Clinical evidence shows that dual inhibition of kinases as well angiogenesis provides ideal therapeutic option in the treatment of medullary thyroid carcinoma (MTC) than inhibiting either of these with the events separately. Although treatment with dual inhibitors has shown good clinical responses in patients with MTC, it has been associated with serious side effects. Some inhibitors are active agents for both angiogenesis or kinase activity. Owing to narrow therapeutic window of established inhibitors, the present study aims to identify high affinity dual inhibitors targeting RET and VEGFR2 respectively for kinase and angiogenesis activity. Established inhibitors like Vandetanib, Cabozantinib, Motesanib, PP121, RAF265 and Sunitinib served as query parent compounds for identification of structurally similar compounds by Tanimoto-based similarity searching with a threshold of 95% against the PubChem database. All the parent inhibitors and respective similar compounds were docked against RET and VEGFR2 in order to retrieve high affinity compounds with these two proteins. AGN-PC-0CUK9P PubCID: 59320403 a compound related to PPI21 showed almost equal affinity for RET and VEGFR2 and unlike other screened compounds with no apparent bias for either of the receptors. Further, AGN-PC-0CUK9P demonstrated appreciable interaction with both RET and VEGFR2 and superior kinase activity in addition to showed optimal ADMET properties and pharmacophore features. From our in silico investigation we suggest AGN-PC-0CUK9P as a superior dual inhibitor targeting RET and VEGFR2 with high efficacy which should be proposed for pharmacodynamic and pharmacokinetic studies for improved treatment of MTC.
Advanced tools of bioinformatics have been employed to assess the features critically required for allergenicity and cross-reactivity. A tremendous accumulation of data on plant proteins in recent years has made it possible to classify allergens in different protein families, with most food allergens grouped into four protein families. These families can be grouped together into superfamilies by comparing sequences and related structures. This information makes it possible to identify a wide range of related proteins that may result in the development of multiple food allergies that initiate the development of cross-reactive antibodies in susceptible individuals. Since peanut allergies are responsible for most episodes of food-induced anaphylaxis, a detailed immunological and molecular characterization of these allergenic components is essential to develop suitable immunotherapies. This would also allow us to screen transgenic plants for the possible development of allergens similar to those allergenic components in peanuts. Homology modeling in combination with residue-wise solvent accessibility of monomers and biological assemblies of allergens certainly gives valuable information about antigenic determinants on protein allergens. Through this review, we discuss the applications of bioinformatics tools toward the mitigation of peanut allergy.
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