SeRenDIP: SEquential REmasteriNg to DerIve Profiles for fast and accurate predictions of PPI interface positions

Qingzhen Hou, Paul De Geest, Christian J Griffioen, Sanne Abeln, Jaap Heringa, K Anton Feenstra

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

MOTIVATION: Interpretation of ubiquitous protein sequence data has become a bottleneck in biomolecular research, due to a lack of structural and other experimental annotation data for these proteins. Prediction of protein interaction sites from sequence may be a viable substitute. We therefore recently developed a sequence-based random-forest method for protein-protein interface prediction, which yielded a significantly increased performance than other methods on both homomeric and heteromeric protein-protein interactions. Here we present a webserver that implements this method efficiently.

RESULTS: With the aim of accelerating our previous approach, we obtained sequence conservation profiles by re-mastering the alignment of homologous sequences found by PSI-BLAST. This yielded a more than ten-fold speedup and at least the same accuracy, as reported previously for our method; these results allowed us to offer the method as a webserver. The web-server interface is targeted to the non-expert user. The input is simply a sequence of the protein of interest, and the output a table with scores indicating the likelihood of having an interaction interface at a certain position. As the method is sequence-based and not sensitive to the type of protein interaction, we expect this webserver to be of interest to many biological researchers in academia and in industry.

AVAILABILITY: Webserver, source code and datasets are available at www.ibi.vu.nl/programs/serendipwww/.

Original languageEnglish
JournalBioinformatics
DOIs
Publication statusE-pub ahead of print - 22 May 2019

Fingerprint

Web Server
Proteins
Protein
Prediction
Interaction
Random Forest
Protein-protein Interaction
Protein Sequence
Substitute
Molecular Sequence Annotation
Annotation
Profile
Conservation
Likelihood
Table
Alignment
Speedup
Fold
Sequence Homology
Industry

Bibliographical note

© The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Cite this

@article{b2add4cc02ac4e32a3e5e22912b55e3e,
title = "SeRenDIP: SEquential REmasteriNg to DerIve Profiles for fast and accurate predictions of PPI interface positions",
abstract = "MOTIVATION: Interpretation of ubiquitous protein sequence data has become a bottleneck in biomolecular research, due to a lack of structural and other experimental annotation data for these proteins. Prediction of protein interaction sites from sequence may be a viable substitute. We therefore recently developed a sequence-based random-forest method for protein-protein interface prediction, which yielded a significantly increased performance than other methods on both homomeric and heteromeric protein-protein interactions. Here we present a webserver that implements this method efficiently.RESULTS: With the aim of accelerating our previous approach, we obtained sequence conservation profiles by re-mastering the alignment of homologous sequences found by PSI-BLAST. This yielded a more than ten-fold speedup and at least the same accuracy, as reported previously for our method; these results allowed us to offer the method as a webserver. The web-server interface is targeted to the non-expert user. The input is simply a sequence of the protein of interest, and the output a table with scores indicating the likelihood of having an interaction interface at a certain position. As the method is sequence-based and not sensitive to the type of protein interaction, we expect this webserver to be of interest to many biological researchers in academia and in industry.AVAILABILITY: Webserver, source code and datasets are available at www.ibi.vu.nl/programs/serendipwww/.",
author = "Qingzhen Hou and {De Geest}, Paul and Griffioen, {Christian J} and Sanne Abeln and Jaap Heringa and Feenstra, {K Anton}",
note = "{\circledC} The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.",
year = "2019",
month = "5",
day = "22",
doi = "10.1093/bioinformatics/btz428",
language = "English",
journal = "Bioinformatics",
issn = "1367-4803",
publisher = "Oxford University Press",

}

SeRenDIP : SEquential REmasteriNg to DerIve Profiles for fast and accurate predictions of PPI interface positions. / Hou, Qingzhen; De Geest, Paul; Griffioen, Christian J; Abeln, Sanne; Heringa, Jaap; Feenstra, K Anton.

In: Bioinformatics, 22.05.2019.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - SeRenDIP

T2 - SEquential REmasteriNg to DerIve Profiles for fast and accurate predictions of PPI interface positions

AU - Hou, Qingzhen

AU - De Geest, Paul

AU - Griffioen, Christian J

AU - Abeln, Sanne

AU - Heringa, Jaap

AU - Feenstra, K Anton

N1 - © The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

PY - 2019/5/22

Y1 - 2019/5/22

N2 - MOTIVATION: Interpretation of ubiquitous protein sequence data has become a bottleneck in biomolecular research, due to a lack of structural and other experimental annotation data for these proteins. Prediction of protein interaction sites from sequence may be a viable substitute. We therefore recently developed a sequence-based random-forest method for protein-protein interface prediction, which yielded a significantly increased performance than other methods on both homomeric and heteromeric protein-protein interactions. Here we present a webserver that implements this method efficiently.RESULTS: With the aim of accelerating our previous approach, we obtained sequence conservation profiles by re-mastering the alignment of homologous sequences found by PSI-BLAST. This yielded a more than ten-fold speedup and at least the same accuracy, as reported previously for our method; these results allowed us to offer the method as a webserver. The web-server interface is targeted to the non-expert user. The input is simply a sequence of the protein of interest, and the output a table with scores indicating the likelihood of having an interaction interface at a certain position. As the method is sequence-based and not sensitive to the type of protein interaction, we expect this webserver to be of interest to many biological researchers in academia and in industry.AVAILABILITY: Webserver, source code and datasets are available at www.ibi.vu.nl/programs/serendipwww/.

AB - MOTIVATION: Interpretation of ubiquitous protein sequence data has become a bottleneck in biomolecular research, due to a lack of structural and other experimental annotation data for these proteins. Prediction of protein interaction sites from sequence may be a viable substitute. We therefore recently developed a sequence-based random-forest method for protein-protein interface prediction, which yielded a significantly increased performance than other methods on both homomeric and heteromeric protein-protein interactions. Here we present a webserver that implements this method efficiently.RESULTS: With the aim of accelerating our previous approach, we obtained sequence conservation profiles by re-mastering the alignment of homologous sequences found by PSI-BLAST. This yielded a more than ten-fold speedup and at least the same accuracy, as reported previously for our method; these results allowed us to offer the method as a webserver. The web-server interface is targeted to the non-expert user. The input is simply a sequence of the protein of interest, and the output a table with scores indicating the likelihood of having an interaction interface at a certain position. As the method is sequence-based and not sensitive to the type of protein interaction, we expect this webserver to be of interest to many biological researchers in academia and in industry.AVAILABILITY: Webserver, source code and datasets are available at www.ibi.vu.nl/programs/serendipwww/.

U2 - 10.1093/bioinformatics/btz428

DO - 10.1093/bioinformatics/btz428

M3 - Article

JO - Bioinformatics

JF - Bioinformatics

SN - 1367-4803

ER -