Insilico Annotation and Prediction of Mutational Hotspots of Optineurin (OPTN), a Novel Approach for Structural Analysis and Peptide Designing

Author Name: *Pritam Kumar Panda, Suman Mishra, Samaya Chakra Pradhan, Biswajit Satapathy, Subhashree Hota, Piyus Pritam, Desu Jyothsna
Author Email: pritampkp15@gmail.com

Abstract

One of the major causes of blindness is primary open-angle glaucoma, which affects millions of elderly people worldwide. Optineurin (OPTN) has recently been linked to glaucoma, a major cause. Mutations in OPTN have been reported in patients, particularly those with normal pressure glaucoma. The purpose of analysis was to determine the potential regions of Optineurin protein that have maximum probability of mutations based on their structural properties. The identification of disordered regions was performed using RONN and GLOBPLOT. From the results of the disordered prediction the regions are identified which are further processed for the identification of mutation hotspot regions. The hotspots selected were further screened for the presence of 19 alternative amino acids along with the calculation of the stability changes due to these alterations using Imutant & Polyphen. The complete mutational sites annotation and structure prediction was carried out. From the mutational sites determined, various Peptides have been designed using ARGUSLAB. Geometry Optimisation was performed to stabilize the designed peptides. Mutations in the receptor Optineurin are associated with the pathogenesis of glaucoma, but the underlying molecular and structural basis is poorly understood, to trace back the structure of this protein Multiple Template Modelling approach was employed using MODELLER 9v12.The structure was further validated using SAVES SERVER which includes the parameters like PROCHECK, PROVE and can be further analysed by using other parametric calculations using RAMPAGE, QMean, Annolea, Gromos Evaluation.

Keywords

Mutational Analysis, Optineurin(OPTN), modeller9v12, SavesServer, Imutant , Polyphen ,Peptide Designing. Swiss Pdb Viewer, RAMPAGE. SWISS MODEL

Introduction

Glaucoma is a group of eye diseases causing optic nerve damage. Glaucoma is a term describing a group of ocular disorders with multi-factorial etiology united by a clinically characteristic intraocular pressure-associated optic neuropathy. The optic nerve carries images from the retina, which is the specialized light sensing tissue, to the brain so we can see. In glaucoma, eye pressure plays a role in damaging the delicate nerve fibers of the optic nerve. When a significant number of nerve fibers are damaged, blind spots develop in the field of vision. Once nerve damage and visual loss occur, it is permanent. Most people don’t notice these blind areas until much of the optic nerve damage has already occurred. If the entire nerve is destroyed, blindness results.
Glaucoma is a leading cause of blindness in the world, especially in older people. Early detection and treatment by your ophthalmologist are the keys to preventing optic nerve damage and vision loss from glaucoma. This can permanently damage vision in the affected eye(s) and lead to blindness if left untreated. It is normally associated with increased fluid pressure in the eye (aqueous humour).The term “ocular hypertension” is used for people with consistently raised intraocular pressure (IOP) without any associated optic nerve damage. Conversely, the term ‘normal tension’ or ‘low tension’ glaucoma is used for those with optic nerve damage and associated visual field loss, but normal or low IOP.
Glaucoma has been called the “silent thief of sight” because the loss of vision often occurs gradually over a long period of time, and symptoms only occur when the disease is quite advanced. Once lost, vision cannot normally be recovered, so treatment is aimed at preventing further loss Worldwide.

Conclusion

The current work aimed to characterize and annotate the Optineurin, an important protein in Glaucoma. The Sequence, Functional and Structural characterization was performed using several tools like BLASTp, SDSC BIOLOGY WORKBENCH. The possible mutational changes along with their effect on the structure and function was evaluated using POLYPHEN2, IMUTANT2.0, RONN,DISEMBL, GlobPlot. A potential hotspot for the probable onset of mutation was identified in the pattern QKEER at the position 79-GlnQ, 80-LysK, 81-GluE, 82-GluE, 83-ArgR in the sequence. The peptide was designed using ARGUS LAB and Geometry Optimization approach was made to stabilize the mutated peptide. As the 3D structure of the protein was not available in the databases Modelling approach was employed to develop the structure of the protein. Modeller9v12 was used for the same. The structure thus designed was further evaluated using Saves server such as PROCHECK and RAMPAGE.

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