Publication Type:

Journal Article

Source:

Journal of Chemical and Pharmaceutical Sciences, Volume 2016, p.6-9 (2016)

URL:

https://www.researchgate.net/publication/316886544_Expectation_-_Maximization_algorithm_for_protein_-_Ligand_complex_of_HFE_gene

Abstract:

In the field of pharmaceutical sciences and biomedicine, the issue of protein stabilization presumes meticulous importance. It plays a significant role in purification, formulation, and storage. Suitably folded proteins are usually stable during expression and purification. The interaction between ligands and proteins generally produces changes in protein thermal stability with changes in the midpoint denaturation temperature, enthalpy of unfolding, and heat capacity. The stability of eleven mutations of the proteins corresponding to HFE gene are identified using Random forest and Support vector machine. Various parameters like Half-life period, aliphatic index and GRAVY are computed using online webservers. Based on the machine learning techniques and the computed parameters, the ligands for HFE proteins are obtained. The contact surface area between ligand atom and protein atoms are also identified. The expectation - maximization algorithm was done on the contact surface area to test whether there exist any change in the destabilizing contact between the ligand atom and protein atoms.

Cite this Research Publication

Dr. Deepa Gopakumar O. S. and Ani R., “Expectation - Maximization algorithm for protein - Ligand complex of HFE gene”, Journal of Chemical and Pharmaceutical Sciences, vol. 2016, pp. 6-9, 2016.