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PhD Research · Computational Biology · Drug Discovery

Research Skills

Bioinformatics & Wet Lab competencies from doctoral research

Research Focus

Bridging computational and experimental cancer research — from AI-driven drug discovery pipelines (SieveAI) and molecular dynamics simulations (coarse-grain MARTINI for membranes, atomistic CHARMM36 for proteins) to cell-based validation assays. Specializing in protein-ligand docking, protein-protein interactions, structure prediction (AlphaFold2, SwissModel, I-TASSER, Rosetta), MMPBSA binding free energy, and exosomal miRNA analysis. Automated workflows from PDB preparation through docking, MD, and result extraction — reducing months of manual work to hours.

Bioinformatics & Computational Biology

Computational drug discovery, molecular dynamics, genomics data analysis, and pipeline development. Built and published multiple open-source tools.

Molecular Docking

Molecular docking to predict drug-target binding — used AutoDock Vina, SwissDock, and PATCHDOCK to screen thousands of compounds and identify potential therapeutic candidates for cancer targets like CXCL9/10 and SKP2.

  • AutoDock Vina — batch protein-ligand docking (1,950+ complexes)
  • Protein-protein docking — HADDOCK, pyDockWeb, PatchDock, ClusPro
  • Protein-protein interaction — CD151 cholesterol binding, TWIST1-OGT/OGase, survivin-caspase complexes
  • Protein-complex docking — ternary systems (survivin + OBPHA + caspase-3/7/9)
  • Peptide-peptide docking — TWIST1-OGT/OGase interactions
  • Ligand preparation — AutoDockTools, OpenBabel, PubChemPy 3D SDF, SwissParam topology
  • Post-docking analysis — ChimeraX H-bond/contact automation, PLIP, PRODIGY
  • Cancer targets — CXCL9/10, SKP2, PPARγ, BRCA1, GRK2, CD63-VEGF, p53, Bcl-2, PDGFR
  • DrugBank & FDA drug screening — 8K+ conformers, immune checkpoints (CD28, TIGIT, PD-1)

Molecular Dynamics

Molecular dynamics simulations with GROMACS and WebGro to study protein stability, ligand binding trajectories, and conformational changes over nanosecond timescales — critical for validating docking predictions.

  • GROMACS — full MD pipeline (pdb2gmx, editconf, solvate, genion, grompp, mdrun) up to 300ns
  • Coarse-grain MD — MARTINI force field for lipid–ligand membrane systems (Lapatinib/DMPC/cholesterol)
  • Atomistic MD — CHARMM36 force field for protein–ligand complexes; AMBER/CHARMM36 for membranes
  • CHARMM-GUI membrane builder — DMPC, DOPC, DOPS, cholesterol bilayer preparation & embedding
  • Desmond MD — local installation & WebGro cloud submission, trajectory analysis
  • MMPBSA — gmx_MMPBSA binding free energy calculations (300ns trajectories)
  • RMSD / RMSF / Rg / SASA / DSSP — protein stability, secondary structure, solvent analysis
  • SwissParam & PRODRG — ligand topology/ITP generation for GROMACS CHARMM force field
  • GMXvg — published GROMACS visualization & plotting tool

Protein Structure Prediction

Protein structure prediction with AlphaFold2 via Google Colab — modeling complexes like IL27, CD151, and CD63 for structural and functional characterization.

  • AlphaFold2 — protein structure prediction via Google Colab (IL27 complex, CD151, CD63)
  • SwissModel — homology modeling + QA (quality assessment) for mutant proteins (3EQH-ALA76GLY)
  • I-TASSER — 3D structure prediction for membrane & transmembrane proteins
  • Rosetta — protein structure prediction and design
  • Avogadro — energy minimization of small molecules & ligand 3D optimization
  • Protein structure comparison — ChimeraX Matchmaker (RMSD, primary/secondary/tertiary structure)
  • PDB processing — UniProt mapping, PDBTM for transmembrane, chain cleanup, HETATM separation
  • O-GlcNAcylation site prediction — YinOYang, dbPTM, PhosphoSitePlus for GRK2 sites (S20, S121, S370)
  • Membrane protein resources — PDBTM, TMDock, MemProtMD, PerMemDB, MBPpred, ProteinTools

Genomics & Transcriptomics

Mining GEO datasets with GEOParse, analyzing RNA-Seq and ncRNA expression profiles, performing pathway enrichment and GO annotation to identify dysregulated genes and regulatory networks in cancer.

