Identification of Antifungal Nature of Novel Natural Compound Corr A Using Comparative Expression Proteomics Approach

Computational biology and bioinformatics approaches have the potential to completely change the way drugs are discovered and designed. Computational methods like classification and network-based algorithms can be used to understand the mode of action and the efficacy of a given compound and to help elucidating the pathophysiology of a disease. In the present work for the identification of mode of action of natural compound (Corr A) comparative expression proteomics approach was applied. The complex genetic landscape and interaction networks were analyzed to significantly identify the response of the compound. It is evident from the results that all the sub networks generated shows that transcription factor proteins are under expressed and translational annotated protein are under expressed as well. This means that our compound is inhibiting the growth of fungus via inhibiting the expression of translational machine. Hence the result predicts that the plant extract is a viable source for being an antifungal compound (Corr A).