2-D Graphical representation of proteins based on physico-chemical properties of amino acids

2007 ◽  
Vol 440 (4-6) ◽  
pp. 291-295 ◽  
Author(s):  
Milan Randić
Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3131
Author(s):  
Olga D. Novikova ◽  
Valentina A. Khomenko ◽  
Natalia Yu. Kim ◽  
Galina N. Likhatskaya ◽  
Lyudmila A. Romanenko ◽  
...  

Marinomonas primoryensis KMM 3633T, extreme living marine bacterium was isolated from a sample of coastal sea ice in the Amursky Bay near Vladivostok, Russia. The goal of our investigation is to study outer membrane channels determining cell permeability. Porin from M. primoryensis KMM 3633T (MpOmp) has been isolated and characterized. Amino acid analysis and whole genome sequencing were the sources of amino acid data of porin, identified as Porin_4 according to the conservative domain searching. The amino acid composition of MpOmp distinguished by high content of acidic amino acids and low content of sulfur-containing amino acids, but there are no tryptophan residues in its molecule. The native MpOmp existed as a trimer. The reconstitution of MpOmp into black lipid membranes demonstrated its ability to form ion channels whose conductivity depends on the electrolyte concentration. The spatial structure of MpOmp had features typical for the classical gram-negative porins. However, the oligomeric structure of isolated MpOmp was distinguished by very low stability: heat-modified monomer was already observed at 30 °C. The data obtained suggest the stabilizing role of lipids in the natural membrane of marine bacteria in the formation of the oligomeric structure of porin.


Author(s):  
David Cavanaugh ◽  
Krishnan Chittur

In a previous paper we have introduced a new hydrophobicity proclivity scale and justified its superior performance characteristics, particularly in the context of a scale for protein alignments, but also for its strong correlation with many other amino-acid physico-chemical properties. Within that paper, we calculated a corrected free energy of residue burial of each amino-acid in folded proteins from a linear regression of amino-acid free energy of transfer from water to n-Octanol (F&P octanol scale dGow, Y axis) and our Hydrophobicity Proclivity Scale<br>(HPS, X axis). In this present paper we pursue the latter general findings in more detail by considering the relationship of hydrophobicity and other physico-amino-<br>acid scales with the molecular geometry of amino-acids and secondary group structure/surface chemistry, with a concommitant discussion of the dimensions/geometry<br>of the caveties that amino-acids make in water. We identify a series of molecular physico-chemical properties that uniquely define the natural selection and geometry of the 20 natural amino-acids. We use the corrected free energy of amino-acid burials in proteins (Y axis) and a multiple linear regression to identify the AA molecular physico-chemical properties (X1, X2, ...) that explain the energetics of amino-<br>acid water contacts in an unfolded protein state to that of the folded protein state by modeling these two states as a solvent-solvent transfer, thus, providing a thermodynamical model for the initial stages of protein folding. Between our previous paper and the current paper we can greatly simplify and reduce the very large number of amino-acid scales in the literature to a small number of amino-acid property scales. Finally, we explore the numerical relationship between the structure of the genetic code and molecular physico-chemical properties of AA’s that in turn can be related directly to hydrophobicity. We validate and explain our novel models we describe herein with extensive data from the literature.<br>


2020 ◽  
Author(s):  
David Cavanaugh ◽  
Krishnan Chittur

In a previous paper we have introduced a new hydrophobicity proclivity scale and justified its superior performance characteristics, particularly in the context of a scale for protein alignments, but also for its strong correlation with many other amino-acid physico-chemical properties. Within that paper, we calculated a corrected free energy of residue burial of each amino-acid in folded proteins from a linear regression of amino-acid free energy of transfer from water to n-Octanol (F&P octanol scale dGow, Y axis) and our Hydrophobicity Proclivity Scale<br>(HPS, X axis). In this present paper we pursue the latter general findings in more detail by considering the relationship of hydrophobicity and other physico-amino-<br>acid scales with the molecular geometry of amino-acids and secondary group structure/surface chemistry, with a concommitant discussion of the dimensions/geometry<br>of the caveties that amino-acids make in water. We identify a series of molecular physico-chemical properties that uniquely define the natural selection and geometry of the 20 natural amino-acids. We use the corrected free energy of amino-acid burials in proteins (Y axis) and a multiple linear regression to identify the AA molecular physico-chemical properties (X1, X2, ...) that explain the energetics of amino-<br>acid water contacts in an unfolded protein state to that of the folded protein state by modeling these two states as a solvent-solvent transfer, thus, providing a thermodynamical model for the initial stages of protein folding. Between our previous paper and the current paper we can greatly simplify and reduce the very large number of amino-acid scales in the literature to a small number of amino-acid property scales. Finally, we explore the numerical relationship between the structure of the genetic code and molecular physico-chemical properties of AA’s that in turn can be related directly to hydrophobicity. We validate and explain our novel models we describe herein with extensive data from the literature.<br>


PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10436
Author(s):  
Mikhail Moldovan ◽  
Mikhail S. Gelfand

Background Protein phosphorylation is the best studied post-translational modification strongly influencing protein function. Phosphorylated amino acids not only differ in physico-chemical properties from non-phosphorylated counterparts, but also exhibit different evolutionary patterns, tending to mutate to and originate from negatively charged amino acids (NCAs). The distribution of phosphosites along protein sequences is non-uniform, as phosphosites tend to cluster, forming so-called phospho-islands. Methods Here, we have developed a hidden Markov model-based procedure for the identification of phospho-islands and studied the properties of the obtained phosphorylation clusters. To check robustness of evolutionary analysis, we consider different models for the reconstructions of ancestral phosphorylation states. Results Clustered phosphosites differ from individual phosphosites in several functional and evolutionary aspects including underrepresentation of phosphotyrosines, higher conservation, more frequent mutations to NCAs. The spectrum of tissues, frequencies of specific phosphorylation contexts, and mutational patterns observed near clustered sites also are different.


2018 ◽  
Vol 69 (6) ◽  
pp. 1398-1402 ◽  
Author(s):  
Livia Apostol ◽  
Lavinia Berca ◽  
Claudia Mosoiu ◽  
Mihaela Badea ◽  
Simona Bungau ◽  
...  

Pumpkin (Cucurbita maxima) seeds are a rich source of ingredients such as aminoacids, fatty acids, minerals, and phytochemicals exhibiting nutraceutical effects on human health. In this work, partially defatted pumpkin seeds flour, a by-product obtained during the manufacture of pumpkin seeds oil, was studied as an additive for common wheat flour. We explored the physico-chemical properties as well the content in amino acids of the partially defatted pumpkin seeds. The obtained results revealed that partially defatted pumpkin seeds are a good source of protein (42.75% d.m.), lipids (12.28% d.m.), total carbohydrates (37.4% d.m.), from which crude fiber (26.64% d.m.). This by-product presents a high mineral content (mg/100g): potassium (1290), magnesium (693), iron (87.8), zinc (11.5) and copper (2.49).The partially defatted pumpkin seeds proteins contain significant amounts of essential amino acids such as valine, histidine, isoleucine, leucine, threonine and methionine.


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