Karl Mounguele

Computational Bioinformatician | Molecular Docking · NGS · Python · Drug Discovery

Biotechnology and Bioinformatics Engineer (Master's degree), I design computational pipelines to accelerate the discovery of drug candidates and the analysis of large-scale genomic data.

My area of expertise is structural bioinformatics: virtual screening, molecular docking (AutoDock Vina, AutoDock4), ADMET analysis, and structural visualization (PyMOL, ChimeraX, Discovery Studio). In parallel, I develop complete NGS pipelines—from quality control (FastQC, Trimmomatic) to variant calling (BWA, GATK)—as well as Python automation scripts to optimize bioinformatics workflows.

Representative recent project: virtual screening campaign of 100 natural compounds (ZINC Natural Products) against the HIV-1 p24 capsid protein (PDB: 4XFX). Best hit identified: CNP0013909.3 at −8.99 kcal/mol, validated by complete ADMET analysis via SwissADME and tunnel analysis via CAVER Web.

Founder of GenoLabGab, an independent computational biology initiative with a scientific blog and documented GitHub repositories—reflecting my commitment to open and reproducible science.

Available for 100% remote missions. Whether for virtual screening, NGS analysis, a custom pipeline, or training, let's talk about your project.