Cyberinformation Studies Of The Amino Acid Composition Insulin Biology Essay

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Abstract:This paper discusses cyberinformation studies of the amino acid composition of insulin, in particular the identification of scientific terminology that could describe this phenomenon, ie, the suty of genetic information, as well as the relationship between the genetic language of proteins and theoretical aspect of this system and cybernetics. The result of this research show that there is a matrix code for insulin. It also shows that the coding system within the amino acidic language gives detailed information, not only on the amino acid „record", but also on its structure, configuration and its various shapes. The issue of the existence of an insulin code and coding of the individual structural elements of this protein are discussed. Answers to the following questions are sought. Does the matrix mechanism for biosynthesis of this protein function within the law of the general theory of information systems, and what is the significance of this for understanding the genetic language of insulin? What is the essence of existence and functioning of this language?

Is the genetic information characterized only by biochemical, or also by cyberinformation principles? The potential effects of physical and chemical, as well as cybernetic and information ptinciples, on the biochemical basis of insulin are also investigated.This aper discusses new methods for developing genetic technologies, in particular more advanced digital technology based on programming, cybernetics, and informational laws and systems, and how this new technology could be useful in medicine, bioinformatics, genetics, biochemistry, and other natural sciences.

Keywords

Human Insulin, Insulin Model, Bio frequencies, Genetics Code; Amino acids

Introduction

The biologic role of any given protein in essential life processes, eg, insulin, depends on the positioning of its component amino acids, and is understood by the „positioning of letters forming words". Each of these words has its biochemical base. If this base is expressed by corresponding discrete numbers, it can be seen that any given base has its own program, along with its own unique cybernetics and information characteristics.

Indeed, the sequencing of the molecule is determined not only by distin biochemical features, but also by cybernetic and information principles. For this reason, research in this field deals more with the quantitative rather than qualitative characteristcs of genetic information and its biochemical basis. For the purposes of this paper, specific physical and chemical factors have been selected in order to express the genetic information for insulin.Numerical values are them assigned to these factors, enabling them to be measured. In this way it is possible to determine oif a connection really exists between the quantitative ratios in the process of transfer of genetic information and the qualitative appearance of the insulin molecule. To select these factors, preference is given to classical physical and chemical parameters, including the number of atoms in the relevant amino acids, their analog values, the position in these amino acids in the peptide chain, and their frenquencies.There is a arge numbers of these parameters, and each of their gives important genetic information. Going through this process, it becomes clear that there is a mathematical relationship between quantitative ratios and the qualitative appearance of the biochemical „genetic processes" and that there is a measurement method that can be used to describe the biochemistry of insulin.

Methods

Insulin can be represented by two different forms, ie, a discrete form and a sequential form.

In the discrete form, a molecule of insulin is represented by a set of discrete codes or a multiple dimension vector. In the sequential form, an insulin molecule is represent by a series of amino acids according to the order of their position in the chains 1AI0.

Therefore, the sequential form can naturally reflect all the information about the sequence order and lenght of an insulin molecule. The key issue is whether we can develop a different discrete method of representing an insulin molecule that will allow accomodation of partial, if not all sequence order information? Because a protein sequence is usually represented by a series of amino acids should be assigned to these codes in order to optimally convert the sequence order information into a series of numbers for the discrete form representation

R6 Insulin Hexamer

The structure 1AI0 has in total 12 chains: A,B,C,D,E,F,G,H,I,J,K,L.

In this group of chains there are three unions with four chains each. Each of these three groups of chain has an identical number of amino acids, identical numbers of atoms and an identical sum of position numbers of these amino acids.

Notes: And in that dimension we can find an explanation for the given empirical reality. Aforementioned aminoacids are positioned from number 1 to 21, and from 1 to 30. Numbers 1, 2, 3, n... present the position of a certain aminoacid.

The aforementioned aminoacids are positioned from number 1 to 30. Numbers 1, 2, 3, n... present the position of a certain aminoacid. This positioning is of the key importance for understanding of programmatic, cybernetic and information principles in this protein. The scientific key for interpretation of biochemical processes is the same for insulin as other proteins and sequences in biochemistry. The first aminoacid in chain B has 23 atoms, the second one 19, the third one 17, etc. They have exactly these numbers of atoms because there are many codes in the insulin molecule, analog codes, and other voded features. In fact, there is a cybernetic algorithm which it is „recorded" that the firs amino acid has to have 23 atoms, the second one 19, the third one 17, etc. The first amino acid has its own biochemistry, as does the second and the third, etc. The obvious conclusion is that there is a concrete relationship between quantitative ratios in the process of transfer of genetic information and qualitative appearance, ie, the characteristcs of the organism.

Bio frequency

Schematic representation of the amino acid and frequency

Insulin is composed of aminoacids with various numerical values. This numerical values are in an irregular order. For example, in chain A the first one has 10 atoms, the second one 22. Their frequency is X. Second amino acid has 22 atoms, and the third one 19. Their frequency is Y; etc... Frequency is the measurement for establishment of intervals of numerical values of amino acids in proteins. This value can be positive, negative or a zero value. These frequencies are showing us one completely new dimension of protein sequencing. Through these frequencies we can establish which of aminoacids are of primary, and which are of secondary significance in biochemical processes of insulin. Here is a concrete example:

Results:

Bio frequency of amino acids from 1 to 51 = [(-)128 ï‚« (+)128];

Therefore, there is a mathematical balance between the group of aminoacids with positive frequency and those of negative frequency. Aminoacids with a positive frequency have a primary role in the mathematical picture of that protein, and the negative frequencies have a secondary role in it. We assume that aminoacids with a positive frequency have a primary role in the biochemical picture of that protein, and the negative frequencies have a secondary role in it. If this really is the case and research on an experimental level proves it, a radically new way of learning about biochemical processes will be opened.

