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Virtual Screening in Drug Discovery

Virtual Screening in Drug Discovery Table of Contents: 00:01 - Virtual Screening in DRUG DISCOVERY 01:12 - Challenge in Drug Discovery 01:44 - Choosing the right molecule 03:38 - Screening Schema in Drug Discovery 05:10 - Virtual Screening 05:14 - Screening Schema in Drug Discovery 05:17 - Virtual Screening 07:25 - Hybrid Virtual Screening 10:36 - Drug Like Properties 13:02 - Leadlike & Druglike 15:31 - Filtering molecules using structural properties 16:12 - Filter out Reactives (false positives for proteins) 17:08 - Filter out: Synthesis Intermediates, Chelators 17:47 - PAINS Filter 18:28 - Rules-of-Thumb for Hit Selection & Lead Optimization 19:56 - Similarity Searching 21:02 - What is required for a similarity search ? 22:01 - 2D fingerprints: molecules represented as binary vectors 22:03 - What is required for a similarity search ? 22:05 - 2D fingerprints: molecules represented as binary vectors 23:24 - Calculate molecular similarity 24:03 - Don’t forget to check out the video of 2D similarity searching on a database 24:21 - 3D based similarity 26:24 - Multiple actives known: pharmacophore searching 27:49 - 3D- pharmacophores 28:56 - Workflow of pharmacophore modeling 30:50 - Watch the video on pharmacophore searching 31:01 - Tools to perform pharmacophore searching 31:37 - Many Actives and inactives known : Machine learning methods 33:15 - 33:33 - Protein Ligand Docking 34:58 - Pose and Binding Site 35:36 - Protein Ligand Docking 36:36 - The search space 37:52 - Dock Algorithms 38:52 - DOCK (Kuntz et al. 1982) 39:19 - DOCK 40:17 - Energetics of protein-ligand binding 41:14 - Conclusions 41:35 - Conclusions 42:59 - Conclusions 42:59 - Energetics of protein-ligand binding 42:59 - Dock Algorithms 43:01 - Tools to perform pharmacophore searching 43:01 - Multiple actives known: pharmacophore searching 43:02 - 2D fingerprints: molecules represented as binary vectors 43:03 - What is required for a similarity search ? 43:03 - Similarity Searching 43:03 - Rules-of-Thumb for Hit Selection & Lead Optimization 43:04 - PAINS Filter 43:04 - Filter out: Synthesis Intermediates, Chelators 43:05 - Filter out Reactives (false positives for proteins) 43:05 - Filtering molecules using structural properties 43:06 - Leadlike & Druglike 43:06 - Drug Like Properties 43:07 - Hybrid Virtual Screening 43:35 - Drug Like Properties 43:36 - Leadlike & Druglike 43:36 - Filtering molecules using structural properties 43:38 - 3D based similarity 43:38 - Multiple actives known: pharmacophore searching 43:39 - Protein Ligand Docking 43:40 - Protein Ligand Docking 43:40 - The search space 43:42 - Energetics of protein-ligand binding 43:42 - Conclusions 43:42 - Conclusions 43:43 - References