Next Article in Journal
Detection of Beta-Glucan Contamination in Nanotechnology-Based Formulations
Next Article in Special Issue
Assessing the Direct Binding of Ark-Like E3 RING Ligases to Ubiquitin and Its Implication on Their Protein Interaction Network
Previous Article in Journal
Bidirectional Modulation of the Voltage-Gated Sodium (Nav1.6) Channel by Rationally Designed Peptidomimetics
Open AccessReview

Bioinformatics of Metalloproteins and Metalloproteomes

by 1,2,3,*,† and 1,2,3,†
1
Shenzhen Key Laboratory of Marine Bioresources and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518055, China
2
Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen 518055, China
3
Shenzhen Bay Laboratory, Shenzhen 518055, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editors: Antonio Rosato, Francesco Musiani and Claudia Andreini
Molecules 2020, 25(15), 3366; https://doi.org/10.3390/molecules25153366
Received: 17 June 2020 / Revised: 17 July 2020 / Accepted: 22 July 2020 / Published: 24 July 2020
Trace metals are inorganic elements that are required for all organisms in very low quantities. They serve as cofactors and activators of metalloproteins involved in a variety of key cellular processes. While substantial effort has been made in experimental characterization of metalloproteins and their functions, the application of bioinformatics in the research of metalloproteins and metalloproteomes is still limited. In the last few years, computational prediction and comparative genomics of metalloprotein genes have arisen, which provide significant insights into their distribution, function, and evolution in nature. This review aims to offer an overview of recent advances in bioinformatic analysis of metalloproteins, mainly focusing on metalloprotein prediction and the use of different metals across the tree of life. We describe current computational approaches for the identification of metalloprotein genes and metal-binding sites/patterns in proteins, and then introduce a set of related databases. Furthermore, we discuss the latest research progress in comparative genomics of several important metals in both prokaryotes and eukaryotes, which demonstrates divergent and dynamic evolutionary patterns of different metalloprotein families and metalloproteomes. Overall, bioinformatic studies of metalloproteins provide a foundation for systematic understanding of trace metal utilization in all three domains of life. View Full-Text
Keywords: metal; metalloprotein; metalloproteome; bioinformatics; comparative genomics; evolution metal; metalloprotein; metalloproteome; bioinformatics; comparative genomics; evolution
Show Figures

Graphical abstract

MDPI and ACS Style

Zhang, Y.; Zheng, J. Bioinformatics of Metalloproteins and Metalloproteomes. Molecules 2020, 25, 3366. https://doi.org/10.3390/molecules25153366

AMA Style

Zhang Y, Zheng J. Bioinformatics of Metalloproteins and Metalloproteomes. Molecules. 2020; 25(15):3366. https://doi.org/10.3390/molecules25153366

Chicago/Turabian Style

Zhang, Yan; Zheng, Junge. 2020. "Bioinformatics of Metalloproteins and Metalloproteomes" Molecules 25, no. 15: 3366. https://doi.org/10.3390/molecules25153366

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop