Inter Carbon Distance from Nearest Atom Reveal Presence of Various Functional Units in Proteins

Introduction

Carbon seems to be playing an important role in biology and materials. Interestingly the newly identified carbon distribution is working out to be crucial for dealing of biochemical reactions [1, 2, 3]. One such a thorough understanding in biology is identified in proteins. Carbon value in proteins identified to be 0.3144 in global one [4, 5, 6, 7]. Whenever a protein having this fraction either in local or global structure is considered as stable, one accordingly any deviation considered as disorder [8, 9, 10]. Sometime this disorder helps in protein’s interactions with other macromolecules. This order and disorders in proteins can be identified using one dimensional sequence information and also from 3D structures. The 3D structures require being with hydrogen atoms attached to it. This is possible from NMR structures or otherwise X-ray structures added with hydrogen atoms computationally. These 3D structures yielded good results in predicting active sites, order, disordered, carbon-rich and poor-carbon regions. These structures require advanced technology to get the input parameters. Otherwise one cannot get this carbon fraction 0.3144 in protein’s 3D structures. Most often the 3D structures are obtained from X-ray crystallography which does not have hydrogen atoms. Having these difficulty and also observed to be the carbon-carbon distances are crucial in maintaining 3D structures, the current study focuses on how the carbon-carbon distances distributed all over the structures and how it vary from one locations to another. For example the distance distribution in active sites, carbon- rich or poor-carbon regions is analysed. Carbon optimised regions are expectedly form evenly distributed and particular carbon-carbon distance called optimum distance.

Results and Discussion

accounting these fractions in each category are taken for further analysis and observation. Observations are further looked into COD, active one, carbon-rich or poor-carbon regions. Other parameter like number of carbon in each sphere is taken in the array for verification as to whether the centre of atoms is located near surface or in the interior of the protein. Here the center of atoms is taken to be alpha one but may be anything which are common in all amino acids that is to say O, C, N, HA etc. that and all found in the main chain of the protein. One comparison for different center atoms is done for variation in distribution. Side chain atoms are not considered as it varies from one another and observations cannot be generalised.

Value of carbon in protein one needs to be taken accurately to identify the defective part or domain one. In this value analysis it is considered here the carbon distribution in each amino acid center. Otherwise it is a detailed analysis on how close the carbon with one another fabricated for possible stability and function. As per analysis a center of atom is chosen from main chain and carbon atoms within the range of 16Å are taken for minimum distance verification. Minimum distance in the sense that closest non-bonded carbon atom to another one. Each carbon will have only one nearest atom. Let’s say there are 80 carbon atoms in a circle and there will be 80 minimum distance for distribution analysis.

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Carbon profile of protein one analysed in term of nearest carbon distance. It is analysed for several proteins. Observations are that the protein prefers to have minimum distance of carbon with one another near 2.5. Varying value is observed. Values vary from 2.1 to 3.1. But majority are observed between 2.4 and 2.6 (Figure 1). More than 80% of the distances are observed in this range. There are distances which are less than 2.1 and more than 3.1. These

are uncommon and observed to be defective one. Active sites are found out to be in domain one while the center of active one non-ICOD. So the active one mostly found near 2.5 with varying degrees at the centred. Otherwise the ICOD is found out to be near 2.5 whereas the carbon-rich regions are mostly found below 2.5. The poor-carbon regions managed to get sufficient number at 2.5 with significant numbers below 2.4. In these kinds of observations one can go on for possible mutations that lead to stability of the protein [11]. The higher end and lower values needs to be mutated leading to carbon values near 2.5. One can be analyse the active regions while in stability factor is considered. Active sites needed to be dealt separately for mutation whether going for stabilising the active site or activating further. Based on these observations one can go for active site finding from this carbon-carbon distance distribution.

This kind of analyses requires pdb structure with carbon coordinates only. That is structure need not have hydrogen atom. That is to say NMR structure not necessary. If there structure with hydrogen atom added to it well it helps further with other ICOD analyses which support these simple findings from carbon coordinates. Generally all these findings of active sites and ICODs can be achieved at sequence level. These also found using all atom 3D structure. Here it is reported with simple carbon coordinates alone. This way one can even identify single most amino acid contributing to instability or activity. The disease proteins involved based on carbon distribution [12, 13, 14] can be solved by this way. One such challenge is that the role of large hydrophobic residues in protein stability [15] is based on this carbon profile of interaction and also pattern recognition [16].

In order to identify any variation of distance distribution with respect to center of atom, it’s been tested with different center of atoms. Particularly variation of distance distribution with center of atoms CA and O are valuated. There is no significant change in distribution overall but mild variation at individual ranges.

Conclusion

The distance between carbon and a nearest carbon are analysed for a group of carbon atoms present in specified diameter. This nearest non-bonded distances is found maximum at 2.5Å. Any deviations from this value are found disordered regions. The disordered regions include carbon- rich and active regions. The analysis can also identify ICOD regions and amino acid sites for mutational study. Using this distance distribution analysis, one can identify active site, order, disorder, carbon-rich and poor-carbon regions. This analysis requires X-ray coordinates of carbon atoms alone.