Recently, machine learning (ML) has established itself in various worldwide benchmarking
competitions in computational biology, including Critical Assessment of Structure Prediction …

We present the performances of our mathematical deep learning (MathDL) models for D3R
Grand Challenge 4 (GC4). This challenge involves pose prediction, affinity ranking, and free …

This work presents a few variational multiscale models for charge transport in complex
physical, chemical, and biological systems and engineering devices, such as fuel cells, solar …

Motivation: Despite its great success in various physical modeling, differential geometry
(DG) has rarely been devised as a versatile tool for analyzing large, diverse, and complex …

Geometric, topological and graph theory modeling and analysis of biomolecules are of
essential importance in the conceptualization of molecular structure, function, dynamics, and …

Molecular surface representations have been advertised as a great tool to study protein
structure and functions, including protein–ligand binding affinity modeling. However, the …

This work extends our earlier two-domain formulation of a differential geometry based
multiscale paradigm into a multidomain theory, which endows us the ability to …

The molecular mechanism of ion channel gating and substrate modulation is elusive for
many voltage gated ion channels, such as eukaryotic sodium ones. The understanding of …

In this work, we propose a new Poisson–Nernst–Planck (PNP) model with ion–water
interactions for biological charge transport in ion channels. Due to narrow geometries of …

As a key process of many biological reactions such as biological energy transduction or
human sensory systems, proton transport has attracted much research attention in …