Machine Learning and Computational Chemistry for the Endocannabinoid System

Overview

Journal Methods Mol Biol

Specialty Molecular Biology

Date 2022 Sep 24

PMID 36152211

Authors

Kenneth Atz

Wolfgang Guba

Uwe Grether

Gisbert Schneider

Affiliations

Soon will be listed here.

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.

Citing Articles

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