scholarly journals Prediction of Molecular Interactions And Physicochemical Properties Relevant For Vasopressin V2 Receptor Antagonism

2021 ◽  
Author(s):  
Ania de la Nuez Veulens ◽  
Yoanna María Álvarez Ginarte ◽  
Rolando Eduardo Rodríguez Fernandez ◽  
Fabrice Leclerc ◽  
Luis Alberto Montero Cabrera
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Physicochemical Properties ◽  
Molecular Dynamics Simulations ◽  
Binding Mode ◽  
Qsar Model ◽  
Antagonist Activity ◽  
Vasopressin V2 Receptor ◽  
V2 Receptor ◽  
Dynamics Simulations

Abstract We have developed two ligand and receptor-based computational approaches to study the physicochemical properties relevant to the biological activity of vasopressin V2 receptor (V2R) antagonist and eventually to predict the expected binding mode to V2R. The obtained Quantitative Structure Activity Relationship (QSAR) model showed a correlation of the antagonist activity with the hydration energy (EH2O) , the polarizability (P) and the calculated partial charge on atom N7 (q6) of the common substructure. The first two descriptors showed a positive contribution to antagonist activity, while the third one had a negative contribution. V2R was modeled and further relaxed on a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocoline (POPC) membrane by molecular dynamics simulations. The receptor antagonist complexes were guessed by molecular docking, and the stability of the most relevant structures were also evaluated by molecular dynamics simulations. As a result, amino acid residues Q96, W99, F105, K116, F178, A194, F307, and M311 were identified with the probably most relevant antagonist-receptor interactions on the studied complexes. The proposed QSAR model could explain the molecular properties relevant to the antagonist activity. The contributions to the antagonist-receptor interaction appeared also in agreement with the binding mode of the complexes obtained by molecular docking and Molecular Dynamics. These models will be used in further studies to look for new V2R potential antagonist molecules.

Insights into the binding mode of curcumin to MD-2: studies from molecular docking, molecular dynamics simulations and experimental assessments

2015 ◽  
Vol 11 (7) ◽  
pp. 1933-1938 ◽  
Author(s):  
Zhe Wang ◽  
Gaozhi Chen ◽  
Linfeng Chen ◽  
Xing Liu ◽  
Weitao Fu ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Hot Spot ◽  
Binding Mode ◽  
Dynamics Simulations

The residues R90 and Y102 of MD-2 are hot spot residues that contribute significantly to the affinity of curcumin binding.

Promising inhibitors of nsp2 of CHIKV using molecular docking and temperature-dependent molecular dynamics simulations

2021 ◽  
pp. 1-9
Author(s):  
Mahendera Kumar Meena ◽  
Durgesh Kumar ◽  
Kamlesh Kumari ◽  
Nagendra Kumar Kaushik ◽  
Rammapa Venkatesh Kumar ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Temperature Dependent ◽  
Dynamics Simulations

scholarly journals In silico chemical profiling and identification of neuromodulators from Curcuma amada targeting Acetylcholinesterase

2020 ◽  
Author(s):  
Md. Chayan Ali ◽  
Yeasmin Akter Munni ◽  
Raju Das ◽  
Marium sultana ◽  
Nasrin Akter ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
In Silico ◽  
Network Pharmacology ◽  
Chemical Profiling ◽  
Ache Inhibitors ◽  
Curcuma Amada ◽  
In Silico Admet ◽  
Dynamics Simulations

AbstractCurcuma amada or Mango ginger, a member of the Zingiberaceae family, has been revealed as a beneficiary medicinal plant having diverse pharmacological activities against a wide range of diseases. Due to having neuromodulation properties of this plant, the present study characterized the secondary metabolites of Curcuma amada for their drug-likeness properties, identified potent hits by targeting Acetylcholinesterase (AChE) and revealed neuromodulatory potentiality by network pharmacology approaches. Here in silico ADMET analysis was performed for chemical profiling, and molecular docking and molecular dynamics simulations were used to hit selection and binding characterizations. Accordingly, ADMET prediction showed that around 87.59% of compounds processed drug-likeness activity, where four compounds have been screened out by molecular docking. Guided from induced-fit docking, molecular dynamics simulations revealed phytosterol and curcumin derivatives as the most favorable AChE inhibitors with the highest binding energy, as resulted from MM-PBSA analysis. Furthermore, all of the four hits were appeared to modulate several signaling molecules and intrinsic cellular pathways in network pharmacology analysis, which are associated with neuronal growth survival, inflammation, and immune response, supporting their capacity to revert the condition of neuro-pathobiology. Together, the present in silico based characterization and system pharmacology based findings demonstrate Curcuma amada, as a great source of neuromodulating compounds, which brings about new development for complementary and alternative medicine for the prevention and treatment of neurodegenerative disorders.

Pyrrolidine Derivatives as Plasmepsin Inhibitors: Binding Mode Analysis Assisted by Molecular Dynamics Simulations of a Highly Flexible Protein

ChemMedChem ◽  
2010 ◽  
Vol 5 (3) ◽  
pp. 443-454 ◽  
Author(s):  
Torsten Luksch ◽  
Andreas Blum ◽  
Nina Klee ◽  
Wibke E. Diederich ◽  
Christoph A. Sotriffer ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Binding Mode ◽  
Mode Analysis ◽  
Flexible Protein ◽  
Dynamics Simulations
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