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I will perform molecular docking and virtual screening for drug discovery
Computational Chemist, Molecular Docking, GROMACS MD and QSAR ML
Hi, I'm Sareer Ahmad, a computational chemist and cheminformatics freelancer.
I hold an MSc in Physical Chemistry and work as a Senior Chemistry Teacher, alongside building molecular docking, GROMACS...
About this Gig
I help researchers, startups, and students turn a target protein and a set of candidate compounds into ranked, defensible binding predictions.
Using AutoDock Vina, I perform structure-based molecular docking: protein and ligand preparation, grid box setup around the binding site, docking runs, and binding-pose visualization in PyMOL. For larger compound sets, I run batch virtual screening and return a ranked binding-affinity table so you can prioritize which molecules to pursue experimentally.
My background is in computational and physical chemistry (MSc, Physical Chemistry), with hands-on project experience running docking and molecular dynamics studies, including an EGFR docking and MD workflow. I also work in GROMACS for MD validation, so a docking result can be followed up with a short simulation to check pose stability.
What you get: a clear methods summary, binding-pose images, a ranked results table for multi-ligand jobs, and honest communication - I will tell you plainly if your target or ligand set has a known limitation rather than promising results docking alone cannot deliver.
Message me with your protein (PDB ID or structure file) and ligand(s) before ordering.
Domain:
Machine Learning
•
Other
Expertise:
Predictive analysis
Programming language:
Python
•
R
Tools:
Jupyter Notebook
Technology:
Python
•
scikit-learn
•
Jupyter Notebook
My Portfolio
FAQ
What files do you need from me to get started?
Ideally a protein structure (PDB ID or a .pdb file) and your ligand(s) as SMILES, .sdf, or .mol2 files. If you only have a protein sequence, message me first and I will let you know if homology modeling is needed.
Can docking alone confirm a compound will work?
No, and I will not tell you otherwise. Docking gives a predicted binding pose and score to help you prioritize candidates. For stronger evidence, add the Premium package's short MD validation run to check pose stability.
