5 research outputs found
Identification a Novel Inhibitor for Aldo�Keto Reductase 1 C3 by Virtual Screening of PubChem Database
No full textAldo�keto reductase1C3 (AKR1C3) is an enzyme with important roles in the metabolism of steroids. AKR1C3 inhibition is a target in cancer treatment. In this study, compounds similar to Stylopine, a strong inhibitor of AKR1C3, were investigated by virtual screening. At the first stage, compounds similar to the Stylopine were excluded from the PubChem database. Then, molecular optimization in Hyperchem software and virtual screening in PyRx software was conducted. Finally, selected compounds were examined by AutoDock to find the compound with the best inhibitory effect. Among 20 selected similar structures to Stylopine in PubChem, 12 molecules had the highest binding affinity by analyzing in PyRx. Subsequently, 5 compounds (8, 21, 32, 35, and 39) were analyzed for ligand and enzyme docking. The ligand number 32 had the best binding affinity and inhibition constant (ki) in comparison with Stylopine. This compound had lower ki than the Stylopine in this research. So, it might inhibit AKR1C3 better than Stylopine. The compound can be studied as a strong inhibitor of AKR1C3 in future in vitro and in vivo researches. © 2022, The National Academy of Sciences, India
Distributed job-shop rescheduling problem considering reconfigurability of machines: a self-adaptive hybrid equilibrium optimiser
No full textInternational audienc
Dynamic Distributed Job-Shop Scheduling Problem Consisting of Reconfigurable Machine Tools
No full textPart 8: New Reconfigurable, Flexible or Agile Production Systems in the Era of Industry 4.0International audienceKeeping pace with rapidly changing customer requirements forces companies to increase the capability of adaptation of their production systems. To fulfill the market requirements in a reasonable time and cost, distributed manufacturing has been emerged as one of the efficient approaches. Moreover, the ability of reconfigurability makes manufacturing systems and tools to be more adaptable. This research deals with a dynamic production scheduling problem simultaneously in several different shop-floors consisting of reconfigurable machine tools (RMTs) by utilizing the real-time data extracted from a cyber-physical system (CPS). First, a mathematical programming model is presented for the static state. Thereafter, by utilizing the CPS capabilities, a dynamic model is extended to schedule new jobs, in which there have already been some other jobs in each facility. A numerical example is solved to illustrate the validation of the model. Finally, some potential solving approaches are proposed to make the model implementable in real-world applications
