Discovery of potent inhibitors for interleukin-2-inducible T-cell kinase: structure-based virtual screening and molecular dynamics simulation approaches

Abstract

In our study, a structure-based virtual screening study was conducted to identify potent ITK inhibitors, as ITK is considered to play an important role in the treatment of inflammatory diseases. We developed a structure-based pharmacophore model using the crystal structure (PDB ID: 3MJ2) of ITK complexed with BMS-50944. The most predictive model, SB-Hypo1, consisted of six features: three hydrogen-bond acceptors (HBA), one hydrogen-bond donor (HBD), one ring aromatic (RA), and one hydrophobic (HY). The statistical significance of SB-Hypo1 was validated using wide range of test set molecules and a decoy set. The resulting well-validated model could then be confidently used as a 3D query to screen for drug-like molecules in a database, in order to retrieve new chemical scaffolds that may be potent ITK inhibitors. The hits retrieved from this search were filtered based on the maximum fit value, drug-likeness, and ADMET properties, and the hits that were retained were used in a molecular docking study to find the binding mode and molecular interactions with crucial residues at the active site of the protein. These hits were then fed into a molecular dynamics simulation to study the flexibility of the activation loop of ITK upon ligand binding. This combination of methodologies is a valuable tool for identifying structurally diverse molecules with desired biological activities, and for designing new classes of selective ITK inhibitors.

Evaluation and Optimization of Virtual Screening Workflows with DEKOIS 2.0 – A Public Library of Challenging Docking Benchmark Sets

“…In practice, the application of benchmark sets provides various benefits for the user. For instance, benchmarking can aid the development of scoring functions and optimization of screening tools. − Also the selection of multiple conformations for a target structure to improve screening performance can be guided by the application of decoy sets. , Benchmark sets can also help with the receptor optimization and validation of homology models . The assessment of docking performance can ultimately help to find an efficient virtual screening workflow for a specific target.…”

Pharmacophore-driven identification of N-methyl-D-receptor antagonists as potent neuroprotective agents validated using in vivo studies

“…As previously mentioned, the “BEST” algorithm was applied to produce energy-minimized conformers (a maximum of 255) for every molecule including an energy threshold of 20 kcal/mol. These conformations were used for hypothesis generation using DS [ 17 , 18 ].…”

Pharmacophore-driven Identification of N-Methyl-D-Receptor Antagonists as Potent Neuroprotective Agents Validated UsingIn-VivoStudies

“…A maximum numbers of “255” conformations were produced for every compound by employing the “BEST” conformation method for model generation which is based on CHARMm force field to guarantee the energy-minimized conformation of every molecule with an energy threshold of 20 kcal/mol. All the possible conformations of the compounds were considered and were used for hypothesis generation using DS 10,11 .…”