  • GEO dataset mining — GEOParse querying, GDS database search, sample/platform/series filtering (GSE15852, GSE73002, GSE77348)
  • Differential gene expression — PyDGE framework, MCF7 vs MCF10A, normal vs tumor expression analysis
  • TCGA cancer genomics — GDC portal data download (gdc-client), TCGA-BRCA miRNA-seq, TNBC cohort filtering, sample type codes
  • miRNA database consolidation — miRBase (2,693 mature), ExoCarta, EVmiRNA, miRCancer cross-referencing & Venn analysis
  • miRNA target prediction — TargetScan, miRDB, DIANA, miRWalk, miRTarBase validated targets
  • Exosomal miRNA analysis — miR-34a, miR-10b, miR-21, miR-9; ExoLoger prediction database
  • ncRNA analysis — lncRNA, circRNA, siRNA, piRNA; RNAComposer, UNAFold, MXfold2 for 3D structure
  • Pathway & network analysis — KEGG (KEGGScape), WikiPathways, Biocarta, STRING interaction networks, FunRich enrichment
  • NCBI/Entrez queries — PubMed search, GDS metadata extraction, Gene database cross-referencing
  • Cancer gene resources — IntOGen (BRCA driver genes), cBioPortal, OncoKB, COSMIC, CancerES (IIITD)
  • PTM databases — dbPTM, PhosphoSitePlus, O-GlcNAc (oglcnac.mcw.edu), VerSeDa

Pipeline Development

Built SieveAI, an automated drug discovery pipeline that orchestrates screening, docking, and scoring in batch — reducing months of manual work to hours. Published and open-sourced with Zenodo DOI.

  • SieveAI — end-to-end automated drug discovery pipeline: PDB prep → ligand prep → docking → result extraction → filtering
  • Bulk docking automation — 576 cancer genes × 5 ligands = 1,950+ complexes; 9,127 Vina results parsed & filtered
  • DrugBank high-throughput screening — GRK2 (3,894 complexes ~60h compute), immune checkpoints (8K+ conformers)
  • Automated PDB processing — Python scripts for ATOM/HETATM separation, chain cleanup, grid box calculation, PDBQT conversion
  • Bulk ligand preparation — AutoDockTools prepare_ligand4.py, OpenBabel batch PDB→SDF→SMILES, PubChemPy 3D SDF download
  • Automated result extraction — Vina score parsing, ChimeraX H-bond/contact command generation, best-pose selection by residue interaction
  • SwissADME bulk — automated SMILES submission, ADME radar scraping, property aggregation across 88+ compounds
  • MDDAA-Mate — docking analysis assistant for validation & cross-checking against published results

Scientific Web Scraping

Developed custom scraping frameworks for PubMed literature mining, extracting structured data from thousands of abstracts and scientific web sources for meta-analysis and systematic reviews.

  • PubMed querying & full-text mining — biopubmed CLI tool
  • Scientific literature meta-analysis — systematic review automation
  • Web scraping framework (Scrapper) — GEO, DrugBank, UniProt, ZINC, PubChem data extraction
  • API integration — PubChemPy 3D SDF download, RCSB ligand fetch, KEGG KGML pathway
  • miR literature curation — exosomal miR article classification & filtering

NLP & Text Mining

Biomedical NLP for named entity recognition and keyword co-occurrence analysis from research abstracts — enabling automated literature synthesis and hypothesis generation from large corpuses.

  • Biomedical NLP — keyword co-occurrence, named entity recognition, spaCy POS/lemma extraction
  • Text mining — structured extraction from thousands of PubMed results
  • Exosomal miR prediction — NLP + clustering for unvalidated miR identification
  • Regex-based data extraction — SMILES conversion, gene ID mapping, UniProt batch queries

Deep Learning & Classification

Deep neural networks for metabolite classification using SMILES/SMARTS fingerprinting, complemented by Random Forest, SVM, and XGBoost models with rigorous evaluation (AUC, F1, MCC).

  • DNN for metabolite classification — SMILES/SMARTS fingerprinting
  • Random Forest / SVM / XGBoost — cancer gene expression classifiers
  • Model evaluation — AUC, F1, MCC metrics
  • PCA & one-hot encoding — miRNA sequence analysis & dimensionality reduction

Computational Software

Authored and published computational software tools — SieveAI (drug discovery), ExoLoger (exosomal miRNA prediction), GMXvg (GROMACS visualization, Zenodo DOI), miRvim (3D miRNA structure database), and UtilityLib (Python utilities, Zenodo DOI).