From 0 to 17 = 17; From 17 to 24 = 7; From 24 to 17 = (-) 7; …,From 10 to 10 = (-)10; etc

Fig.4. Schematic representation of the amino acids and bio frequency structure chain of the Insulin1AI0:A,B, from amino acids 51 to 1.

Bio frequency (+)

Bio frequency (+) = (17+7+7+1+16…, + 3) = (+)128;

Bio frequency (-)

Bio frequency (-) = [(-7) + (-2) + (-13) …+ (-10)] = (-)128;

Bio frequency of amino acids from 51 to 1 = [(-)128 ï‚« (+)128];

In this example there is a mathematical balance between the group of aminoacids with positive frequency and those of negative frequency.

Bio frequency (+)

Bio frequency (+) = (15+7+6+16…, + 10) = (+)202;

Bio frequency (-)

Bio frequency (-) = [(-10) + (-2) + (-3) …+ (-17)] = (-)202;

Bio frequency of amino acids from 51 to 1 and 51 to 1 = [(-)202 ï‚« (+)202];

There are discrete codes that can show us one radical new dimension of the genetic process functioning.

Discret codes 19 and 7

26 = (19 + 7)

{SA(R1,2,3,n) x B - SB(R1,2,3,n) x A + (AB)} = ABA;

SA, SB = Groups of AB frequencies in group of amino acids from X to Y

R1,2,3,n = Frequencies;

A = 7; B = 19;

Frequencies from 1 to 51

R = 128;

{S7(128) x 19 - S19(128) x 7 + (7x19)} = (7x19x7);

S7(128) = (122+123+124+125+126+127+128) = 875;

S19(128) = (110+111+112…, + 128) = 2261;

(875 x 19) - (2261 x 7) + (7 x 19) = (7 x 19 x 7);

Discret codes 19 and 7 > Frequency 128;

Frequencies from 3 to 49

R = 118;

{S7(118) x 19 - S19(118) x 7 + (7x19)} = (7x19x7);

{S7(118) x 19 - S19(118) x 7 + (7x19)} = (7x19x7);

S7(118) = (112+113+114+115+116+117+118) = 805;

S19(118) = (100+101+102…, + 118) = 2071;

(805 x 19) - (2071 x 7) + (7 x 19) = (7 x 19 x 7);

Discret codes 19 and 7 > Frequency 118;

Frequencies from 6 to 46

R = 110;

Discret codes 19 and 7 > Frequency 110;

Frequencies from 8 to 44

R = 97;

Discret codes 19 and 7 > Frequency 97;

Frequencies from 8 to 44

R = 97;

Discret codes 19 and 7 > Frequency 97;

Frequencies from 9 to 43

R = 94;

Discret codes 19 and 7 > Frequency 94;

Frequencies from 10 to 42

R = 87;

Discret codes 19 and 7 > Frequency 87;

Frequencies from 11 to 41

R = 70;

Discret codes 19 and 7 > Frequency 70;

Frequencies from 15 to 37

R = 66;

Discret codes 19 and 7 > Frequency 66;

etc.

Levels of frequencies

In the group of aminoacids with positive frequency there are two sub-unions. One is the sub-union with positive, and the other one is sub-union with negative frequencies. Also, in the union of aminoacids with negative frequency there are sub-unions with positive and negative frequencies. These groups also have their sub-unions with positive and negative frequencies. All these groups show us one radically new dimension of biochemistry of insulin. We expect that this discovery will help a better understanding of many secrets of biochemistry of protein.

DISCUSSION

The results of our research show that the processes of sequencing the molecules are conditioned and arranged not only with chemical and biochemical lawfulness, but also with program, cybernetic and informational lawfulness too. At the first stage of our research we replaced nucleotides from the Amino Acid Code Matrix with numbers of the atoms in those nucleotides. Translation of the biochemical language of these amino acids into a digital language may be very useful for developing new methods of predicting protein sub-cellular localization, membrane protein type, protein structure secondary prediction or any other protein attributes. Since the concept of Chou's pseudo amino acid composition was proposed 1,2, there have been many efforts to try to use various digital numbers to represent the 20 native amino acids in order to better reflect the sequence-order effects through the vehicle of pseudo amino acid composition. Some investigators used complexity measure factor 3, some used the values derived from the cellular automata 4-7, some used hydrophobic and/or hydrophilic values 8-16, some were through Fourier transform 17,18, and some used the physicochemical distance 19. It is going to be possible to use a completely new strategy of research in genetics in the future. However, close observation of all these relationships, which are the outcomes of periodic laws (more specifically the law of binary coding), stereo-chemical and digital structure of proteins.

DISCLOSURE

The author reports no conflict of interest in this research.

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