Computational Strategy for Bound State Structure Prediction in Structure-Based Virtual Screening: A Case Study of Protein Tyrosine Phosphatase Receptor Type O Inhibitors-Reference-Cited by-同舟云学术

Computational Strategy for Bound State Structure Prediction in Structure-Based Virtual Screening: A Case Study of Protein Tyrosine Phosphatase Receptor Type O Inhibitors

Published:2018-10-09 Issue:11 Volume:58 Page:2331-2342
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Hou Xuben¹²^ORCID,Rooklin David²,Yang Duxiao³,Liang Xiao¹,Li Kangshuai³,Lu Jianing²,Wang Cheng²,Xiao Peng³,Zhang Yingkai²⁴^ORCID,Sun Jin-peng³^ORCID,Fang Hao¹^ORCID

Affiliation:

1. Department of Medicinal Chemistry and Key Laboratory of Chemical Biology of Natural Products (MOE), School of Pharmacy, Shandong University, Jinan, Shandong 250012, China

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

3. Key Laboratory of Experimental Teratology of the Ministry of Education and Department of Biochemistry and Molecular Biology, School of Medicine, Shandong University, Jinan, Shandong 250012, China

4. NYU-ECNU Center for Computational Chemistry, New York University−Shanghai, Shanghai 200122, China

Funder

Shandong Province

Shandong University

National Natural Science Foundation of China

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.8b00548