Identification of novel nt-MGAM inhibitors for potential treatment of type 2 diabetes: Virtual screening, atom based 3D-QSAR model, docking analysis and ADME study.
Identifieur interne : 000426 ( Main/Exploration ); précédent : 000425; suivant : 000427Identification of novel nt-MGAM inhibitors for potential treatment of type 2 diabetes: Virtual screening, atom based 3D-QSAR model, docking analysis and ADME study.
Auteurs : Aicha Laoud [Algérie] ; Fouad Ferkous [Algérie] ; Laura Maccari [Italie] ; Giorgio Maccari [Italie] ; Youcef Saihi [Algérie] ; Khaireddine Kraim [Algérie]Source :
- Computational biology and chemistry [ 1476-928X ] ; 2018.
Descripteurs français
- KwdFr :
- Diabète de type 2 (traitement médicamenteux), Hypoglycémiants (composition chimique), Inhibiteurs des glycoside hydrolases (composition chimique), Liaison hydrogène (MeSH), Ligands (MeSH), Polyols (composition chimique), Relation quantitative structure-activité (MeSH), Simulation de docking moléculaire (MeSH), Sulfates organiques (composition chimique), alpha-Glucosidase (composition chimique), Évaluation préclinique de médicament (MeSH).
- MESH :
- composition chimique : Hypoglycémiants, Inhibiteurs des glycoside hydrolases, Polyols, Sulfates organiques, alpha-Glucosidase.
- traitement médicamenteux : Diabète de type 2.
- Liaison hydrogène, Ligands, Relation quantitative structure-activité, Simulation de docking moléculaire, Évaluation préclinique de médicament.
English descriptors
- KwdEn :
- Diabetes Mellitus, Type 2 (drug therapy), Drug Evaluation, Preclinical (MeSH), Glycoside Hydrolase Inhibitors (chemistry), Hydrogen Bonding (MeSH), Hypoglycemic Agents (chemistry), Ligands (MeSH), Molecular Docking Simulation (MeSH), Quantitative Structure-Activity Relationship (MeSH), Sugar Alcohols (chemistry), Sulfuric Acid Esters (chemistry), alpha-Glucosidases (chemistry).
- MESH :
- chemical , chemistry : Glycoside Hydrolase Inhibitors, Hypoglycemic Agents, Sugar Alcohols, Sulfuric Acid Esters, alpha-Glucosidases.
- drug therapy : Diabetes Mellitus, Type 2.
- Drug Evaluation, Preclinical, Hydrogen Bonding, Ligands, Molecular Docking Simulation, Quantitative Structure-Activity Relationship.
Abstract
In this study, a virtual screening procedure was applied to identify new potential nt-MGAM inhibitors as a possible medication for type 2 diabetes. To this aim, a series of salacinol analogues were first investigated by docking analysis for their binding to the X-ray structure of the biological target nt-MGAM. Key interactions for ligand binding into the receptor active site were identified which shared common features to those found for other known inhibitors, which strengthen the results of this study. 3D QSAR model was then built and showed to be statistically significant and with a good predictive power for the training (R2 = 0.99, SD = 0.17, F = 555.3 and N = 27) and test set (Q2 = 0.81, Pearson(r) = 0.92, RMSE = 0.52, N = 08). The model was then used to virtually screen the ZINC database with the aim of identifying novel chemical scaffolds as potential nt-MGAM inhibitors. Further, in silico predicted ADME properties were investigated for the most promising molecules. The outcome of this investigation sheds light on the molecular characteristics of the binding of salacinol analogues to nt-MGAM enzyme and identifies new possible inhibitors which have the potential to be developed into drugs, thus significantly contributing to the design and optimization of therapeutic strategies against type 2 diabetes.
