145 citations · 317 across the 24 of their papers we have counts for
24 papers
CRISP: Compositional Relations as Invariant Structural Priors for Domain Generalization
Dat Nguyen, Duc-Duy Nguyen
Domain generalization requires identifying stable representations that support reliable classification across domains. Domains may differ in low-level attributes, such as color, te…
Geometric Multi-color Message Passing Graph Neural Networks for Blood-brain Barrier Permeability Prediction
Trung Nguyen, Md Masud Rana, Farjana Tasnim Mukta +2
Accurate prediction of blood-brain barrier permeability (BBBP) is essential for central nervous system (CNS) drug development. While graph neural networks (GNNs) have advanced mole…
GGL-PPI: Geometric Graph Learning to Predict Mutation-Induced Binding Free Energy Changes
Md Masud Rana, Duc Duy Nguyen
Protein-protein interactions (PPIs) are critical for various biological processes, and understanding their dynamics is essential for decoding molecular mechanisms and advancing fie…
Geometric Graph Learning with Extended Atom-Types Features for Protein-Ligand Binding Affinity Prediction
Md Masud Rana, Duc Duy Nguyen
Understanding and accurately predicting protein-ligand binding affinity are essential in the drug design and discovery process. At present, machine learning-based methodologies are…
EISA-Score: Element Interactive Surface Area Score for Protein-Ligand Binding Affinity Prediction
Md Masud Rana, Duc Duy Nguyen
Molecular surface representations have been advertised as a great tool to study protein structure and functions, including protein-ligand binding affinity modeling. However, the co…
Multiscale Laplacian Learning
Ekaterina Merkurjev, Duc DUy Nguyen, Guo-Wei Wei
Machine learning methods have greatly changed science, engineering, finance, business, and other fields. Despite the tremendous accomplishments of machine learning and deep learnin…
Review of COVID-19 Antibody Therapies
Jiahui Chen, Kaifu Gao, Rui Wang +2
Under the global health emergency caused by coronavirus disease 2019 (COVID-19), efficient and specific therapies are urgently needed. Compared with traditional small-molecular dru…
Generative network complex for the automated generation of druglike molecules
Kaifu Gao, Duc D Nguyen, Meihua Tu +1
Current drug discovery is expensive and time-consuming. It remains a challenging task to create a wide variety of novel compounds with desirable pharmacological properties and chea…
Unveiling the molecular mechanism of SARS-CoV-2 main protease inhibition from 92 crystal structures
Duc D Nguyen, Kaifu Gao, Jiahui Chen +2
Currently, there is no effective antiviral drugs nor vaccine for coronavirus disease 2019 (COVID-19) caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to its hig…
Repositioning of 8565 existing drugs for COVID-19
Kaifu Gao, Duc Duy Nguyen, Jiahui Chen +2
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected near 5 million people and led to over 0.3 milli…
Persistent spectral graph
Rui Wang, Duc Duy Nguyen, Guo-Wei Wei
Persistent homology is constrained to purely topological persistence while multiscale graphs account only for geometric information. This work introduces persistent spectral theory…
A review of mathematical representations of biomolecules
Duc D Nguyen, Zixuan Cang, Guo-Wei Wei
Recently, machine learning (ML) has established itself in various worldwide benchmarking competitions in computational biology, including Critical Assessment of Structure Predictio…
Are 2D fingerprints still valuable for drug discovery?
Kaifu Gao, Duc Duy Nguyen, Vishnu Sresht +3
Recently, molecular fingerprints extracted from three-dimensional (3D) structures using advanced mathematics, such as algebraic topology, differential geometry, and graph theory ha…
Generative network complex (GNC) for drug discovery
Christopher Grow, Kaifu Gao, Duc Duy Nguyen +1
It remains a challenging task to generate a vast variety of novel compounds with desirable pharmacological properties. In this work, a generative network complex (GNC) is proposed…
MathDL: Mathematical deep learning for D3R Grand Challenge 4
Duc Duy Nguyen, Kaifu Gao, Menglun Wang +1
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 e…
Algebraic graph learning of protein-ligand binding affinity
Duc Duy Nguyen, Guo-Wei Wei
Although algebraic graph theory based models have been widely applied in physical modeling and molecular studies, they are typically incompetent in the analysis and prediction of b…
DG-GL: Differential geometry based geometric learning of molecular datasets
Duc Duy Nguyen, Guo-Wei Wei
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…
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
Duc Duy Nguyen, Zixuan Cang, Kedi Wu +3
Advanced mathematics, such as multiscale weighted colored graph and element specific persistent homology, and machine learning including deep neural networks were integrated to con…
Rigidity strengthening is a vital mechanism for protein-ligand binding
Duc Duy Nguyen, Tian Xiao, Menglun Wang +1
Protein-ligand binding is essential to almost all life processes. The understanding of protein-ligand interactions is fundamentally important to rational drug design and protein de…
Feature functional theory - binding predictor (FFT-BP) for the blind prediction of binding free energies
Bao Wang, Zhixiong Zhao, Duc D. Nguyen +1
We present a feature functional theory - binding predictor (FFT-BP) for the protein-ligand binding affinity prediction. The underpinning assumptions of FFT-BP are as follows: i) re…
Generalized flexibility-rigidity index
Duc Duy Nguyen, Kelin Xia, Guo-Wei Wei
Flexibility-rigidity index (FRI) has been developed as a robust, accurate and efficient method for macromolecular thermal fluctuation analysis and B-factor prediction. The performa…
The impact of surface area, volume, curvature and Lennard-Jones potential to solvation modeling
Duc Duy Nguyen, Guo-Wei Wei
This paper explores the impact of surface area, volume, curvature and Lennard-Jones potential on solvation free energy predictions. Rigidity surfaces are utilized to generate robus…
Accurate, robust and reliable calculations of Poisson-Boltzmann binding energies
Duc D. Nguyen, Bao Wang, Guo-wei Wei
Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimatio…
First cohomology for finite groups of Lie type: simple modules with small dominant weights
Brian D. Boe, Adrian M. Brunyate, Jon F. Carlson +12
Let be an algebraically closed field of characteristic , and let be a simple, simply connected algebraic group defined over . Given , set $q=…