Variational analysis of molecular free energy landscapes and AI implementations

Author:

Bochuan Du ,Pu Tian

Abstract

Accurate description of the free energy landscape (FES) is the basis for understanding complex molecular systems, and for further realization of molecular design, manufacturing and industrialization. Major challenges include multiple metastable states,which usually are separated by high barriers and are not linearly separable, and may exist in more than one hierarchy of time and spatial scales. Consequently FES is not amenable to both analytical analyses and brute force simulations. To meet these challenges, many enhanced sampling methods have been developed. However, utility of them usually involves many empirical choices, which on the one hand hinders research advancement, and on the other hand renders error control highly nontrivial. Variation has been very successfully applied in physics, engineering and statistics, and its application in describing free energy landscapes of complex molecular systems started picking up momentum recently. This short review is to summarize the background, major developments, current limitations and prospects of applying variation in this regard. It is hoped to intrigue further methodology development in this line of research in particular, and to facilitate AI algorithm development for complex molecular systems in general.

Publisher

Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences

Subject

General Physics and Astronomy

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