Evidence map›Paper›PMID 33153432›Full record

ArticleBMC bioinformatics2020

ISSEC: inferring contacts among protein secondary structure elements using deep object detection.

Qi Zhang, Jianwei Zhu, Fusong Ju, Lupeng Kong, Shiwei Sun, Wei-Mou Zheng, Dongbo Bu

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Qi ZhangKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Jianwei ZhuKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Fusong JuKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Lupeng KongKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Shiwei SunKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Wei-Mou ZhengInstitute of Theoretical Physics, Chinese Academy of Sciences, Beijing, 100190, China.
Dongbo BuKey Lab of Intelligent Information Processing, Big Data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China. dbu@ict.ac.cn.ORCID http://orcid.org/0000-0003-4119-4238

Funding

National Key Research and Development Program of China 2018YFC0910405National Natural Science Foundation of China 31671369National Natural Science Foundation of China 31770775
6 · The paper itself

Abstract

backgroundThe formation of contacts among protein secondary structure elements (SSEs) is an important step in protein folding as it determines topology of protein tertiary structure; hence, inferring inter-SSE contacts is crucial to protein structure prediction. One of the existing strategies infers inter-SSE contacts directly from the predicted possibilities of inter-residue contacts without any preprocessing, and thus suffers from the excessive noises existing in the predicted inter-residue contacts. Another strategy defines SSEs based on protein secondary structure prediction first, and then judges whether each candidate SSE pair could form contact or not. However, it is difficult to accurately determine boundary of SSEs due to the errors in secondary structure prediction. The incorrectly-deduced SSEs definitely hinder subsequent prediction of the contacts among them.

resultsWe here report an accurate approach to infer the inter-SSE contacts (thus called as ISSEC) using the deep object detection technique. The design of ISSEC is based on the observation that, in the inter-residue contact map, the contacting SSEs usually form rectangle regions with characteristic patterns. Therefore, ISSEC infers inter-SSE contacts through detecting such rectangle regions. Unlike the existing approach directly using the predicted probabilities of inter-residue contact, ISSEC applies the deep convolution technique to extract high-level features from the inter-residue contacts. More importantly, ISSEC does not rely on the pre-defined SSEs. Instead, ISSEC enumerates multiple candidate rectangle regions in the predicted inter-residue contact map, and for each region, ISSEC calculates a confidence score to measure whether it has characteristic patterns or not. ISSEC employs greedy strategy to select non-overlapping regions with high confidence score, and finally infers inter-SSE contacts according to these regions.

conclusionsComprehensive experimental results suggested that ISSEC outperformed the state-of-the-art approaches in predicting inter-SSE contacts. We further demonstrated the successful applications of ISSEC to improve prediction of both inter-residue contacts and tertiary structure as well.

Indexed as

AlgorithmsDatabases, ProteinMembrane ProteinsProtein Conformation, beta-StrandProteinsProtein Structure, SecondaryMembrane ProteinsProteinsInter-SSE contactsProtein structureSecondary structure elements

Identifiers

PMID33153432
PMCPMC7643357

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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.