DOI: 10.1016/j.compbiolchem.2017.12.003
PubMed: 29274684
Affiliations:
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Electronic address: kkhchem@gmail.com.</nlm:affiliation><country xml:lang="fr">Algérie</country><wicri:regionArea>LCOA: Laboratoire de Chimie Organique Appliquée, Département de Chimie, Faculté des Sciences, Université Badji-Mokhtar - Annaba, BP 12, Annaba, Algeria; ENSET: Ecole Normale Supérieure d'Enseignement Technologique, Azzaba, Skikda</wicri:regionArea><wicri:noRegion>Skikda</wicri:noRegion></affiliation></author></analytic><series><title level="j">Computational biology and chemistry</title><idno type="eISSN">1476-928X</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Diabetes Mellitus, Type 2 (drug therapy)</term><term>Drug Evaluation, Preclinical (MeSH)</term><term>Glycoside Hydrolase Inhibitors (chemistry)</term><term>Hydrogen Bonding (MeSH)</term><term>Hypoglycemic Agents (chemistry)</term><term>Ligands (MeSH)</term><term>Molecular Docking Simulation (MeSH)</term><term>Quantitative Structure-Activity Relationship (MeSH)</term><term>Sugar Alcohols (chemistry)</term><term>Sulfuric Acid Esters (chemistry)</term><term>alpha-Glucosidases (chemistry)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Diabète de type 2 (traitement médicamenteux)</term><term>Hypoglycémiants (composition chimique)</term><term>Inhibiteurs des glycoside hydrolases (composition chimique)</term><term>Liaison hydrogène (MeSH)</term><term>Ligands (MeSH)</term><term>Polyols (composition chimique)</term><term>Relation quantitative structure-activité (MeSH)</term><term>Simulation de docking moléculaire (MeSH)</term><term>Sulfates organiques (composition chimique)</term><term>alpha-Glucosidase (composition chimique)</term><term>Évaluation préclinique de médicament (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="chemistry" xml:lang="en"><term>Glycoside Hydrolase Inhibitors</term><term>Hypoglycemic Agents</term><term>Sugar Alcohols</term><term>Sulfuric Acid Esters</term><term>alpha-Glucosidases</term></keywords><keywords scheme="MESH" qualifier="composition chimique" xml:lang="fr"><term>Hypoglycémiants</term><term>Inhibiteurs des glycoside hydrolases</term><term>Polyols</term><term>Sulfates organiques</term><term>alpha-Glucosidase</term></keywords><keywords scheme="MESH" qualifier="drug therapy" xml:lang="en"><term>Diabetes Mellitus, Type 2</term></keywords><keywords scheme="MESH" qualifier="traitement médicamenteux" xml:lang="fr"><term>Diabète de type 2</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Drug Evaluation, Preclinical</term><term>Hydrogen Bonding</term><term>Ligands</term><term>Molecular Docking Simulation</term><term>Quantitative Structure-Activity Relationship</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Liaison hydrogène</term><term>Ligands</term><term>Relation quantitative structure-activité</term><term>Simulation de docking moléculaire</term><term>Évaluation préclinique de médicament</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this study, a virtual screening procedure was applied to identify new potential nt-MGAM inhibitors as a possible medication for type 2 diabetes. To this aim, a series of salacinol analogues were first investigated by docking analysis for their binding to the X-ray structure of the biological target nt-MGAM. Key interactions for ligand binding into the receptor active site were identified which shared common features to those found for other known inhibitors, which strengthen the results of this study. 3D QSAR model was then built and showed to be statistically significant and with a good predictive power for the training (R<sup>2</sup> = 0.99, SD = 0.17, F = 555.3 and N = 27) and test set (Q<sup>2</sup> = 0.81, Pearson(r) = 0.92, RMSE = 0.52, N = 08). The model was then used to virtually screen the ZINC database with the aim of identifying novel chemical scaffolds as potential nt-MGAM inhibitors. Further, in silico predicted ADME properties were investigated for the most promising molecules. The outcome of this investigation sheds light on the molecular characteristics of the binding of salacinol analogues to nt-MGAM enzyme and identifies new possible inhibitors which have the potential to be developed into drugs, thus significantly contributing to the design and optimization of therapeutic strategies against type 2 diabetes.</div></front></TEI><affiliations><list><country><li>Algérie</li><li>Italie</li></country></list><tree><country name="Algérie"><noRegion><name sortKey="Laoud, Aicha" sort="Laoud, Aicha" uniqKey="Laoud A" first="Aicha" last="Laoud">Aicha Laoud</name></noRegion><name sortKey="Ferkous, Fouad" sort="Ferkous, Fouad" uniqKey="Ferkous F" first="Fouad" last="Ferkous">Fouad Ferkous</name><name sortKey="Kraim, Khaireddine" sort="Kraim, Khaireddine" uniqKey="Kraim K" first="Khaireddine" last="Kraim">Khaireddine Kraim</name><name sortKey="Saihi, Youcef" sort="Saihi, Youcef" uniqKey="Saihi Y" first="Youcef" last="Saihi">Youcef Saihi</name></country><country name="Italie"><noRegion><name sortKey="Maccari, Laura" sort="Maccari, Laura" uniqKey="Maccari L" first="Laura" last="Maccari">Laura Maccari</name></noRegion><name sortKey="Maccari, Giorgio" sort="Maccari, Giorgio" uniqKey="Maccari G" first="Giorgio" last="Maccari">Giorgio Maccari</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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