Prediction of G-protein Coupled Receptors using Deep Learning: A Review

Anuj Singh, Arvind Kumar Tiwari

2021

Abstract

The biggest super classes of the membrane proteins are G-protein coupled receptors as well as GPCRs are very significant for drug design goals. GPCRs are sometimes known as heptahelical receptor as well as seven-transmembrane receptor. GPCRs are accountable for several physicochemical and biological activities like cellular growth, neurotransmission, smell as well as vision. This paper presents a review related to current approaches to predict GPCRs. Extensive research on GPCRs have progressed to novel discoveries that open undiscovered and promising drug design opportunities and efficient drug-targeting G-protein coupled receptors therapies. This paper concentrates primarily on the process of deep learning to estimate GPCRs

Paper Citation

in Harvard Style

Singh A. and Tiwari A. (2021). Prediction of G-protein Coupled Receptors using Deep Learning: A Review. In Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE, ISBN 978-989-758-544-9, pages 101-105. DOI: 10.5220/0010563200003161

in Bibtex Style

@conference{icacse21,
author={Anuj Singh and Arvind Kumar Tiwari},
title={Prediction of G-protein Coupled Receptors using Deep Learning: A Review},
booktitle={Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,},
year={2021},
pages={101-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010563200003161},
isbn={978-989-758-544-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,
TI - Prediction of G-protein Coupled Receptors using Deep Learning: A Review
SN - 978-989-758-544-9
AU - Singh A.
AU - Tiwari A.
PY - 2021
SP - 101
EP - 105
DO - 10.5220/0010563200003161