3 papers
cond-mat.stat-mech2020
Arbitrarily accurate representation of atomistic dynamics via Markov Renewal Processes
Animesh Agarwal, Sandrasegaram Gnanakaran, Nicholas Hengartner +2
Atomistic simulations with methods such as molecular dynamics are extremely powerful tools to understand nanoscale dynamical behavior. The resulting trajectories, by the virtue of…
q-bio.QM2019
Development of a Fragment-Based Machine Learning Algorithm for Designing Hybrid Drugs Optimized for Permeating Gram-Negative Bacteria
Rachael A. Mansbach, Inga V. Leus, Jitender Mehla +6
Gram-negative bacteria are a serious health concern due to the strong multidrug resistance that they display, partly due to the presence of a permeability barrier comprising two me…
physics.chem-ph2019
Computing Long Timescale Biomolecular Dynamics using Quasi-Stationary Distribution Kinetic Monte Carlo (QSD-KMC)
Animesh Agarwal, Nicolas W. Hengartner, S. Gnanakaran +1
It is a challenge to obtain an accurate model of the state-to-state dynamics of a complex biological system from molecular dynamics (MD) simulations. In recent years, Markov State…