School of Bioinformatics · Structural biology & drug discovery
Molecular Docking & Structure-Based Drug Discovery
Molecular docking is one of the most used, and most misused, methods in computational drug discovery. This course teaches the full structure-based workflow and the controls that separate a meaningful docking result from a coloured picture.
Course overview
Molecular Docking & Structure-Based Drug Discovery teaches the full structure-based workflow: choosing and preparing a target structure, defining the binding site, docking ligands, screening a library and analysing the resulting poses.
A docking score is not a measure of activity, and many published docking studies cannot be reproduced. Validation is therefore at the centre of the course: redocking a co-crystallised ligand, measuring how well known actives rank above decoys, and reporting results with the parameters and limits someone else needs to repeat them.
Learning outcomes
By the end of the course you will be able to:
- Select and prepare protein targets and ligands correctly
- Define binding sites from co-crystal ligands and pocket detection
- Dock and screen with AutoDock Vina reproducibly
- Analyse protein–ligand interactions and produce clear figures
- Validate protocols with redocking RMSD and active-versus-decoy enrichment
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates of B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm., M.Pharm., MBBS, BDS, B.V.Sc. or a PhD programme in the life sciences, biotechnology, bioinformatics, pharmacy, medicine, agriculture, chemistry, statistics or computer science
- Researchers, faculty and industry professionals moving into data-driven biology
- Final-year students may apply before their results are declared
Prerequisites
- Basic biochemistry
- Bioinformatics Foundations recommended
Best suited to
- Pharmacy, biotechnology and chemistry students
- Researchers planning in-silico screening
- Students preparing for drug-discovery internships
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Reading PDB entries: resolution, B-factors, missing residues
- AlphaFold models and pLDDT
- Choosing a target structure
Topics
- Protonation states and waters
- Ligand preparation and tautomers
- Converting formats with Open Babel
Topics
- Co-crystallised ligands
- Pocket detection
- Defining the search box
Topics
- AutoDock Vina scoring and search
- Virtual screening of a library
- Exhaustiveness and reproducibility
Topics
- Redocking and RMSD
- Decoys and enrichment
- Interaction fingerprints; PyMOL figures
Topics
- Target to ranked hits
- ADMET filtering
- A defensible report
Practical sessions and projects
Capstone project
Run a validated virtual screen
Screen a compound library against a protein target, validate the protocol with known actives and decoys, and report the hits with interaction analysis and the limits of the method.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Structures and targets
Assess candidate structures for one target by resolution, completeness and ligand state, and compare them with its AlphaFold model.
- Preparation
Prepare the HIV-1 protease structure 1HSG and its ligand: protonation, waters, charges and file conversion.
- Binding sites
Define the search box from the co-crystallised ligand and compare it with a pocket-detection result.
- Docking and screening
Dock with AutoDock Vina at several exhaustiveness settings, measure run-to-run variation and screen a small library.
- Validation and analysis
Redock the native ligand and compute RMSD, measure active-versus-decoy enrichment and profile the interactions of the top poses.
- Project: a mini screening campaign
Run a validated screening campaign on a new target and report hits with interaction diagrams and clearly stated limits.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- HIV-1 protease with a bound inhibitor: Preparation, redocking and interaction analysis.RCSB PDB entry 1HSG
- DUD-E actives and decoys: Measuring enrichment of known actives over decoys.dude.docking.org (Mysinger et al. 2012)
- AlphaFold Protein Structure Database models: Comparing predicted and experimental targets.EMBL-EBI AlphaFold DB
Core reading
- Trott O, Olson AJ (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry 31:455–461.
- Eberhardt J, Santos-Martins D, Tillack AF, Forli S (2021). AutoDock Vina 1.2.0: new docking methods, expanded force field, and Python bindings. Journal of Chemical Information and Modeling 61:3891–3898.
- Mysinger MM, Carchia M, Irwin JJ, Shoichet BK (2012). Directory of useful decoys, enhanced (DUD-E). Journal of Medicinal Chemistry 55:6582–6594.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for Molecular Docking & Structure-Based Drug Discovery, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for Molecular Docking & Structure-Based Drug Discovery
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
Molecular dynamics is introduced as the next step after docking, with a short demonstration. It is not covered in depth.
No. Docking ranks plausible binders and suggests poses; activity has to be measured experimentally. The course teaches how to report docking as what it is, a prioritisation step.
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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