Scientific discovery in the age of artificial intelligence

H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu… - Nature, 2023 - nature.com
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …

New Insights into the Cooperativity and Dynamics of Dimeric Enzymes

KW Chen, TY Sun, YD Wu - Chemical Reviews, 2023 - ACS Publications
A survey of protein databases indicates that the majority of enzymes exist in oligomeric
forms, with about half of those found in the UniProt database being homodimeric …

Direct generation of protein conformational ensembles via machine learning

G Janson, G Valdes-Garcia, L Heo, M Feig - Nature Communications, 2023 - nature.com
Dynamics and conformational sampling are essential for linking protein structure to
biological function. While challenging to probe experimentally, computer simulations are …

Adaptive sampling methods for molecular dynamics in the era of machine learning

DE Kleiman, H Nadeem, D Shukla - The Journal of Physical …, 2023 - ACS Publications
Molecular dynamics (MD) simulations are fundamental computational tools for the study of
proteins and their free energy landscapes. However, sampling protein conformational …

Multiagent reinforcement learning-based adaptive sampling for conformational dynamics of proteins

DE Kleiman, D Shukla - Journal of Chemical Theory and …, 2022 - ACS Publications
Machine learning is increasingly applied to improve the efficiency and accuracy of molecular
dynamics (MD) simulations. Although the growth of distributed computer clusters has …

Strategy to improve Cu-BTC metal-organic frameworks performance in removal of Rhodamine B: MD and WT-MtD simulations assessment

L Razavi, H Raissi, H Hashemzadeh, F Farzad - NPJ Clean Water, 2022 - nature.com
With industry progress, environmental problems have begun to threaten human health.
Among them, water pollution is closely related to human life and has attracted researchers' …

Active learning of the conformational ensemble of proteins using maximum entropy VAMPNets

DE Kleiman, D Shukla - Journal of Chemical Theory and …, 2023 - ACS Publications
Rapid computational exploration of the free energy landscape of biological molecules
remains an active area of research due to the difficulty of sampling rare state transitions in …

Simulate time-integrated coarse-grained molecular dynamics with geometric machine learning

X Fu - 2022 - dspace.mit.edu
Molecular dynamics (MD) simulation is the workhorse of various scientific domains but is
limited by high computational cost. Learning-based force fields have made major progress …

An equivariant generative framework for molecular graph-structure co-design

Z Zhang, Q Liu, CK Lee, CY Hsieh, E Chen - Chemical Science, 2023 - pubs.rsc.org
Designing molecules with desirable physiochemical properties and functionalities is a long-
standing challenge in chemistry, material science, and drug discovery. Recently, machine …

Simulation and machine learning methods for ion-channel structure determination, mechanistic studies and drug design

Z Zhu, Z Deng, Q Wang, Y Wang, D Zhang… - Frontiers in …, 2022 - frontiersin.org
Ion channels are expressed in almost all living cells, controlling the in-and-out
communications, making them ideal drug targets, especially for central nervous system …