Evidence map›Paper›PMID 29282565›Full record

ArticleJournal of cheminformatics2017

HawkRank: a new scoring function for protein-protein docking based on weighted energy terms.

Ting Feng, Fu Chen, Yu Kang, Huiyong Sun, Hui Liu, Dan Li, Feng Zhu, Tingjun Hou

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  19. An Immunoinformatic Strategy to Develop NewInternational journal of peptide research and therapeutics · 2022
    Article
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Ting FengCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Fu ChenCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Yu KangCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Huiyong SunCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Hui LiuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Dan LiCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Feng ZhuCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
Tingjun HouCollege of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China. tingjunhou@zju.edu.cn.

Funding

the Fundamental Research Funds for the Central Universities 2017QNA7032the Fundamental Research Funds for the Central Universities 2017QNA7033the Fundamental Research Funds for the Central Universities 2017QNA7034the National Key R&D Program of China 2016YFA0501701the National Science Foundation of China 21575128the National Science Foundation of China 81302679the National Science Foundation of China 81773632
6 · The paper itself

Abstract

Deciphering the structural determinants of protein-protein interactions (PPIs) is essential to gain a deep understanding of many important biological functions in the living cells. Computational approaches for the structural modeling of PPIs, such as protein-protein docking, are quite needed to complement existing experimental techniques. The reliability of a protein-protein docking method is dependent on the ability of the scoring function to accurately distinguish the near-native binding structures from a huge number of decoys. In this study, we developed HawkRank, a novel scoring function designed for the sampling stage of protein-protein docking by summing the contributions from several energy terms, including van der Waals potentials, electrostatic potentials and desolvation potentials. First, based on the solvation free energies predicted by the Generalized Born model for ~ 800 proteins, a SASA (solvent accessible surface area)-based solvation model was developed, which can give the aqueous solvation free energies for proteins by summing the contributions of 21 atom types. Then, the van der Waals potentials and electrostatic potentials based on the Amber ff14SB force field were computed. Finally, the HawkRank scoring function was derived by determining the most optimal weights for five energy terms based on the training set. Here, MSR (modified success rate), a novel protein-protein scoring quality index, was used to assess the performance of HawkRank and three other popular protein-protein scoring functions, including ZRANK, FireDock and dDFIRE. The results show that HawkRank outperformed the other three scoring functions according to the total number of hits and MSR. HawkRank is available at http://cadd.zju.edu.cn/programs/hawkrank .

Indexed as

DockingHawkRankProtein–protein interactionScoring

Identifiers

PMID29282565
PMCPMC5745212

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.