The unbinding studies of vascular endothelial growth factor receptor-2 protein tyrosine kinase type II inhibitors

Synthesis, Characterizations, and Quantum Chemical Investigations on Imidazo[1,2-a]pyrimidine-Schiff Base Derivative: (E)-2-Phenyl-N-(thiophen-2-ylmethylene)imidazo[1,2-a]pyrimidin-3-amine

In this study, (E)-2-phenyl-N-(thiophen-2-ylmethylene)imidazo[1,2-a]pyrimidin-3-amine (3) is synthesized, and detailed spectral characterizations using 1H NMR, 13C NMR, mass, and Fourier transform infrared (FT-IR) spectroscopy were performed. The optimized geometry was computed using the density functional theory method at the B3LYP/6-311++G(d,p) basis set. The theoretical FT-IR and NMR (1H and 13C) analysis are agreed to validate the structural assignment made for (3). Frontier molecular orbitals, molecular electrostatic potential, Mulliken atomic charge, electron localization function, localized orbital locator, natural bond orbital, nonlinear optical, Fukui functions, and quantum theory of atoms in molecules analyses are undertaken and meticulously interpreted, providing profound insights into the molecular nature and behaviors. In addition, ADMET and drug-likeness studies were carried out and investigated. Furthermore, molecular docking and molecular dynamics simulations have been studied, indicating that this is an ideal molecule to develop as a potential vascular endothelial growth factor receptor-2 inhibitor.

The prediction of protein-ligand unbinding for modern drug discovery

INTRODUCTION

Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods.

AREAS COVERED

In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed.

EXPERT OPINION

Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.

Design, synthesis, and antitumor activity of novel benzoheterocycle derivatives as inhibitors of vascular endothelial growth factor receptor-2 tyrosine kinase

The vascular endothelial growth factor receptor-2 signaling pathway promotes the formation of new blood vessels, and vascular endothelial growth factor receptor-2 tyrosine kinase exists in both active and inactive conformations. Novel indole–benzimidazole and indole–benzothiazole derivatives joined by different linkers are designed and synthesized as inhibitors of vascular endothelial growth factor receptor-2 tyrosine kinase. All the synthesized compounds were evaluated for their cytotoxicity against four human cancer cell lines (HeLa, HT29, A549, and MDA-MB-435) and human umbilical vein endothelial cell. Meanwhile, the inhibitory activities against vascular endothelial growth factor receptor-2 are estimated in vitro and the binding interactions with dual conformations of vascular endothelial growth factor receptor-2 tyrosine kinase are evaluated by molecular docking. Compounds 5a–c and 14 show inhibitory activity against vascular endothelial growth factor receptor-2 tyrosine kinase and promising cytotoxicity, specifically with IC50 values ranging between 0.1 and 1 μM, which imply broad-spectrum antitumor activity. These results provide a deep insight into potential structural modifications for developing potent vascular endothelial growth factor receptor-2 tyrosine kinase inhibitors.

Molecular Modeling of ALK L1198F and/or G1202R Mutations to Determine Differential Crizotinib Sensitivity

Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that has been recognized as a therapeutic target for EML4-ALK fusion-positive nonsmall cell lung cancer (NSCLC) treatment using type I kinase inhibitors such as crizotinib to take over the ATP binding site. According to Shaw’s measurements, ALK carrying G1202R mutation shows reduced response to crizotinib (IC₅₀ = 382 nM vs. IC₅₀ = 20 nM for wild-type), whereas L1198F mutant is more responsive (IC₅₀ = 0.4 nM). Interestingly, the double mutant L1198F/G1202R maintains a similar response (IC₅₀ = 31 nM) to the wild-type. Herein we conducted molecular modeling simulations to elucidate the varied crizotinib sensitivities in three mutants carrying L1198F and/or G1202R. Both L1198 and G1202 are near the ATP pocket. Mutation G1202R causes steric hindrance that blocks crizotinib accessibility, which greatly reduces efficacy, whereas mutation L1198F enlarges the binding pocket entrance and hydrophobically interacts with crizotinib to enhance sensitivity. With respect to the double mutant L1198F/G1202R, F1198 indirectly pulls R1202 away from the binding entrance and consequently alleviates the steric obstacle introduced by R1202. These results demonstrated how the mutated residues tune the crizotinib response and may assist kinase inhibitor development especially for ALK G1202R, analogous to the ROS1 G2302R and MET G1163R mutations that are also resistant to crizotinib treatment in NSCLC.

Advanced molecular dynamics simulation methods for kinase drug discovery

Interest in the application of molecular dynamics (MD) simulations has increased in the field of protein kinase (PK) drug discovery. PKs belong to an important drug target class because they are directly involved in a number of diseases, including cancer. MD methods simulate dynamic biological and chemical events at an atomic level. This information can be combined with other in silico and experimental methods to efficiently target selected receptors. In this review, we present common and advanced methods of MD simulations and we focus on the recent applications of MD-based methodologies that provided significant insights into the elucidation of biological mechanisms involving PKs and into the discovery of novel kinase inhibitors.