Biomolecular Modeling and Simulation: A Prospering Multidisciplinary Field

Abstract

We reassess progress in the field of biomolecular modeling and simulation, following up on our perspective published in 2011. By reviewing metrics for the field's productivity and providing examples of success, we underscore the productive phase of the field, whose short-term expectations were overestimated and long-term effects underestimated. Such successes include prediction of structures and mechanisms; generation of new insights into biomolecular activity; and thriving collaborations between modeling and experimentation, including experiments driven by modeling. We also discuss the impact of field exercises and web games on the field's progress. Overall, we note tremendous success by the biomolecular modeling community in utilization of computer power; improvement in force fields; and development and application of new algorithms, notably machine learning and artificial intelligence. The combined advances are enhancing the accuracy and scope of modeling and simulation, establishing an exemplary discipline where experiment and theory or simulations are full partners. Expected final online publication date for the Annual Review of Biophysics, Volume 50 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Biomolecular modeling thrives in the age of technology

“…This in turn means that urgent problems can be solved to improve our lives, health and environment, from wind farms to vaccines. In particular, biomolecular modeling and simulation is thriving in this ever-evolving landscape, evidenced by many successes, and in experiments driven by modeling 15 .…”

Dynamical nonequilibrium molecular dynamics reveals the structural basis for allostery and signal propagation in biomolecular systems

“…Some of these approaches rely on the use of information from equilibrium molecular dynamics (MD) simulations (e.g., [4][5][6][7][8][9][10][11]). However, for most conformational changes of interest in proteins, equilibrium MD simulations cannot access the relevant timescales and the number of events needed to determine the timedependent structural changes and the order of the events associated with it, in a statistically significant way (for a detailed discussion about the 'sampling problem', see, e.g., [1,12,13]). a e-mail: sofia.oliveira@bristol.ac.uk (corresponding author)…”

Searching for Low Probability Opening Events in a DNA Sliding Clamp

“…Simulations of nucleic acid systems expand scales of different lengths, with mesoscopic and coarse-grained models bridging between atomistic simulations and relevant lengthscales in the cell [34][35][36][37]. In recent years, several approaches involving coarse-grained and multiscale simulation strategies have been developed to combine proteins and nucleic acids [38][39][40][41].…”