scholarly journals Dual anti-inflammatory and selective inhibition mechanism of leukotriene A4 hydrolase/aminopeptidase: insights from comparative molecular dynamics and binding free energy analyses

2016 ◽  
Vol 34 (11) ◽  
pp. 2418-2433 ◽  
Author(s):  
Patrick Appiah-Kubi ◽  
Mahmoud E.S. Soliman
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Free Energy ◽  
Selective Inhibition ◽  
Inhibition Mechanism ◽  
Leukotriene A4 Hydrolase ◽  
Anti Inflammatory ◽  
Leukotriene A4

scholarly journals Hydrogen Bond Stability of Quinazoline Derivatives Compounds in Complex against EGFR using Molecular Dynamics Simulation

2019 ◽  
Vol 19 (2) ◽  
pp. 461
Author(s):  
Herlina Rasyid ◽  
Bambang Purwono ◽  
Thomas S Hofer ◽  
Harno Dwi Pranowo
Keyword(s):  
Molecular Dynamics ◽  
Hydrogen Bond ◽  
Free Energy ◽  
Molecular Dynamics Simulation ◽  
Binding Free Energy ◽  
Dynamics Simulation ◽  
Inhibition Mechanism ◽  
Energy Calculation ◽  
Protein Receptor ◽  
The Stability

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.

scholarly journals Molecular Basis of Artemisinin Derivatives Inhibition of Myeloid Differentiation Protein 2 by Combined in Silico and Experimental Study

Molecules ◽  
2021 ◽  
Vol 26 (18) ◽  
pp. 5698
Author(s):  
Sennan Qiao ◽  
Hansi Zhang ◽  
Fei Sun ◽  
Zhenyan Jiang
Keyword(s):  
Free Energy ◽  
Hydrophobic Interactions ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Experimental Results ◽  
Myeloid Differentiation ◽  
Inhibition Mechanism ◽  
Artemisinin Derivatives ◽  
Anti Inflammatory ◽  
Dynamics Simulations

Artemisinin (also known as Qinghaosu) , an active component of the Qinghao extract, is widely used as antimalarial drug. Previous studies reveal that artemisinin and its derivatives also have effective anti-inflammatory and immunomodulatory properties, but the direct molecular target remains unknown. Recently, several reports mentioned that myeloid differentiation factor 2 (MD-2, also known as lymphocyte antigen 96) may be the endogenous target of artemisinin in the inhibition of lipopolysaccharide signaling. However, the exact interaction between artemisinin and MD-2 is still not fully understood. Here, experimental and computational methods were employed to elucidate the relationship between the artemisinin and its inhibition mechanism. Experimental results showed that artemether exhibit higher anti-inflammatory activity performance than artemisinin and artesunate. Molecular docking results showed that artemisinin, artesunate, and artemether had similar binding poses, and all complexes remained stable throughout the whole molecular dynamics simulations, whereas the binding of artemisinin and its derivatives to MD-2 decreased the TLR4(Toll-Like Receptor 4)/MD-2 stability. Moreover, artemether exhibited lower binding energy as compared to artemisinin and artesunate, which is in good agreement with the experimental results. Leu61, Leu78, and Ile117 are indeed key residues that contribute to the binding free energy. Binding free energy analysis further confirmed that hydrophobic interactions were critical to maintain the binding mode of artemisinin and its derivatives with MD-2.

scholarly journals Binding free energy predictions in host-guest systems using Autodock4. A retrospective analysis on SAMPL6, SAMPL7 and SAMPL8 challenges

2021 ◽  
Author(s):  
Lorenzo Casbarra ◽  
Piero Procacci
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Drug Discovery ◽  
Binding Free Energy ◽  
Cost Ratio ◽  
Benefit Cost Ratio ◽  
Docking Program ◽  
Benefit Cost ◽  
Overall Reliability ◽  
Absolute Binding Free Energy

AbstractWe systematically tested the Autodock4 docking program for absolute binding free energy predictions using the host-guest systems from the recent SAMPL6, SAMPL7 and SAMPL8 challenges. We found that Autodock4 behaves surprisingly well, outperforming in many instances expensive molecular dynamics or quantum chemistry techniques, with an extremely favorable benefit-cost ratio. Some interesting features of Autodock4 predictions are revealed, yielding valuable hints on the overall reliability of docking screening campaigns in drug discovery projects.

Assessing the ligand selectivity of sphingosine kinases using molecular dynamics and MM-PBSA binding free energy calculations

2016 ◽  
Vol 12 (4) ◽  
pp. 1174-1182 ◽  
Author(s):  
Liang Fang ◽  
Xiaojian Wang ◽  
Meiyang Xi ◽  
Tianqi Liu ◽  
Dali Yin
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Model Building ◽  
Binding Free Energy ◽  
Homology Model ◽  
Free Energy Calculations ◽  
Dynamics Simulation ◽  
Ligand Selectivity ◽  
Sphingosine Kinases ◽  
Binding Free Energy Calculations

Three residues of SK1 were identified important for selective SK1 inhibitory activity via SK2 homology model building, molecular dynamics simulation, and MM-PBSA studies.

Molecular dynamics simulations and binding free energy analysis of DNA minor groove complexes of curcumin

2011 ◽  
Vol 17 (11) ◽  
pp. 2805-2816 ◽  
Author(s):  
Mathew Varghese Koonammackal ◽  
Unnikrishnan Viswambharan Nair Nellipparambil ◽  
Chellappanpillai Sudarsanakumar
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Molecular Dynamics Simulations ◽  
Energy Analysis ◽  
Binding Free Energy ◽  
Minor Groove ◽  
Dna Minor Groove ◽  
Dynamics Simulations ◽  
Free Energy Analysis

scholarly journals Prediction of GluN2B-CT1290-1310/DAPK1 Interaction by Protein–Peptide Docking and Molecular Dynamics Simulation

Molecules ◽  
2018 ◽  
Vol 23 (11) ◽  
pp. 3018 ◽  
Author(s):  
Gao Tu ◽  
Tingting Fu ◽  
Fengyuan Yang ◽  
Lixia Yao ◽  
Weiwei Xue ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Computational Simulation ◽  
Critical Role ◽  
Dynamics Simulation ◽  
Peptide Docking ◽  
C Terminus ◽  
Free Energy Decomposition

The interaction of death-associated protein kinase 1 (DAPK1) with the 2B subunit (GluN2B) C-terminus of N-methyl-D-aspartate receptor (NMDAR) plays a critical role in the pathophysiology of depression and is considered a potential target for the structure-based discovery of new antidepressants. However, the 3D structures of C-terminus residues 1290–1310 of GluN2B (GluN2B-CT1290-1310) remain elusive and the interaction between GluN2B-CT1290-1310 and DAPK1 is unknown. In this study, the mechanism of interaction between DAPK1 and GluN2B-CT1290-1310 was predicted by computational simulation methods including protein–peptide docking and molecular dynamics (MD) simulation. Based on the equilibrated MD trajectory, the total binding free energy between GluN2B-CT1290-1310 and DAPK1 was computed by the mechanics generalized born surface area (MM/GBSA) approach. The simulation results showed that hydrophobic, van der Waals, and electrostatic interactions are responsible for the binding of GluN2B-CT1290–1310/DAPK1. Moreover, through per-residue free energy decomposition and in silico alanine scanning analysis, hotspot residues between GluN2B-CT1290-1310 and DAPK1 interface were identified. In conclusion, this work predicted the binding mode and quantitatively characterized the protein–peptide interface, which will aid in the discovery of novel drugs targeting the GluN2B-CT1290-1310 and DAPK1 interface.

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