QSAR modelling, molecular docking, molecular dynamic and ADMET prediction of pyrrolopyrimidine derivatives as novel Bruton's tyrosine kinase (BTK) inhibitors

In recent years, there has been a focus on developing and discovering novel Bruton's tyrosine kinase (BTK) inhibitors, as they offer an effective treatment strategy for B-cell malignancies. BTK plays a crucial role in B cell receptor (BCR)-mediated activation and proliferation by regulating downstream factors such as the NF-κB and MAP kinase pathways. To address this challenge and propose potential therapeutic options for B-cell lymphomas, researchers conducted 2D-QSAR and ADMET studies on pyrrolopyrimidine derivatives that act as inhibitors of the BCR site in cytochrome b. These studies aim to improve and identify new compounds that could serve as more potent potential BTK inhibitors, which would lead to the identification of new drug candidates in this field. In our study, we used 2D-QSAR (multiple linear regression, multiple nonlinear regression, and artificial neural networks), molecular docking, molecular dynamics, and ADMET properties to investigate the potential of 35 pyrrolopyrimidine derivatives as BTK inhibitors. A molecular docking study and molecular dynamics simulations of molecule 13 over 10 ns revealed that it establishes multiple hydrogen bonds with several residues and exhibits frequent stability throughout the simulation period. Based on the results obtained by molecular modeling, we proposed six new compounds (Pred1, Pred2, Pred3, Pred4, Pred5, and Pred6) with highly significant predicted activity by MLR models. A study based on the in silico evaluation of the predicted ADMET properties of the new candidate molecules is strongly recommended to classify these molecules as promising candidates for new anticancer agents specifically designed to target Bruton's tyrosine kinase (BTK) inhibition.

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

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.