Syllabus
Drug targets. Structure of proteins, structure of nucleic acids. The importance of specific amino acids for the tertiary structure of the protein and for the catalysis of biochemical reactions.
In silico prediction of 3D structure of proteins. Homology models and possibilities of their use. Creating a homology model, automated web services for creating homology models. Critical evaluation of the quality of homology models (Ramachandran plot).
Rational approaches to design and development of new drugs. Combinatorial libraries. Chemical information systems and databases. Biological information systems and databases. Crystallographic databases. Critical assessment of 3D protein structures. Data mining from public sources.
The importance of physicochemical properties for the action of drugs. Methods of in silico prediction of physico-chemical properties of compounds. In silico prediction of pharmacokinetic parameters, metabolism and toxicity of compounds.
Quantitative Structure-Activity Relationships (QSAR) and Quantitative Structure-Property Relationships (QSPR).
Drug-receptor interactions, intermolecular forces, hydrogen bonds.
Experimental methods for monitoring drug-receptor interaction. X-ray crystallographic analysis, NMR experiments, radioligands, isothermal titration calorimetry, thermal shift assay.
In silico methods for predicting drug-receptor interaction. Molecular docking. Molecular dynamics.
Overview of molecular docking methods. Rigid docking, flexible docking. Search function, conformational sampling, scoring functions. Overview of common molecular docking software and comparison of their functions. Freely available software (AutoDock Vina, DOCK), commercially available programs, online docking services (servers).
Critical evaluation of results of molecular docking. Special applications of molecular docking - virtual screening (HTVS), ligand modification.
Rational methods of design and development of drugs with known receptor (Structure-based drug design).
Rational methods of design and development of drugs with unknown receptor (Ligand-based drug design). QSAR. Pharmacophore models. 3D-QSAR.
Case studies. Examples of significant active substances developed with Computer Aided Drug Design (CADD) methods.
Annotation
The aim of the course is to acquaint students with basic methods of Computer Aided Drug Design (CADD). CADD methods are routinely used in rational design of new biologically active compounds (drugs). Students will learn basic theoretical principles of modelling of small molecules (drugs), biological structures (receptors) and their interactions. Emphasis will be placed on the practical application of these methods, which will be practiced in seminars. The principle outcome of the course is to learn CADD methods and understand their principles and utilization. Absolvents of the course, are supposed to be able to design and perform a simple CADD project on their own.
Themes: Drug targets, Structure of proteins, Information systems and databases, In silico prediction of physicochemical properties, Drug-receptor interactions, Experimental methods to study drug-receptor interactions, Rational design and development of drugs with known receptor (structure-based drug design), Molecular docking. Molecular dynamics, Rational design and development of drugs with unknown receptor (ligand-based drug design), Analysis of Quantitative Structure-Activity Relationships (QSAR), Pharmacophore models, Case studies.