Molecular Dynamics Free Energy Simulation study to Investigate Binding Pattern of Isoliquiritigenin as PPAR𝛾 Agonist

2022 ◽  
Author(s):  
Amit Singh ◽  
Abha Mishra
Keyword(s):  
Diabetes Mellitus ◽  
Free Energy ◽  
Binding Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Solvation Energy ◽  
Bioactive Constituents ◽  
Binding Interaction ◽  
Pparγ Agonist ◽  
Polar Solvation

Abstract Phytochemicals are rich source of bioactive constituents and can be used as another alternative to currently used drugs for diseases like Diabetes mellitus. The potential of Isoliquiritigenin (a constituent of Pterocarpus marsupium) as PPAR𝛾 agonist was evaluated by in silico technique. Autodock results showed that Tyr327, and Tyr473 of the PPARγ forms H-bonds with Isoliquiritigenin (binding energy of -7.46 kcal/mol) and Troglitazone (known drug) showed H bond with Tyr327, Ser289, with binding energy of -11.01 kcal/mol. Isoliquiritigenin, binding energy in Extra precision (XP) was -6.74 kcal/mol while Troglitazone docking, gave binding energy in XP mode as -9.59 kcal/mol. The best Induced fit docking (IFD) score of the optimised PPARγ- Isoliquiritigenin complexes was -9.39 Kcal/mol. The important residues in IFD forming H bond were Cys 285, Arg 288, Tyr 327 and Leu 340. The post docking MM/GBSA free energy for PPARγ with Isoliquiritigenin and Troglitazone was -49.29 and -71.48 Kcal/mol respectively. Binding interaction in MD simulation and Principal Component Analysis studies revealed stable binding throughout 100 ns simulation. Post Simulation MM/PBSA free energy was calculated. The results indicated that compound possessed a negative binding free energy with -114.37KJ/mol. It was observed that van der Waals, electrostatic interactions and non-polar solvation energy negatively contributed to the total interaction energy while only polar solvation energy positively contributed to total free binding energy. The Isoliquiritigenin fulfils the criteria of drug-likeness property. Thus, study presents a systematic analysis on molecular mechanism of action of Isoliquiritigenin as PPARγ agonist in controlling Diabetes mellitus.

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.

scholarly journals Omicron SARS-CoV-2 Variant Spike Protein Shows an Increased Affinity to the Human ACE2 Receptor: An In Silico Analysis

Pathogens ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 45
Author(s):  
Joseph Thomas Ortega ◽  
Beata Jastrzebska ◽  
Hector Rafael Rangel
Keyword(s):  
Free Energy ◽  
Electrostatic Interactions ◽  
Structural Model ◽  
Binding Free Energy ◽  
In Silico Analysis ◽  
Spike Protein ◽  
Medical Community ◽  
Converting Enzyme ◽  
Angiotensin Converting Enzyme 2 ◽  
Silico Analysis

The rise of SARS-CoV-2 variants, with changes that could be related to an increased virus pathogenicity, have received the interest of the scientific and medical community. In this study, we evaluated the changes that occurred in the viral spike of the SARS-CoV-2 Omicron variant and whether these changes modulate the interactions with the angiotensin-converting enzyme 2 (ACE2) host receptor. The mutations associated with the Omicron variant were retrieved from the GISAID and covariants.org databases, and a structural model was built using the SWISS-Model server. The interaction between the spike and the human ACE2 was evaluated using two different docking software, Zdock and Haddock. We found that the binding free energy was lower for the Omicron variant as compared to the WT spike. In addition, the Omicron spike protein showed an increased number of electrostatic interactions with ACE2 than the WT spike, especially the interactions related to charged residues. This study contributes to a better understanding of the changes in the interaction between the Omicron spike and the human host ACE2 receptor.

