Structural systems biology approach delineate the functional implications of SNPs in exon junction complex interaction network

Abstract

In eukaryotes, transcripts that carry premature termination codons (PTC) leading to truncated proteins are degraded by the Nonsense Mediated Decay (NMD) machinery. Missense and nonsense Single Nucleotide Polymorphisms (SNPs) in proteins belonging to Exon junction complex (EJC) and up-frameshift protein (UPF) will compromise NMD leading to the accumulation of truncated proteins in various diseases. The EJC and UPF which are involved in NMD is a good model system to study the effect of SNPs at a system level. Despite the availability of crystal structures, computational tools, and data on mutational and deletion studies, with functional implications, an integrated effort to understand the impact of SNPs at the systems level is lacking. To study the functional consequences of missense SNPs, sequence-based techniques like SIFT and PolyPhen which classify SNPs as deleterious or non-deleterious and structure-based methods like FoldX which calculate the Delta Delta G, (ddGs, ∆∆G) are used. Using FoldX, the ddG for mutations with experimentally validated functional effects is calculated and compared with those calculated for SNPs in the same protein–protein interaction interface. Further, a model is conceived to explain the functional implications of SNPs based on the effects observed for known mutants. The results are visualized in a network format. The effects of nonsense mutations are discerned by comparing with deletion mutation studies and loss of interaction in the crystal structure. The present work not only integrates genomics, proteomics, and classical genetics with ‘Structural Biology’ but also helps to integrate it into a ‘systems-level functional network’.

Communicated by Ramaswamy H. Sarma

Keywords:

• Exon junction complex
• SNP
• structural system biology
• functional genomics
• systems biology

Authors’ contributions

Mr. Datta Darshan V. M. worked to generate data and prepared figures, Dr. Venketesh S. and Dr. Arvind K. conceptualized the idea and played a major role in the preparation of the manuscript. All the authors reviewed the manuscript.

Acknowledgements

We thank the administration of Sri Sathya Sai Institute of Higher Learning (SSSIHL), for the infrastructure support, Central Research Instruments Facility (CRIF) and research support. We are thankful to the Department of Biosciences, SSSIHL, Prasanthi Nilayam. We thank FoldX and FoldX-Yasara team for providing us with an academic license. We thank Late Prof. Rajan S. S., for his advice on structural aspects.

Disclosure statement

No, I declare that the authors have no competing interests as defined by Publishing Group.

Additional information

Funding

We acknowledge the grant support from the Department of Biotechnology-Basic Research in Modern Biology DBT (BRB): (BT/PR8226/BRB/10/1224/2013), Department of Science and Technology—The Science and Engineering Research Board–Extra Mural Research DST-SERB-EMR: (EMR/2017/005381), Department of Biotechnology – Bioinformatics facility (DBT-BIF): (BT/BI/25/063/2012), Department of Science and Technology (DST-FIST): (SR/FST/LSI-616/2014), University Grants Commission-Special Assistance Program (UGC-SAP III: F.3-19/2018/DRS-III(SAP-II)) for infrastructure funding.