N C Mg O C N Fe S H H Cl P O F
BN

Binod Nepal, PhD

Computational Chemist  ·  Structural Bioinformatician  ·  Drug Discovery Researcher

Developing computational frameworks for rational drug design

Research overview · 

👤 About Me

Target Identification MD Simulation & QM Calc. Virtual Screening ML / AI Optimization Drug Lead Discovery COMPUTATIONAL DRUG DISCOVERY PIPELINE PfATP4 · D3R · DAT Pharmacophore · Docking Malaria · Neuro · Influenza

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 & 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-inhibitor interactions targeting PfATP4 (malaria), ribonucleoprotein complex assembly (influenza), PfCyt bc1 complex (malaria), Dopamine D3 receptor (neural and other neurodegenerative diseases), and 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. Additionally, I had been involved in analyzing RNAseq data of various biological samples utilizing differential gene expression 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

Computational Chemistry Structural Biology Drug Discovery Molecular Dynamics Quantum Mechanics Machine Learning Bioinformatics Pharmacophore Modeling Virtual Screening Infectious Diseases Neurological Disorders

📄 Publications

Journal Articles  — newest first

Conference Presentations  — newest first

📰 News & Highlights

// More updates coming soon

✉️ 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.

Phone
InstitutionDrexel University College of Medicine
Google ScholarView Profile
Download CV (PDF)