FFLUX: Transferability of polarizable machine-learned electrostatics in peptide chains

Partitioning dynamic electron correlation energy: Viewing Møller-Plesset correlation energies through Interacting Quantum Atom (IQA) energy partitioning

(2016) James L. McDonagh et al.   CHEMICAL PHYSICS LETTERS

Multipolar Electrostatic Energy Prediction for all 20 Natural Amino Acids Using Kriging Machine Learning

(2016) Timothy L. Fletcher et al.   Journal of Chemical Theory and Computation

Optimization Algorithms in Optimal Predictions of Atomistic Properties by Kriging

(2016) Nicodemo Di Pasquale et al.   Journal of Chemical Theory and Computation

FEREBUS: Highly parallelized engine for kriging training

(2016) Nicodemo Di Pasquale et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Toward amino acid typing for proteins in FFLUX

(2016) Timothy L. Fletcher et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Molecular simulation by knowledgeable quantum atoms

(2016) Paul L A Popelier   PHYSICA SCRIPTA

Extension of the interacting quantum atoms (IQA) approach to B3LYP level density functional theory (DFT)

(2016) Peter Maxwell et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

QCTFF: On the construction of a novel protein force field

(2015) Paul L. A. Popelier   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Structural Ensembles of Intrinsically Disordered Proteins Depend Strongly on Force Field: A Comparison to Experiment

(2015) Sarah Rauscher et al.   Journal of Chemical Theory and Computation

Realistic sampling of amino acid geometries for a multipolar polarizable force field

(2015) Timothy J. Hughes et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Prediction of conformationally dependent atomic multipole moments in carbohydrates

(2015) Salvatore Cardamone et al.   JOURNAL OF COMPUTATIONAL CHEMISTRY

Transferable atoms: an intra-atomic perspective through the study of homogeneous oligopeptides

(2015) Peter Maxwell et al.   MOLECULAR PHYSICS

Transferable kriging machine learning models for the multipolar electrostatics of helical deca-alanine

(2015) Timothy L. Fletcher et al.   THEORETICAL CHEMISTRY ACCOUNTS

Multipolar electrostatics

(2014) Salvatore Cardamone et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Polarisable multipolar electrostatics from the machine learning method Kriging: an application to alanine

(2012) Matthew J. L. Mills et al.   THEORETICAL CHEMISTRY ACCOUNTS

Polarizable Atomic Multipole-Based Molecular Mechanics for Organic Molecules

(2011) Pengyu Ren et al.   Journal of Chemical Theory and Computation

Intramolecular polarisable multipolar electrostatics from the machine learning method Kriging

(2011) Matthew J.L. Mills et al.   Computational and Theoretical Chemistry

Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning

(2009) Chris M. Handley et al.   Journal of Chemical Theory and Computation

Beyond Point Charges: Dynamic Polarization from Neural Net Predicted Multipole Moments

(2008) Michael G. Darley et al.   Journal of Chemical Theory and Computation