Identification of Novel Nrf2 Activator via Protein-ligand Interactions as Remedy for Oxidative Stress in Diabetes Mellitus

2021 ◽  
Vol 18 ◽  
Author(s):  
Afolashade Toritseju Onunkun ◽  
Opeyemi Iwaloye ◽  
Olusola Olalekan Elekofehinti
Keyword(s):  
Oxidative Stress ◽  
Diabetes Mellitus ◽  
Free Energy ◽  
Protein Interaction ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Protein Protein Interaction ◽  
Glide Docking ◽  
Adme Properties ◽  
Nrf2 Protein

Background: Oxidative stress is a significant player in the pathogenesis of diabetes mellitus and the Kelch-like ECH-associated protein1/nuclear factor erythroid 2-related factor 2/antioxidant response element (Keap1/Nrf2/ARE) signaling pathway serves as the essential defense system to mitigate oxidative stress. Nrf2 is responsible for the mitigation of oxidative stress while Keap1 represses Nrf2’s activation upon binding. Identification of Nrf2 activators has started to pick up enthusiasm as they can be used as therapeutic agents against diabetes mellitus. One of the ongoing mechanisms in the activation of Nrf2 is to disrupt Keap1/Nrf2 protein-protein interaction. This study aimed at using computational analysis to screen natural compounds capable of inhibiting Keap1/Nrf2 protein-protein interaction. Methods: A manual curated library of natural compounds was screened against crystal structure of Keap1 using glide docking algorithm. Binding free energy of the docked complexes, and adsorption, digestion, metabolism and excretion (ADME) properties were further employed to identify the hit compounds. The bioactivity of the identified hit against Keap1 was predicted using quantitative structure-activity relationship (QSAR) model. Results: A total of 7 natural compounds (Compound 222, 230, 310, 208, 210, 229 and 205) identified from different medicinal plants were found to be potent against Keap1 based on their binding affinity and binding free energy. The internal validated model kpls_radial_30 with R2 of 0.9109, Q2 of 0.7287 was used to predict the compounds’ bioactivities. Compound 205 was considered as the ideal drug candidate because it showed moderation for ADME properties, had predicted pIC50 of 6.614 and obeyed Lipinski’s rule of five. Conclusion: This study revealed that Compound 205, a compound isolated from Amphipterygium adstringens is worth considering for further experimental analysis.

MOLECULAR DYNAMICS AND FREE ENERGY ANALYSES OF ERK2–PYRAZOLYLPYRROLE INHIBITORS INTERACTIONS: INSIGHT INTO STRUCTURE-BASED LIGAND DESIGN

2009 ◽  
Vol 08 (05) ◽  
pp. 887-908 ◽  
Author(s):  
JIN-HUI ZHAN ◽  
XI ZHAO ◽  
XU-RI HUANG ◽  
CHIA-CHUNG SUN
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Signal Transduction Pathway ◽  
Binding Mode ◽  
Inhibitory Effect ◽  
Dynamics Simulation ◽  
Protein Motions ◽  
Extracellular Signal

The extracellular signal-regulated protein kinase 2 (ERK2) is a pivotal member involving in Ras/Raf/MEK/ERK signal transduction pathway, acting as a central point where multiple signaling pathways coalesce to drive transcription. The pyrazolylpyrrole compounds as ATP competitive inhibitors of ERK2 can bind target with a special binding mode and have higher inhibitory potency than other ERK2-inhibitors. We investigated the interaction mode of ERK2-inhibitor using molecular dynamics simulation. The molecular mechanics Poisson–Boltzmann surface area approach is used to calculate the binding free energy of ERK2 with pyrazolylpyrrole inhibitors to analyze the factors of improving the affinity. The results indicated that the electrostatic interactions play the most important role in keeping the stabilization of ERK2-inhibitor. The structural analyses showed that the protein motions can be controlled by changing the structures of inhibitors; furthermore, the full use of available space in the binding site by improving the flexibilities of inhibitors and introducing hydrophobic groups can increase the inhibitory effect.

scholarly journals Accelerating the Calculation of Protein-Ligand Binding Free Energy and Residence Times using Dynamically Optimized Collective Variables

2018 ◽  
Author(s):  
Z. Faidon Brotzakis ◽  
Vittorio Limongelli ◽  
Michele Parrinello
Keyword(s):  
Free Energy ◽  
Ligand Binding ◽  
Degrees Of Freedom ◽  
Binding Free Energy ◽  
Conformational Dynamics ◽  
Computational Cost ◽  
Binding Pocket ◽  
Binding Mode ◽  
Collective Variables ◽  
Binding Interaction

