Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods

Betanidin (Bd) is a nitrogenous metabolite with significant bioactive potential influenced by pH. Its free radical scavenging activity and deprotonation pathway are crucial to studying its physicochemical properties. Motivated by the published discrepancies about the best deprotonation routes in Bd,...

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Main Authors: Iliana María Ramírez-Velásquez, Álvaro H. Bedoya-Calle, Ederley Vélez, Francisco J. Caro-Lopera
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:International Journal of Molecular Sciences
Subjects:
Online Access:https://www.mdpi.com/1422-0067/24/3/2923
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author Iliana María Ramírez-Velásquez
Álvaro H. Bedoya-Calle
Ederley Vélez
Francisco J. Caro-Lopera
author_facet Iliana María Ramírez-Velásquez
Álvaro H. Bedoya-Calle
Ederley Vélez
Francisco J. Caro-Lopera
author_sort Iliana María Ramírez-Velásquez
collection DOAJ
description Betanidin (Bd) is a nitrogenous metabolite with significant bioactive potential influenced by pH. Its free radical scavenging activity and deprotonation pathway are crucial to studying its physicochemical properties. Motivated by the published discrepancies about the best deprotonation routes in Bd, this work explores all possible pathways for proton extractions on that molecule, by using the direct approach method based on pK<sub>a</sub>. The complete space of exploration is supported by a linear relation with constant slope, where the pK<sub>a</sub> is written in terms of the associated deprotonated molecule energy. The deprotonation rounds 1, …, 6 define groups of parallel linear models with constant slope. The intercepts of the models just depend on the protonated energy for each round, and then the pK<sub>a</sub> can be trivially ordered and explained by the energy. We use the direct approximation method to obtain the value of pK<sub>a</sub>. We predict all possible outcomes based on a linear model of the energy and some related verified assumptions. We also include a new measure of similarity or dissimilarity between the protonated and deprotonated molecules, via a geometric–chemical descriptor called the Riemann–Mulliken distance (RMD). The RMD considers the cartesian coordinates of the atoms, the atomic mass, and the Mulliken charges. After exploring the complete set of permutations, we show that the successive deprotonation process does not inherit the local energy minimum and that the commutativity of the paths does not hold either. The resulting clusterization of pK<sub>a</sub> can be explained by the local acid and basic groups of the BD, and the successive deprotonation can be predicted by using the chemical explained linear models, which can avoid unnecessary optimizations. Another part of the research uses our own algorithm based on shape theory to determine the protein’s active site automatically, and molecular dynamics confirmed the results of the molecular docking of Bd in protonated and anionic form with the enzyme aldose reductase (AR). Also, we calculate the descriptors associated with the SET and SPLET mechanisms.
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spelling doaj.art-831f5f1528d149d3b552499521fd1e2a2023-11-16T17:04:21ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-02-01243292310.3390/ijms24032923Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT MethodsIliana María Ramírez-Velásquez0Álvaro H. Bedoya-Calle1Ederley Vélez2Francisco J. Caro-Lopera3Faculty of Exact and Applied Sciences, Instituto Tecnológico Metropolitano, Medellín 050034, ColombiaFaculty of Basic Sciences, University of Medellin, Medellín 050026, ColombiaFaculty of Basic Sciences, University of Medellin, Medellín 050026, ColombiaFaculty of Basic Sciences, University of Medellin, Medellín 050026, ColombiaBetanidin (Bd) is a nitrogenous metabolite with significant bioactive potential influenced by pH. Its free radical scavenging activity and deprotonation pathway are crucial to studying its physicochemical properties. Motivated by the published discrepancies about the best deprotonation routes in Bd, this work explores all possible pathways for proton extractions on that molecule, by using the direct approach method based on pK<sub>a</sub>. The complete space of exploration is supported by a linear relation with constant slope, where the pK<sub>a</sub> is written in terms of the associated deprotonated molecule energy. The deprotonation rounds 1, …, 6 define groups of parallel linear models with constant slope. The intercepts of the models just depend on the protonated energy for each round, and then the pK<sub>a</sub> can be trivially ordered and explained by the energy. We use the direct approximation method to obtain the value of pK<sub>a</sub>. We predict all possible outcomes based on a linear model of the energy and some related verified assumptions. We also include a new measure of similarity or dissimilarity between the protonated and deprotonated molecules, via a geometric–chemical descriptor called the Riemann–Mulliken distance (RMD). The RMD considers the cartesian coordinates of the atoms, the atomic mass, and the Mulliken charges. After exploring the complete set of permutations, we show that the successive deprotonation process does not inherit the local energy minimum and that the commutativity of the paths does not hold either. The resulting clusterization of pK<sub>a</sub> can be explained by the local acid and basic groups of the BD, and the successive deprotonation can be predicted by using the chemical explained linear models, which can avoid unnecessary optimizations. Another part of the research uses our own algorithm based on shape theory to determine the protein’s active site automatically, and molecular dynamics confirmed the results of the molecular docking of Bd in protonated and anionic form with the enzyme aldose reductase (AR). Also, we calculate the descriptors associated with the SET and SPLET mechanisms.https://www.mdpi.com/1422-0067/24/3/2923betanidinlinear modelcluster predictionpK<sub>a</sub> predictionRiemann–Mulliken distancedeprotonation
spellingShingle Iliana María Ramírez-Velásquez
Álvaro H. Bedoya-Calle
Ederley Vélez
Francisco J. Caro-Lopera
Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
International Journal of Molecular Sciences
betanidin
linear model
cluster prediction
pK<sub>a</sub> prediction
Riemann–Mulliken distance
deprotonation
title Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
title_full Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
title_fullStr Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
title_full_unstemmed Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
title_short Dissociation Mode of the O–H Bond in Betanidin, pK<sub>a</sub>-Clusterization Prediction, and Molecular Interactions via Shape Theory and DFT Methods
title_sort dissociation mode of the o h bond in betanidin pk sub a sub clusterization prediction and molecular interactions via shape theory and dft methods
topic betanidin
linear model
cluster prediction
pK<sub>a</sub> prediction
Riemann–Mulliken distance
deprotonation
url https://www.mdpi.com/1422-0067/24/3/2923
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AT alvarohbedoyacalle dissociationmodeoftheohbondinbetanidinpksubasubclusterizationpredictionandmolecularinteractionsviashapetheoryanddftmethods
AT ederleyvelez dissociationmodeoftheohbondinbetanidinpksubasubclusterizationpredictionandmolecularinteractionsviashapetheoryanddftmethods
AT franciscojcarolopera dissociationmodeoftheohbondinbetanidinpksubasubclusterizationpredictionandmolecularinteractionsviashapetheoryanddftmethods