Enhanced sampling with machine learning
Molecular dynamics (MD) enables the study of physical systems with excellent
spatiotemporal resolution but suffers from severe timescale limitations. To address this …
spatiotemporal resolution but suffers from severe timescale limitations. To address this …
Open-source machine learning in computational chemistry
A Hagg, KN Kirschner - Journal of Chemical Information and …, 2023 - ACS Publications
The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …
Alphafold2-rave: From sequence to boltzmann ranking
While AlphaFold2 is rapidly being adopted as a new standard in protein structure
predictions, it is limited to single structures. This can be insufficient for the inherently …
predictions, it is limited to single structures. This can be insufficient for the inherently …
Driving and characterizing nucleation of urea and glycine polymorphs in water
Z Zou, ER Beyerle, ST Tsai… - Proceedings of the …, 2023 - National Acad Sciences
Crystal nucleation is relevant across the domains of fundamental and applied sciences.
However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial …
However, in many cases, its mechanism remains unclear due to a lack of temporal or spatial …
Attention-based generative models for de novo molecular design
Attention mechanisms have led to many breakthroughs in sequential data modeling but
have yet to be incorporated into any generative algorithms for molecular design. Here we …
have yet to be incorporated into any generative algorithms for molecular design. Here we …
Thermodynamics-inspired explanations of artificial intelligence
In recent years, predictive machine learning models have gained prominence across
various scientific domains. However, their black-box nature necessitates establishing trust in …
various scientific domains. However, their black-box nature necessitates establishing trust in …
An efficient path classification algorithm based on variational autoencoder to identify metastable path channels for complex conformational changes
Conformational changes (ie, dynamic transitions between pairs of conformational states)
play important roles in many chemical and biological processes. Constructing the Markov …
play important roles in many chemical and biological processes. Constructing the Markov …
Exploring kinase asp-phe-gly (dfg) loop conformational stability with alphafold2-rave
Kinases compose one of the largest fractions of the human proteome, and their misfunction
is implicated in many diseases, in particular, cancers. The ubiquitousness and structural …
is implicated in many diseases, in particular, cancers. The ubiquitousness and structural …
Exploring and learning the universe of protein allostery using artificial intelligence augmented biophysical and computational approaches
Allosteric mechanisms are commonly employed regulatory tools used by proteins to
orchestrate complex biochemical processes and control communications in cells. The …
orchestrate complex biochemical processes and control communications in cells. The …
Accelerating all-atom simulations and gaining mechanistic understanding of biophysical systems through state predictive information bottleneck
An effective implementation of enhanced sampling algorithms for molecular dynamics
simulations requires a priori knowledge of the approximate reaction coordinate describing …
simulations requires a priori knowledge of the approximate reaction coordinate describing …