AbstractElucidation of the ligand/protein binding interaction is of paramount relevance in pharmacology to increase the success rate of drug design. To this end a number of computational methods have been proposed, however all of them suffer from limitations since the ligand binding/unbinding transitions to the molecular target involve many slow degrees of freedom that hamper a full characterization of the binding process. Being able to express this transition in simple and general slow degrees of freedom, would give a distinctive advantage, since it would require minimal knowledge of the system under study, while in turn it would elucidate its physics and accelerate the convergence speed of enhanced sampling methods relying on collective variables. In this study we pursuit this goal by combining for the first time Variation Approach to Conformational dynamics with Funnel-Metadynamics. In so doing, we predict for the benzamidine/trypsin system the ligand binding mode, and we accurately compute the absolute protein-ligand binding free energy and unbinding rate at unprecedented low computational cost. Finally, our simulation protocol reveals the energetics and structural details of the ligand binding mechanism and shows that water and binding pocket solvation/desolvation are the dominant slow degrees of freedom.

scholarly journals Computational Determination of Potential Multiprotein Targeting Natural Compounds for Rational Drug Design Against SARS-COV-2

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 674
Author(s):  
Ziyad Tariq Muhseen ◽  
Alaa R. Hameed ◽  
Halah M. H. Al-Hasani ◽  
Sajjad Ahmad ◽  
Guanglin Li
Keyword(s):  
Free Energy ◽  
Binding Energy ◽  
Binding Free Energy ◽  
Binding Mode ◽  
Natural Compounds ◽  
Rational Drug Design ◽  
Dynamics Simulation ◽  
Antiviral Compounds ◽  
Rational Drug ◽  
Key Residues

SARS-CoV-2 caused the current COVID-19 pandemic and there is an urgent need to explore effective therapeutics that can inhibit enzymes that are imperative in virus reproduction. To this end, we computationally investigated the MPD3 phytochemical database along with the pool of reported natural antiviral compounds with potential to be used as anti-SARS-CoV-2. The docking results demonstrated glycyrrhizin followed by azadirachtanin, mycophenolic acid, kushenol-w and 6-azauridine, as potential candidates. Glycyrrhizin depicted very stable binding mode to the active pocket of the Mpro (binding energy, −8.7 kcal/mol), PLpro (binding energy, −7.9 kcal/mol), and Nucleocapsid (binding energy, −7.9 kcal/mol) enzymes. This compound showed binding with several key residues that are critical to natural substrate binding and functionality to all the receptors. To test docking prediction, the compound with each receptor was subjected to molecular dynamics simulation to characterize the molecule stability and decipher its possible mechanism of binding. Each complex concludes that the receptor dynamics are stable (Mpro (mean RMSD, 0.93 Å), PLpro (mean RMSD, 0.96 Å), and Nucleocapsid (mean RMSD, 3.48 Å)). Moreover, binding free energy analyses such as MMGB/PBSA and WaterSwap were run over selected trajectory snapshots to affirm intermolecular affinity in the complexes. Glycyrrhizin was rescored to form strong affinity complexes with the virus enzymes: Mpro (MMGBSA, −24.42 kcal/mol and MMPBSA, −10.80 kcal/mol), PLpro (MMGBSA, −48.69 kcal/mol and MMPBSA, −38.17 kcal/mol) and Nucleocapsid (MMGBSA, −30.05 kcal/mol and MMPBSA, −25.95 kcal/mol), were dominated mainly by vigorous van der Waals energy. Further affirmation was achieved by WaterSwap absolute binding free energy that concluded all the complexes in good equilibrium and stability (Mpro (mean, −22.44 kcal/mol), PLpro (mean, −25.46 kcal/mol), and Nucleocapsid (mean, −23.30 kcal/mol)). These promising findings substantially advance our understanding of how natural compounds could be shaped to counter SARS-CoV-2 infection.

scholarly journals Improved binding affinity of the Omicron's spike protein with hACE2 receptor is the key factor behind its increased virulence