  • SieveAI — automated drug discovery pipeline
  • ExoLoger — exosomal miRNA prediction database
  • GMXvg — GROMACS visualization & plotting
  • miRVim — 3D miRNA structure database
  • UtilityLib — Python utility library (PyPI v2.21.4)
  • TheBiomics — Drupal education platform (17K+ users)
  • biopubmed — PubMed scraping & processing CLI
  • Scrapper — scientific web data extraction framework
  • MDDAA-Mate — docking analysis assistant & validation tool
  • PyDGE — differential gene expression analysis framework

Wet Lab & Experimental Biology

Hands-on experience in cell culture, molecular biology assays, protein work, and in vitro studies across cancer biology and pharmacology.

Cell Culture & Maintenance

Maintained mammalian cell lines (MG63, MCF7, MM231, LN229) with strict aseptic technique — cryopreservation, sub-culturing, passaging, transfection optimization, and mycoplasma testing.

  • Mammalian cell culture — MG63, MCF7, MDA-MB-231, LN229, A549
  • Animal cell culture — aseptic technique, laminar flow hood, CO₂ incubator operation
  • Cell line maintenance — sub-culturing, passaging, cell counting (hemocytometer), viability assessment
  • Cryopreservation — liquid nitrogen storage, freeze-thaw recovery, DMSO cryoprotectant protocols
  • Transfection optimization — lipid-based and electroporation methods
  • Mycoplasma testing & contamination control
  • Cancer cell to adipocyte differentiation (PPARγ agonist studies)

Protein Estimation & Assays

Protein quantification (Bradford, BCA), separation and detection via SDS-PAGE and Western blotting, and interaction studies with ELISA and co-immunoprecipitation.

  • Protein estimation — Bradford & BCA assay (standard curve preparation)
  • SDS-PAGE & Western blotting — Vimentin, target protein detection
  • Wet blot transfer — tank transfer system for protein membrane immobilization
  • Dry blot transfer — semi-dry transfer for rapid protein detection
  • Gel Doc imaging — documentation & analysis of electrophoresis gels and blots
  • ELISA — quantitative protein interaction analysis
  • Co-immunoprecipitation — protein-protein interaction validation
  • A280 protein quantification

Molecular Biology Techniques

Standard molecular biology workflow — RNA extraction with TRIzol, cDNA synthesis, qPCR/RT-PCR for gene expression, agarose gel electrophoresis, and plasmid isolation with cloning and primer design.

  • RNA extraction — TRIzol method
  • cDNA synthesis & gene expression analysis
  • RT-PCR & qPCR — reverse transcription, quantitative expression profiling
  • Agarose gel electrophoresis — nucleic acid separation & Gel Doc visualization
  • Plasmid isolation, cloning & primer design
  • Competent cell transformation

In Vitro Studies

Cell-based assays for drug screening — MTT/XTT viability, colony formation, wound healing migration, invasion assays, apoptosis detection (Annexin V), and drug combination synergy (CI index).

  • MTT & XTT viability assays — dose-response drug screening, IC₅₀ determination
  • Colony formation assay — clonogenic survival quantification
  • Wound healing migration assay — scratch assay for cell motility
  • Invasion assays — transwell migration & Matrigel invasion
  • Apoptosis detection — Annexin V / PI staining
  • Drug combination synergy — Combination Index (CI) method
  • Cancer cell vs normal cell comparative studies

Laboratory Instruments

Hands-on operation of laboratory instruments — gel documentation systems, blot imaging, and densitometry analysis for protein and nucleic acid work.

  • Gel Doc system — gel documentation, blot imaging & densitometry analysis
  • CO₂ incubator — mammalian cell culture environment control
  • Laminar flow hood — aseptic technique & sterile workspace
  • Microplate reader — absorbance/fluorescence for MTT, Bradford, BCA, ELISA
  • Centrifuge — refrigerated & bench-top, cell pelleting, fractionation
  • PCR thermal cycler — RT-PCR & qPCR amplification
  • Electrophoresis apparatus — vertical SDS-PAGE & horizontal agarose gel
  • Wet & dry blot transfer systems — tank & semi-dry protein transfer
  • HPLC system — basic operation & familiarization with analytical chromatography devices

Chromatography & HPLC

HPLC operation and method development for compound identification and purity analysis, along with column and thin-layer chromatography techniques.

  • Chromatography basics — column, thin-layer & basic HPLC familiarization
  • Column & thin-layer chromatography
  • Standard curve & peak integration