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