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Structure-Based In Silico Drug Design

USD $59.00 USD $249.00Price range: USD $59.00 through USD $249.00

Duration: 1 Month | Mode: Offline/Online (Live + LMS)

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SKU: BIOI-004 Category: Tags: , , , Brand:

Aim

This course trains participants in practical Structure-Based Drug Design (SBDD) workflows used in modern in silico discovery. You’ll learn how to select and prepare protein structures, identify binding pockets, design and screen ligands using docking, analyze interactions, optimize hits, and build a decision-ready shortlist—supported by validation steps and a final mini-project that mirrors real early-stage drug discovery pipelines.

Program Objectives

  • Understand SBDD Fundamentals: Learn how structure guides target-based drug discovery decisions.
  • Protein & Binding Site Preparation: Prepare structures correctly and define realistic docking sites.
  • Molecular Docking Skills: Perform docking runs and interpret poses beyond “just the score.”
  • Hit Evaluation & Optimization: Use interaction logic and basic property filters to improve candidates.
  • Validation & Rigor: Learn redocking, RMSD checks, controls, and common pitfalls in docking studies.
  • Workflow Integration: Build a complete screening pipeline you can reuse in research or internships.
  • Portfolio Output: Complete a structure-based screening mini-project with a final report.

Program Structure

Module 1: Structure-Based Drug Design — The Core Idea

  • Why structure matters: binding site, interactions, and selectivity.
  • Hit vs lead vs optimized candidate: how SBDD supports each stage.
  • Strengths and limitations of in silico screening (what to trust and what not to).
  • Choosing a target: druggability, relevance, and available structural evidence.

Module 2: Protein Structures & Binding Site Identification

  • Finding structures: PDB basics, resolution, ligands, chains, and biological assemblies.
  • Binding site identification: co-crystal ligands, known residues, pocket detection (concept).
  • Understanding cofactors, metals, water networks, and why they matter.
  • Assessing structure quality: missing residues, mutations, alternate conformations.

Module 3: Protein Preparation (Make the Target Docking-Ready)

  • Cleaning and fixing structures: missing atoms/residues (concept), protonation, charges.
  • Deciding about waters: when to keep/remove them and why.
  • Adding hydrogens and selecting correct states (pH considerations overview).
  • Defining the docking box/grid correctly for meaningful results.

Module 4: Ligand Preparation & Library Building

  • SMILES to 3D: conformers, minimization, stereochemistry basics.
  • Tautomers and ionization states: how they change docking outcomes.
  • Building a small screening library: sources, curation, and duplicates.
  • Property checks: basic drug-likeness and “avoid obvious bad actors.”

Module 5: Molecular Docking (Hands-on Screening Workflow)

  • Docking fundamentals: scoring, search, poses, and ranking logic.
  • Single-ligand docking vs batch docking: when and why.
  • Reading results: docking score + interaction quality + pose plausibility.
  • Interaction analysis: H-bonds, hydrophobic contacts, salt bridges, π interactions.

Module 6: Validation & Quality Control (Don’t Trust the Wrong Pose)

  • Redocking and RMSD: checking whether your docking setup is reliable.
  • Positive/negative controls: how to set expectations for your workflow.
  • Common pitfalls: overfitting the grid, unrealistic protonation, wrong pocket.
  • Rescoring and consensus thinking (overview) for better confidence.

Module 7: Hit Prioritization & Lead Optimization Thinking

  • From hit list to shortlist: practical ranking criteria beyond score.
  • Interaction-driven optimization: what to modify and why.
  • Basic ADMET and safety flags (concept): solubility, permeability, toxicity risks.
  • Designing “next round” compounds: analog selection and rational changes.

Module 8: Beyond Docking (SBDD Extensions — Overview)

  • Molecular dynamics (MD) concept: why flexibility matters.
  • Binding free energy concepts (MM/PBSA overview).
  • Pharmacophore screening and fragment-based ideas (overview).
  • How real pipelines combine methods for stronger confidence.

Final Project

  • Select a target protein (provided list or your own) and run a structure-based screening workflow.
  • Deliverables: prepared protein + ligand set, docking results, interaction analysis, top shortlist, and rationale.
  • Include validation notes: redocking/controls and limitations.
  • Example projects: enzyme inhibitor screening, receptor ligand shortlist, antimicrobial target screening, cancer target docking study.

Participant Eligibility

  • UG/PG/PhD students in Pharmacy, Biotechnology, Chemistry, Bioinformatics, or related fields
  • Researchers working in drug discovery, molecular biology, or computational biology
  • Professionals seeking hands-on upskilling in in silico drug design
  • Basic knowledge of biomolecules and chemistry is recommended (coding not mandatory)

Program Outcomes

  • SBDD Workflow Skill: Ability to perform structure-based screening from target prep to shortlist.
  • Better Interpretation: Confidence in evaluating docking poses and avoiding common errors.
  • Research Readiness: Ability to structure a docking-based results section for reports/papers.
  • Portfolio Deliverable: A complete structure-based in silico project you can showcase.

Program Deliverables

  • Access to e-LMS: Full access to course content, tutorials, and practice datasets.
  • Workflow Templates: Protein prep checklist, docking setup sheet, hit ranking rubric, reporting format.
  • Hands-on Exercises: Guided docking and interaction analysis tasks.
  • Project Guidance: Mentor support for target selection, workflow setup, and final reporting.
  • Final Assessment: Certification after assignments + final project submission.
  • e-Certification and e-Marksheet: Digital credentials provided upon successful completion.

Future Career Prospects

  • Structure-Based Drug Design (SBDD) Intern / Associate
  • Molecular Docking & Virtual Screening Analyst
  • Computational Biology / Bioinformatics Research Assistant
  • Cheminformatics & CADD Associate (Entry-level)
  • Pharma R&D Support (In Silico Discovery)

Job Opportunities

  • Pharma & Biotech: Discovery research and computational chemistry teams.
  • CROs: Modeling, docking, and screening service divisions.
  • Academic Labs: Structural biology and computational drug discovery groups.
  • Drug Discovery Startups: Virtual screening and AI-driven discovery platforms.
Category

E-LMS, E-LMS+Videos, E-LMS+Videos+Live

Certification

  • Upon successful completion of the workshop, participants will be awarded a Certificate of Completion, validating their skills and knowledge in advanced AI ethics and regulatory frameworks. This certification can be added to your LinkedIn profile or shared with employers to demonstrate your commitment to ethical AI practices.

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Hall of Fame.

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