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Computational Peptidology Assisted by Conceptual DensityFunctional Theory for the Study of Five New Antifungal Tripeptides

机译:概念密度辅助的计算肽学研究五种新型抗真菌三肽的功能理论

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摘要

A well-behaved model chemistry previously validated for the study of the chemical reactivity of peptides was considered for the calculation of the molecular properties and structures of a group of five new antifungal tripeptides, namely (2R)-2-[(2S)-2-[(2S)-2-amino-3-phenylpropanamido]propanamido]-5-[(diaminomethylidene)amino]pentanoic acid, (2S)-2-[(2S)-2-[(2S)-2-amino-3-phenyl propanamido]propanamido]-3-(4-hydroxyphenyl)propanoic acid, (2S)-2-[(2S)-2-[(2S)-2-amino-3-phenylpropanamido]-3-methylbutanamido]-3-(4-hydroxyphenyl)propanoic acid, (2R)-2-[(2S)-2-[(2S)-2-amino-3-phenylpropanamido]-3-(1H-indol-3-yl)propanamido]-3-sulfanylpropanoic acid, and (2S)-2-[(2S)-2-[(2S)-2-amino-3-phenylpropanamido]-3-(1H-indol-3-yl)propanamido]-3-(4-hydroxyphenyl)propanoic acid, according to their amino acid sequences. A methodology based on conceptual density functional theory was chosen for the determination of the reactivity descriptors. The molecular active sites were associated with the active regions of the molecules that were associated with the nucleophilic, electrophilic, and radical Fukui functions. Additionally, the pKa values for the different peptides are predicted with great accuracy, which constitutes a useful knowledge for the process of drug design. Finally, the bioactivity scores forthe new antifungal peptides are predicted through a homology methodologyrelating them with the calculated reactivity descriptors.
机译:考虑过行为良好的模型化学,该化学方法先前已被验证可用于研究肽的化学反应性,可用于计算一组五个新的抗真菌三肽,即(2R)-2-[(2S)-2]的分子特性和结构。 -[[(2S)-2-氨基-3-苯基丙酰胺基]丙酰胺基] -5-[(二氨基亚甲基)氨基]戊酸,(2S)-2-[[2S)-2-[(2S)-2-氨基- 3-苯基丙酰胺基]丙酰胺基] -3-(4-羟基苯基)丙酸,(2S)-2-[(2S)-2-[(2S)-2-氨基-3-苯基丙酰胺基] -3-甲基丁酰胺基]- 3-(4-羟基苯基)丙酸,(2R)-2-[(2S)-2-[(2S)-2-氨基-3-苯基丙酰胺基] -3-(1H-吲哚-3-基)丙酰胺基] -3-硫烷基丙酸和(2S)-2-[(2S)-2-[(2S)-2-氨基-3-苯基丙酰胺基] -3-(1 H -吲哚-3 [-基)丙酰胺基] -3-(4-羟基苯基)丙酸,根据其氨基酸序列。选择了一种基于概念密度泛函理论的方法来确定反应性描述符。分子活性位点与与亲核,亲电和自由基Fukui功能有关的分子的活性区有关。此外,可以非常准确地预测不同肽的p K a值,这对药物设计过程具有重要的帮助。最后,生物活性得分为通过同源性方法预测新的抗真菌肽将它们与计算出的反应性描述符关联起来。

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