In silico Identification of potential 5α‒reductase inhibitors for prostatic diseases: QSAR modelling, molecular docking, and pre ADME predictions

Abstract

Background: Benign Prostatic Hyperplasia and prostate cancer are some of the most common old age men diseases and caused by augmented level of potent androgen dihydrotestosterone (DHT). Preventing DHT synthesis via 5α-reductase (5-AR) inhibition has been shown to have a remarkable effect on prostatic disease with low toxicity. Thus, there is much interest in the potential role for 5-AR inhibitors (5-ARIs) in the management of prostatic diseases. Some of the natural products, semi synthetic derivatives especially steroidal molecules, are effective inhibitors of 5AR. However, given the limited number of clinically approved inhibitors and the associated side effects, the discovery of new inhibitors is urgent. Here, the In silico approaches have been performed to identify new potential inhibitors of 5-AR. Methods: In the present study, two and three-dimensional (2D and 3D) QSAR models have been developed using a selected series of steroidal derivatives as 5ARIs, in order to elucidate the structural properties required for 5α-Reductase (5AR) inhibitory activity and anticancer activity. Further In-silico studies (molecular docking and pre-ADME) of selected series have also been carried out to identify the binding orientation and the receptor ligand interactions responsible for exhibited activity and the drug like properties. Results: Best 2D-QSAR model was generated using Simulated Annealing-Partial Least Square (SA-PLS) method (r 2 =0.9669, q 2 =0.8720, F-value=109.4339 and pred-r 2 =0.8289), whereas simulated annealing-k nearest neighbor (SA-kNN) approach provided us with best 3D-QSAR model (q 2 =0.9523 and pred-r 2 =0.8068). The compounds were further sorted by applying ADME properties against prostate cancer cell lines PC-3. Docking analysis indicated that the selected series of compounds have comparable binding affinity with the receptor protein and suggested that hydrophobic and electrostatic moieties can have a key role in the inhibition mechanism. These findings can provide a new strategy to develop new steroidal 5ARIs useful in prostatic disease.

Development of 2-dimensional and 3-dimensional QSAR models of Indazole derivatives as TTK inhibitors having Anticancer potential

“…By enabling early in silico evaluation of crucial parameters related to compound performance, specificity, and toxicity, QSAR/QSPR models significantly enhance drug discovery programs. The utilization of these models not only improves the effectiveness of drug development but also saves valuable time and resources, making the process more efficient and costeffective 6 .…”