Investigating the function of single nucleotide polymorphisms in the CTSB gene: a computational approach

Author:

Chitranshi Nitin12,Tiwari Amit K3,Somvanshi Pallavi4,Tripathi Pushpendra K1,Seth Prahlad K5

Affiliation:

1. Gautam Buddh Technical University, Lucknow 227202, Uttar Pradesh, India

2. Bioinformatics Centre, Biotech Park, Sector-G, Jankipuram, Lucknow-226021, Uttar Pradesh, India. .

3. Department of Biomedical Sciences, College of Veterinary Medicine, Nursing & Allied Health, Tuskegee University, Tuskegee, AL 36088, USA

4. Department of Biotechnology, TERI University, 10, Institutional Area, Vasantkunj, New Delhi 110070, India

5. Bioinformatics Centre, Biotech Park, Sector-G, Jankipuram, Lucknow-226021, Uttar Pradesh, India

Abstract

Aim: Recent genome-wide association studies have revealed large numbers of single nucleotide polymorphisms (SNPs) related to Alzheimer’s disease. Here, we have investigated the gene CTSB, which plays a crucial role in encoding CTSB, a lysosomal cysteine proteinase protein. CTSB is also involved in the proteolytic processing of amyloid precursor protein (APP), which is believed to be a causative factor in Alzheimer’s disease. Materials & methods: Several bioinformatics algorithms such as, Sorting Intolerant from Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen) and CUPSAT could identify the synonymous SNPs and nonsynonymous SNPs (nsSNPs), which are predicted to be deleterious and nondeleterious, respectively. Similar tools were used to predict the impact of single amino acid substitutions on CTSB protein activity. The FASTSNP server and UTRscan were used to predict the influence on splicing regulations. The stability and solvent-accessible surface area of modeled mutated proteins were analyzed using PBEQ solver and NetASA view. Furthermore, the DSP program was used to determine the secondary structures of the modeled protein. Results: A total of 999 SNPs in CTSB were retrieved from the SNP database; 55 nsSNPs, 35 synonymous SNPs, 165 mRNA were found in the 3´untranslated region SNPs, 12 SNPs were found in the 5´untranslated region in addition to 732 intronic SNPs. Potential functions of SNPs in the CTSB gene were identified using different web servers. For example, SIFT, PolyPhen and CUPSAT servers predicted ten nsSNPs to be intolerant, three nsSNPs to be damaging and eight nsSNPs to have the potential to destabilize protein structure. The FASTSNP server predicted 12 SNPs to influence splicing regulation, whereas two SNPs could predict a risk in the range of 3–4 (medium to high). Furthermore, mutant proteins were modeled and the total energy values were compared with the native CTSB protein. It was observed that on the surface of the protein, a mutation from threonine to serine at position 235 (rs17573) caused the greatest impact on stability. Conclusion: The genome-wide association studies database has already found rs7003814 of the CTSB gene reported against Alzheimer’s disease. Our study demonstrates the presence of other deleterious nsSNPs, which may play a crucial role in predicting Alzheimer’s disease risk.

Publisher

Future Medicine Ltd

Subject

Neurology (clinical),Neurology

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