Yassir Boulaamane
Postdoctoral researcher, computational drug discovery
Yassir Boulaamane is a postdoctoral researcher in the InSiliChem group at the Universitat Autònoma de Barcelona, where he works on cross-species cytochrome P450 metabolism prediction in collaboration with Syngenta. He holds a PhD in computational drug discovery from Abdelmalek Essaâdi University (Morocco), and an MSc in Biology & Biomaterials and a BSc in Biology & Health from Mohammed V University in Rabat.
His research combines structure- and ligand-based methods (molecular docking, molecular dynamics simulations and free energy calculations) with machine learning for molecular property prediction, applied to drug metabolism, neurodegenerative diseases and antimicrobial resistance. During his PhD he was a visiting PhD student at Pablo de Olavide University (Spain) and the University of Patras (Greece). His publications in computational and medicinal chemistry are listed on Google Scholar and ORCID.
On this site he writes, runs and reviews the tutorials, notes and browser tools: molecular docking (AutoDock Vina, Meeko), molecular dynamics with GROMACS, end-point binding free energies (MM-PBSA and MM-GBSA), QSAR and cheminformatics.
Areas of expertise
- Molecular docking
- Molecular dynamics (GROMACS)
- MM-PBSA / MM-GBSA
- QSAR and machine learning for molecular properties
- Drug metabolism (cytochrome P450)
Elsewhere
Tutorials
- Redocking with AutoDock Vina 1.2 and Meeko: a reproducible 1HSG walkthrough (23 Oct 2026)
- Choosing GROMACS .mdp parameters: a stage-by-stage guide for GROMACS 2026 (23 Oct 2026)
- Common GROMACS errors and how to fix them (2026 edition) (23 Oct 2026)
- Protein–ligand MD in GROMACS 2026 with AMBER99SB-ILDN and GAFF2 (ACPYPE): HIV-1 protease + indinavir (23 Oct 2026)
- MM-GBSA and MM-PBSA with gmx_MMPBSA 1.7: a tested workflow and how to read the numbers (23 Oct 2026)
- Using PaDELPy to Generate Molecular Fingerprints for Machine-Learning QSAR (15 Jan 2023)
- How to Curate and Classify Bioactivity Data From ChEMBL (7 Sept 2022)
Notes
- Honest QSAR Models Start With the Assay, Not the Algorithm (25 Oct 2026)
- BindingDB Meets PubChem: A Practical Workflow for Mining Bioactivity and Patent Chemistry (19 Oct 2026)
- Making AI Work in Discovery Chemistry: Precision, Trust, and Practical Value (28 Aug 2026)
- BindingDB for Computational Drug Discovery: From Experimental Affinity Data to ML and Docking Benchmarks (2 Aug 2026)
- 3D-QSAR Explained: CoMFA vs CoMSIA (2 Feb 2026)
- Bioisosteric Replacement In Silico: From Classical Rules to Data-Driven Suggestions (7 Jan 2026)
- Chemical Space Is Not One Map: PCA, t-SNE, UMAP, and What They Actually Show (12 Dec 2025)
- A Practical Guide to QSAR Model Validation: Internal, Cross, and External Checks (18 Nov 2024)
- How to Use DataWarrior for Drug Discovery: Key Workflows From the Villoutreix Tutorials (7 Feb 2024)
- How to Build and Validate 3D-QSAR Models: Insights From Xu et al. (2020) (2 Apr 2023)
- Chemical Databases Every ML Scientist Should Know for Drug Discovery (3 Oct 2022)