2021 ◽  
Author(s):  
Rajender Kumar ◽  
Murugan Natarajan Arul ◽  
Vaibhav Srivastava
Keyword(s):  
Free Energy ◽  
Hydrogen Bonding ◽  
Binding Affinity ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Free Energy Calculations ◽  
Spike Protein ◽  
Strong Interactions ◽  
Salt Bridges ◽  
New Variant

The new variant of SARS-CoV-2, Omicron, has been quickly spreading in many countries worldwide. Compared to the original virus, Omicron is characterized by several mutations in its genomic region, including spike protein's receptor-binding domain (RBD). We have computationally investigated the interaction between RBD of both wild-type and omicron variants with hACE2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The mode of the interaction between Omicron's RBD to the human ACE2 (hACE2) receptor is similar to the original SARS-CoV-2 RBD except for a few key differences. The bind-ing free energy difference shows that the spike protein of Omicron has increased binding affinity for the hACE-2 receptor. The mutated residues in the RBD showed strong interactions with a few amino acid residues of the hACE2. More specifically, strong electrostatic interactions (salt bridges) and hydrogen bonding were observed between R493 and R498 residues of the Omicron RBD with D30/E35 and D38 residues of the hACE2, respectively. Other mutated amino acids in the Omicron RBD, e.g. S496 and H505, also exhibited hydrogen bonding with the hACE2 receptor. The pi-stacking interaction was also observed between tyrosine residues (RBD-Tyr501: hACE2-Tyr41) in the complex, which contributes majorly to binding free energies suggesting this as one of the key interactions stabilizing the complex formation. The structural insights of RBD:hACE2 complex, their binding mode information and residue wise contributions to binding free energy provide insight on the increased transmissibility of Omicron and pave the way to design and optimize novel antiviral agents.

scholarly journals Virtual screening, molecular dynamics and binding energy-MM-PBSA studies of natural compounds to identify potential EcR inhibitors against Bemisia tabaci Gennadius

2021 ◽  
Author(s):  
Harmilan Kaur Mangat ◽  
Manisha Rani ◽  
Rajesh Kumar Pathak ◽  
Inderjit Singh Yadav ◽  
Divya Utreja ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Free Energy ◽  
Binding Energy ◽  
Virtual Screening ◽  
Bemisia Tabaci ◽  
Binding Free Energy ◽  
Insect Pest ◽  
Natural Compounds ◽  
Dynamics Simulation ◽  
Economic Losses

Abstract Whitefly (Bemisia tabaci Gennadius) is a hmpteran phyto polyphagous sucking insect pest which is an important pest of cotton that causes economic losses to the crop by reducing its yield and quality. Ecdysteroids like 20-hydroxy ecdysone (20-E), have significant role in larval moulting, development, and reproduction in pterygota insects. Intending to obstruct these fundamental, developmental physiological processes, the receptor of 20-E, the Ecdysone Receptor (BtEcR) of Bemisia tabaci has been targeted. To identify potent inhibitors of BtEcr, 98,072 natural compounds were retrieved from ZINC database. A structure-based virtual screening of these compounds was conducted for their binding to BtEcR and the top two compounds (ZINC08952607 and ZINC04264850) were selected based on minimum binding energy. 50 ns molecular dynamics simulation (MDS) study was then performed for the prediction of dynamics and stability of BtEcR and top-scoring ligand-BtEcR complexes. Besides, g_mmpbsa tool was used to calculate and analyse binding free energy of BtEcR-ligand complexes. The results revealed that ZINC08952607 and ZINC04264850 had binding free energy of −170.156 kJ/mol and −200.349 kJ/mol, respectively. Thus, these ligands can be utilized as lead compounds for the development of environmentally safe insecticides against the whitefly.

scholarly journals Correction Terms for Calculating Binding Free Energy Using Rates from Nonequilibrium Simulations

2020 ◽  
Author(s):  
Robert Hall ◽  
Tom Dixon ◽  
Alex Dickson
Keyword(s):  
Free Energy ◽  
Electrostatic Interactions ◽  
Binding Free Energy ◽  
Molecular Simulations ◽  
Binding Kinetics ◽  
Drug Candidate ◽  
Free Energies ◽  
Unbound States ◽  
Correction Terms ◽  
Binding Free Energies

