Assessing the performance of MM/PBSA and MM/GBSA methods. 10. Prediction reliability of binding affinities and binding poses for RNA–ligand complexes-Reference-Cited by-同舟云学术

Assessing the performance of MM/PBSA and MM/GBSA methods. 10. Prediction reliability of binding affinities and binding poses for RNA–ligand complexes

Published:2024 Issue:13 Volume:26 Page:10323-10335
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Jiang Dejun¹²,Du Hongyan¹,Zhao Huifeng¹²,Deng Yafeng²,Wu Zhenxing¹,Wang Jike¹^ORCID,Zeng Yundian¹,Zhang Haotian¹,Wang Xiaorui³,Wang Ercheng⁴,Hou Tingjun¹^ORCID,Hsieh Chang-Yu¹^ORCID

Affiliation:

1. Innovation Institute for Artificial Intelligence in Medicine of Zhejiang University, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China

2. Hangzhou Carbonsilicon AI Technology Co., Ltd, Hangzhou, Zhejiang 310018, China

3. China State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau 999078, China

4. Zhejiang Laboratory, Hangzhou, Zhejiang 311100, China

Abstract

The first study to evaluate the capability of MM/PBSA and MM/GBSA to predict the binding affinities and recognize the near-native binding poses for RNA-ligand systems.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province

China Postdoctoral Science Foundation

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/CP/D3CP04366E

Reference74 articles.

1. Neurocomputational models of altruistic decision‐making and social motives: Advances, pitfalls, and future directions

2. Computer-aided design of RNA-targeted small molecules: A growing need in drug discovery

3. Tertiary Motifs in RNA Structure and Folding

4. Design of RNA-binding proteins and ligands

5. ITScore-NL: An Iterative Knowledge-Based Scoring Function for Nucleic Acid–Ligand Interactions

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