In Silico Evidence for Prednisone and Progesterone Efficacy in Recurrent Implantation Failure Treatment Publisher Pubmed



Mahdian S¹ ; Zarrabi M² ; Moini A^{3, 4, 5} ; Shahhoseini M^{6, 7} ; Movahedi M¹ Show Affiliations
Source: Journal of Molecular Modeling Published:2022

Abstract

Increased expression and activation of tumor necrosis factor-α (TNF-α) could lead to recurrent implantation failure (RIF). Therefore, TNF-α inhibition may be a strategic way to enhance the implantation rate in women with RIF. Nowadays, monoclonal antibodies are considered an effective therapeutic method for TNF-α inhibition. Unfortunately, monoclonal antibody treatments have several disadvantages. Thus, the design of small molecules capable of inhibiting TNF-α has become critical in recent years. In silico drug repurposing of FDA-approved drugs for TNF-α inhibition was used in this study. PyRx tools were employed for virtual screening. Additionally, the free energy of binding, the number of hydrogen bonds, and the number of drug contacts with the protein were calculated using the molecular dynamics (MD) simulation method. Virtual screening results reveal that 17 of 2471 FDA-approved drugs benefited from favorable binding energy with TNF-α (delta G < − 10 kcal/mol). Two of the 17 drugs, progesterone and prednisone, were the most frequently used without adverse effects during pregnancy. As a result, MD simulation was used to investigate these two drugs further. According to the MD simulation results, prednisone appears to have a higher affinity for TNF-α than progesterone, and consequently, the prednisone complex stability is higher. For the first time, this study examined the possible role of prednisone and progesterone in inhibiting TNF-α using in silico methods. Graphical abstract: [Figure not available: see fulltext.] © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.