School of Bioinformatics · Structural biology & drug discovery
Computer-Aided Drug Design: Screening, Pharmacophores & ADMET
Computer-aided drug design combines structure-based and ligand-based methods to find and improve molecules worth testing. This course connects the methods into one workflow, from target to a prioritised list of compounds.
Course overview
Computer-Aided Drug Design takes a target from assessment (druggability, known ligands, structural data) to a screening campaign that combines similarity searching, pharmacophore models and docking, so that each method compensates for the weaknesses of the others.
You then filter hits for drug-likeness, liabilities and predicted ADMET properties, cluster them by scaffold and build a prioritised list with a rationale for each compound. Throughout, the course stresses retrospective validation and the limits of every prediction.
Learning outcomes
By the end of the course you will be able to:
- Assess a target’s druggability and available chemical matter
- Run ligand-based screens with fingerprints and pharmacophores
- Combine docking with consensus and rescoring strategies
- Predict ADMET properties and flag liabilities
- Prioritise hits by scaffold diversity, evidence and risk
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
- Molecular Docking & Structure-Based Drug Discovery or equivalent
- Basic organic chemistry
Best suited to
- Pharmacy, pharmaceutical chemistry and biotechnology postgraduates
- Researchers starting a drug-discovery project
- Docking users who want a complete screening workflow
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Target validation evidence
- Druggability and pocket analysis
- Mining ChEMBL for known ligands
Topics
- Fingerprints and similarity
- Pharmacophore models
- Shape-based screening
Topics
- Docking at scale
- Consensus and rescoring
- Retrospective validation
Topics
- Drug-likeness rules and their limits
- PAINS and structural alerts
- Predicted absorption, metabolism and toxicity
Topics
- Scaffold clustering
- Multi-parameter optimisation
- Purchasable analogues
Topics
- Workflow design
- Validation
- Recommendation
Practical sessions and projects
Capstone project
Run a virtual-screening campaign
Design and validate a combined ligand- and structure-based screen against a target and deliver a prioritised, justified shortlist of compounds.
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.
- Target to hypothesis
Assess a kinase target, collect its known actives and define a screening hypothesis.
- Ligand-based screening
Screen a library with fingerprints and a pharmacophore and measure enrichment of known actives.
- Structure-based screening
Dock a focused library, compare scoring strategies and compute enrichment against decoys.
- ADMET and liabilities
Profile the hit list for ADMET risks and remove compounds with liabilities, recording the reason for each.
- Prioritisation
Build a diverse, justified shortlist of compounds to order for testing.
- Project: a screening campaign
Run a complete virtual-screening campaign on a target and present a ranked shortlist with evidence and risks.
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
- ChEMBL bioactivity data: Known actives and validation.ChEMBL (CC BY-SA 3.0)
- DUD-E actives and decoys: Retrospective enrichment.dude.docking.org
- ZINC purchasable compounds: Screening library.ZINC database
Core reading
- Sliwoski G, Kothiwale S, Meiler J, Lowe EW (2014). Computational methods in drug discovery. Pharmacological Reviews 66:334–395.
- Daina A, Michielin O, Zoete V (2017). SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness. Scientific Reports 7:42717.
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 Computer-Aided Drug Design: Screening, Pharmacophores & ADMET, 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 Computer-Aided Drug Design: Screening, Pharmacophores & ADMET
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
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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