Available for research collaborations
REVANTH NAIDU REVANTH NAIDU REVANTH NAIDU REVANTH NAIDU
Revanth Naidu
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0 Projects Completed
0+ MD Simulations
0 Publication
Bioinformatics Molecular Dynamics Python Drug Discovery GROMACS AutoDock Vina Structural Biology MMPBSA RNA-seq Barcelona Bioinformatics Molecular Dynamics Python Drug Discovery GROMACS AutoDock Vina Structural Biology MMGBSA RNA-seq Barcelona

The Story So Far

RN
LocationBarcelona, Spain
Emailnaidurevanth2003@gmail.com
GitHubgithub.com/naidurev
ORCID0009-0009-6851-7640
Phone+34 671 326 02

I'm Revanth — a bioinformatician with experience in protein structure prediction, molecular dynamics simulations, and computational drug design.

Currently pursuing my MSc in Bioinformatics for Health Sciences at Universitat Pompeu Fabra & Universitat de Barcelona, with coursework in Structural Bioinformatics, Computer-Assisted Drug Discovery, Data Mining & Intelligence, and Databases and Web Design.

From building POPC membrane simulations with CHARMM-GUI to running full RNA-seq pipelines, I turn biological questions into computational answers.

2025 – 2027
MSc Bioinformatics for Health Sciences
UPF / UB · Barcelona, Spain
Structural Bioinformatics · Computer-Assisted Drug Discovery · Data Mining & Intelligence · Databases and Web Design
2021 – 2024
BSc (Hons) Biotechnology — First Division with Distinction
Amity University Mumbai · CGPA 9.14 / 10

Technical Skills

Molecular Dynamics

GROMACSCHARMM-GUISchrodinger MaestroDesmondNAMDAMBERMMPBSAMMGBSA

Docking & Structure

AutoDock VinaGOLDMMPBSAMMGBSAModellerI-TASSERPyMOLChimeraXSwiss-PdbViewer

NGS & Genomics

FastQCTrimmomaticBowtie2BWASAMtoolsMACS2DESeq2MAFFTIQ-TREEOrthoFinderHOMERBLASTClustal OmegaMEGA

Programming

PythonFlaskPandasNumPyBiopythonMatplotlib Rggplot2Bioconductordplyr OtherBashGit / GitHub

Laboratory

DNA IsolationPCRPAGECell CultureUV SpectrophotometryEnzyme Assays

Research Journey

Jun 2024 – Aug 2025 Research
Research Assistant
AiSense Laboratory · Mumbai, India
  • Built a fragment-based protein structure prediction pipeline targeting CAV2.2; benchmarked against experimental reference structures using Ramachandran plots, Z-scores, cross-correlation plots, and PCA.
  • Set up a POPC membrane simulation of CAV2.2 using CHARMM-GUI; ran MD trajectories in GROMACS and analysed RMSD, RMSF, lipid-protein contacts, and MMPBSA binding free energies.
CAV2.2CHARMM-GUIGROMACSMMPBSA
Jul 2023 – Aug 2023 Internship
Research Intern
ACTREC · Mumbai, India
  • Predicted and validated the 3D structure of HER2; Ramachandran favoured >95%, RMSD <2 Å from experimental structures.
  • Screened a large library of FDA-approved compounds against HER2 using AutoDock Vina; top candidates with binding affinity <−9.0 kcal/mol taken forward.
  • Ran MD simulations in GROMACS; RMSD, RMSF, H-bond, MMPBSA, and MMGBSA analyses performed.
  • Applied PCA to trajectory data to identify essential protein motions and conformational substates.
HER2AutoDock VinaGROMACSMMPBSAMMGBSA
Publication

Velhal K., Sah P., Raut R., Yamgar R., Naidu R., Kalra P., Barage S., Lakkakula J., Uddin I. (2025). A novel approach: inclusion complex-capped gold nanoparticles for paclitaxel delivery in triple-negative breast cancer. Medical Oncology, 42, 243.

Contribution: In silico target identification (STRING / Cytoscape), molecular docking of paclitaxel against AKT1, GAPDH, and MMP9 (AutoDock Vina), and 100 ns MD simulations (Schrodinger Maestro / Desmond).

Medical Oncology 2025 DOI: 10.1007/s12032-025-02805-2

Selected Work

01
DiseaseNet — Disease-Gene-Protein-Ligand Search Tool

Flask web application integrating KEGG, UniProt, and PubChem APIs. Parallel processing, fuzzy matching, and CSV export. Returns 100+ genes per query in under 60 seconds.

PythonFlaskKEGGUniProtPubChem
github.com/naidurev/diseasenet
02
Transcriptomic Analysis of Anti-Cancer Peptides

Full RNA-seq pipeline on Conus species data to characterise omega-conotoxin peptides. MAFFT alignment; peptide structures simulated against CAV2.2 using Schrodinger Maestro / Desmond.

RDESeq2FastQCMAFFTDesmond
03
Fragment-Based Protein Structure Prediction Pipeline

End-to-end pipeline for multi-domain protein structure prediction via fragment assembly. Validated using Ramachandran plots, Z-scores, and PCA against experimental reference structures.

PythonModellerGROMACSMMPBSA
04
MYOD1 Conservation Analysis Across Vertebrates

BLASTP, OrthoFinder ortholog clustering, and MAFFT alignment across 12 vertebrate species. Maximum-likelihood phylogenetic tree built with IQ-TREE.

BLASTPOrthoFinderMAFFTIQ-TREE
05
ChIP-seq Binding Site Analysis

Full ChIP-seq pipeline: FastQC, Bowtie2 alignment, MACS2 peak calling, and HOMER transcription factor motif enrichment analysis.

FastQCBowtie2MACS2HOMER

Course Projects

Group and individual projects developed for the Design of Biomedical Websites course (UPF & UB, 2025–26).

DiseaseNet

Disease–Gene–Protein–Ligand search tool. Flask web app integrating KEGG, UniProt, and PubChem APIs with parallel processing and CSV export.

Python Flask KEGG UniProt
ClustalOmega Web App

Multiple sequence alignment web interface. Accepts FASTA text, UniProt IDs, PDB IDs, or file upload. Supports Clustal, FASTA, and Phylip output formats.

Python Flask ClustalOmega
Hospital Clinical Trials Data Model

Relational database schema for pseudonymised clinical trial participants, longitudinal measurements, and role-based access control. ER diagram and MySQL implementation.

MySQL ER Diagram SQL

Solved Exercises

Individual deliverables completed for the DBW course.

01
ClustalOmega Web App

Multiple sequence alignment tool built with Flask and ClustalOmega. Accepts FASTA text, UniProt IDs, PDB IDs, and file uploads. Outputs alignment in Clustal, FASTA, or Phylip format.

Python Flask ClustalOmega BioPython
02
Hospital Clinical Trials Data Model

Relational data model for a hospital clinical trials system. Covers pseudonymised participants, longitudinal data (items & files), variable definitions, and role-based access. Delivered as an ER diagram and MySQL schema.

MySQL ER Diagram SQL Data Modelling

Get In Touch

Open to research collaborations, internship opportunities, and discussions around structural bioinformatics, drug discovery, or NGS analysis.