activity
20172026
most citedRecent developments in the PySCF program package

1.2k citations · 1.3k across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

TerraBind: Fast and Accurate Binding Affinity Prediction through Coarse Structural Representations

Matteo Rossi, Ryan Pederson, Miles Wang-Henderson +8

We present TerraBind, a foundation model for protein-ligand structure and binding affinity prediction that achieves 26-fold faster inference than state-of-the-art methods while imp…

cs.LG2025

Pretrained Joint Predictions for Scalable Batch Bayesian Optimization of Molecular Designs

Miles Wang-Henderson, Benjamin Kaufman, Edward Williams +6

Batched synthesis and testing of molecular designs is the key bottleneck of drug development. There has been great interest in leveraging biomolecular foundation models as surrogat…

physics.chem-ph2020★ 4 cited

Novel algorithms and high-performance cloud computing enable efficient fully quantum mechanical protein-ligand scoring

Narbe Mardirossian, Yuhang Wang, David A. Pearlman +2

Ranking the binding of small molecules to protein receptors through physics-based computation remains challenging. Though inroads have been made using free energy methods, these fa…

physics.chem-ph2020★ 1.2k cited

Recent developments in the PySCF program package

Qiming Sun, Xing Zhang, Samragni Banerjee +46

PYSCF is a Python-based general-purpose electronic structure platform that both supports first-principles simulations of molecules and solids, as well as accelerates the developmen…

physics.chem-ph2017★ 32 cited

Lowering of the complexity of quantum chemistry methods by choice of representation

Narbe Mardirossian, James D. McClain, Garnet Kin-Lic Chan

The complexity of the standard hierarchy of quantum chemistry methods is not invariant to the choice of representation. This work explores how the scaling of common quantum chemist…