Integrated QSAR Models for Prediction of Serotonergic Activity: Machine Learning Unveiling Activity and Selectivity Patterns of Molecular Descriptors

Understanding the features of compounds that determine their high serotonergic activity and selectivity for specific receptor subtypes represents a pivotal challenge in drug discovery, directly impacting the ability to minimize adverse events while maximizing therapeutic efficacy. Up to now, this pr...

詳細記述

書誌詳細

主要な著者:	Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-03-01
シリーズ:	Pharmaceutics
主題:	serotonin receptors molecular descriptors Mordred machine learning statistical analysis selectivity and activity
オンライン･アクセス:	https://www.mdpi.com/1999-4923/16/3/349
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!