• 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

相似文献

1
The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions.生物片段数据库(BFDb):一个用于非共价相互作用计算化学分析的开放数据平台。
J Chem Phys. 2017 Oct 28;147(16):161727. doi: 10.1063/1.5001028.
2
Calculations on noncovalent interactions and databases of benchmark interaction energies.非共价相互作用的计算和基准相互作用能数据库。
Acc Chem Res. 2012 Apr 17;45(4):663-72. doi: 10.1021/ar200255p. Epub 2012 Jan 6.
3
Improving "Silver-Standard" Benchmark Interaction Energies with Bond Functions.用键函数改进“银标准”基准相互作用能。
J Chem Theory Comput. 2018 Jun 12;14(6):3053-3070. doi: 10.1021/acs.jctc.8b00204. Epub 2018 May 30.
4
Prediction of Reaction Barriers and Thermochemical Properties with Explicitly Correlated Coupled-Cluster Methods: A Basis Set Assessment.使用显式相关耦合簇方法预测反应势垒和热化学性质:基组评估
J Chem Theory Comput. 2012 Sep 11;8(9):3175-86. doi: 10.1021/ct3005547. Epub 2012 Aug 29.
5
Electronic structure theory on modeling short-range noncovalent interactions between amino acids.电子结构理论在建模氨基酸之间短程非共价相互作用中的应用。
J Chem Phys. 2023 Mar 7;158(9):094301. doi: 10.1063/5.0138032.
6
Platinum, gold, and silver standards of intermolecular interaction energy calculations.分子间相互作用能计算的铂、金和银标准。
J Chem Phys. 2019 Aug 21;151(7):070901. doi: 10.1063/1.5116151.
7
NENCI-2021. I. A large benchmark database of non-equilibrium non-covalent interactions emphasizing close intermolecular contacts.NENCI-2021. I. 一个强调近距离分子间相互作用的非平衡非共价相互作用大型基准数据库。
J Chem Phys. 2021 Nov 14;155(18):184303. doi: 10.1063/5.0068862.
8
Accurate Interaction Energies of CO with the 20 Naturally Occurring Amino Acids.CO 与 20 种天然氨基酸的精确相互作用能。
Chemphyschem. 2023 Jul 3;24(13):e202300027. doi: 10.1002/cphc.202300027. Epub 2023 May 5.
9
Simple coupled-cluster singles and doubles method with perturbative inclusion of triples and explicitly correlated geminals: The CCSD(T)R12 model.包含微扰三重激发和显式相关双电子对的简单耦合簇单双激发方法:CCSD(T)R12模型
J Chem Phys. 2008 Jun 28;128(24):244113. doi: 10.1063/1.2939577.
10
Orbital-optimized MP2.5 and its analytic gradients: approaching CCSD(T) quality for noncovalent interactions.轨道优化的MP2.5及其解析梯度:在非共价相互作用方面逼近CCSD(T)的精度
J Chem Phys. 2014 Nov 28;141(20):204105. doi: 10.1063/1.4902226.

