A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level.
Clear evidence has shown that metal ions strongly connect and delicately tune the dynamic homeostasis in living bodies. They have been proved to be associated with protein structure, stability, regulation, and function. Even small changes in the concentration of metal ions can shift their effects fr...
| Publicado en: | BioMed Research International pp. 1 - 20 |
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| Autores principales: | , , , , , , |
| Formato: | equations & formulas pictorial review tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
3/31/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=156056518&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 156056518 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 3/31/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 156056518 156056518 156056518 10.1155/2022/8965712 156056518 ppf: 1 ppct: 19 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Comprehensive Review of Computation-Based Metal-Binding Prediction Approaches at the Residue Level. aug: au: Ye, Nan Zhou, Feng Liang, Xingchen Chai, Haiting Fan, Jianwei Li, Bo Zhang, Jian affil: School of Finance and Economics, Xinyang Agriculture and Forestry University, Xinyang 464000, China sug: subj: Metals Analysis Ions Analysis Proteins Analysis Binding Sites Homeostasis Evaluation Bioinformatics Utilization Molecular Structure High-Throughput Screening Assays Algorithms Molecular Docking Simulation ab: Clear evidence has shown that metal ions strongly connect and delicately tune the dynamic homeostasis in living bodies. They have been proved to be associated with protein structure, stability, regulation, and function. Even small changes in the concentration of metal ions can shift their effects from natural beneficial functions to harmful. This leads to degenerative diseases, malignant tumors, and cancers. Accurate characterizations and predictions of metalloproteins at the residue level promise informative clues to the investigation of intrinsic mechanisms of protein-metal ion interactions. Compared to biophysical or biochemical wet-lab technologies, computational methods provide open web interfaces of high-resolution databases and high-throughput predictors for efficient investigation of metal-binding residues. This review surveys and details 18 public databases of metal-protein binding. We collect a comprehensive set of 44 computation-based methods and classify them into four categories, namely, learning-, docking-, template-, and meta-based methods. We analyze the benchmark datasets, assessment criteria, feature construction, and algorithms. We also compare several methods on two benchmark testing datasets and include a discussion about currently publicly available predictive tools. Finally, we summarize the challenges and underlying limitations of the current studies and propose several prospective directions concerning the future development of the related databases and methods. pubtype: Academic Journal doctype: equations & formulas pictorial review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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