کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9127323 | 1160209 | 2005 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Looking at structure, stability, and evolution of proteins through the principal eigenvector of contact matrices and hydrophobicity profiles
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
ژنتیک
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Looking at structure, stability, and evolution of proteins through the principal eigenvector of contact matrices and hydrophobicity profiles Looking at structure, stability, and evolution of proteins through the principal eigenvector of contact matrices and hydrophobicity profiles](/preview/png/9127323.png)
چکیده انگلیسی
We review and further develop an analytical model that describes how thermodynamic constraints on the stability of the native state influence protein evolution in a site-specific manner. To this end, we represent both protein sequences and protein structures as vectors: structures are represented by the principal eigenvector (PE) of the protein contact matrix, a quantity that resembles closely the effective connectivity of each site; sequences are represented through the “interactivity” of each amino acid type, using novel parameters that are correlated with hydropathy scales. These interactivity parameters are more strongly correlated than the other hydropathy scales that we examine with: (1) the change upon mutations of the unfolding free energy of proteins with two-states thermodynamics; (2) genomic properties as the genome-size and the genome-wide GC content; (3) the main eigenvectors of the substitution matrices. The evolutionary average of the interactivity vector correlates very strongly with the PE of a protein structure. Using this result, we derive an analytic expression for site-specific distributions of amino acids across protein families in the form of Boltzmann distributions whose “inverse temperature” is a function of the PE component. We show that our predictions are in agreement with site-specific amino acid distributions obtained from the Protein Data Bank, and we determine the mutational model that best fits the observed site-specific amino acid distributions. Interestingly, the optimal model almost minimizes the rate at which deleterious mutations are eliminated by natural selection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Gene - Volume 347, Issue 2, 14 March 2005, Pages 219-230
Journal: Gene - Volume 347, Issue 2, 14 March 2005, Pages 219-230
نویسندگان
Ugo Bastolla, Markus Porto, H. Eduardo Roman, Michele Vendruscolo,