Identification of small molecule inhibitors against Lin28/let-7 to suppress tumor progression and its alleviation role in LIN28-dependent glucose metabolism.

The reciprocal suppression of an RNA-binding protein LIN28 (human abnormal cell lineage 28) and miRNA Let-7 (Lethal 7) is considered to have a prime role in hepatocellular carcinoma (HCC). Though targeting this inhibition interaction is effective for therapeutics, it causes other unfavorable effects on glucose metabolism and increased insulin resistance. Hence, this study aims to identify small molecules targeting Lin28/let-7 interaction along with additional potency to improve insulin sensitivity. Of 22,14,996 small molecules screened by high throughput virtual screening, 6 molecules, namely 41354, 1558, 12437, 23837, 15710, and 8319 were able to block the LIN28 interaction with let-7 and increase the insulin sensitivity via interacting with PPARγ (peroxisome proliferator-activated receptors γ). MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) analysis is used to re-score the binding affinity of docked complexes. Upon further analysis, it is also seen that these molecules have superior ADME (Absorption, Distribution, Metabolism, and Excretion) properties and form stable complexes with the targets for a significant period in a biologically simulated environment (Molecular Dynamics simulation) for 100 ns. From our results, we hypothesize that these identified 6 small molecules can be potential candidates for HCC treatment and the glucose metabolic disorder caused by the HCC treatment.

In silico approaches for the identification of potential allergens among hypothetical proteins from Alternaria alternata and its functional annotation.

Direct exposure to the fungal species Alternaria alternata is a major risk factor for the development of asthma, allergic rhinitis, and inflammation. As of November 23rd 2020, the NCBI protein database showed 11,227 proteins from A. alternata genome as hypothetical proteins (HPs). Allergens are the main causative of several life-threatening diseases, especially in fungal infections. Therefore, the main aim of the study is to identify the potentially allergenic inducible proteins from the HPs in A. alternata and their associated functional assignment for the complete understanding of the complex biological systems at the molecular level. AlgPred and Structural Database of Allergenic Proteins (SDAP) were used for the prediction of potential allergens from the HPs of A. alternata. While analyzing the proteome data, 29 potential allergens were predicted by AlgPred and further screening in SDAP confirmed the allergic response of 10 proteins. Extensive bioinformatics tools including protein family classification, sequence-function relationship, protein motif discovery, pathway interactions, and intrinsic features from the amino acid sequence were used to successfully predict the probable functions of the 10 HPs. The functions of the HPs are characterized as chitin-binding, ribosomal protein P1, thaumatin, glycosyl hydrolase, and NOB1 proteins. The subcellular localization and signal peptide prediction of these 10 proteins has further provided additional information on localization and function. The allergens prediction and functional annotation of the 10 proteins may facilitate a better understanding of the allergenic mechanism of A. alternata in asthma and other diseases. The functional domain level insights and predicted structural features of the allergenic proteins help to understand the pathogenesis and host immune tolerance. The outcomes of the study would aid in the development of specific drugs to combat A. alternata infections.