Molecular Dynamics Simulation on Scale Inhibition Mechanism of Polyepoxysuccinic Acid to Calcium Sulphate

Lung cancer was a second common cancer case due to the high cigarette smoking activity both in men and women. One of protein receptor which plays an important role in the growth of the tumor is Epidermal Growth Factor Receptor (EGFR). EGFR protein is the most frequent protein mutation in cancer and promising target to inhibit the cancer growth. In this work, the stability of the hydrogen bond as the main interaction in the inhibition mechanism of cancer will be evaluated using molecular dynamics simulation. There were two compounds (A1 and A2) as new potential inhibitors that were complexed against the EGFR protein. The dynamic properties of each complexed were compared with respect to erlotinib against EGFR. The result revealed that both compounds had an interaction in the main catalytic area of protein receptor which is at methionine residue. Inhibitor A1 showed additional interactions during simulation time but the interactions tend to be weak. Inhibitor A2 displayed a more stable interaction. Following dynamics simulation, binding free energy calculation was performed by two scoring techniques MM/GB(PB)SA method and gave a good correlation with the stability of the complex. Furthermore, potential inhibitor A2 had a lower binding free energy as a direct consequence of the stability of hydrogen bond interaction.

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The Potential role of Procyanidin as a Therapeutic Agent against SARS-CoV-2: A Text Mining, Molecular Docking and Molecular Dynamics Simulation Approach

10.26434/chemrxiv.12579599 ◽

2020 ◽

Author(s):

Nikhil Maroli ◽

Balu Bhasuran ◽

Jeyakumar Natarajan ◽

Ponmalai Kolandaivel

Keyword(s):

Molecular Dynamics ◽

Molecular Docking ◽

Molecular Dynamics Simulation ◽

Text Mining ◽

Van Der Waals ◽

Interaction Network ◽

Van Der Waals Interactions ◽

Entity Recognition ◽

Dynamics Simulation ◽

Inhibition Mechanism

A novel coronavirus (SARS-CoV-2) has caused a major outbreak in human all over the world. There are several proteins interplay during the entry and replication of this virus in human. Here, we have used text mining and named entity recognition method to identify co-occurrence of the important COVID 19 genes/proteins in the interaction network based on the frequency of the interaction. Network analysis revealed a set of genes/proteins, highly dense genes/protein clusters and sub-networks of Angiotensin-converting enzyme 2 (ACE2), Helicase, spike (S) protein (trimeric), membrane (M) protein, envelop (E) protein, and the nucleocapsid (N) protein. The isolated proteins are screened against procyanidin-a flavonoid from plants using molecular docking. Further, molecular dynamics simulation of critical proteins such as ACE2, Mpro and spike proteins are performed to elucidate the inhibition mechanism. The strong network of hydrogen bonds and hydrophobic interactions along with van der Waals interactions inhibit receptors, which are essential to the entry and replication of the SARS-CoV-2. The binding energy which largely arises from van der Waals interactions is calculated (ACE2=-50.21 ± 6.3, Mpro=-89.50 ± 6.32 and spike=-23.06 ± 4.39) through molecular mechanics Poisson-Boltzmann surface area also confirm the affinity of procyanidin towards the critical receptors.

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