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Article

Modelling the Anti-Methicillin-Resistant Staphylococcus Aureus (MRSA) Activity of Cannabinoids: A QSAR and Docking Study

1
Grupo de Investigación en Ciencias Naturales y Exactas, Departamento de Ciencias Naturales y Exactas, Universidad de la Costa, Barranquilla 080002, Colombia
2
Grupo de Química Computacional y Teórica (QCT-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, Quito 170901, Ecuador
3
Grupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Exactas, Universidad del Norte, Carrera 51B, Km 5, vía Puerto Colombia, Barranquilla 081007, Colombia
*
Authors to whom correspondence should be addressed.
Crystals 2020, 10(8), 692; https://doi.org/10.3390/cryst10080692
Received: 23 July 2020 / Revised: 2 August 2020 / Accepted: 3 August 2020 / Published: 11 August 2020
Twenty-four cannabinoids active against MRSA SA1199B and XU212 were optimized at WB97XD/6-31G(d,p), and several molecular descriptors were obtained. Using a multiple linear regression method, several mathematical models with statistical significance were obtained. The robustness of the models was validated, employing the leave-one-out cross-validation and Y-scrambling methods. The entire data set was docked against penicillin-binding protein, iso-tyrosyl tRNA synthetase, and DNA gyrase. The most active cannabinoids had high affinity to penicillin-binding protein (PBP), whereas the least active compounds had low affinities for all of the targets. Among the cannabinoid compounds, Cannabinoid 2 was highlighted due to its suitable combination of both antimicrobial activity and higher scoring values against the selected target; therefore, its docking performance was compared to that of oxacillin, a commercial PBP inhibitor. The 2D figures reveal that both compounds hit the protein in the active site with a similar type of molecular interaction, where the hydroxyl groups in the aromatic ring of cannabinoids play a pivotal role in the biological activity. These results provide some evidence that the anti-Staphylococcus aureus activity of these cannabinoids may be related to the inhibition of the PBP protein; besides, the robustness of the models along with the docking and Quantitative Structure–Activity Relationship (QSAR) results allow the proposal of three new compounds; the predicted activity combined with the scoring values against PBP should encourage future synthesis and experimental testing. View Full-Text
Keywords: cannabinoids; anti-MRSA; QSAR; molecular docking; DFT cannabinoids; anti-MRSA; QSAR; molecular docking; DFT
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MDPI and ACS Style

Cortes, E.; Mora, J.; Márquez, E. Modelling the Anti-Methicillin-Resistant Staphylococcus Aureus (MRSA) Activity of Cannabinoids: A QSAR and Docking Study. Crystals 2020, 10, 692. https://doi.org/10.3390/cryst10080692

AMA Style

Cortes E, Mora J, Márquez E. Modelling the Anti-Methicillin-Resistant Staphylococcus Aureus (MRSA) Activity of Cannabinoids: A QSAR and Docking Study. Crystals. 2020; 10(8):692. https://doi.org/10.3390/cryst10080692

Chicago/Turabian Style

Cortes, Eliceo; Mora, José; Márquez, Edgar. 2020. "Modelling the Anti-Methicillin-Resistant Staphylococcus Aureus (MRSA) Activity of Cannabinoids: A QSAR and Docking Study" Crystals 10, no. 8: 692. https://doi.org/10.3390/cryst10080692

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