Studies of NMR, molecular docking, and molecular dynamics simulation of new promising inhibitors of cruzaine from the parasite Trypanosoma cruzi

Costa, Renato Araújo da; Cruz, Jorddy Neves; Nascimento, Fabiana C. A.; Silva, Sebastião Gomes; Silva, Silvana O.; Martelli, Marlice Cruz; Carvalho, Samira Maria Leão de; Santos, Cleydson Breno Rodrigues dos; Neto, A. M. J. C.; Brasil, Davi do Socorro Barros

doi:10.1007/s00044-018-2280-z

Cited by 16 publications

(9 citation statements)

References 45 publications

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“…The initial structure for the system was obtained from molecular docking methods. The restrained electrostatic potential (RESP) protocol with the HF/6-31G* basis sets was applied to obtain the partial atomic charges of the atoms of each ligand [ 62 , 63 , 64 , 65 ]. The parameters of the ligand were constructed with the Antechamber module [ 66 ] using General Amber Force Field (GAFF) [ 67 ].…”

Section: Methodsmentioning

confidence: 99%

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

et al. 2020

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Non-steroidal anti-inflammatory drugs are inhibitors of cyclooxygenase-2 (COX-2) that were developed in order to avoid the side effects of non-selective inhibitors of COX-1. Thus, the present study aims to identify new selective chemical entities for the COX-2 enzyme via molecular modeling approaches. The best pharmacophore model was used to identify compounds within the ZINC database. The molecular properties were determined and selected with Pearson’s correlation for the construction of quantitative structure–activity relationship (QSAR) models to predict the biological activities of the compounds obtained with virtual screening. The pharmacokinetic/toxicological profiles of the compounds were determined, as well as the binding modes through molecular docking compared to commercial compounds (rofecoxib and celecoxib). The QSAR analysis showed a fit with R = 0.9617, R2 = 0.9250, standard error of estimate (SEE) = 0.2238, and F = 46.2739, with the tetra-parametric regression model. After the analysis, only three promising inhibitors were selected, Z-964, Z-627, and Z-814, with their predicted pIC50 (−log IC50) values, Z-814 = 7.9484, Z-627 = 9.3458, and Z-964 = 9.5272. All candidates inhibitors complied with Lipinski’s rule of five, which predicts a good oral availability and can be used in in vitro and in vivo tests in the zebrafish model in order to confirm the obtained in silico data.

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Section: Methodsmentioning

confidence: 99%

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

et al. 2020

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“…As shown in Equation ( 1), the enthalpy part is expressed as the summation of the molecular mechanical energy (∆E MM ) and the solvation free energy (∆G sol ), where ∆E MM is composed of the intra-molecular energy (∆E internal , including the bond, angle and dihedral energies of the system), the electrostatic energy (∆E ele ) and the van der Waals interactions (∆E vdW ) (Equation ( 2)). The solvation free energy (∆G sol ) is also composed of two parts, namely, the polar part (∆G pol ) and the non-polar (∆G np ) part (Equation ( 3)), where ∆G pol is usually computed by the Generalized Born (GB) model or by solving the Poisson-Boltzmann (PB) equation, while ∆G np is estimated by the solvent accessible surface area (SASA)-based approach [26,63].…”

Section: Binding Free Energy Calculations Mm/pbsa and Mm/gbsamentioning

confidence: 99%

A Computational Approach Applied to the Study of Potential Allosteric Inhibitors Protease NS2B/NS3 from Dengue Virus

et al. 2022

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Dengue virus (DENV) is a danger to more than 400 million people in the world, and there is no specific treatment. Thus, there is an urgent need to develop an effective method to combat this pathology. NS2B/NS3 protease is an important biological target due it being necessary for viral replication and the fact that it promotes the spread of the infection. Thus, this study aimed to design DENV NS2B/NS3pro allosteric inhibitors from a matrix compound. The search was conducted using the Swiss Similarity tool. The compounds were subjected to molecular docking calculations, molecular dynamics simulations (MD) and free energy calculations. The molecular docking results showed that two compounds, ZINC000001680989 and ZINC000001679427, were promising and performed important hydrogen interactions with the Asn152, Leu149 and Ala164 residues, showing the same interactions obtained in the literature. In the MD, the results indicated that five residues, Lys74, Leu76, Asn152, Leu149 and Ala166, contribute to the stability of the ligand at the allosteric site for all of the simulated systems. Hydrophobic, electrostatic and van der Waals interactions had significant effects on binding affinity. Physicochemical properties, lipophilicity, water solubility, pharmacokinetics, druglikeness and medicinal chemistry were evaluated for four compounds that were more promising, showed negative indices for the potential penetration of the Blood Brain Barrier and expressed high human intestinal absorption, indicating a low risk of central nervous system depression or drowsiness as the the side effects. The compound ZINC000006694490 exhibited an alert with a plausible level of toxicity for the purine base chemical moiety, indicating hepatotoxicity and chromosome damage in vivo in mouse, rat and human organisms. All of the compounds selected in this study showed a synthetic accessibility (SA) score lower than 4, suggesting the ease of new syntheses. The results corroborate with other studies in the literature, and the computational approach used here can contribute to the discovery of new and potent anti-dengue agents.

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“…A per-residue energy decomposition method was used to determine the total energy contribution of each residue to the drug-receptor interaction and also to investigate the chemical nature of its interactions. 34 MM/GBSA allows analysis of the contributions of individual residues or energetic terms by free energy decomposition analysis, which provides detailed energetic contributions to each specific amino acid residue sidechain to the binding state of the system, identifying the leading interactions in the binding process. That information can help further researchers to get a drug developed with the help of theoretical studies in the complex formation with proteins or another receptor type.…”

Section: Per-residue Energy Decompositionmentioning

confidence: 99%

In silico identification of novel allosteric inhibitors of Dengue virus NS2B/NS3 serine protease

Rocha²,

Pinheiro

et al. 2022

JSCS

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Although dengue is a disease that affects more than 100 countries and puts almost 400 million lives at risk each year, there is no approved antiviral in the treatment of this pathology. In this context, proteases are potential biological targets since they are essential in the replication process of this virus. In this study, a library of more than 3,000 structures was used to explore the allosteric inhibition of the NS2B/NS3 protease complex using Consensual Docking techniques. The results show four best ranked structures that were selected for molecular dynamics and free energy simulations. Our analysis corroborate with other studies (experimental and theoretical) presented in the literature. Thus, the computational approach used here proved to be useful for planning new inhibitors in the combat against Dengue disease.

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Studies of NMR, molecular docking, and molecular dynamics simulation of new promising inhibitors of cruzaine from the parasite Trypanosoma cruzi

Cited by 16 publications

References 45 publications

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

A Computational Approach Applied to the Study of Potential Allosteric Inhibitors Protease NS2B/NS3 from Dengue Virus

In silico identification of novel allosteric inhibitors of Dengue virus NS2B/NS3 serine protease

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