Identification of new small molecule allosteric SHP2 inhibitor through pharmacophore-based virtual screening, molecular docking, molecular dynamics simulation studies, synthesis and in vitro evaluation

In silico validation of allosteric inhibitors targeting Zika virus NS2B-NS3 protease

The Zika virus (ZIKV), a member of the Flaviviridae family, poses a major threat to human health because of the lack of effective antiviral drugs. Although the NS2B-NS3 protease of ZIKV (NS2B-NS3pro) is regarded as a major target for antiviral inhibitors, viral mutations can lead to ineffective competitive inhibitors. Allosteric inhibitors bind to highly conserved nonprotease active sites, induce conformational changes in the protease active site, and prevent substrate binding. Currently, no molecular simulation techniques are available for accurately predicting and analysing conformational changes in the protease catalytic domain. In this study, we developed a combined approach that involves blind docking, Gaussian accelerated molecular dynamics, two-dimensional potential of mean force profiling, density functional theory (DFT) calculations, and interaction region indicator (IRI) analysis and employed it to examine the allosteric inhibitor-01 molecule and its interaction with ZIKV NS2B-NS3pro. Our results indicated that the binding of inhibitor-01 to NS2B-NS3pro resulted in two major conformational states, state I and state II, which in turn changed the volume of the protease active site from 1014 Å3 to 710 and 820 Å3, respectively. These two states had an inactive catalytic domain (residues His116, Asp140, and Ser200). DFT and IRI analyses revealed that, in state I, Lys138 and Gln139 formed hydrogen bonds with inhibitor-01, whereas Lys138, Leu214, Asn217, Val220, and Ile221 engaged in van der Waals interactions with inhibitor-01. Advancements in computational techniques and power are expected to facilitate further progress in overcoming challenges associated with designing allosteric inhibitors for viral proteases.

Targeting human progesterone receptor (PR), through pharmacophore-based screening and molecular simulation revealed potent inhibitors against breast cancer

Breast cancer, the prevailing malignant tumor among women, is linked to progesterone and its receptor (PR) in both tumorigenesis and treatment responsiveness. Despite thorough investigation, the precise molecular mechanisms of progesterone in breast cancer remain unclear. The human progesterone receptor (PR) serves as an essential therapeutic target for breast cancer treatment, warranting the rapid design of small molecule therapeutics that can effectively inhibit HPR. By employing cutting-edge computational techniques like molecular screening, simulation, and free energy calculation, the process of identifying potential lead molecules from natural products has been significantly expedited. In this study, we employed pharmacophore-based virtual screening and molecular simulations to identify natural product-based inhibitors of human progesterone receptor (PR) in breast cancer treatment. High-throughput molecular screening of traditional Chinese medicine (TCM) and zinc databases was performed, leading to the identification of potential lead compounds. The analysis of binding modes for the top five compounds from both database provides valuable structural insights into the inhibition of HPR for breast cancer treatment. The top five hits exhibited enhanced stability and compactness compared to the reference compound. In conclusion, our study provides valuable insights for identifying and refining lead compounds as HPR inhibitors.