• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

对用于配体对接的基于经验和体积的溶剂化函数进行批判性评估。

Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking.

作者信息

Muniz Heloisa S, Nascimento Alessandro S

机构信息

Instituto de Física de São Carlos. Av. Trabalhador São-Carlense, 400. Centro São Carlos, SP, Brazil.

出版信息

PLoS One. 2017 Mar 21;12(3):e0174336. doi: 10.1371/journal.pone.0174336. eCollection 2017.

DOI:10.1371/journal.pone.0174336
PMID:28323889
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5360343/
Abstract

Molecular docking is an important tool for the discovery of new biologically active molecules given that the receptor structure is known. An excellent environment for the development of new methods and improvement of the current methods is being provided by the rapid growth in the number of proteins with known structure. The evaluation of the solvation energies outstands among the challenges for the modeling of the receptor-ligand interactions, especially in the context of molecular docking where a fast, though accurate, evaluation is ought to be achieved. Here we evaluated a variation of the desolvation energy model proposed by Stouten (Stouten P.F.W. et al, Molecular Simulation, 1993, 10: 97-120), or SV model. The SV model showed a linear correlation with experimentally determined solvation energies, as available in the database FreeSolv. However, when used in retrospective docking simulations using the benchmarks DUD, charged-matched DUD and DUD-Enhanced, the SV model resulted in poorer enrichments when compared to a pure force field model with no correction for solvation effects. The data provided here is consistent with other empirical solvation models employed in the context of molecular docking and indicates that a good model to account for solvent effects is still a goal to achieve. On the other hand, despite the inability to improve the enrichment of retrospective simulations, the SV solvation model showed an interesting ability to reduce the number of molecules with net charge -2 and -3 e among the top-scored molecules in a prospective test.

摘要

鉴于受体结构已知,分子对接是发现新的生物活性分子的重要工具。已知结构蛋白质数量的快速增长为新方法的开发和现有方法的改进提供了一个绝佳的环境。在受体 - 配体相互作用建模的诸多挑战中,溶剂化能的评估尤为突出,特别是在分子对接的背景下,需要实现快速且准确的评估。在此,我们评估了由斯托滕(Stouten P.F.W.等人,《分子模拟》,1993年,第10卷:97 - 120页)提出的去溶剂化能模型的一个变体,即SV模型。SV模型与数据库FreeSolv中实验测定的溶剂化能呈现出线性相关性。然而,当在使用基准数据集DUD、电荷匹配的DUD和DUD - 增强版进行回顾性对接模拟时,与未对溶剂化效应进行校正的纯力场模型相比,SV模型的富集效果较差。此处提供的数据与分子对接背景下使用的其他经验溶剂化模型一致,表明一个能解释溶剂效应的良好模型仍是有待实现的目标。另一方面,尽管无法提高回顾性模拟的富集效果,但在一项前瞻性测试中,SV溶剂化模型显示出一种有趣的能力,即能够减少得分最高的分子中净电荷为 - 2和 - 3e的分子数量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/b42a88aa84d5/pone.0174336.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/5345c0e86b02/pone.0174336.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/5c21e5d5a12d/pone.0174336.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/b26eff3ce4af/pone.0174336.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/a80599a7fad4/pone.0174336.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/de79ee41aa03/pone.0174336.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/b42a88aa84d5/pone.0174336.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/5345c0e86b02/pone.0174336.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/5c21e5d5a12d/pone.0174336.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/b26eff3ce4af/pone.0174336.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/a80599a7fad4/pone.0174336.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/de79ee41aa03/pone.0174336.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a0f4/5360343/b42a88aa84d5/pone.0174336.g006.jpg

相似文献

1
Towards a critical evaluation of an empirical and volume-based solvation function for ligand docking.对用于配体对接的基于经验和体积的溶剂化函数进行批判性评估。
PLoS One. 2017 Mar 21;12(3):e0174336. doi: 10.1371/journal.pone.0174336. eCollection 2017.
2
Accuracy comparison of several common implicit solvent models and their implementations in the context of protein-ligand binding.几种常见隐式溶剂模型在蛋白质-配体结合背景下的准确性比较及其实现方式
J Mol Graph Model. 2017 Mar;72:70-80. doi: 10.1016/j.jmgm.2016.12.011. Epub 2016 Dec 21.
3
Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.使用 FACTS 溶剂化模型进行蛋白质-配体对接计算。在 EADock 中的应用。
J Mol Recognit. 2010 Sep-Oct;23(5):457-61. doi: 10.1002/jmr.1012.
4
Ligand- and receptor-based docking with LiBELa.基于配体和受体的LiBELa对接
J Comput Aided Mol Des. 2015 Aug;29(8):713-23. doi: 10.1007/s10822-015-9856-1. Epub 2015 Jul 4.
5
AutoDock-GIST: Incorporating Thermodynamics of Active-Site Water into Scoring Function for Accurate Protein-Ligand Docking.自动对接-广义相互作用场:将活性位点水的热力学纳入评分函数以实现精确的蛋白质-配体对接。
Molecules. 2016 Nov 23;21(11):1604. doi: 10.3390/molecules21111604.
6
Ligand solvation in molecular docking.分子对接中的配体溶剂化
Proteins. 1999 Jan 1;34(1):4-16. doi: 10.1002/(sici)1097-0134(19990101)34:1<4::aid-prot2>3.0.co;2-6.
7
Multi-Body Interactions in Molecular Docking Program Devised with Key Water Molecules in Protein Binding Sites.设计具有关键结合位点水分子的分子对接程序中的多体相互作用。
Molecules. 2018 Sep 11;23(9):2321. doi: 10.3390/molecules23092321.
8
Rapid context-dependent ligand desolvation in molecular docking.快速上下文相关配体去溶剂化在分子对接中的作用。
J Chem Inf Model. 2010 Sep 27;50(9):1561-73. doi: 10.1021/ci100214a.
9
Systematic and efficient side chain optimization for molecular docking using a cheapest-path procedure.使用最便宜路径程序进行分子对接的系统和有效侧链优化。
J Comput Chem. 2013 May 30;34(14):1258-69. doi: 10.1002/jcc.23251. Epub 2013 Feb 19.
10
Testing inhomogeneous solvation theory in structure-based ligand discovery.基于结构的配体发现中不均匀溶剂化理论的测试。
Proc Natl Acad Sci U S A. 2017 Aug 15;114(33):E6839-E6846. doi: 10.1073/pnas.1703287114. Epub 2017 Jul 31.

