PI-620: Pharmacoinformatics-Chemoinformatics		(2 credits)
1.	Structure prediction methods: 2D, 3D, representing chemical structures in 1D notations searching analyzing. 4D-7D definition of structure. Morgan algorithm. Similarity searching: Tanimoto coefficient, Sorensen coefficient, Carbo coefficient, Euclidean distance, power distance, Soergel distance, Hamming distance. Full structure search and partial structure search.
2.	Matrices of chemical structures: Adjacency matrix, bond matrix, distance matrix, etc., Hash codes, bitmap generation, fragment based methods. Coordinate matrix, z-matrix; their interconversion. Descriptor generation: Molecular graphs and molecular trees, 2D QSAR: structure-activity relationships; Weiner index, Hosaya index, Randic index, Balaban index, etc. topological descriptor generation.
3.	Chemoinformatic tools: CDK tools, CCSD tools; Scifinder tools and algorithms associates with these tools, algorithms associated with search tools. Web based applications in chemoinformatics: MolEngine, ChemAxon, sysment reaction tool. Combinatorial library: design and molecular diversity; Applications in structure-based drug design, enumeration techniques.
4.	Algorithms in chemoinformatics: C++ code generation for smiles notation, matrices, linear regression, Newton-Raphson method, conformational search. Genetic algorithms. Chemoinformatics databases: Creation, analysis of chemoinformatics databases. Generate reports from the chemical databases.
5.	Pharmacoinformatics: Integration of Bioinformatics, Chemoinformatics, genomics and proteomics. In silico identification and validation of novel therapeutic targets: Bioinformatics followed by computational biology, Homology modeling. Pattern searching methods in drug identification. Ab initio gene prediction techniques to predict novel gene targets. Case studies.
6.	Databases in pharmacoinformatics: Evaluation of diverse compound subsets from chemical structure databases. Recognition of hypotheses, validation of hypotheses using pharmacophore pattern searching methods in chemoinformatics. Spectral and Crystallographic databases. 3D database search methods: Artificial neural network methods, Genetic algorithm methods in chemoinformatics.
7.	Virtual screening: Lead compound selection and lead optimization using virtual screening. Filtering methods. Rapid QSAR methods for virtual screening, Rapid molecular docking methods for virtual screening.
8.	Receptor selectivity mapping. Testing the lead drug candidates (from chemoinformatics methods) for their selectivity across a broad panel of targets (from bioinformatics methods). Scoring functions and their importance in virtual screening. Case studies. Internet computing in drug discovery.
9.	Algorithms in pharmacoinformatics: Development of small packages for Pharmacoinformatics analysis. Advanced algorithms in descriptor development. Algorithms for QSAR.
10.	Case studies: Pharmacoinformatics in anti-diabetic drug design, Pharmacoinformatics in anti-malarial drug design. Quantum chemical methods in troglitazone toxicity, metabolism of omeprazole, proguanil, mechanism based inhibition.