引用本文的文献

1
Studying Noncovalent Interactions in Molecular Systems with Machine Learning.利用机器学习研究分子系统中的非共价相互作用。
Chem Rev. 2025 Jun 25;125(12):5776-5829. doi: 10.1021/acs.chemrev.4c00893. Epub 2025 Jun 9.
2
Non-Covalent Molecular Interaction Rules to Define Internal Dimer Coordinates for Quantum Mechanical Potential Energy Scans.用于定义量子力学势能扫描内部二聚体坐标的非共价分子相互作用规则。
J Comput Chem. 2025 May 30;46(14):e70136. doi: 10.1002/jcc.70136.
3
Physics-based modeling in the new era of enzyme engineering.酶工程新时代基于物理学的建模
Nat Comput Sci. 2025 Apr;5(4):279-291. doi: 10.1038/s43588-025-00788-8. Epub 2025 Apr 24.
4
Three-Dimensional CH/π and CH/N Interactions from Quantum-Mechanical and Database Analyses.基于量子力学和数据库分析的三维CH/π和CH/N相互作用
J Chem Inf Model. 2025 Apr 28;65(8):4116-4127. doi: 10.1021/acs.jcim.5c00124. Epub 2025 Apr 14.
5
Stacking Interactions of Druglike Heterocycles with Nucleobases.类药物杂环与核碱基的堆积相互作用。
J Chem Inf Model. 2025 Apr 14;65(7):3502-3516. doi: 10.1021/acs.jcim.4c02420. Epub 2025 Mar 27.
6
Accurate Neural Network Fine-Tuning Approach for Transferable Ab Initio Energy Prediction across Varying Molecular and Crystalline Scales.用于跨不同分子和晶体尺度进行可转移从头算能量预测的精确神经网络微调方法。
J Chem Theory Comput. 2025 Feb 25;21(4):1602-1614. doi: 10.1021/acs.jctc.4c01261. Epub 2025 Feb 4.
7
The influence of model building schemes and molecular dynamics sampling on QM-cluster models: the chorismate mutase case study.模型构建方案和分子动力学采样对 QM-团簇模型的影响:分支酸变位酶案例研究。
Phys Chem Chem Phys. 2024 Apr 24;26(16):12467-12482. doi: 10.1039/d3cp06100k.
8
Computational Design of Photosensitive Polymer Templates To Drive Molecular Nanofabrication.用于驱动分子纳米制造的光敏聚合物模板的计算设计。
ACS Nano. 2024 Apr 9;18(14):9969-9979. doi: 10.1021/acsnano.3c10575. Epub 2024 Mar 28.
9
A Machine Learning Force Field for Bio-Macromolecular Modeling Based on Quantum Chemistry-Calculated Interaction Energy Datasets.基于量子化学计算的相互作用能数据集的生物大分子建模机器学习力场
Bioengineering (Basel). 2024 Jan 3;11(1):0. doi: 10.3390/bioengineering11010051.
10
Intermolecular Non-Bonded Interactions from Machine Learning Datasets.来自机器学习数据集的分子间非键相互作用
Molecules. 2023 Dec 1;28(23):7900. doi: 10.3390/molecules28237900.

本文引用的文献

1
Psi4 1.1: An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability.Psi4 1.1:一个强调自动化、高级库和互操作性的开源电子结构程序。
J Chem Theory Comput. 2017 Jul 11;13(7):3185-3197. doi: 10.1021/acs.jctc.7b00174. Epub 2017 Jun 6.
2
Overview of the SAMPL5 host-guest challenge: Are we doing better?SAMPL5主客体挑战概述:我们是否取得了进步?
J Comput Aided Mol Des. 2017 Jan;31(1):1-19. doi: 10.1007/s10822-016-9974-4. Epub 2016 Sep 22.
3
ωB97M-V: A combinatorially optimized, range-separated hybrid, meta-GGA density functional with VV10 nonlocal correlation.ωB97M-V:一种经过组合优化的、具有范围分离的杂化元广义梯度近似密度泛函,带有VV10非局域相关。
J Chem Phys. 2016 Jun 7;144(21):214110. doi: 10.1063/1.4952647.
4
Revised Damping Parameters for the D3 Dispersion Correction to Density Functional Theory.用于密度泛函理论中D3色散校正的修正阻尼参数
J Phys Chem Lett. 2016 Jun 16;7(12):2197-203. doi: 10.1021/acs.jpclett.6b00780. Epub 2016 May 27.
5
Introduction: Noncovalent Interactions.引言:非共价相互作用。
Chem Rev. 2016 May 11;116(9):4911-2. doi: 10.1021/acs.chemrev.6b00247.
6
CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma.2014年临床研究分析报告:一项使用制药行业未公开数据的基准测试。
J Chem Inf Model. 2016 Jun 27;56(6):1063-77. doi: 10.1021/acs.jcim.5b00523. Epub 2016 May 17.
7
Dispersion-Corrected Mean-Field Electronic Structure Methods.弥散修正平均场电子结构方法。
Chem Rev. 2016 May 11;116(9):5105-54. doi: 10.1021/acs.chemrev.5b00533. Epub 2016 Apr 14.
8
Benchmark Calculations of Interaction Energies in Noncovalent Complexes and Their Applications.非共价复合物相互作用能的基准计算及其应用。
Chem Rev. 2016 May 11;116(9):5038-71. doi: 10.1021/acs.chemrev.5b00526. Epub 2016 Mar 4.
9
Large-Scale Quantitative Assessment of Binding Preferences in Protein-Nucleic Acid Complexes.蛋白质-核酸复合物中结合偏好性的大规模定量评估
J Chem Theory Comput. 2015 Apr 14;11(4):1939-48. doi: 10.1021/ct501168n.
10
Design of Density Functionals by Combining the Method of Constraint Satisfaction with Parametrization for Thermochemistry, Thermochemical Kinetics, and Noncovalent Interactions.通过将约束满足方法与热化学、热化学动力学和非共价相互作用的参数化相结合来设计密度泛函
J Chem Theory Comput. 2006 Mar;2(2):364-82. doi: 10.1021/ct0502763.

