Browse
Submit Data
Databases
API
Help

Dataset Information

15 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0].

ABSTRACT: The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that "consumers" of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some 'enhanced' sampling approaches. We do not discuss systematic errors arising, e.g., from inaccuracy in the chosen model or force field.

SUBMITTER: Grossfield A

PROVIDER: S-EPMC6286151 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Best Practices for Foundations in Molecular Simulations [Article v1.0].

Project description:This document provides a starting point for approaching molecular simulations, guiding beginning practitioners to what issues they need to know about before and while starting their first simulations, and why those issues are so critical. This document makes no claims to provide an adequate introduction to the subject on its own. Instead, our goal is to help people know what issues are critical before beginning, and to provide references to good resources on those topics. We also provide a checklist of key issues to consider before and while setting up molecular simulations which may serve as a foundation for other best practices documents.

| S-EPMC6884151 | biostudies-literature

Best Practices in Constant pH MD Simulations: Accuracy and Sampling.

Project description:Various approaches have been proposed to include the effect of pH in molecular dynamics (MD) simulations. Among these, the λ-dynamics approach proposed by Brooks and co-workers [Kong, X.; Brooks III, C. L. J. Chem. Phys. 1996, 105, 2414-2423] can be performed with little computational overhead and hfor each typeence be used to routinely perform MD simulations at microsecond time scales, as shown in the accompanying paper [Aho, N. et al. J. Chem. Theory Comput. 2022, DOI: 10.1021/acs.jctc.2c00516]. At such time scales, however, the accuracy of the molecular mechanics force field and the parametrization becomes critical. Here, we address these issues and provide the community with guidelines on how to set up and perform long time scale constant pH MD simulations. We found that barriers associated with the torsions of side chains in the CHARMM36m force field are too high for reaching convergence in constant pH MD simulations on microsecond time scales. To avoid the high computational cost of extending the sampling, we propose small modifications to the force field to selectively reduce the torsional barriers. We demonstrate that with such modifications we obtain converged distributions of both protonation and torsional degrees of freedom and hence consistent pKa estimates, while the sampling of the overall configurational space accessible to proteins is unaffected as compared to normal MD simulations. We also show that the results of constant pH MD depend on the accuracy of the correction potentials. While these potentials are typically obtained by fitting a low-order polynomial to calculated free energy profiles, we find that higher order fits are essential to provide accurate and consistent results. By resolving problems in accuracy and sampling, the work described in this and the accompanying paper paves the way to the widespread application of constant pH MD beyond pKa prediction.

| S-EPMC9558372 | biostudies-literature

Best practices for eCLIP experiments and analysis [poor quality]

Project description:Enhanced cross-linking immunoprecipitation (eCLIP) featuring a size-matched input control has been recently applied to profile the binding sites of more than one hundred RNA binding proteins (RBPs). However computational pipelines and quality control metrics needed to process CLIP data at scale have yet to be well defined. Here, we describe our ENCODE eCLIP processing pipeline (https://github.com/YeoLab/eclip), enabling users to go from raw reads to processed peaks that are enriched above paired input, reproducible across biological replicates, and can be directly compared against the public ENCODE eCLIP resource. In particular, we discuss processing steps designed to address common artifacts, including properly quantifying unique RNA fragments bound by both unique genomic- and repetitive element-mapped reads. Using manual quality annotation of 350 ENCODE eCLIP experiments, we develop metrics for quality assessment of eCLIP experiments prior to and after sequencing, including library yield, number of unique fragments in the library, total binding relative information, and biological reproducibility. In particular, we quantify the commonly believed linkage between depth of sequencing and peak discovery, and derive methods for estimating required sequencing depth based on pre-sequencing metrics. Finally we provide recommendations for the common question of integrating RBP binding information with RNA-seq to generate splicing maps representing the positional effect of binding on alternative splicing. These pipelines and QC metrics enable large-scale processing and analysis of eCLIP data, and will help to standardize rigorous analysis of RBP binding data.

2018-06-08 | GSE107767 | GEO

Best practices for eCLIP experiments and analysis [uncertain quality]

2018-06-08 | GSE107766 | GEO

A Suite of Tutorials for the WESTPA Rare-Events Sampling Software [Article v1.0].

Project description:The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present five tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. Users are expected to already have significant experience with running standard molecular dynamics simulations using the underlying dynamics engine of interest (e.g. Amber, Gromacs, OpenMM). The tutorials range from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.

| S-EPMC7213600 | biostudies-literature

Interpreting Hydrogen-Deuterium Exchange Experiments with Molecular Simulations: Tutorials and Applications of the HDXer Ensemble Reweighting Software [Article v1.0].

Project description: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.

| S-EPMC9835200 | biostudies-literature

Best practices for eCLIP experiments and analysis

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-06-08 | GSE107768 | GEO

A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0].

Project description:Like temperature and pressure, solution pH is an important environmental variable in biomolecular simulations. Virtually all proteins depend on pH to maintain their structure and function. In conventional molecular dynamics (MD) simulations of proteins, pH is implicitly accounted for by assigning and fixing protonation states of titratable sidechains. This is a significant limitation, as the assigned protonation states may be wrong and they may change during dynamics. In this tutorial, we guide the reader in learning and using the various continuous constant pH MD methods in Amber and CHARMM packages, which have been applied to predict pK a values and elucidate proton-coupled conformational dynamics of a variety of proteins including enzymes and membrane transporters.

| S-EPMC9910290 | biostudies-literature