LATTICE STRUCTURE AND DISTANCE MATRIX OF GENETIC CODE

2015 ◽  
Vol 23 (03) ◽  
pp. 485-504 ◽  
Author(s):  
NISHA GOHAIN ◽  
TAZID ALI ◽  
ADIL AKHTAR
Keyword(s):  
Amino Acids ◽  
Genetic Code ◽  
Lattice Structure ◽  
Real Life ◽  
Chemical Properties ◽  
Distance Matrix ◽  
Protein Molecule ◽  
Bond Number ◽  
Partial Ordering ◽  
Physico Chemical

The genetic code is the rule by which DNA stores the genetic information about formation of protein molecule. In this paper, a partial ordering is equipped on the genetic code and a lattice structure has been developed from it. The codon–anticodon interaction, hydrogen bond number and the chemical types of bases play an important role in the partial ordering. We have established some relations between the lattice structure of the genetic code and physico-chemical properties of amino acids. Taking into consideration the evolutionary importance of base positions in codons we have constructed a distance matrix for the amino acids. Further with a real life example we have demonstrated the relationship between frequently occurring mutations and codon distances.

scholarly journals Porin from Marine Bacterium Marinomonas primoryensis KMM 3633T: Isolation, Physico-Chemical Properties, and Functional Activity

Molecules ◽  
2020 ◽  
Vol 25 (14) ◽  
pp. 3131
Author(s):  
Olga D. Novikova ◽  
Valentina A. Khomenko ◽  
Natalia Yu. Kim ◽  
Galina N. Likhatskaya ◽  
Lyudmila A. Romanenko ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Lipid Membranes ◽  
Marine Bacterium ◽  
Chemical Properties ◽  
Cell Permeability ◽  
Oligomeric Structure ◽  
Black Lipid Membranes ◽  
Physico Chemical ◽  
Coastal Sea

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.

Analysis of 14 drugs in dried blood microsamples in a single workflow using whole blood and serum calibrators

Bioanalysis ◽  
2020 ◽  
Vol 12 (17) ◽  
pp. 1243-1261
Author(s):  
István Vincze ◽  
James Rudge ◽  
Barna Vásárhelyi ◽  
Gellért Balázs Karvaly
Keyword(s):  
Whole Blood ◽  
Total Error ◽  
Real Life ◽  
Chemical Properties ◽  
Extraction Methods ◽  
Therapeutic Drug ◽  
High Throughput Analysis ◽  
Method Performance ◽  
Physico Chemical ◽  
High Polarity

Aim: Multiplexed, high-throughput analysis facilitates therapeutic drug monitoring. 14 drugs with various physico-chemical properties were quantitated in dried blood microsamples. Methods: Analytes were extracted employing eight solvent compositions and seven extraction methods. The applicability of liquid serum, dried serum and dried whole blood calibrators was investigated. Results: High recoveries were attained. Calibration using dried serum yielded lowest total error. Reducing sample hematocrit caused outstanding elevations in recovery of analytes with high polarity or affinity to erythrocytes. 9-day analyte stability was demonstrated. Conclusion: Based on the analysis of spiked samples, multiplexed testing of drugs in dried blood microsamples seems feasible, but with analyte-dependent method performance. Dried serum calibration allows the adaptation of serum-based workflows. Further evaluation using real-life specimens is needed.

scholarly journals Hydrophobicity Revisited: a Molecular Story

2020 ◽  
Author(s):  
David Cavanaugh ◽  
Krishnan Chittur
Keyword(s):  
Amino Acids ◽  
Free Energy ◽  
Amino Acid ◽  
Linear Regression ◽  
Group Structure ◽  
Chemical Properties ◽  
Molecular Geometry ◽  
Superior Performance ◽  
Acid Property ◽  
Physico Chemical

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>

scholarly journals Hydrophobicity Revisited: a Molecular Story

2020 ◽  
Author(s):  
David Cavanaugh ◽  
Krishnan Chittur
Keyword(s):  
Amino Acids ◽  
Free Energy ◽  
Amino Acid ◽  
Linear Regression ◽  
Group Structure ◽  
Chemical Properties ◽  
Molecular Geometry ◽  
Superior Performance ◽  
Acid Property ◽  
Physico Chemical

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>

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