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Quartile: search.filters.quartile.Q1Subject: search.filters.subject.Bioinformatics

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    PublicationOpen Access
    Artificial intelligence approaches to human-microbiome protein-protein interactions
    (Elsevier, 2022) Lim, Hansaim; Tsai, Chung-Jung; Nussinov, Ruth; Department of Computer Engineering; Department of Chemical and Biological Engineering; Gürsoy, Attila; Keskin, Özlem; Faculty Member; Department of Computer Engineering; Department of Chemical and Biological Engineering; Koç University Research Center for Translational Medicine (KUTTAM) / Koç Üniversitesi Translasyonel Tıp Araştırma Merkezi (KUTTAM); College of Engineering; Graduate School of Sciences and Engineering; 8745; 26605; N/A
    Host-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review recent advancements in computational methods to predict microbial effects on human cells with a special focus on protein–protein interactions. We categorize recent methods from traditional ones to more recent deep learning methods, followed by several challenges and potential solutions in structure-based approaches. This review serves as a brief guide to the current status and future directions in the field.
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    PublicationOpen Access
    Web interface for 3D visualization and analysis of SARS-CoV-2-human mimicry and interactions
    (Oxford University Press (OUP), 2021) Tsai, Chung-Jung; Nussinov, Ruth; Department of Chemical and Biological Engineering; Department of Computer Engineering; Keskin, Özlem; Gürsoy, Attila; Övek, Damla; Taweel, Ameer; Abalı, Zeynep; Tezsezen, Ece; Köroğlu, Yunus Emre; Faculty Member; Department of Chemical and Biological Engineering; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; 26605; 8745; N/A; N/A; N/A; N/A; N/A
    Summary: we present a web-based server for navigating and visualizing possible interactions between SARS-CoV-2 and human host proteins. The interactions are obtained from HMI_Pred which relies on the rationale that virus proteins mimic host proteins. The structural alignment of the viral protein with one side of the human protein-protein interface determines the mimicry. The mimicked human proteins and predicted interactions, and the binding sites are presented. The user can choose one of the 18 SARS-CoV-2 protein structures and visualize the potential 3D complexes it forms with human proteins. The mimicked interface is also provided. The user can superimpose two interacting human proteins in order to see whether they bind to the same site or different sites on the viral protein. The server also tabulates all available mimicked interactions together with their match scores and number of aligned residues. This is the first server listing and cataloging all interactions between SARS-CoV-2 and human protein structures, enabled by our innovative interface mimicry strategy.