This is a repository of Phong to archive his codes and useful files used in his thesis and his recent projects in the field of cheminformatics and health informatics. In this repository, you may find some useful codes used in his projects:

1. GROMACS mdp files used in molecular dynamics simulations (MDs) used in his two publications
2. Python notebooks used to visuallise the data in his publications
3. Python notebooks used to mine the data and group the same flavonoid structures used in a systematic review (Repository)
4. Python notebooks used to train machine learning models in predicting susceptibility of microbials derived from impatients in a hospital in HoChiMinh City against different types of antimicrobials (In process, writing)

I am a pharmacist interested in computer-aided drug design using both in-silico approaches and in-vitro approaches to evaluate the computer-based predictions. My research interests include, but are not limited to metabolism-related syndromes, cardiovascular diseases and auto-inflammatory diseases. My graduation thesis is about finding small molecules that can inhibit the interleukin-33/ST2 axis, which is involved in pathology of inflammatory, infectious, and autoimmune diseases, using different in-silico methods such as homology modelling, molecular docking, molecular dynamics simulations. Additionally, I am also involved in synthesizing and purifying the IL-33 protein and using fluorescent spectroscopy to evaluate the binding affinity of screened compounds.

ResearchGate: https://www.researchgate.net/profile/Thua_Phong_Lam

Scholar: https://scholar.google.com/citations?user=6cgYvfIAAAAJ

1. Discovery of IL-33/ST2 small molecule inhibitors (In process https://sites.google.com/site/il33iproject/)
2. Discovery the inhibitory activity of in-house chalcones against SARS-Cov-2 Main protease (https://doi.org/10.1007/s11224-022-02000-3)
3. Repurposing commercial drugs against the infusion stage of monkeypox virus (https://doi.org/10.3390/ijms231911570)
4. Discovery the inhibitory activity of flavonoid compounds against α-glucosidase and α-amylase in the treatment of diabetes mellitus (https://doi.org/10.1007/s11030-023-10680-0)
5. Prediction of antibiotic resistance in hospitalized patients using machine learning algorithms from medical record data (In process)

If you find my notebooks useful in your research, consider citing us in our most recent publications:

Mai TT, Phan MH, Thai TT, Lam T-P, et al. Discovery of novel flavonoid derivatives as potential dual inhibitors against α-glucosidase and α-amylase: virtual screening, synthesis, and biological evaluation. Molecular diversity. 2023; https://doi.org/10.1007/s11030-023-10680-0

Lam T-P, Tran V-H, Mai TT, Lai NV-T, Dang B-TN, Le M-T, Tran T-D, Trinh D-TT, Thai K-M. Identification of Diosmin and Flavin Adenine Dinucleotide as Repurposing Treatments for Monkeypox Virus: A Computational Study. International Journal of Molecular Sciences. 2022; 23(19):11570. https://doi.org/10.3390/ijms231911570

Also consider my first publication about SARS-CoV-2:

Lam, TP., Nguyen, DN., Mai, T.T. et al. Exploration of chalcones as 3-chymotrypsin-like protease (3CLpro) inhibitors of SARS-CoV-2 using computational approaches. Structural Chemistry 33, 1707–1725 (2022). https://doi.org/10.1007/s11224-022-02000-3