Published 1/2023 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 14.53 GB | Duration: 22h 42m Drug Design
What you'll learn Module 1: Introduction to CADD Module 2: Ligand-based drug design (Pharmacophore design) Module 3: Structure-based drug design (target-ligand docking) Module 4: Significance and limitations of CADD in Drug Discovery Module 5: Case study Requirements A basic level of knowledge about various concepts involved in Chemistry and biotechnology is required. Description Computer-Aided drug design(CADD) is an amazing approach that applies computational methods to discover, develop, and analyze drugs and similar biologically active molecules. Over the past few years, CADD has been involved in some of the most significant contributions in the discovery of new drugs, active molecules, etc. One cannot ignore the role of Computer-aided drug design in the vaccine development for the COVID 19 virus.CADD aims to equip you with the knowledge about drug discovery, Ligand-based drug design, structure-based drug design, its importance, and limitations. Each lecture in the courses covers the topics at a perfect pace in an elaborate manner.What this course covers:Module 1: Introduction to CADDOverview of the process of drug discoveryIntroduction to Bioinformatics and Understanding Genomics, Proteomics and CADDDatabasesSequence-Based Search ToolLASTFactors affecting drug discoveryTypes of CADDModule 2: Ligand-based drug design (Pharmacophore design)Pharmacophore ModellingQSAR analysisSimilarity search/clusteringR-group decompositionMatched pair analysisModule 3: Structure-based drug design (target-ligand docking)Introduction to Structure-based Drug Design and process layout of DockingData mining, literature study, and acquisition of target structureComparative modeling of protein (Homology modeling)Active site/ Pocket identification –MetaPocket,CastP,Active site identification using PyMolProtein and ligand preparationDocking analysis (based on binding energy, Hydrogen bond interactions, electrostatic interactions, hydrophobic interactions, etc.)Approaches of Structure-based drug design: Structure-based virtual high-throughput screening, Fragment-based lead discovery, In silico structure-based lead optimization, ADMET modelingModule 4: Significance and limitations of CADD in Drug Discovery and DevelopmentModule 5: Case study Overview Section 1: Module 1: Introduction to CADD Lecture 1 Day 1 : Overall Drug Discovery Process Lecture 2 Day 2 : Introduction to Bioinformatics and Understanding Genomics, Proteomics an Lecture 3 Day 3 : Databases Lecture 4 Day 4 : Sequence Based Search ToolLAST Lecture 5 Day 5 : Factors Affecting Drug Discovery Lecture 6 Day 6 : Types of CADD Section 2: Module 2: Ligand-based drug design (Pharmacophore design) Lecture 7 Day 7 : Pharmacophore Modelling Lecture 8 Day 8 : QSAR Analysis Lecture 9 Day 9 : Similarity Search / Clustering Lecture 10 Day 10 : R-Group Decomposition Lecture 11 Day 11 : Matched Pair Analysis Section 3: Module 3: Structure-based drug design (target-ligand docking) Lecture 12 Day 12 : Introduction to Structure based Drug Design and process layout of Docki Lecture 13 Day 13 : Data mining, literature study and acquisition of target structure Lecture 14 Day 14 : Comparative modelling of protein (Homology modelling) Lecture 15 Day 15 : Active site/ Pocket identification –MetaPocket, CastP, Active site id Lecture 16 Day 16 : Protein & Ligand Preparation Lecture 17 Day 17 : Docking Analysis (based on binding energy, Hydrogen bond interactions, Lecture 18 Day 18 : Approaches of Structure based drug design: Structure-based virtual hi Section 4: Module 4 : Significance and limitations of CADD in Drug Discovery Lecture 19 Day 19 : Significance and limitations of CADD in Drug Discovery and Development Section 5: Module 5 : -Case study The courses are designed to suit graduates, postgraduates, teaching, and industry professionals along with research enthusiasts.