引用本文的文献

1
Anti-Fungal Potential of Structurally Diverse FDA-Approved Therapeutics Targeting Secreted Aspartyl Proteinase (SAP) of Candida albicans: an In Silico Drug Repurposing Approach.抗真菌药物的再利用:靶向白念珠菌分泌型天冬氨酸蛋白酶(SAP)的结构多样的 FDA 批准治疗药物的抗真菌潜力:一种基于计算机的药物再利用方法。
Appl Biochem Biotechnol. 2023 Mar;195(3):1983-1998. doi: 10.1007/s12010-022-04207-w. Epub 2022 Nov 19.
2
Exploration of stilbenoid trimers as potential inhibitors of sirtuin1 enzyme using a molecular docking and molecular dynamics simulation approach.使用分子对接和分子动力学模拟方法探索芪类三聚体作为沉默调节蛋白1酶的潜在抑制剂。
RSC Adv. 2021 May 27;11(31):19323-19332. doi: 10.1039/d1ra02233d. eCollection 2021 May 24.
3

本文引用的文献

1
Ligand- and receptor-based docking with LiBELa.基于配体和受体的LiBELa对接
J Comput Aided Mol Des. 2015 Aug;29(8):713-23. doi: 10.1007/s10822-015-9856-1. Epub 2015 Jul 4.
2
FreeSolv: a database of experimental and calculated hydration free energies, with input files.FreeSolv:一个包含实验和计算得到的水合自由能以及输入文件的数据库。
J Comput Aided Mol Des. 2014 Jul;28(7):711-20. doi: 10.1007/s10822-014-9747-x. Epub 2014 Jun 14.
3
PLIC: protein-ligand interaction clusters.PLIC:蛋白配体相互作用簇。
A structure-based computational workflow to predict liability and binding modes of small molecules to hERG.
基于结构的计算工作流程,用于预测小分子与 hERG 的易感性和结合模式。
Sci Rep. 2020 Oct 1;10(1):16262. doi: 10.1038/s41598-020-72889-5.
4
Comparative Analysis of Electrostatic Models for Ligand Docking.配体对接静电模型的比较分析
Front Mol Biosci. 2019 Jul 3;6:52. doi: 10.3389/fmolb.2019.00052. eCollection 2019.
Database (Oxford). 2014 Apr 23;2014(0):bau029. doi: 10.1093/database/bau029. Print 2014.
4
SAMPL4 & DOCK3.7: lessons for automated docking procedures.SAMPL4与DOCK3.7:自动对接程序的经验教训。
J Comput Aided Mol Des. 2014 Mar;28(3):201-9. doi: 10.1007/s10822-014-9722-6. Epub 2014 Feb 11.
5
Identification of distant drug off-targets by direct superposition of binding pocket surfaces.通过结合口袋表面的直接叠加来鉴定远程药物非靶标。
PLoS One. 2013 Dec 31;8(12):e83533. doi: 10.1371/journal.pone.0083533. eCollection 2013.
6
Toward fully automated high performance computing drug discovery: a massively parallel virtual screening pipeline for docking and molecular mechanics/generalized Born surface area rescoring to improve enrichment.迈向全自动高性能计算药物发现:一种大规模并行虚拟筛选管道,用于对接和分子力学/广义 Born 表面面积再评分,以提高富集度。
J Chem Inf Model. 2014 Jan 27;54(1):324-37. doi: 10.1021/ci4005145. Epub 2014 Jan 3.
7
A comprehensive survey of small-molecule binding pockets in proteins.蛋白质中小分子结合口袋的综合调查。
PLoS Comput Biol. 2013 Oct;9(10):e1003302. doi: 10.1371/journal.pcbi.1003302. Epub 2013 Oct 24.
8
MolShaCS: a free and open source tool for ligand similarity identification based on Gaussian descriptors.MolShaCS:一个基于高斯描述符的免费开源配体相似性识别工具。
Eur J Med Chem. 2013 Jan;59:296-303. doi: 10.1016/j.ejmech.2012.11.013. Epub 2012 Nov 17.
9
Directory of useful decoys, enhanced (DUD-E): better ligands and decoys for better benchmarking.有用诱饵目录增强版(DUD-E):更好的配体和诱饵,用于更好的基准测试。
J Med Chem. 2012 Jul 26;55(14):6582-94. doi: 10.1021/jm300687e. Epub 2012 Jul 5.
10
ZINC: a free tool to discover chemistry for biology.ZINC:一款用于生物学的免费化学发现工具。
J Chem Inf Model. 2012 Jul 23;52(7):1757-68. doi: 10.1021/ci3001277. Epub 2012 Jun 15.