Molecular docking prediction and in vitro studies elucidate anti-cancer activity of phytoestrogens

Almeida-Neto

et al. 2021

Heliyon

Chagas disease is a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, with approximately 6-7 million people infected worldwide, becoming a public health problem in tropical countries, thus generating an increasing demand for the development of more effective drugs, due to the low efficiency of the existing drugs. Aiming at the development of a new antichagasic pharmacological tool, the density functional theory was used to calculate the reactivity descriptors of amentoflavone, a biflavonoid with proven antitrypanosomal activity in vitro, as well as to perform a study of interactions with the enzyme cruzain, an enzyme key in the evolutionary process of T-cruzi. Structural properties (in solvents with different values of dielectric constant), the infrared spectrum, the frontier orbitals, Fukui analysis, thermodynamic properties were the parameters calculated from DFT method with the monomeric structure of the apigenin used for comparison. Furthermore, molecular docking studies were performed to assess the potential use of this biflavonoid as a pharmacological antichagasic tool. The frontier orbitals (HOMO-LUMO) study to find the band gap of compound has been extended to calculate electron affinity, ionization energy, electronegativity electrophilicity index, chemical potential, global chemical hardness and global chemical softness to study the chemical behaviour of compound. The optimized structure was subjected to molecular Docking to characterize the interaction between amentoflavone and cruzain enzyme, a classic pharmacological target for substances with anti-gas activity, where significant interactions were observed with amino acid residues from each one's catalytic sites enzyme. These results suggest that amentoflavone has the potential to interfere with the enzymatic activity of cruzain, thus being an indicative of being a promising antichagasic agent.

Section: Docking Analysismentioning

confidence: 99%

Quantum computational investigations and molecular docking studies on amentoflavone

Almeida-Neto

et al. 2021

Heliyon

Journal of Molecular Structure

“…In this way, the molecular docking, a computational strategy that allows one to predict binding site complementarity between a drug and its therapeutic target, has been massively used to assist drug repositioning for several diseases [6] , [9] . For example, in silico simulations were used to evaluate non-nucleoside reverse transcriptase inhibitors for HIV treatment [10] , as well as currently used drugs against HIV-1 protease of subtype D [11] ; to study the substrate recognition processes for influenza drug targets [12] , [13] ; to investigate and screening inhibitors against Ebola virus [14] , [15] , [16] ; to explore potential binding pockets and inhibitors for Zika [17] , [18] , Chikungunya [19] and Dengue virus [20] , [21] ; to perform structure-based virtual screening studies of potential drug target of Leishmania donovani [22] ; to evaluate the anticancer activity of chloro and bromo-pyrazole curcumin knoevenagel condensates and phytoestrogens [23] , [24] ; to investigate the efficacy of direct acting antivirals (DAAs) to the treatment of different Hepatitis C virus [25] and to design modified peptidomimetic cellulose derivatives Hepatitis C virus protease inhibitors [26] . In addition, in silico simulationshave have also been used to evaluate potential inhibitors of the interaction between ACE2 and SARS-CoV-2 region binding domain [27] , to help in the drug repositioning of anti-Hepatitis C virus drugs [28] and anti-polymerase drugs [29] against SARS-CoV-2.…”

Section: Introductionmentioning

confidence: 99%

Molecular dynamics simulation of docking structures of SARS-CoV-2 main protease and HIV protease inhibitors

Cardoso

Mendanha

2021

“…Those structures are useful to understand the structural changes due to agonist and antagonist binding in the ERα LBP. Various computational techniques such as molecular docking [18][19][20][21][22][23][24], MD simulations [25][26][27][28][29][30], predictive modeling [31][32][33][34][35][36][37][38][39][40][41], and in vitro studies were conducted to predict ER binders or non-binders [42,43] and agonists or antagonists [44,45].…”

Section: Introductionmentioning

confidence: 99%

Elucidation of Agonist and Antagonist Dynamic Binding Patterns in ER-α by Integration of Molecular Docking, Molecular Dynamics Simulations and Quantum Mechanical Calculations

Sakkiah

Selvaraj

Guo

et al. 2021

IJMS

Estrogen receptor alpha (ERα) is a ligand-dependent transcriptional factor in the nuclear receptor superfamily. Many structures of ERα bound with agonists and antagonists have been determined. However, the dynamic binding patterns of agonists and antagonists in the binding site of ERα remains unclear. Therefore, we performed molecular docking, molecular dynamics (MD) simulations, and quantum mechanical calculations to elucidate agonist and antagonist dynamic binding patterns in ERα. 17β-estradiol (E2) and 4-hydroxytamoxifen (OHT) were docked in the ligand binding pockets of the agonist and antagonist bound ERα. The best complex conformations from molecular docking were subjected to 100 nanosecond MD simulations. Hierarchical clustering was conducted to group the structures in the trajectory from MD simulations. The representative structure from each cluster was selected to calculate the binding interaction energy value for elucidation of the dynamic binding patterns of agonists and antagonists in the binding site of ERα. The binding interaction energy analysis revealed that OHT binds ERα more tightly in the antagonist conformer, while E2 prefers the agonist conformer. The results may help identify ERα antagonists as drug candidates and facilitate risk assessment of chemicals through ER-mediated responses.