Living journal of computational molecular science最新文献

Software is ubiquitous in modern science - almost any project, in almost any discipline, requires some code to work. However, many (or even most) scientists are not programmers, and must rely on programs written and maintained by others. A crucial but often neglected part of a scientist's training is learning how to use new tools, and how to exist as part of a community of users. This article will discuss key behaviors that can make the experience quicker, more efficient, and more pleasant for the user and developer alike.

Hydrogen-deuterium exchange (HDX) is a comprehensive yet detailed probe of protein structure and dynamics and, coupled to mass spectrometry, has become a powerful tool for investigating an increasingly large array of systems. Computer simulations are often used to help rationalize experimental observations of exchange, but interpretations have frequently been limited to simple, subjective correlations between microscopic dynamical fluctuations and the observed macroscopic exchange behavior. With this in mind, we previously developed the HDX ensemble reweighting approach and associated software, HDXer, to aid the objective interpretation of HDX data using molecular simulations. HDXer has two main functions; first, to compute H-D exchange rates that describe each structure in a candidate ensemble of protein structures, for example from molecular simulations, and second, to objectively reweight the conformational populations present in a candidate ensemble to conform to experimental exchange data. In this article, we first describe the HDXer approach, theory, and implementation. We then guide users through a suite of tutorials that demonstrate the practical aspects of preparing experimental data, computing HDX levels from molecular simulations, and performing ensemble reweighting analyses. Finally we provide a practical discussion of the capabilities and limitations of the HDXer methods including recommendations for a user's own analyses. Overall, this article is intended to provide an up-to-date, pedagogical counterpart to the software, which is freely available at https://github.com/Lucy-Forrest-Lab/HDXer.

Alchemical free energy calculations are a useful tool for predicting free energy differences associated with the transfer of molecules from one environment to another. The hallmark of these methods is the use of "bridging" potential energy functions representing alchemical intermediate states that cannot exist as real chemical species. The data collected from these bridging alchemical thermodynamic states allows the efficient computation of transfer free energies (or differences in transfer free energies) with orders of magnitude less simulation time than simulating the transfer process directly. While these methods are highly flexible, care must be taken in avoiding common pitfalls to ensure that computed free energy differences can be robust and reproducible for the chosen force field, and that appropriate corrections are included to permit direct comparison with experimental data. In this paper, we review current best practices for several popular application domains of alchemical free energy calculations performed with equilibrium simulations, in particular relative and absolute small molecule binding free energy calculations to biomolecular targets.

We establish a reliable and robust standardization of settings for practical molecular dynamics (MD) simulations of pure and mixed (single- and multi-component) lipid bilayer membranes. In lipid membranes research, particle-based molecular simulations are a powerful tool alongside continuum theory, lipidomics, and model, in vitro, and in vivo experiments. Molecular simulations can provide precise and reproducible spatiotemporal (atomic- and femtosecond-level) information about membrane structure, mechanics, thermodynamics, kinetics, and dynamics. Yet the simulation of lipid membranes can be a daunting task, given the uniqueness of lipid membranes relative to conventional liquid-liquid and solid-liquid interfaces, the immense and complex thermodynamic and statistical mechanical theory, the diversity of multiscale lipid models, limitations of modern computing power, the difficulty and ambiguity of simulation controls, finite size effects, competitive continuum simulation alternatives, and the desired application, including vesicle experiments and biological membranes. These issues can complicate an essential understanding of the field of lipid membranes, and create major bottlenecks to simulation advancement. In this article, we clarify these issues and present a consistent, thorough, and user-friendly framework for the design of state-of-the-art lipid membrane MD simulations. We hope to allow early-career researchers to quickly overcome common obstacles in the field of lipid membranes and reach maximal impact in their simulations.