生物片段数据库(BFDb):一个用于非共价相互作用计算化学分析的开放数据平台。

The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions.

机构信息

Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, USA.

Quantum Theory Project, The University of Florida, 2328 New Physics Building, Gainesville, Florida 32611-8435, USA.

出版信息

J Chem Phys. 2017 Oct 28;147(16):161727. doi: 10.1063/1.5001028.

DOI:10.1063/1.5001028
PMID:29096505
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5656042/
Abstract

Accurate potential energy models are necessary for reliable atomistic simulations of chemical phenomena. In the realm of biomolecular modeling, large systems like proteins comprise very many noncovalent interactions (NCIs) that can contribute to the protein's stability and structure. This work presents two high-quality chemical databases of common fragment interactions in biomolecular systems as extracted from high-resolution Protein DataBank crystal structures: 3380 sidechain-sidechain interactions and 100 backbone-backbone interactions that inaugurate the BioFragment Database (BFDb). Absolute interaction energies are generated with a computationally tractable explicitly correlated coupled cluster with perturbative triples [CCSD(T)-F12] "silver standard" (0.05 kcal/mol average error) for NCI that demands only a fraction of the cost of the conventional "gold standard," CCSD(T) at the complete basis set limit. By sampling extensively from biological environments, BFDb spans the natural diversity of protein NCI motifs and orientations. In addition to supplying a thorough assessment for lower scaling force-field (2), semi-empirical (3), density functional (244), and wavefunction (45) methods (comprising >1M interaction energies), BFDb provides interactive tools for running and manipulating the resulting large datasets and offers a valuable resource for potential energy model development and validation.

摘要

准确的势能模型对于化学现象的可靠原子模拟是必要的。在生物分子建模领域,蛋白质等大型系统包含许多非共价相互作用(NCIs),这些相互作用有助于蛋白质的稳定性和结构。这项工作从高分辨率蛋白质数据库晶体结构中提取了生物分子系统中常见片段相互作用的两个高质量化学数据库:3380 个侧链-侧链相互作用和 100 个骨架-骨架相互作用,开创了生物片段数据库(BFDb)。绝对相互作用能是通过具有计算可处理性的显式相关耦合簇与微扰三分量 [CCSD(T)-F12]“银标准”(NCI 的平均误差为 0.05 kcal/mol)生成的,该方法仅需要传统“金标准”CCSD(T)在完全基组极限的一小部分成本。通过从生物环境中广泛采样,BFDb 涵盖了蛋白质 NCI 基序和取向的自然多样性。除了为较低的比例力场(2)、半经验(3)、密度泛函(244)和波函数(45)方法(包括>1M 相互作用能)提供全面评估外,BFDb 还提供了用于运行和操作由此产生的大型数据集的交互工具,并为势能模型开发和验证提供了有价值的资源。