ABSTRACT
Background: Endometriosis is a chronic inflammatory disease defined as the presence of endometrial tissue outside the uterus, which causes pelvic pain and infertility. Cytokines appear to play vital roles in the development and progression of endometriosis and associated infertility. Tumor necrosis factoralpha (TNF-alpha) is a multifunctional pro-inflammatory cytokine, responsible for autoimmune and inflammatory disorders. TNF- alpha plays an important role in endometrial physiology as well as during early implantation. In addition, this cytokine has a considerable pathophysiological function in diseases such as menorrhagia, endometriosis, or infertility due to its regulatory impact on proliferation, differentiation, and angiogenesis in the human endometrium. In women with endometriosis, TNF-alpha levels increases in peritoneal fluid and serum significantly. In the present study, we focused on finding novel small molecules that can directly block TNFalpha- hTNFR1 (human TNF receptor 1) interaction. Method(s): In this regard, TNF-alpha inhibiting capacity of natural carotenoids was investigated in terms of blocking TNF-alpha-hTNFR1 interaction with the help of a combination of in silico approaches, based on virtual screening, molecular docking, and molecular dynamics (MD) simulation. Result(s): A total of 125 carotenoids were selected out of 1204 natural molecules, based on their pharmacokinetics properties, and they all met Lipinski's rule of five. Among them, sorgomol, strigol, and orobanchol had the most favorable DELTAG with the best pharmacokinetics properties and were selected for MD simulation studies, which explored the complex stability and the impact of ligands on protein conformation. It was shown that sorgomol formed the most hydrogen bonds, resulting in the highest binding energy with the lowest RMSD and RMSF. Conclusion(s): Our results showed that sorgomol was the most appropriate candidate as a TNF-alpha inhibitor. In conclusion, the present study could serve to expand possibilities to develop new therapeutic small molecules against TNF-alpha which plays an important role in the inflammation of endometriosis.
ABSTRACT
Home healthcare routing and scheduling problems provide a better condition for elderly and disabled people. In the presence of the worldwide pandemic of coronavirus disease 2019 (COVID-19 pandemic), these problems have shown their efficiency and necessity to notice this new group of patients suffering from COVID-19. For this purpose, a new mathematical model is developed for a home healthcare routing and scheduling problem (HHCRSP) regarding the impact of the COVID-19 outbreak. The satisfaction and cost of assigning staff to patients with suspected or confirmed COVID-19 are considered. This problem considers travel time between patients and aims to minimize it. The proposed model is solved using GAMS optimization software. Computational experiments are considered for several test problems and a sensitivity analysis is conducted to validate the model performance. © 2021, IFIP International Federation for Information Processing.