4.7 Article

DFFR: A New Method for High-Throughput Recalibration of Automatic Force-Fields for Drugs

期刊

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
卷 16, 期 10, 页码 6598-6608

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.0c00306

关键词

-

资金

  1. Spanish Ministry of Science [RTI2018-096704-B-100]
  2. Catalan SGR
  3. Instituto Nacional de Bioinformatica
  4. European Union's Horizon 2020 Research and Innovation program [BioExcel-2 project]
  5. Biomolecular and Bioinformatics Resources Platform [ISCIII PT 13/0001/0030]
  6. Fondo Europeo de Desarrollo Regional (FEDER)
  7. MINECO Severo Ochoa Award of Excellence (Government of Spain)
  8. CDTI (Neotec grant) [EXP 00094141/SNEO-20161127]
  9. Fundacion Botin (Mind the Gap Program)
  10. BSC
  11. Horizon 2020 Research and Innovation programme of the European Union under the Marie Skl.odowska-Curie grant [752415]
  12. Marie Curie Actions (MSCA) [752415] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

We present drug force-field recalibration (DFFR), a new method for refining of automatic force-fields used to represent small drugs in docking and molecular dynamics simulations. The method is based on fine-tuning of torsional terms to obtain ensembles that reproduce observables derived from reference data. DFFR is fast and flexible and can be easily automatized for a high-throughput regime, making it useful in drug-design projects. We tested the performance of the method in a few model systems and also in a variety of druglike molecules using reference data derived from: (i) density functional theory coupled to a self-consistent reaction field (DFT/SCRF) calculations on highly populated conformers and (ii) enhanced sampling quantum mechanical/molecular mechanics (QM/MM) where the drug is reproduced at the QM level, while the solvent is represented by classical force-fields. Extension of the method to include other sources of reference data is discussed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据