Lead optimization of <i>Allium sativum</i> L. compounds for PTP1B inhibition in diabetes treatment: <i>in silico</i> molecular docking and dynamics simulation
Creators: name: Ojo, Oluwafemi Adeleke
name: Adegboyega, Abayomi Emmanuel
name: Taiwo, Odunayo Anthonia
name: Olowosoke, Christopher Busayo
name: Johnson, Grace Inioluwa
name: Umedum, Ngozi Lillian
name: Onuh, Kingsley
name: Adeduro, Mary Nneka
name: Nwobodo, Valentine Osita
name: Elekan, Ayodele O.
name: Alemika, Taiwo Emmanuel
name: Johnson, Titilayo Omolara
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Pharmacology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified

description: Protein tyrosine phosphatase 1B (PTP1B) has been identified as a promising drug target for the development of diabetes medications <i>via</i> an inhibition mechanism. Using a computational approach, this study investigates the binding mechanism of lead optimized natural compounds from <i>Allium sativum</i> against the human PTP1B. The molecular docking, induced-fit docking, and binding free energy calculations were analyzed using Schrödinger Suite 2021-2. MD simulation, and gene enrichment analysis was achieved <i>via</i> the Desmond module of Schrödinger to identify best compounds as inhibitors against PTP1B in diabetes management. The docking scores of the lead optimized compounds were good; 5280443_121 from apigenin had the best binding score of −9.345 kcal/mol, followed by 5280443_129 with a binding score of −9.200 kcal/mol, and 5280863_177 from kaempferol had a binding score of −8.528 kcal/mol, followed by 5280863_462 with a binding score of −8.338 kcal/mol. The top two lead optimized compounds, docked better than the standard PTP1B inhibitor (−7.155 kcal/mol), suggesting them as potent inhibitors than the standard PTP1B inhibitor. The outcomes of the induced-fit docking were consistent with the increased binding affinity used in the Glide computation of the five conformed poses between the derivatives (5280443_121, 5280443_129, 5280863_177, and 5280863_462) and the protein (PTP1B). Based on the binding fee energies (MM-GBSA), the lead optimized compounds from kaempferol exhibited more stability than those from apigenin. In the pharmacophore development, all the models exhibit good results across the different metrics. The best performing model with five of five matches on a 1.34 and 1.33 phase score was DDRRR_1, DDRRR_2, and DDDRR_1. The average BEDROC value (= 160.9) was 1, while the average EF 1% value across all models was 101. There were no substantial conformational modifications during the MD simulation process, indicating that the apigenin derivatives (5280443_121) was stable in the protein’s active site in 100 ns. IGF1R, EGFR, INSR, PTPN1, SRC, JAK2, GRB2, BCAR1, and IRS1 are among the 11 potential targets found in the protein–protein interaction (PPI) of <i>A. sativum</i> against PTP1B that may be important in <i>A. sativum’</i>s defense against PTP1B. Sixty-four (64) pathways were found by KEGG pathway enrichment analysis to be potentially involved in the anti-PTP1B of <i>A. sativum</i>. Consequently, data obtained indicates the effectiveness of the <i>in silico</i> studies in identifying potential lead compounds in <i>A. sativum</i> against PTP1B target.