美利体育登录入口官网:药物发现中的自由能计算
On Free Energy Calculations in Drug Discovery
作者:Alessia Ghidini;Eleonora Serra;Andrea Cavalli;
DOI:https://doi.org/10.1021/acs.accounts.5c00465
引用量:64
发表时间:2025年
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美利体育登录入口官网:摘要
点击复制章节链接。章节链接已复制!下载高分辨率图像。下载MS PowerPoint幻灯片。概要:本报告讨论了结合自由能计算在药物发现中的最新进展和挑战,重点介绍两类增强采样技术:化学转换和基于路径的方法。结合自由能是药物发现中的关键指标,因为它衡量配体与其靶标受体的亲和力。自由能和亲和力指导潜在药物候选物的排名和筛选。几十年前自由能计算的理论基础已被建立,但其在药物-靶标结合中的高效应用仍是计算药物设计领域的一大挑战。主要障碍源于采样问题(因为结合是一个罕见事件)、力场精度的局限性以及模拟收敛性。目前,化学转换方法是制药行业中计算结合自由能最常用的方法。然而,尽管它们能高效计算能量差异,这些方法的应用通常局限于相对结合自由能计算。绝对且准确(误差
美利体育登录入口官网:Abstract
AbstractClick to copy section linkSection link copied!High Resolution ImageDownload MS PowerPoint SlideConspectusThis Account discusses recent progress and challenges in binding free energy computations, focusing on two classes of enhanced sampling techniques: alchemical transformations and path-based methods. Binding free energy is a crucial metric in drug discovery, as it measures the affinity of a ligand for its target receptor. Free energy and affinity guide the ranking and selection of potential drug candidates. The theoretical foundations of free energy calculations were established several decades ago, but their efficient application to drug-target binding remains a grand challenge in computational drug design. The main obstacles stem from sampling issues (as binding is a rare event), force field accuracy limitations, and simulation convergence. Alchemical transformations are now the most used methods for computing binding free energies in the pharmaceutical industry. However, while they efficiently calculate energy differences, the application of these methods is often limited to relative binding free energy calculations. Absolute and accurate (error < 1 kcal/mol) binding free energy predictions remain one of the great challenges for computational chemists and physicists. Another limitation of alchemical methods is that they lack the ability to provide mechanistic or kinetic insights into the binding process, crucial for optimizing lead compounds and designing novel therapies. Path-based methods offer, in principle, the possibility to accurately estimate absolute binding free energy while also providing insights into binding pathways and interactions.This Account explores recent advances in binding free energy methods for drug-target recognition and binding. In particular, we discuss the similarities and differences between alchemical and path-based approaches, highlighting recent innovations in both families of methods and providing perspectives from our group’s contributions. We examine the foundational role of alchemical methods, which have been employed since the inception of free energy calculations, in both equilibrium and nonequilibrium contexts. We also emphasize the growing importance of path-based methods in drug discovery and their ability to predict binding and unbinding pathways, free energy profiles, and binding free energy estimates. In particular, the combination of path methods with machine learning has proven to be a powerful means for accurate path generation and free energy estimations. Building on our recent research, we discuss several path-based applications for drug discovery. Moreover, we focus on two semiautomatic protocols representing our group’s state-of-the-art in free energy calculations. The first protocol is based on MetaDynamics simulation. From this, a recent innovation is instead based on nonequilibrium simulations combined with nonequilibrium estimators. We discuss in depth the advantages and drawbacks of equilibrium and nonequilibrium approaches to drug-target binding free energy predictions.This publication is licensed underCC-BY 4.0 . License Summary*You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.View full license *DisclaimerThis summary highlights only some of the key features and terms of the actual license. It is not a license and has no legal value. Carefully review the actual license before using these materials. License Summary*You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. View full license *DisclaimerThis summary highlights only some of the key features and terms of the actual license. It is not a license and has no legal value. Carefully review the actual license before using these materials. License Summary*You are free to share(copy and redistribute) this article in any medium or format and to adapt(remix, transform, and build upon) the material for any purpose, even commercially within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. View full license *DisclaimerThis summary highlights only some of the key features and terms of the actual license. It is not a license and has no legal value. Carefully review the actual license before using these materials. ACS PublicationsCopyright ? 2025 The Authors. Published by American Chemical SocietySubjectswhat are subjects Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Chemical calculations Computer simulations Drug discovery Ligands Thermodynamic properties
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