人工智能/ML方法和未来 - - 他们能否成功设计下一代新的化学实体?

Rachelle J Bienstock1

  • 1RJB Computational Modeling LLC, Chapel Hill, NC, USA. rachelleb1@gmail.com.

PubMed
概括

机器学习 (ML) 和人工智能 (AI) 正在通过增强化学数据分析来进行分子性质预测和目标识别来改变药物发现. 将机器学习与传统基于物理的方法和实验数据相结合,为改善药物设计提供了互补的优势.

相关概念视频

Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
7.2K
Structure-Activity Relationships and Drug Design01:28

Structure-Activity Relationships and Drug Design

Drug design is a dynamic field that involves discovering and developing new medications based on specific biological targets. This process heavily relies on structure-activity relationships (SAR) and quantitative structure-activity relationships (QSAR) to guide the design and optimization of efficient drugs.
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
461
Preclinical Development: Overview01:28

Preclinical Development: Overview

Preclinical development consists of a series of tests that ensure the safety and efficacy of a new therapeutic compound before it is tested in humans. There are four main phases to this process. First, safety pharmacology tests are conducted to ensure the drug does not produce any acutely harmful effects. These tests examine parameters such as bronchoconstriction, cardiac dysrhythmias, blood pressure changes, and ataxia. Next, preliminary toxicological testing is performed to determine the...
4.1K