Design of new small molecules derived from indolin-2-one as potent TRKs inhibitors using a computer-aided drug design approach.

Tropomyosin receptor kinase (TRKs) enzymes are responsible for cancers associated with the neurotrophic tyrosine kinase receptor gene fusion and are identified as effective targets for anticancer drug discovery. A series of small-molecule indolin-2-one derivatives showed remarkable biological activity against TRKs enzymatic activity. These small molecules could have an excellent profile for pharmaceutical application in the treatment of cancers caused by TRKs activity. The aim of this study is to modify the structure of these molecules to obtain new molecules with improved TRK inhibitory activity and pharmacokinetic properties favorable to the design of new drugs. Based on these series, we carried out a 3D-QSAR study. As a result, robust and reliable CoMFA and CoMSIA models are developed and applied to the design of 11 new molecules. These new molecules have a biological activity superior to the most active molecule in the starting series. The eleven designed molecules are screened using drug-likeness, ADMET proprieties, molecular docking, and MM-GBSA filters. The results of this screening identified the T1, T3, and T4 molecules as the best candidates for strong inhibition of TRKs enzymatic activity. In addition, molecular dynamics simulations are performed for TRK free and complexed with ligands T1, T3, and T4 to evaluate the stability of ligand-protein complexes over the simulation time. On the other hand, we proposed experimental synthesis routes for these newly designed molecules. Finally, the designed molecules T1, T2, and T3 have great potential to become reliable candidates for the conception of new drug inhibitors of TRKs.Communicated by Ramaswamy H. Sarma.

Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach.

In this study, using the Comparative Molecular Field Analysis (CoMFA) approach, the structure-activity relationship of 33 small quinoline-based compounds with biological anti-gastric cancer activity in vitro was analyzed in 3D space. Once the 3D geometric and energy structure of the target chemical library has been optimized and their steric and electrostatic molecular field descriptions computed, the ideal 3D-QSAR model is generated and matched using the Partial Least Squares regression (PLS) algorithm. The accuracy, statistical precision, and predictive power of the developed 3D-QSAR model were confirmed by a range of internal and external validations, which were interpreted by robust correlation coefficients (RTrain2=0.931; Qcv2=0.625; RTest2=0.875). After carefully analyzing the contour maps produced by the trained 3D-QSAR model, it was discovered that certain structural characteristics are beneficial for enhancing the anti-gastric cancer properties of Quinoline derivatives. Based on this information, a total of five new quinoline compounds were developed, with their biological activity improved and their drug-like bioavailability measured using POM calculations. To further explore the potential of these compounds, molecular docking and molecular dynamics simulations were performed in an aqueous environment for 100 nanoseconds, specifically targeting serine/threonine protein kinase. Overall, the new findings of this study can serve as a starting point for further experiments with a view to the identification and design of a potential next-generation drug for target therapy against cancer.