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QSAR, ADME-Tox, molecular docking and molecular dynamics simulations of novel selective glycine transporter type 1 inhibitors with memory enhancing properties.

ABSTRACT: A structural class of forty glycine transporter type 1 (GlyT1) inhibitors, was examined using molecular modeling techniques. The quantitative structure-activity relationships (QSAR) technology confirmed that human GlyT1 activity is strongly and significantly affected by constitutional, geometrical, physicochemical and topological descriptors. ADME-Tox in-silico pharmacokinetics revealed that L28 and L30 ligands were predicted as non-toxic inhibitors with a good ADME profile and the highest probability to penetrate the central nervous system (CNS). Molecular docking results indicated that the predicted inhibitors block GlyT1, reacting specifically with Phe319, Phe325, Tyr123, Tyr 124, Arg52, Asp475, Ala117, Ala479, Ile116 and Ile483 amino acids of the dopamine transporter (DAT) membrane protein. These results were qualified and strengthened using molecular dynamics (MD) study, which affirmed that the established intermolecular interactions for (L28, L30-DAT protein) complexes remain perfectly stable along 50 ns of MD simulation time. Therefore, they could be strongly recommended as therapeutics in medicine to improve memory performance.

SUBMITTER: El Fadili M

PROVIDER: S-EPMC9971180 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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QSAR, ADME-Tox, molecular docking and molecular dynamics simulations of novel selective glycine transporter type 1 inhibitors with memory enhancing properties.

El Fadili Mohamed M Er-Rajy Mohammed M Imtara Hamada H Noman Omar M OM Mothana Ramzi A RA Abdullah Sheaf S Zerougui Sara S Elhallaoui Menana M

Heliyon 20230213 2

A structural class of forty glycine transporter type 1 (GlyT1) inhibitors, was examined using molecular modeling techniques. The quantitative structure-activity relationships (QSAR) technology confirmed that human GlyT1 activity is strongly and significantly affected by constitutional, geometrical, physicochemical and topological descriptors. ADME-Tox in-silico pharmacokinetics revealed that L28 and L30 ligands were predicted as non-toxic inhibitors with a good ADME profile and the highest proba ...[more]

PMID: 36865465

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Project description:Tuberculosis (TB) has become the biggest threat to human society because of the rapid rise in resistance to the causative bacteria Mycobacterium tuberculosis (MTB) against the available anti-tubercular drugs. There is an urgent need to design new multi-targeted anti-tubercular agents to overcome the resistance species of MTB through computational design tools. With this aim in mind, we performed a combination of atom-based three-dimensional quantitative structure-activity relationship (3D-QSAR), six-point pharmacophore (AHHRRR), and molecular docking analysis on a series of fifty-eight anti-tubercular agents. The created QSAR model had a R2 value of 0.9521, a Q2 value of 0.8589, and a Pearson r-factor of 0.8988, all of which are statistically significant. This means that the model was effective at making predictions. We performed the molecular docking study for the data set of compounds with the two important anti-tubercular target proteins, Enoyl acyl carrier protein reductase (InhA) (PDBID: 2NSD) and Decaprenyl phosphoryl-β-D-Ribose 20-epimerase (DprE1) (PDBID: 4FDO). We used the similarity search principle to do virtual screening on 237 compounds from the PubChem database in order to find strong anti-tubercular agents that act against multiple targets. The screened compound, MK3, showed the highest docking score of -9.2 and -8.3 kJ/mol towards both the target proteins InhA and DprE1, which were picked for a 100 ns molecular-dynamic simulation study using GROMACS. The data showed that the compound MK3 was thermodynamically stable and effectively bound to both target proteins in their active binding pockets without much movement. The analysis of the highest occupied molecular orbital (HOMO), lowest unoccupied molecular orbital (LUMO), and energy gap predicts the molecular reactivity and stability of the identified molecule. Based on the result of the above studies, the proposed compound MK3 can be successfully used for the development of a novel multi-targeted anti-tubercular agent with high binding affinity and favourable ADME-T properties.

Dataset Information

QSAR, ADME-Tox, molecular docking and molecular dynamics simulations of novel selective glycine transporter type 1 inhibitors with memory enhancing properties.

Publications

QSAR, ADME-Tox, molecular docking and molecular dynamics simulations of novel selective glycine transporter type 1 inhibitors with memory enhancing properties.

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