Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study.

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments

Toxicity analysis from pkCSM.

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin’s effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments.</div

Docking score and interaction between protein residues and ligand.

Docking score and interaction between protein residues and ligand.</p

Admet properties of compounds and metformin (CID 4091).

Admet properties of compounds and metformin (CID 4091).</p

Ligand-based modelling for screening natural compounds targeting Minichromosome Maintenance Complex Component-7 for potential anticancer effects

Minichromosome Maintenance Complex Component-7 (MCM7) plays a significant role in DNA replication. A comprehensive search of oncogenic databases (UALCAN and KMplot) revealed overexpression or upregulation of MCM7 in a number of cancers (including top prevalent cancer types worldwide). Thus, identification of novel compounds that can decrease expression level of MCM7 can act as a therapeutic strategy against the malignancies in which MCM7 is upregulated. In pursuit of this, computational drug discovery methodology was adopted to identify compounds which can antagonize MCM7 protein. At first, MCM7 protein was docked with control inhibitors of the protein such as Simvastatin, Atorvastatin, Lovastatin, Pravastatin and Breviscapine which showed binding affinity ranging from −8.6 to −7.5 kcal/mol. Ligand-based pharmacophore was generated based on these five compounds. Through ligand-based pharmacophore screening of 11,325 natural compounds, 68 hit compounds were identified. These compounds were docked against MCM7 protein unit. Furthermore, ADMET analysis has been performed to evaluate drug-like properties of all these 68 compounds. Among these, five compounds (Neoandrographolide, Pseudojervine, Isowighteone, Kushenol N and Bucharaine) showed promising ADMET properties and acceptable binding affinities, ranging from −7.7 kcal/mol to −9.3 kcal/mol. Molecular dynamics simulation was performed to evaluate interaction stability of the five compounds with MCM7 inside human body. For Neoandrographolide, Kushenol N and Bucharaine, each system was mostly stable after 15 ns of simulation. Taken together, these compounds can be further evaluated using appropriate cell-based and in vitro models to develop drugs targeting MCM7