Identification of molecular signatures and molecular dynamics simulation of highly deleterious missense variants of key autophagy regulator beclin 1: a computational based approach

AbstractBeclin 1 is a key autophagy regulator that also plays significant roles in other intracellular processes such as vacuolar protein sorting. Beclin 1 protein functions as a scaffold in the formation of a multiprotein assemblage during autophagy. Beclin 1 is involved in various diseases such as cancers, neurodegenerative and autophagy-related disorders. In this study, we have used various in silico tools to scan beclin 1 at the molecular level to find its molecular signatures. We have predicted and analysed deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) of beclin 1 causing alterations in its structure and also affecting its interactions with other proteins. In total, twelve coding region deleterious variants were predicted using sequence-based tools and nine were predicted using various structure-based tools. The molecular dynamics (MD) simulations revealed an altered stability of the native structure due to the introduction of mutations. Destabilization of beclin 1 ECD domain was observed due to nsSNPs W300R and E302K. Beclin 1 deleterious nsSNPs were predicted to show significant effects on beclin 1 interactions with ATG14L1, UVRAG and VPS34 proteins and were also predicted to alter the protein-protein interface of beclin 1 complexes. Additionally, beclin 1 was predicted to have thirty-one potential phosphorylation and three ubiquitination sites. In conclusion, the molecular details of beclin 1 could help in the better understanding of its functioning. The study of nsSNPs and their effect on beclin 1 and its interactions might aid in understanding the basis of anomalies caused due to beclin 1 dysfunction.Communicated by Ramaswamy H. SarmaKeywords: Beclin 1autophagyin-silico analysissingle nucleotide polymorphismmolecular dynamics simulationsintrinsically disordered regionprotein-protein interaction AcknowledgementsThe facilities provided by the Jaypee University of Information Technology, Solan, Himachal Pradesh, India to carry out this research work are duly acknowledged. The authors also acknowledge the help provided by Dr Shikha Mittal during the MSA analysis.Author contributionsSargeet Kaur: performed and analyzed in silico data, writing the first draft of the manuscript. Jitendraa Vashistt: analyzed data, writing the first draft. Harish Changotra: Study concept and design, analyzed data, edited the first draft of the manuscript and supervised.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe author(s) reported there is no funding associated with the work featured in this article.