<div>The free energy of a process is the fundamental quantity that determines its spontaneity or propensity at a given temperature. Binding free energy of a drug candidate to its biomolecular target is used as an objective quantity in drug design. Binding kinetics -- rates of association (k<sub>on</sub>) and dissociation (k<sub>off</sub>) -- have also demonstrated utility for their ability to predict efficacy and in some cases have been shown to be more predictive than the binding free energy alone. Although challenging, some methods exist to calculate binding kinetics from molecular simulations. While the kinetics of the binding process are related to the free energy by the log of their ratio, it is not straightforward to account for common, practical details pertaining to the calculation of rates in molecular simulations, such as the finite simulation volume or the particular definition of the ``bound" and ``unbound" states. Here we derive a set of correction terms that can be applied to calculations of binding free energies using rates observed in simulations. One term accounts for the particular definitions of the bound and unbound states. The second term accounts for residual electrostatic interactions that might still be present between the molecules, which is especially useful if one or both of the molecules carry an explicit charge. The third term accounts for the volume of the unbound state in the simulation box, which is useful to keep the simulated volume as small as possible during rate calculations. We apply these correction terms to revisit the calculation of binding free energies from rate constants for a host-guest system that was part of a blind prediction challenge, where significant deviations were observed between free energies calculated with rate ratios and those calculated from alchemical perturbation. The correction terms combine to significantly decrease the error with respect to computational benchmarks, from 3.4 to 0.76 kcal/mol.</div>

scholarly journals Phytochemical Moieties From Indian Traditional Medicine for Targeting Dual Hotspots on SARS-CoV-2 Spike Protein: An Integrative in-silico Approach

2021 ◽  
Vol 8 ◽  
Author(s):  
V. Umashankar ◽  
Sanjay H. Deshpande ◽  
Harsha V. Hegde ◽  
Ishwar Singh ◽  
Debprasad Chattopadhyay
Keyword(s):  
Free Energy ◽  
Binding Energy ◽  
Traditional Medicine ◽  
Binding Affinity ◽  
In Silico ◽  
Binding Free Energy ◽  
Contemporary Literature ◽  
Dynamics Simulation ◽  
Spike Protein ◽  
Syzygium Aromaticum

SARS-CoV-2 infection across the world has led to immense turbulence in the treatment modality, thus demanding a swift drug discovery process. Spike protein of SARS-CoV-2 binds to ACE2 receptor of human to initiate host invasion. Plethora of studies demonstrate the inhibition of Spike-ACE2 interactions to impair infection. The ancient Indian traditional medicine has been of great interest of Virologists worldwide to decipher potential antivirals. Hence, in this study, phytochemicals (1,952 compounds) from eight potential medicinal plants used in Indian traditional medicine were meticulously collated, based on their usage in respiratory disorders, along with immunomodulatory and anti-viral potential from contemporary literature. Further, these compounds were virtually screened against Receptor Binding Domain (RBD) of Spike protein. The potential compounds from each plant were prioritized based on the binding affinity, key hotspot interactions at ACE2 binding region and glycosylation sites. Finally, the potential hits in complex with spike protein were subjected to Molecular Dynamics simulation (450 ns), to infer the stability of complex formation. Among the compounds screened, Tellimagrandin-II (binding energy of −8.2 kcal/mol and binding free energy of −32.08 kcal/mol) from Syzygium aromaticum L. and O-Demethyl-demethoxy-curcumin (binding energy of −8.0 kcal/mol and binding free energy of −12.48 kcal/mol) from Curcuma longa L. were found to be highly potential due to their higher binding affinity and significant binding free energy (MM-PBSA), along with favorable ADMET properties and stable intermolecular interactions with hotspots (including the ASN343 glycosylation site). The proposed hits are highly promising, as these are resultant of stringent in silico checkpoints, traditionally used, and are documented through contemporary literature. Hence, could serve as promising leads for subsequent experimental validations.

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