarily to the development of improved biochemical and biophysical technologies.
1,349 citations
TL;DR: An overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions are provided.
Abstract: The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.
711 citations
TL;DR: The theoretical background of MD and enhanced sampling methods is reviewed, focusing on free-energy perturbation, metadynamics, steered MD, and other methods most consistently used to study drug-target binding.
Abstract: Molecular dynamics (MD) and related methods are close to becoming routine computational tools for drug discovery. Their main advantage is in explicitly treating structural flexibility and entropic effects. This allows a more accurate estimate of the thermodynamics and kinetics associated with drug-target recognition and binding, as better algorithms and hardware architectures increase their use. Here, we review the theoretical background of MD and enhanced sampling methods, focusing on free-energy perturbation, metadynamics, steered MD, and other methods most consistently used to study drug-target binding. We discuss unbiased MD simulations that nowadays allow the observation of unsupervised ligand-target binding, assessing how these approaches help optimizing target affinity and drug residence time toward improved drug efficacy. Further issues discussed include allosteric modulation and the role of water molecules in ligand binding and optimization. We conclude by calling for more prospective studies to attest to these methods' utility in discovering novel drug candidates.
693 citations
TL;DR: Recent progress in Markov state models, which reproduce the long-time statistical conformational dynamics of biomolecules using data from molecular dynamics simulations, is reviewed, considering theoretical and methodological advances, new software tools, and recent applications of these approaches in several domains of biochemistry and biophysics.
651 citations
References
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TL;DR: NAMD as discussed by the authors is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales to hundreds of processors on high-end parallel platforms, as well as tens of processors in low-cost commodity clusters, and also runs on individual desktop and laptop computers.
Abstract: NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms, as well as tens of processors on low-cost commodity clusters, and also runs on individual desktop and laptop computers. NAMD works with AMBER and CHARMM potential functions, parameters, and file formats. This article, directed to novices as well as experts, first introduces concepts and methods used in the NAMD program, describing the classical molecular dynamics force field, equations of motion, and integration methods along with the efficient electrostatics evaluation algorithms employed and temperature and pressure controls used. Features for steering the simulation across barriers and for calculating both alchemical and conformational free energy differences are presented. The motivations for and a roadmap to the internal design of NAMD, implemented in C++ and based on Charm++ parallel objects, are outlined. The factors affecting the serial and parallel performance of a simulation are discussed. Finally, typical NAMD use is illustrated with representative applications to a small, a medium, and a large biomolecular system, highlighting particular features of NAMD, for example, the Tcl scripting language. The article also provides a list of the key features of NAMD and discusses the benefits of combining NAMD with the molecular graphics/sequence analysis software VMD and the grid computing/collaboratory software BioCoRE. NAMD is distributed free of charge with source code at www.ks.uiuc.edu.
14,558 citations
TL;DR: A new implementation of the molecular simulation toolkit GROMACS is presented which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines.
Abstract: Molecular simulation is an extremely useful, but computationally very expensive tool for studies of chemical and biomolecular systems Here, we present a new implementation of our molecular simulation toolkit GROMACS which now both achieves extremely high performance on single processors from algorithmic optimizations and hand-coded routines and simultaneously scales very well on parallel machines The code encompasses a minimal-communication domain decomposition algorithm, full dynamic load balancing, a state-of-the-art parallel constraint solver, and efficient virtual site algorithms that allow removal of hydrogen atom degrees of freedom to enable integration time steps up to 5 fs for atomistic simulations also in parallel To improve the scaling properties of the common particle mesh Ewald electrostatics algorithms, we have in addition used a Multiple-Program, Multiple-Data approach, with separate node domains responsible for direct and reciprocal space interactions Not only does this combination of a
14,032 citations
TL;DR: The development, current features, and some directions for future development of the Amber package of computer programs, which contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.
Abstract: We describe the development, current features, and some directions for future development of the Amber package of computer programs. This package evolved from a program that was constructed in the late 1970s to do Assisted Model Building with Energy Refinement, and now contains a group of programs embodying a number of powerful tools of modern computational chemistry, focused on molecular dynamics and free energy calculations of proteins, nucleic acids, and carbohydrates.
7,672 citations
TL;DR: Anfinsen as discussed by the authors provided a sketch of the rich history of research that provided the foundation for his work on protein folding and the Thermodynamic Hypothesis, and outlined potential avenues of current and future scientific exploration.
Abstract: Stanford Moore, William Stein, and Anfinsen were awarded the Nobel Prize in Chemistry in 1972 for \"their contribution
to the understanding of the connection between chemical structure and catalytic activity of the active center of the ribonuclease
molecule.\" In his Nobel Lecture, Anfinsen provided a sketch of the rich history of research that provided the foundation
for his work on protein folding and the \"Thermodynamic Hypothesis,\" and outlined potential avenues of current and
future scientific exploration.
6,520 citations