{"id":3411,"date":"2025-04-10T21:15:21","date_gmt":"2025-04-10T12:15:21","guid":{"rendered":"https:\/\/misterx95.myds.me\/wordpress\/?p=3411"},"modified":"2025-04-10T21:15:23","modified_gmt":"2025-04-10T12:15:23","slug":"journal-club-2025-04-11","status":"publish","type":"post","link":"https:\/\/misterx95.myds.me\/wordpress\/?p=3411","title":{"rendered":"Journal club: 2025.04.11"},"content":{"rendered":"\n

TPepPro: a deep learning model for predicting peptide\u2013protein interactions<\/strong><\/h2>\n\n\n\n

Xiaohong Jin,\u00a0Zimeng Chen,\u00a0Dan Yu,\u00a0Qianhui Jiang,\u00a0Zhuobin Chen,\u00a0Bin Yan,\u00a0Jing Qin,\u00a0Yong Liu,\u00a0Junwen Wang\u00a0<\/p>\n\n\n\n

Bioinformatics<\/em>, Volume 41, Issue 1, January 2025, btae708, https:\/\/doi.org\/10.1093\/bioinformatics\/btae708<\/a><\/p>\n\n\n\n

Published:<\/p>\n\n\n\n

25 November 2024<\/p>\n\n\n\n

\u00a0Article history<\/a><\/p>\n\n\n\n

Abstract<\/h2>\n\n\n\n

Motivation<\/p>\n\n\n\n

Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing approval rates by the FDA of USA. To identify the most potential peptides, study on peptide-protein interactions (PepPIs) presents a very important approach but poses considerable technical challenges. In experimental aspects, the transient nature of PepPIs and the high flexibility of peptides contribute to elevated costs and inefficiency. Traditional docking and molecular dynamics simulation methods require substantial computational resources, and the predictive accuracy of their results remain unsatisfactory.<\/p>\n\n\n\n

Results<\/p>\n\n\n\n

To address this gap, we proposed TPepPro, a Transformer-based model for PepPI prediction. We trained TPepPro on a dataset of 19,187 pairs of peptide-protein complexes with both sequential and structural features. TPepPro utilizes a strategy that combines local protein sequence feature extraction with global protein structure feature extraction. Moreover, TPepPro optimizes the architecture of structural featuring neural network in BN-ReLU arrangement, which notably reduced the amount of computing resources required for PepPIs prediction. According to comparison analysis, the accuracy reached 0.855 in TPepPro, achieving an 8.1% improvement compared to the second-best model TAGPPI. TPepPro achieved an AUC of 0.922, surpassing the second-best model TAGPPI with 0.844. Moreover, the newly developed TPepPro identify certain PepPIs that can be validated according to previous experimental evidence, thus indicating the efficiency of TPepPro to detect high potential PepPIs that would be helpful for amino acid drug applications.<\/p>\n\n\n\n

Availability and implementation<\/p>\n\n\n\n

The source code of TPepPro is available at https:\/\/github.com\/wanglabhku\/TPepPro<\/a>.<\/p>\n\n\n\n

\"\"<\/a>
TPepPro: Framework <\/figcaption><\/figure>\n\n\n\n
<\/object>TPepPro_a-deep-learning-model-for-predicting-protein_peptide-interactions<\/a>Download<\/a><\/div>\n","protected":false},"excerpt":{"rendered":"

TPepPro: a deep learning model for predicting peptide\u2013protein interactions Xiaohong Jin,\u00a0Zimeng Chen,\u00a0Dan Yu,\u00a0Qianhui Jiang,\u00a0Zhuobin Chen,\u00a0Bin Yan,\u00a0Jing Qin,\u00a0Yong Liu,\u00a0Junwen Wang\u00a0 Bioinformatics, Volume 41, Issue 1, January 2025, btae708, https:\/\/doi.org\/10.1093\/bioinformatics\/btae708 Published: 25 November 2024 \u00a0Article history Abstract Motivation Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing […]<\/p>\n","protected":false},"author":14,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}}},"categories":[1],"tags":[],"_links":{"self":[{"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3411"}],"collection":[{"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3411"}],"version-history":[{"count":1,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3411\/revisions"}],"predecessor-version":[{"id":3414,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/3411\/revisions\/3414"}],"wp:attachment":[{"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3411"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3411"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/misterx95.myds.me\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3411"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}