相关实验视频

Updated: Jun 17, 2025

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery

Published on: May 16, 2021

在药物发现中对虚拟查的当前方法的观点

Ingo Muegge¹, Jörg Bentzien¹, Yunhui Ge¹

¹Research department, Alkermes, Inc, Waltham, MA, USA.

Expert opinion on drug discovery

|August 12, 2024

概括

虚拟查 (VS) 是一种强大的药物发现工具,随着机器学习和基于物理的方法的发展. 选择合适的化学空间对于高效的命中识别至关重要,即使是超大图书馆.

科学领域:

计算化学是一种计算化学.
药物发现药物发现
化学信息学化学信息学

背景情况:

20年来,虚拟查 (VS) 是药物发现的一个关键方法.
数十亿种化合物被选,报告了许多成功的VS实例.
VS方法正在不断进步,包括机器学习和基于物理的技术.

研究的目的:

审查近期在药物发现中的VS应用.
讨论计算机命中探测实验 (CACHE) 挑战的批判性评估结果.
分析成本,开源选项,化学空间覆盖面和VS的图书馆选择.

主要方法:

审查最近的虚拟查案例研究.
从CACHE挑战中分析未来的发现结果.
对VS的成本效益和开源平台的评估.

主要成果:

数十亿个分子的超大图书馆 (ULL) 可以使用先进的VS技术进行选.
未来的ULL VS活动在各种目标上取得了强大而新的成功.
有效的VS通常涉及使用更小的,针对特定目标量身定制的集中式库.

结论:

虚拟选最有效的是以适合目的的方式进行,并仔细选择化学空间.
虽然ULL选正在推进,但传统的专注图书馆仍然很有价值.
需要进一步开发VS方法,以应对更具挑战性的药物目标.

关键词:

超大的图书馆.积极学习是积极学习.化学空间化学空间停靠的对接方式击中发现发现发现发现

更多相关视频

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin

Published on: March 3, 2021

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Published on: December 1, 2020

相关概念视频

Drug Discovery: Overview

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...

Structure-Activity Relationships and Drug Design

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...