virusMED: an atlas of hotspots of viral proteins

Zhang, Huihui; Chen, Pei; Ma, Huijuan; Woińska, Magdalena; Liu, Dejian; Cooper, David R.; Peng, Guo; Peng, Yousong; Deng, Lei; Minor, Władek; Zheng, Heping

doi:10.1107/s2052252521009076

Cited by 5 publications

(1 citation statement)

References 75 publications

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“…VirusMED (https://virusmed.biocloud.top/ (accessed on 5 July 2022)) is a database of epitopes, drug-binding site and metal-binding sites in viral proteins of known 3D structures [71]. For metal-binding sites, this database provides information on the coordination bonds between the protein and the metal ion(s).…”

Section: Metalloprotein Databasesmentioning

confidence: 99%

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

Andreini

Rosato

2022

IJMS

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All living organisms require metal ions for their energy production and metabolic and biosynthetic processes. Within cells, the metal ions involved in the formation of adducts interact with metabolites and macromolecules (proteins and nucleic acids). The proteins that require binding to one or more metal ions in order to be able to carry out their physiological function are called metalloproteins. About one third of all protein structures in the Protein Data Bank involve metalloproteins. Over the past few years there has been tremendous progress in the number of computational tools and techniques making use of 3D structural information to support the investigation of metalloproteins. This trend has been boosted by the successful applications of neural networks and machine/deep learning approaches in molecular and structural biology at large. In this review, we discuss recent advances in the development and availability of resources dealing with metalloproteins from a structure-based perspective. We start by addressing tools for the prediction of metal-binding sites (MBSs) using structural information on apo-proteins. Then, we provide an overview of the methods for and lessons learned from the structural comparison of MBSs in a fold-independent manner. We then move to describing databases of metalloprotein/MBS structures. Finally, we summarizing recent ML/DL applications enhancing the functional interpretation of metalloprotein structures.

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Section: Metalloprotein Databasesmentioning

confidence: 99%

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

Andreini

Rosato

2022

IJMS

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Structural biology and public health response to biomedical threats

Lenkiewicz,

Bijak,

Poonuganti

et al. 2023

Structural Dynamics

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Over the course of the pandemic caused by SARS-CoV-2, structural biologists have worked hand in hand with groups developing vaccines and treatments. However, relying solely on in vitro and clinical studies may be insufficient to guide vaccination and treatment developments, and other healthcare policies during virus mutations or peaks in infections and fatalities. Therefore, it is crucial to track statistical data related to the number of infections, deaths, and vaccinations in specific regions and present it in an easy-to-understand way.

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CytoSIP: An annotated structural atlas for interactions involving cytokine or cytokine receptor

Wang

Sun

et al. 2023

Preprint

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Therapeutic agents targeting cytokine-cytokine receptor (CK-CKR) interactions lead to the disruption in cellular signaling and are effective in treating many diseases including tumors. However, a lack of universal and quick access to annotated structural surface regions on CK/CKR has limited the progress of a structure-driven approach in developing targeted macromolecular drugs and precision medicine therapeutics. Herein we report CytoSIP (Single nucleotide polymorphisms (SNPs), Interface, and Phenotype), a database-driven internet application based on atomic interactions around hotspots in experimentally determined CK/CKR structural complexes. CytoSIP contains: (1) SNPs on CK/CKR; (2) interactions involving CK/CKR domains, including CK/CKR interfaces, oligomeric interfaces, epitopes, or other drug-targeting surfaces; and (3) diseases and phenotypes associated with CK/CKR or SNPs. The database framework introduces a unique tri-level SIP data model to bridge genetic variants (atomic level) to disease phenotypes (organism level) using protein structure (complexes) as an underlying framework (molecule level). Customized screening tools are implemented to retrieve relevant CK/CKR subset, which reduces the time and resources needed to interrogate large datasets involving CK/CKR surface hotspots and associated pathologies. CytoSIP portal is publicly accessible (https://CytoSIP.biocloud.top), facilitating the panoramic investigation of the context-dependent crosstalk between CK/CKR and the development of targeted therapeutic agents.

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virusMED: an atlas of hotspots of viral proteins

Cited by 5 publications

References 75 publications

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

Structural Bioinformatics and Deep Learning of Metalloproteins: Recent Advances and Applications

Structural biology and public health response to biomedical threats

CytoSIP: An annotated structural atlas for interactions involving cytokine or cytokine receptor

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