Figure 1.
Flow chart for Post translational modification (PTM) analysis.
Intersection between PTM related tools, databases and experimental determination techniques. In silico methods used for the analysis and storage of PTM annotations – set in the context of the experimental techniques that are used to detect them.
Figure 2.
Schema representing the process of functional assessment of SNPs by in silico methods.
SNPs were categorized based on its impact on coding region, regulatory region and post-translational modification sites. Once a tractable set of SNP is selected, in silico methods were used carefully to evaluate them based on the certain criteria specified by the users. Tools represented in shaded box were taken for our current analysis.
Table 1.
The Prediction Results of nsSNPs of human ATM Using SIFT, PolyPhen and I Mutant 3.0 algorithms.
Table 2.
List of SNPs in regulatory region found to be functionally significant by PupaSuite, UTRScan and FASTSNP.
Table 3.
Concordance Analysis between the functional consequences of each nsSNP predicted by SIFT and PolyPhen.
Table 4.
Conservation score of amino acid residues analyzed by Consurf.
Figure 3.
Summary of the multiple sequence alignment of different vertebrate sequences for PTM sites.
Human ATM gene were compared with four different species. i) Mammals- Mus musculus (EDL25796.1) and Bos Taurus (NP_001192864.1), ii) Amphibia - Xenopus tropicalis (NP_001081968.1), iii) Aves - Taeniopygia guttata (XP_002197770.1) and Gallus gallus (NP_001155872.1), iv) Actinopterygii - Danio rerio (BAD91491.1). The consensus sequence is marked by an asterisk, conserved substitution by a double dot, and semi conserved substitution by a single dot. The different sequences are ordered as in aligned results from ClustalW.
Table 5.
Prediction of various PTM residues with its positions using different In silico tools.
Table 6.
Correlation analysis between prediction score for deleterious and validated nsSNPs by In Vivo/In Vitro analysis.
Figure 4.
Integrative ranking system for nsSNPs in coding region.
Predicted SNPs were categorized into four ranking groups based on the degree of deleterious effects. Coding SNPs were evaluated based on scores from SIFT, PolyPhen and I Mutant 3.0.