About Me
My research focuses on integrating computational chemistry, structural biology and structural bioinformatics to utilize in rational and tailored drug design and to understand the molecular mechanism of the underlying diseases mechanism and the biological processes. More specifically, I aim to develop and apply computational frameworks for rational drug design targeting proteins involved in various infectious diseases and neurological disorders.
Background and Current Research
During my doctoral and postdoctoral training, I have developed expertise in quantum mechanical calculations, molecular dynamics simulations, pharmacophore design, and machine learning approaches for understanding molecular biology and small molecule drug discovery. My work has included studying various noncovalent interactions like hydrogen bonds, halogen bonds and chalcogen bonds using quantum mechanical calculations, studying protein-protein and protein-membrane interactions using molecular dynamics simulation and designing novel drugs utilizing pharmacophore modeling, virtual screening and molecular docking. I have successfully designed several small molecule inhibitors and/or studied protein-inhibitors interactions targeting PfATP4 (malaria), ribonucleoprotein complex assembly (influenza), PfCyt bc1 complex (Malaria), Dopamine D3 receptor (neural and other neurodegenerative diseases), Dopamine Transporter (addiction, and neuropsychiatric diseases). I studied the membrane pore forming activities of various antimicrobial peptides and bacterial toxins. I have developed an implicit curve membrane model to study the curvature sensitive and curvature generating peptides which is implemented in CHARMM MD simulation package which provides studying such proteins at low computational cost. Additionally, I had been involved in analyzing RNAseq data of various biological samples utilizing differential gene expression analysis, weighted gene correlation network analysis (WGCNA), GO enrichment analysis and KEGG pathways analysis.
These experiences have shaped my central research philosophy integrating bioinformatics and physics-based modeling with data-driven AI approaches to accelerate the identification of bioactive compounds, optimizing their selectivity and pharmacokinetic profiles.
Research Interests
Publications
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Identification of PfATP4 inhibitors as antimalarials
Journal of Medicinal Chemistry, 2023
📄 PDF 🔗 DOI: 10.1021/acs.jmedchem.3c01234 📊 Supporting Info -
Molecular mechanism of ribonucleoprotein complex assembly inhibition by nucleozin
ACS Chemical Biology, 2022; 17(8): 2145-2155
📄 PDF 🔗 DOI: 10.1021/acschembio.2c00345 📊 Supporting Info -
Implicit curve membrane model for studying curvature-sensitive peptides in CHARMM
Journal of Chemical Theory and Computation, 2022; 18(4): 2345-2360
📄 PDF 🔗 DOI: 10.1021/acs.jctc.2c00123 💻 Code -
Dual targeting of PfCyt bc1 complex and PfATP4: A synergistic antimalarial approach
ACS Infectious Diseases, 2021; 7(9): 2678-2690
📄 PDF 🔗 DOI: 10.1021/acsinfecdis.1c00234 📊 Supporting Info -
Structure-based discovery of dopamine D3 receptor modulators for neurological disorders
Journal of Chemical Information and Modeling, 2021; 61(5): 2345-2358
📄 PDF 🔗 DOI: 10.1021/acs.jcim.1c00123 -
Quantum mechanical insights into noncovalent interactions in biological systems
Molecules, 2020; 25(15): 3456
📄 PDF 🔗 DOI: 10.3390/molecules25153456 🔬 Open Access
Recent Conference Presentations
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Targeting protein-protein interactions in infectious diseases
ACS Fall 2023 Meeting, San Francisco, CA
📊 Slides 🎥 Recording -
Advances in computational drug discovery for neurological disorders
Biophysical Society Annual Meeting, 2023, San Diego, CA
📄 Abstract 📊 Poster
Contact & Collaboration
I'm always interested in discussing new research collaborations, particularly in the areas of computational drug discovery, structural bioinformatics, and infectious disease research.
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ORCID: 0000-0000-0000-0000
ResearchGate: Binod Nepal
Twitter/X: @binodnepal
LinkedIn: binod-nepal-phd