Distortion/interaction analysis via machine learning
SG Espley, SS Allsop, D Buttar, S Tomasi… - Digital …, 2024 - pubs.rsc.org
Machine learning (ML) models have provided a highly efficient pathway to quantum
mechanical accurate reaction barrier predictions. Previous approaches have, however …
mechanical accurate reaction barrier predictions. Previous approaches have, however …
CLIPZyme: Reaction-Conditioned Virtual Screening of Enzymes
PG Mikhael, I Chinn, R Barzilay - arXiv preprint arXiv:2402.06748, 2024 - arxiv.org
Computational screening of naturally occurring proteins has the potential to identify efficient
catalysts among the hundreds of millions of sequences that remain uncharacterized. Current …
catalysts among the hundreds of millions of sequences that remain uncharacterized. Current …
Integer linear programming for unsupervised training set selection in molecular machine learning
M Haeberle, P van Gerwen, R Laplaza… - arXiv preprint arXiv …, 2024 - arxiv.org
Integer linear programming (ILP) is an elegant approach to solve linear optimization
problems, naturally described using integer decision variables. Within the context of physics …
problems, naturally described using integer decision variables. Within the context of physics …
Challenges and Opportunities for Machine Learning Potentials in Transition Path Sampling: Alanine Dipeptide and Azobenzene Studies
The growing interest in machine learning (ML) tools within chemistry and material science
stems from their novelty and ability to predict properties almost as accurately as underlying …
stems from their novelty and ability to predict properties almost as accurately as underlying …
Towards Deep Learning Models of Metabolism
I Chinn - 2024 - dspace.mit.edu
Enzymes play a critical role in catalyzing the chemical reactions that underpin metabolic
processes in living organisms. Despite their importance, a vast majority of enzymes remain …
processes in living organisms. Despite their importance, a vast majority of enzymes remain …