chilonis protein homogenate exhibited significance growth inhibitory activity against gram positive, gram negative bacterial and fungal pathogens. chilonis and the antimicrobial screening of T. Based on in silico results, Alo2 protein/knottin motif, was confirmed, which present in T.
In silico physicochemical characteristics analysis of knottin motif has revealed approximate molecular weight of 6515.76 Da, theoretical Isoelectric point (pI): 7.55 and an aliphatic index: 63.06, instability index: 32.71, and grand average of hydropathicity (GRAVY): 0.547. Further, the similarity linkage clustering was identified the knottin motif at both sequence as well as structure level for Alo2. Simultaneously the parasitoid egg homogenate was screened and subjected to antimicrobial property against pathogenic bacteria and fungal strains. chilonis transcript through sequence and phylogenetic analysis that clustered the transcript to Alo2 protein. In the present study, the bioinformatics analysis was attempted to identify T. Trichogramma chilonis is a type of egg endoparasitoid wasp, well known as a biological control agent for pests that express various proteins to sustain and grown in host egg. Cluster analysis is used as data mining model to retrieve the results.Īntimicrobial peptides (AMPs) from insects possess potent antimicrobial properties against various microbial related diseases. A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time. Protein structure determination and prediction has been a focal research subject in the field of bioinformatics due to the importance of protein structure in understanding the biological and chemical activities of organisms. In the present research work, the Chou-Fasman Method is implemented with the help of data mining. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of biology. Knowledge discovery from these large and complex databases is the key problem of this era.
The biological data is available in different formats and is comparatively more complex. As the hardware technology advancing, the cost of storing is decreasing.
\)Ī protein’s primary structure is the unique sequence of amino acids in each polypeptide chain that makes up the protein.-The research in bioinformatics has accumulated large amount of data.
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