Literature DB >> 36152211

Machine Learning and Computational Chemistry for the Endocannabinoid System.

Kenneth Atz1, Wolfgang Guba2, Uwe Grether3, Gisbert Schneider1,4.   

Abstract

Computational methods in medicinal chemistry facilitate drug discovery and design. In particular, machine learning methodologies have recently gained increasing attention. This chapter provides a structured overview of the current state of computational chemistry and its applications for the interrogation of the endocannabinoid system (ECS), highlighting methods in structure-based drug design, virtual screening, ligand-based quantitative structure-activity relationship (QSAR) modeling, and de novo molecular design. We emphasize emerging methods in machine learning and anticipate a forecast of future opportunities of computational medicinal chemistry for the ECS.
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Computational Chemistry; De Novo Drug Design; Endocannabinoid System; Machine Learning; QSAR; Structure-Based Drug Design; Virtual Screening

Mesh:

Substances:

Year:  2023        PMID: 36152211     DOI: 10.1007/978-1-0716-2728-0_39

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  63 in total

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Journal:  Nat Rev Drug Discov       Date:  2003-05       Impact factor: 84.694

Review 2.  Hypothesis driven drug design: improving quality and effectiveness of the design-make-test-analyse cycle.

Authors:  Alleyn T Plowright; Craig Johnstone; Jan Kihlberg; Jonas Pettersson; Graeme Robb; Richard A Thompson
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Review 4.  Navigating chemical space for biology and medicine.

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Journal:  Nature       Date:  2004-12-16       Impact factor: 49.962

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Journal:  J Mol Recognit       Date:  1993-09       Impact factor: 2.137

6.  Design, activity, and 2.8 A crystal structure of a C2 symmetric inhibitor complexed to HIV-1 protease.

Authors:  J Erickson; D J Neidhart; J VanDrie; D J Kempf; X C Wang; D W Norbeck; J J Plattner; J W Rittenhouse; M Turon; N Wideburg
Journal:  Science       Date:  1990-08-03       Impact factor: 47.728

7.  Rational design of peptide-based HIV proteinase inhibitors.

Authors:  N A Roberts; J A Martin; D Kinchington; A V Broadhurst; J C Craig; I B Duncan; S A Galpin; B K Handa; J Kay; A Kröhn
Journal:  Science       Date:  1990-04-20       Impact factor: 47.728

Review 8.  Missing Pieces to the Endocannabinoid Puzzle.

Authors:  Mauro Maccarrone
Journal:  Trends Mol Med       Date:  2019-12-07       Impact factor: 11.951

Review 9.  Rethinking drug design in the artificial intelligence era.

Authors:  Petra Schneider; W Patrick Walters; Alleyn T Plowright; Norman Sieroka; Jennifer Listgarten; Robert A Goodnow; Jasmin Fisher; Johanna M Jansen; José S Duca; Thomas S Rush; Matthias Zentgraf; John Edward Hill; Elizabeth Krutoholow; Matthias Kohler; Jeff Blaney; Kimito Funatsu; Chris Luebkemann; Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2019-12-04       Impact factor: 84.694

Review 10.  Cannabinoids and the expanded endocannabinoid system in neurological disorders.

Authors:  Luigia Cristino; Tiziana Bisogno; Vincenzo Di Marzo
Journal:  Nat Rev Neurol       Date:  2019-12-12       Impact factor: 42.937

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