There are several tools available to predict such implication, but the why of using one or even more remains unclear to me. Does someone have an idea of "the best" methods to be used. Moreover, is there an uniform approach for predicting implications. My mutations is novel and was found in a known protein in humans.
For this purpose, you ca use Foldx (predicting free energy change due to mutation in protein stability) and Modeller (structural changes in the protein).
Dear Amitabh, thanks for your reply. Would these tools be sufficient or should they be combined with other prediction tools like SIFT or Polyphen?
SIFT and Polyphen are sequnce based tools that can predict the deleterious effect based on the residue consevation whereas with (structure based) modeller u can predict structural deviation and FOLD is a force field to calculate free folding energy. combining both sequence and structure based analyzes is nothing wrong but usefull if u got a correlated result
“Life is marked by change over time, and biologists explore this
phenomenon by watching” [Henzler-Wildman and Kern, 2007].
Rather than predicting I would suggest you to go for Molecular Dynamic simulations, they will give you an atomic insight of the effect of mutation on protein dynamics.The results generated by this method are more acceptable than the one generated by nSNP predicting servers.
Yes MD can be very usefull for understanding deviations but it also requires importance of performing it at the first place. the importance of mutaion can be predicted only by understanding evolutionary conservation of wild type residue. mutaion at an unconserved site will have less or no effect on structure(may be not!!. its arguable!!). such importance canpredicted only by conservation tools like SIFT,POLYPHEN,Consurf without it Perfomring MD is meaningless..
THINK FIRST AND SIMULATE
Dear Dr Rene,
These all are prediction softwares, if you use two or more softwares, like SIFT or PolyPhen2 and prediction from all these are same, then it strengthen the prediction probability.
So different software's can be tried which have different principle to predict pathogenic.
The Site Directed Mutator (SDM) server might be useful for you. The algorithm is explained here: Worth CL, Preissner R, Blundell TL (2011) SDM–a server for predicting effects of mutations on protein stability and malfunction. Nucleic Acids Res 39: W215–22. doi: 10.1093/nar/gkr363
You are asking the best tool or the best set of tools. Yet these mentioned tools can have distinct underlying principles. The veracity of these tools are depending upon the potential functional impact of mutation that you are exploiting. For those evolutionary based tools, conserved or not conserved might does or does not matter, because the genotype-phenotype mapping can be extremely complex, i.e., considering the complexity of evolution, evolutionarily conserved mutation does not mean change of function of the protein or not. For those structural based tools, no significant stability or folding change predicted does not mean no functional change, as obviously there can be post translational modification impact.
It is a fantastic dream to predict function from sequence. I would envision a real integrated algorithm combining both or more aspects.
Dear Rene
I recently proposed that translational rate is modulated by pairs of consecutive codons or bicodons [1]. By a statistical analysis of coding sequences, we compute a rate translational measure of all bicodons. We found that bicodons associated with sequences encoding low abundant proteins are involved in translational rate attenuation. Furthermore, we observe that the misfolding in many protein, such MDR1 gene [2], is better explained by a big change in the translational rate due to the synonymous bicodon variant, rather than by a relatively small change in the codon usage.
1.- Coding translational rates: the hidden genetic code
http://biorxiv.org/content/early/2016/07/08/062935
2.- Kimchi-Sarfaty, et al. A silent polymorphism in the MDR1 gene changes substrate specificity.
Science 315, 525–528 (2007).
Dear Luis Diambra
Very Interesting "Bicodons" concept,
Do you have tool/script to identify potential bicondons effected from VCF / NGS data sets
Thanks,
Raghu
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