Escobar-Muciño Esmeralda
Postgrado en ciencias ambientales, Instituto Potosino de Investigación Científica y Tecnológica A.C (IPICYT). Camino a la Presa San José No. 2055. Col. Lomas 4ª. Sección, San Luis Potosí C.P. 78216, México.
MethodsX. 2022 Jun 23;9:101771. doi: 10.1016/j.mex.2022.101771. eCollection 2022.
Search inhibitors of Quorum Sensing (QS) in are challenging to find therapies due to the broad antibiotic resistance. Therefore, this study aimed to probe ten aromatic compounds as inhibitors of three transcriptional regulators of QS in . The methodology consisted in determining the Binding Gibbs Energy (BGE) with software Chimera (tool vina) and Mcule, comparing the averages by the Tukey method (p≤0.05) to find inhibitors of QS. Subsequently, the LD in the mice model was evaluated by three QSAR models, and the pharmacokinetic values were obtained from the ADME (the absorption distribution metabolism excretion) and PubChem databases. Found three potential inhibitors of RhlR with the lower BGE values in the range -6.70±0.21 to -7.43±0.35 kcal/mol. On the other side, all compounds were acceptable for Lipinski's rule of fives and the oral mice LD and ADME values. Concluding, the ferulic acid and eugenol showed the best total BGE values (-75.07±0.892 and -70.36±1.022 kcal/mol), proposing them as a new therapy against the virulence of . Finally, the studies have demonstrated are reproducible and valuable for putative QS inhibitors predicting and obtaining new studies derivatives from the results obtained in the present study. • The key benefits of this methodology are: Use free, licensed, flexible, and efficient software for molecular docking. • Validation and comparison of BGE employing two molecular docking software in three different proteins. • Use classical molecular dynamics to define the stability and the total BGE of interaction protein-ligand and find the best inhibitor of a protein for proposing them as a possible therapy against the virulence of specific pathogens.
由于广泛的抗生素耐药性，寻找群体感应（QS）抑制剂具有挑战性，难以找到治疗方法。因此，本研究旨在探究十种芳香族化合物作为QS三种转录调节因子的抑制剂。该方法包括使用Chimera软件（工具vina）和Mcule确定结合吉布斯自由能（BGE），通过Tukey方法比较平均值（p≤0.05）以找到QS抑制剂。随后，通过三种QSAR模型评估小鼠模型中的半数致死剂量（LD），并从ADME（吸收、分布、代谢、排泄）和PubChem数据库中获得药代动力学值。发现三种RhlR的潜在抑制剂，其BGE值较低，范围在-6.70±0.21至-7.43±0.35千卡/摩尔之间。另一方面，所有化合物均符合Lipinski的五规则以及小鼠口服LD和ADME值。结论是，阿魏酸和丁香酚显示出最佳的总BGE值（-75.07±0.892和-70.36±1.022千卡/摩尔），将它们作为针对[具体病原体名称未给出]毒力的新疗法。最后，[具体病原体名称未给出]的研究表明，对于预测QS抑制剂并从本研究获得的结果中获得新的研究衍生物而言，这些研究是可重复且有价值的。• 该方法的主要优点包括：使用免费、有许可证、灵活且高效的软件进行分子对接。• 在三种不同蛋白质中使用两种分子对接软件对BGE进行验证和比较。• 使用经典分子动力学来定义蛋白质-配体相互作用的稳定性和总BGE，并找到蛋白质的最佳抑制剂，将其作为针对特定病原体毒力的可能疗法。
