IMPContact: An Interhelical Residue Contact Prediction Method.
As an important category of proteins, alpha-helix transmembrane proteins (αTMPs) play an important role in various biological activities. Because the solved αTMP structures are inadequate, predicting the residue contacts among the transmembrane segments of an αTMP exhibits the basis of protein fold,...
| Publicado en: | BioMed Research International pp. 1 - 11 |
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| Autores principales: | , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
3/27/2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=142494628&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 142494628 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 3/27/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 142494628 142494628 142494628 10.1155/2020/4569037 142494628 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: IMPContact: An Interhelical Residue Contact Prediction Method. aug: au: Fang, Chao Jia, Yajie Hu, Lihong Lu, Yinghua Wang, Han affil: School of Information Science and Technology, Northeast Normal University, Changchun 130117, China sug: subj: Membrane Proteins Molecular Structure Neural Networks (Computer) Bioinformatics Sequence Analysis Deep Learning ab: As an important category of proteins, alpha-helix transmembrane proteins (αTMPs) play an important role in various biological activities. Because the solved αTMP structures are inadequate, predicting the residue contacts among the transmembrane segments of an αTMP exhibits the basis of protein fold, which can be used to further discover more protein functions. A few efforts have been devoted to predict the interhelical residue contact using machine learning methods based on the prior knowledge of transmembrane protein structure. However, it is still a challenge to improve the prediction accuracy, while the deep learning method provides an opportunity to utilize the structural knowledge in a different insight. For this purpose, we proposed a novel αTMP residue-residue contact prediction method IMPContact, in which a convolutional neural network (CNN) was applied to recognize those interhelical contacts in a TMP using its specific structural features. There were four sequence-based TMP-specific features selected to descript a pair of residues, namely, evolutionary covariation, predicted topology structure, residue relative position, and evolutionary conservation. An up-to-date dataset was used to train and test the IMPContact; our method achieved better performance compared to peer methods. In the case studies, IHRCs in the regular transmembrane helixes were better predicted than in the irregular ones. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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