SCREENING AND DESIGNING OF KIF5A LIKE MOTOR PROTEINS IN AMYOTROPHIC LATERAL SCLEROSIS (ALS)

Abstract

KIF5A a motor neuron protein expressed in neuron is responsible for anterograde transportation of organelles, proteins and RNA. Variation within KIF5A leading to disruption of axonal transport serve as a hallmark for various neurodegenerative diseases such as hereditary spastic paraplegia (HSP10), Charcot-Marie-Tooth disease type 2 (CMT2), amyotrophic lateral sclerosis (ALS). Amyotrophic Lateral Sclerosis (ALS) is one of the incurable motor neuron disorders in which progressive loss of upper and lower motor neuron occur, with the incidence of 1-5 per 100,000. Studies have shown KIF5A is a novel ALS gene, an association of rare KIF5A variant with was predominantly due to a mutation in splice site region which result in loss of function of KIF5A protein involved in vesicular transport in mitochondria, Golgi-ER region. Non-synonymous single nucleotide polymorphism (nsSNPs) has potential to alter structure and function of protein thus it is important to differentiate potential damaging and deleterious nsSNPs from neutral. The aim of our study is analyse the functional effect of non-synonymous single nucleotide polymorphism (nsSNPs) leading to dysfunction of KIF5A protein in axonal transport using bioinformatics tools. In-silico screening of 512 missense SNPs associated with KIF5A predicted 109 nsSNPs to be damaging in nature. Subsequent analysis of these nsSNPs predicted 5 nsSNPs (A268T, R369W, T644M, R712L and P986L) to be highly deleterious among the entire prediction program. The complete KIF5A protein structure was modeled using ab-initio modeling. The study highlighted three possible nsSNPs (T644M, R712L and P986L) to increased stability of mutant protein, thus altering the function of protein. Exact biological mechanism associated with above predicted nsSNPs still needs to validate by invitro studies. Further we designed novel synthetic compounds to inhibit Pro986Leu variant of KIF5A. A compound library was prepared that consisted of natural compounds retrieved from the ZINC database. The prepared library was then screened against this missense variant KIF5A at specific domains which is involved in ALS and then docking was done. This was completely a new approach to target ALS. The results obtained from this study need to be experimentally validated further so that we can prove our computational work and keep working in that direction with the assurance that our approach is right. The study provided a path to explore association of these predicted nsSNPs in disease susceptibility and to design target dependent drugs for therapeutic application.