Abstract
The SMD solvation model (Solvation Model based on the Density) and eight density functionals, CAM-B3LYP, LC-ωPBE, M11, MN12SX, N12SX, ωB97, ωB97X, and ωB97XD, were assessed in link with the Def2TZVP basis set for the calculation of the structure of the Leu-Enkephalin Opioid Peptide Neurotransmitter as well as their molecular properties. Through the Conceptual Density Functional Theory (CDFT), the entire chemical descriptors for the system were calculated. The active regions of the molecules necessary for electrophilic, nucleophilic and radical attacks were chosen through linking them with the corresponding Fukui functions. Furthermore, the prediction of the pKa value for the peptide is done with great accuracy as well as the ability of the studied molecule in acting as an efficient inhibitor of the formation of Advanced Glycation Endproducts (AGEs), which comprises of a useful knowledge for the development of drugs for preventing Alzheimer, Diabetes and Parkinson diseases. Lastly, the bioactivity scores for the studied peptides are predicted via various methodologies.
Highlights
The molecular structure of Leu-Enkephalin, which graphical sketch is shown in Figure 1, was preoptimized in the gas phase by considering the DFTBA model available in Gaussian 09 and reoptimized using the eight density functionals mentioned in the previous section together with the Def2SVP basis set and the Solvation Model Density (SMD) solvent model using water as the solvent
It was concluded that the key factor in the study of the chemical reactivity of the potential Advanced Glycation Endproducts (AGEs) inhibitors was on their nucleophilic character and there are several definitions of nucleophilicity [37], our results suggested that the inverse of the net electrophilicity ∆ω± could be a good definition for the nucleophilicity N
We have presented the results of a study of the chemical reactivity of the Leucine-Enkephalin opioid neurotransmitter peptide based on the Conceptual DFT as a tool to explain the molecular interactions
Summary
It is our belief that the bioactivity of these peptides is intimately related to their chemical reactivity from a molecular perspective. For this reason, we consider it essential to study the chemical reactivity of natural products that have the potential to become medicines through the tools provided by Computational Chemistry and Molecular Modeling. The most powerful tool currently available to study the chemical reactivity of molecular systems from the point of view of Computational Chemistry and Molecular Modeling is the Conceptual DFT [1] [2], called Chemical Reactivity Theory, which using a series of global and local descriptors allow to predict the interactions between molecules and understand the way in that chemical reactions proceed. The larger the number of studies with different groups of molecules increases the validity of the used methodologies
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