Identification of Small Inhibitors for Human Metadherin, an Oncoprotein, through in silico Approach.

AIMS: Cancer is a disease that takes lives of thousands of people each year. There are more than 100 different types of cancers known to man. This fatal disease is one of the leading causes of death today. BACKGROUND: Astrocyte elevated gene-1(AEG-1)/Metadherin (MTDH) activates multiple oncogenic signaling pathways and leads to different types of cancers. MTDH interacting with staphylococcal nuclease domain containing 1(SND1) supports the survival and growth of mammary epithelial cells under oncogenic conditions. OBJECTIVE: Silencing MTDH or SND1 individually or disrupting their interaction compromises the tumorigenic potential of tumor-initiating cells. The aim of our present study was to investigate novel interactions of staphylococcal nuclease domain containing 1 (SND1) binding domain of AEG-1/MTDH with different lead compounds through molecular docking approach using MOE software. METHODS: Molecular docking was done by docking the ChemBridge database against important residues of MTDH involved in interaction with SND1. After docking the whole ChemBridge database, the top 200 interactive compounds were selected based on docking scores. After applying Lipinski's rule, all the remaining chosen compounds were studied on the basis of binding affinity, binding energy, docking score and protein-ligand interactions. Finally, 10 compounds showing multiple interactions with different amino acid residues were selected as the top interacting compounds. RESULTS: Three compounds were selected for simulation studies after testing these compounds using topkat toxicity and ADMET studies. The simulation study indicated that compound 32538601 is a lead compound for inhibiting MTDH-SND1 complex formation. CONCLUSION: These novels, potent inhibitors of MTDH-SND1 complex can ultimately help us in controlling cancer up to some extent.

In-Silico Lead Druggable Compounds Identification against SARS COVID-19 Main Protease Target from In-House, Chembridge and Zinc Databases by Structure-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations.

Pharmacological strategies to lower the viral load among patients suffering from severe diseases were researched in great detail during the SARS-CoV-2 outbreak. The viral protease Mpro (3CLpro) is necessary for viral replication and is among the main therapeutic targets proposed, thus far. To stop the pandemic from spreading, researchers are working to find more effective Mpro inhibitors against SARS-CoV-2. The 33.8 kDa Mpro protease of SARS-CoV-2, being a nonhuman homologue, has the possibility of being utilized as a therapeutic target against coronaviruses. To develop drug-like compounds capable of preventing the replication of SARS-main CoV-2's protease (Mpro), a computer-aided drug design (CADD) approach is extremely viable. Using MOE, structure-based virtual screening (SBVS) of in-house and commercial databases was carried out using SARS-CoV-2 proteins. The most promising hits obtained during virtual screening (VS) were put through molecular docking with the help of MOE. The virtual screening yielded 3/5 hits (in-house database) and 56/66 hits (commercial databases). Finally, 3/5 hits (in-house database), 3/5 hits (ZINC database), and 2/7 hits (ChemBridge database) were chosen as potent lead compounds using various scaffolds due to their considerable binding affinity with Mpro protein. The outcomes of SBVS were then validated using an analysis based on molecular dynamics simulation (MDS). The complexes' stability was tested using MDS and post-MDS. The most promising candidates were found to exhibit a high capacity for fitting into the protein-binding pocket and interacting with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.