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BP610P SECSemester 61 creditsPractical

SEC Elective — Computer-Aided Drug Design / Analytical Method Development / Principles of Preclinical Studies (Practical)

Complete unit-wise syllabus for BP610P SEC as per the PCI B.Pharm NEP 2020 curriculum (Semester 6 — AI in Pharma + Analysis + Internship II).

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Course Objectives

  • Familiarize students with target identification and protein preparation using biological databases and molecular visualization tools.
  • Develop skills in ligand design, optimization, and 3D conformer generation using computational chemistry software.
  • Provide practical understanding of molecular docking and interaction analysis for structure-based drug design.
  • Introduce pharmacophore modelling and QSAR techniques for virtual screening and predictive modelling.
  • Train students in ADMET prediction and molecular dynamics simulations for evaluating drug-likeness and stability of drug–target complexes.
  • Provide practical exposure to analytical method development using spectrophotometric, chromatographic, and titrimetric techniques for pharmaceutical analysis.

Unit-wise Syllabus

3 Units
1
Option 1: BP610P SEC1 — Computer-Aided Drug Design (30 Hours)30 Hours
  • General Instruction on Computational Tools Open-source computational tools are preferred for teaching and learning purposes. However, institutions may select appropriate software platforms or online resources based on availability, institutional policy, and technical feasibility. The choice of software should enable students to perform the required computational tasks effectively. The specific software used may vary, but the learning outcomes and computational procedures described below must be achieved using suitable tools.
  • 1. Target Identification and Preparation; • Retrieve protein sequence or structural information from publicly available biological databases.; • Prepare the target protein by removing unwanted molecules, correcting structural issues, and adding necessary atoms or charges using appropriate molecular visualization or preparation tools.; • Identify potential binding or active sites using computational methods that analyze structural pockets and cavities.
  • 2. Ligand Design and Optimization; • Design or sketch candidate molecules using suitable molecular drawing tools.; • Convert structures into three-dimensional form and optimize their geometry using computational chemistry methods.; • Generate multiple conformations of the molecule and perform energy minimization to obtain stable structures.
  • 3. Molecular Docking; • Perform docking simulations using computational docking platforms to predict the interaction between ligands and the target protein.; • Examine binding orientations and molecular interactions using visualization tools.; • Rank compounds based on predicted binding affinity and interaction quality.
  • 4. Pharmacophore Modeling; • Identify essential molecular features responsible for biological activity such as hydrogen bond donors/acceptors, hydrophobic regions, and aromatic centers.; • Construct pharmacophore models representing these key features.; • Use these models to screen compound libraries for molecules that match the required feature pattern.
  • 5. QSAR Modeling; • Calculate molecular descriptors that represent structural and physicochemical properties of compounds.; • Develop predictive statistical or machine learning models that relate these descriptors to biological activity.; • Validate models using appropriate validation techniques such as cross-validation and external datasets.
  • 6. ADMET Prediction; • Evaluate pharmacokinetic and toxicity properties computationally, including:; o Absorption; o Distribution; o Metabolism; o Excretion; o Toxicity; • Use predictive computational models and online resources to assess drug- likeness and safety profiles.
  • 7. Molecular Dynamics Simulations; • Conduct simulations to study the dynamic behavior of the protein–ligand complex over time.; • Analyze parameters such as structural stability, atomic fluctuations, hydrogen bonding, and interaction persistence.; • Visualize simulation trajectories to understand conformational changes and binding stability.
2
Option 2: BP610P SEC2 — Analytical Method Development and Validation (30 Hours)30 Hours
  • 1. Development of a UV-Visible spectrophotometric method for the assay of paracetamol API. Construction of calibration curve for a model API using UV-Visible spectrophotometry.
  • 2. Determination of solid dosage form by using dissolution method.
  • 3. Analytical method development and validation of Atenolol/metformin by using HPLC.
  • 4. Investigation of different columns for HPLC separation of a Multi-component Drug Mixture.
  • 5. Optimization of mobile Phase composition for HPLC analysis of a selected drug.
  • 6. Optimization of Flow rate and temperature in HPLC for paracetamol/ caffeine.
  • 7. Selection of wavelength for spectrophotometric analysis by HPLC of Marketed drugs.
  • 8. Determination of λmax and calibration curve for qualitative analysis of paracetamol.
  • 9. Determination of effect of pH on Retention time in RP-HPLC.
  • 10. Validation of HPLC method : Determination of LOD and LOQ for paracetamol by HPLC
  • 11. Preliminary Investigation of forced Degradation studies on Ibuprofen by HPLC.
  • 12. Method development for related substances of a drug substance using HPLC.
  • 13. Determination of residual solvent analysis for ethanol/acetone in API by using Gas Chromatography.
  • 14. Development of titrimetric method for the assay of marketed drugs(Ascorbic acid/sodium bicarbonate).
3
Option 3: BP610P SEC3 — Principles of Preclinical Studies (30 Hours)30 Hours
  • 1. Handling, restraining, and sex differentiation of laboratory animals (demo/video)
  • 2. Calculation of dose for animals based on body surface area
  • 3. Routes of administration: oral, intraperitoneal, subcutaneous (simulation)
  • 4. Observation of behavioral effects using actophotometer/rotarod (if available)
  • 5. Determination of acute toxicity (LD50 concept) – case-based calculation
  • 6. Planning a 28-day sub-acute toxicity study protocol
  • 7. Pharmacokinetic study: Cmax, Tmax, AUC calculation (sample dataset)
  • 8. Observation of histopathological slides from toxicity studies
  • 9. Demonstration of sampling methods – blood, urine (case or video)
  • 10. Writing an animal study protocol using CPCSEA format
  • 11. Identification of organs for toxicity evaluation – liver, kidney, brain
  • 12. Visit to CPCSEA-approved animal house/laboratory
  • 13. Observation of animal behavior – grooming, nesting (case-based)
  • 14. Simulated ethics committee approval process (IAEC)

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Recommended Textbooks & References

  1. 1. Leach, A.R., Molecular Modelling: Principles and Applications. Harlow: Prentice Hall.
  2. Todeschini, R. and Consonni, V., Molecular Descriptors for Chemoinformatics. Weinheim: Wiley-VCH.
  3. Gupta, S.P., QSAR and Molecular Modeling. Berlin: Springer.
  4. Jorgensen, W.L., Efficient Drug Discovery and Development. Hoboken, NJ: Wiley.
  5. Bultinck, P., De Winter, H., Langenaeker, W. and Tollenaere, J.P., Computational Medicinal Chemistry for Drug Discovery. New York: Marcel Dekker.
  6. Andrew, L.H. and Brown, F.K., Rational Drug Design: Novel Methodology and Practical Applications. Washington, DC: American Chemical Society.
  7. Ward, S.E. and Davis, A., The Handbook of Medicinal Chemistry: Principles and Practice.
  8. 1. Ahuja S, Dong MW, editors. Handbook of pharmaceutical analysis by HPLC. Amsterdam: Elsevier; 2005.

What's coming next on this page

  • Previous year question papers (PYQ)
  • Topic-wise short notes and revision summaries
  • MCQs and self-assessment quizzes
  • Suggested external resources and video tutorials

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