Nguyen, Duc D

Nguyen Lab – A&S, Mathematics

Research Overview

Drug discovery is one of the most challenging tasks in the biological sciences since it requires over 10 years and costs more than $2.6 billion to put an average novel medicine on the marketplace. The abundant availability of biological data along with the flourishing advanced AI algorithms opens a future with great hope for discovering new drugs faster and cheaper. Unfortunately, AI faces an enormous obstacle in drug discovery due to the intricate complexity of biomolecular structures and the high dimensionality of biological datasets. In our lab,  these challenges will be tackled mathematically. We will develop multiscale modeling, differential geometry, algebraic topology, and graph theory-based models to systematically represent the diverse biological datasets in the low-dimensional spaces. Combining these mathematical representations with cutting edge deep neural networks, we hope to arrive at novel models not only perform well on virtual-screening targeting important drug properties but also have the ability to design new drugs at an unprecedented speed.

COVID-19 Drug Repositioning

Description:  

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 31.7 million people and led to over 972 thousand deaths as of September 23rd, 2020. Up to now, there are no effective drugs against COVID-19. Some promising vaccines have been undergoing the Phase 3 Clinical Trails but their safety and efficacy to the human body are still in doubt. Drug repositioning is regarded as the most feasible and fastest way to fight this deadly disease. In this project, we will develop robust mathematical-based scoring functions to reliably rank the binding affinity of nearly 8000 drugs available on DrugBank as well as more than 100 million compounds from SciFinder.

Computational methods:

Persistent graph theory, persistent homology, differential geometry, CNN, LSTM, transformers,  decision tree-based models

Software:

Python

Keras

Tensorflow

VMD

Amber with GPU support

NAMD, NCBI BLAST

Schrodinger

Gaussian 16

Matlab

R

C++

Fortran

Students:

MD Masud Rana, Added 07/14/2021

Avery E Meyer, Added 05/31/2022 on LCC

Benjamin A Philpot, Added 05/31/2022 on LCC

Farjana Tasnim Mukta, Added 05/31/2022 on LCC

Edison Mucllari, Graduate, Added 08/09/2022 on LCC

Grants:

Publications: