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  1. Article ; Online: Conformational diversity and protein-protein interfaces in drug repurposing in Ras signaling pathway.

    Sayin, Ahenk Zeynep / Abali, Zeynep / Senyuz, Simge / Cankara, Fatma / Gursoy, Attila / Keskin, Ozlem

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 1239

    Abstract: We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by ... ...

    Abstract We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.
    MeSH term(s) Indinavir ; Drug Repositioning ; HIV Protease Inhibitors ; Proteins/metabolism ; Signal Transduction ; ErbB Receptors/metabolism ; Pyridines ; Pyrones ; Sulfonamides
    Chemical Substances tipranavir (ZZT404XD09) ; Indinavir (5W6YA9PKKH) ; HIV Protease Inhibitors ; Proteins ; ErbB Receptors (EC 2.7.10.1) ; Pyridines ; Pyrones ; Sulfonamides
    Language English
    Publishing date 2024-01-12
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-50913-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Artificial intelligence based methods for hot spot prediction.

    Ovek, Damla / Abali, Zeynep / Zeylan, Melisa Ece / Keskin, Ozlem / Gursoy, Attila / Tuncbag, Nurcan

    Current opinion in structural biology

    2021  Volume 72, Page(s) 209–218

    Abstract: Proteins interact through their interfaces to fulfill essential functions in the cell. They bind to their partners in a highly specific manner and form complexes that have a profound effect on understanding the biological pathways they are involved in. ... ...

    Abstract Proteins interact through their interfaces to fulfill essential functions in the cell. They bind to their partners in a highly specific manner and form complexes that have a profound effect on understanding the biological pathways they are involved in. Any abnormal interactions may cause diseases. Therefore, the identification of small molecules which modulate protein interactions through their interfaces has high therapeutic potential. However, discovering such molecules is challenging. Most protein-protein binding affinity is attributed to a small set of amino acids found in protein interfaces known as hot spots. Recent studies demonstrate that drug-like small molecules specifically may bind to hot spots. Therefore, hot spot prediction is crucial. As experimental data accumulates, artificial intelligence begins to be used for computational hot spot prediction. First, we review machine learning and deep learning for computational hot spot prediction and then explain the significance of hot spots toward drug design.
    MeSH term(s) Amino Acids/chemistry ; Artificial Intelligence ; Databases, Protein ; Machine Learning ; Protein Binding ; Proteins/chemistry
    Chemical Substances Amino Acids ; Proteins
    Language English
    Publishing date 2021-12-23
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 1068353-7
    ISSN 1879-033X ; 0959-440X
    ISSN (online) 1879-033X
    ISSN 0959-440X
    DOI 10.1016/j.sbi.2021.11.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3206: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article ; Online: Web interface for 3D visualization and analysis of SARS-CoV-2-human mimicry and interactions.

    Ovek, Damla / Taweel, Ameer / Abali, Zeynep / Tezsezen, Ece / Koroglu, Yunus Emre / Tsai, Chung-Jung / Nussinov, Ruth / Keskin, Ozlem / Gursoy, Attila

    Bioinformatics (Oxford, England)

    2021  

    Abstract: 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. ... ...

    Abstract 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.
    Availability: The server is available at https://interactome.ku.edu.tr/sars/.
    Language English
    Publishing date 2021-12-02
    Publishing country England
    Document type Journal Article
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btab799
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2374: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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