title: Counting the zinc-proteins encoded in the human genome.
abstract: Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, or for regulation of their activities or for structural purposes. Genome sequencing projects have provided a huge number of protein primary sequences, but, even though several different elaborate analyses and annotations have been enabled by a rich and ever-increasing portfolio of bioinformatic tools, metal-binding properties remain difficult to predict as well as to investigate experimentally. Consequently, the present knowledge about metalloproteins is only partial. The present bioinformatic research proposes a strategy to answer the question of how many and which proteins encoded in the human genome may require zinc for their physiological function. This is achieved by a combination of approaches, which include: (i) searching in the proteome for the zinc-binding patterns that, on their turn, are obtained from all available X-ray data; (ii) using libraries of metal-binding protein domains based on multiple sequence alignments of known metalloproteins obtained from the Pfam database; and (iii) mining the annotations of human gene sequences, which are based on any type of information available. It is found that 1684 proteins in the human proteome are independently identified by all three approaches as zinc-proteins, 746 are identified by two, and 777 are identified by only one method. By assuming that all proteins identified by at least two approaches are truly zinc-binding and inspecting the proteins identified by a single method, it can be proposed that ca. 2800 human proteins are potentially zinc-binding in vivo, corresponding to 10% of the human proteome, with an uncertainty of 400 sequences. Available functional information suggests that the large majority of human zinc-binding proteins are involved in the regulation of gene expression. The most abundant class of zinc-binding proteins in humans is that of zinc-fingers, with Cys4 and Cys2His2 being the most common types of coordination environment.
authors.affiliation: Magnetic Resonance Center (CERM), University of Florence, Via L. Sacconi 6, 50019 Sesto Fiorentino, Italy.
authors.forename: Claudia
authors.initials: C
authors.lastname: Andreini
authors.forename: Lucia
authors.initials: L
authors.lastname: Banci
authors.forename: Ivano
authors.initials: I
authors.lastname: Bertini
authors.forename: Antonio
authors.initials: A
authors.lastname: Rosato
mesh_terms: D019295:Computational Biology; D015894:Genome, Human; D006801:Humans; D008667:Metalloproteins / Q000235:genetics* / Q000378:metabolism*; D015032:Zinc / Q000378:metabolism*; D016335:Zinc Fingers / Q000235:genetics*
chemical_list: D008667:Metalloproteins; D015032:Zinc