COURSE NAME: Pharmacoinformatics
PROGRAM: MSc Bioinformatics


Introduction: Classification of drugs, Major sources of drugs, Common filters for drugs design, Molecular descriptors, Structure activity relationship, Pharmacophore and pharmacophoric graph, Machine learning approach in designing filters; Targets of drug design: Protein as the target, structural and sequence analysis, Nucleus as target, coding and noncoding RNA, SNP analysis, other important targets; Molecular modeling and simulation in drug designing: QM and MM modeling, computation of weak interaction, docking, MD simulation based docking; Pharmacokinetics: One-compartment model, Two-compartment model, Multi-compartment models, Pharmacokinetic parameters, Absorption, Distribution, Metabolism, Excretion, Multiple doses, Salt factor, Bioavailability, Clinical case studies;Pharmacodynamics: Drug receptor action, Direct physiological action, Drug-drug interaction, Polymorphism and drug metabolism, Drug potency and efficacy, Agonists and antagonists, Receptor effector coupling, Spare receptors, Therapeutic index; Types of drug design: Strucure based, ligand based, fragment based, metabolites and their importance in drug design; Pharmacogenomics: SNPs analysis, Statistical methods, Gene-gene interaction, Gene –environment interaction, Gene silencing techniques; Pharmacoinformatics: Chemogenomics, chemoinformatics,immunoinformatics, cancer informatics, neuroinformatics, toxicoinformatics, Tools used in pharmacoinformatics, Case studies and applied pharmacoinformatics.


  1. Malone, P.M., Kier, K.L., Srtanovich, J.E.  Drug Information-A Guide for Pharmacists. McGraw-Hill, 2006.
  2. Krishnan Namboori P K and Deepak O M. Computational Drug Design and Delivery systems-principles and applications, Springer. 2012.


  1. Prasad V. Bharatam, Modeling and Informatics in Drug Design, John Wiley & Sons Inc.2007.
  2. Tagelsir Mohamed Gasmelseid, Pharmacoinformatics and Drug Discovery Technologies: Theories and Applications, IGI-Global, 2012