Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions-Reference-Cited by-同舟云学术

Incorporating Explicit Water Molecules and Ligand Conformation Stability in Machine-Learning Scoring Functions

Published:2019-10-22 Issue:11 Volume:59 Page:4540-4549
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Lu Jianing¹,Hou Xuben¹²^ORCID,Wang Cheng¹,Zhang Yingkai¹³^ORCID

Affiliation:

1. Department of Chemistry, New York University, New York, New York 10003, United States

2. Department of Medicinal Chemistry, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Science, Shandong University, Jinan, Shandong 250012, China

3. NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China

Funder

National Institute of General Medical Sciences

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.9b00645

Reference93 articles.

1. Computational protein–ligand docking and virtual drug screening with the AutoDock suite

2. Docking Screens for Novel Ligands Conferring New Biology

3. Ultra-large library docking for discovering new chemotypes

4. Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

5. Comparative Assessment of Scoring Functions on a Diverse Test Set

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