A Computational Investigation on Chitosan Derivatives using Pharmacophore- based Screening, Molecular Docking, and Molecular Dynamics Simulations against Kaposi Sarcoma


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Background:Cancer is one of the most dangerous illnesses to the human body due to its severity and progressive nature. Kaposi's Sarcoma (KS) tumor can appear as painless purple spots on the legs, foot, or face. This cancer develops in the lining of lymph arteries and blood vessels. Along with the enlargement of lymph nodes, the vaginal region and the mouth portion are the additional target areas of KS. DNA-binding proteins known as Sox proteins are found in all mammals and belong to the HMG box superfamily. They controlled a wide range of developmental procedures, such as the formation of the germ layer, the growth of organs, and the selection of the cell type. Human developmental abnormalities and congenital illnesses are frequently caused by the deletion or mutation of the Sox protein.

Aim:The purpose of this study is to determine the promising Kaposi's sarcoma inhibitors through computational studies.

Objective:In this present study computational approaches were used to evaluate the anti- carcinogenic efficacy against Kaposi's sarcoma.

Methods:Ligand-based pharmacophore screening was performed utilising four different chemical libraries (Asinex, Chembridge, Specs, and NCI Natural products (NSC)) depending on the top hypothesis. The top hits were examined using molecular docking, absorption, distribution, metabolism and excretion. Highest occupied molecular orbital and lowest unoccupied molecular orbital were analysed to determine the lead compounds' biological and pharmacological efficacy. The results of the study indicated that the leading candidates were possible SOX protein inhibitors.

Conclusion:The results revealed that the top hits responded to all of the pharmacological druglikening criteria and had the best interaction residues, fitness scores, and docking scores. The resulting leads might be potential Kaposi's Sarcoma alternative treatments.

Об авторах

Kiruba Sakthivel

Department of Bioinformatics, Science Campus, Alagappa University

Email: info@benthamscience.net

Priyanka Ganapathy

Department of Physiology, Sree Balaji Medical College and Hospital

Email: info@benthamscience.net

Kirubhanand Chandrasekaran

Department of Anatomy, All India Institute of Medical Sciences

Email: info@benthamscience.net

Gowtham Subbaraj

Faculty of Allied Health Sciences, Chettinad Hospital & Research Institute, Chettinad Academy of Research and Education

Email: info@benthamscience.net

Langeswaran Kulanthaivel

Department of Bioinformatics, Science Campus, Alagappa University

Автор, ответственный за переписку.
Email: info@benthamscience.net

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