[PDF][PDF] Ensemble docking in drug discovery

RE Amaro, J Baudry, J Chodera, Ö Demir… - Biophysical journal, 2018 - cell.com
Ensemble docking corresponds to the generation of an" ensemble" of drug target
conformations in computational structure-based drug discovery, often obtained by using …

Predicting binding free energies: frontiers and benchmarks

DL Mobley, MK Gilson - Annual review of biophysics, 2017 - annualreviews.org
Binding free energy calculations based on molecular simulations provide predicted affinities
for biomolecular complexes. These calculations begin with a detailed description of a …

[HTML][HTML] A suite of tutorials for the WESTPA rare-events sampling software [Article v1. 0]

AT Bogetti, B Mostofian, A Dickson… - Living journal of …, 2019 - ncbi.nlm.nih.gov
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 …

Machine learning of coarse-grained molecular dynamics force fields

J Wang, S Olsson, C Wehmeyer, A Pérez… - ACS central …, 2019 - ACS Publications
Atomistic or ab initio molecular dynamics simulations are widely used to predict
thermodynamics and kinetics and relate them to molecular structure. A common approach to …

[HTML][HTML] Best practices for alchemical free energy calculations [article v1. 0]

ASJS Mey, BK Allen, HEB Macdonald… - Living journal of …, 2020 - ncbi.nlm.nih.gov
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 …

Role of molecular dynamics and related methods in drug discovery

M De Vivo, M Masetti, G Bottegoni… - Journal of medicinal …, 2016 - ACS Publications
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 …

PyEMMA 2: A software package for estimation, validation, and analysis of Markov models

MK Scherer, B Trendelkamp-Schroer… - Journal of chemical …, 2015 - ACS Publications
Markov (state) models (MSMs) and related models of molecular kinetics have recently
received a surge of interest as they can systematically reconcile simulation data from either …

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

C Wehmeyer, F Noé - The Journal of chemical physics, 2018 - pubs.aip.org
Inspired by the success of deep learning techniques in the physical and chemical sciences,
we apply a modification of an autoencoder type deep neural network to the task of …

Complete protein–protein association kinetics in atomic detail revealed by molecular dynamics simulations and Markov modelling

N Plattner, S Doerr, G De Fabritiis, F Noé - Nature chemistry, 2017 - nature.com
Protein–protein association is fundamental to many life processes. However, a microscopic
model describing the structures and kinetics during association and dissociation is lacking …

HTMD: high-throughput molecular dynamics for molecular discovery

S Doerr, MJ Harvey, F Noé… - Journal of chemical …, 2016 - ACS Publications
Recent advances in molecular simulations have allowed scientists to investigate slower
biological processes than ever before. Together with these advances came an explosion of …