RESUMO
The accurate experimental estimation of protein-ligand systems' residence time (τ) has become very relevant in drug design projects due to its importance in the last stages of refinement of the drug's pharmacodynamics and pharmacokinetics. It is now well-known that it is not sufficient to estimate the affinity of a protein-drug complex in the thermodynamic equilibrium process in in vitro experiments (closed systems), where the concentrations of the drug and protein remain constant. On the contrary, it is mandatory to consider the conformational dynamics of the system in terms of the binding and unbinding processes between protein and drugs in in vivo experiments (open systems), where their concentrations are in constant flux. This last model has been proven to dictate much of several drugs' pharmacological activities in vivo. At the atomistic level, molecular dynamics simulations can explain why some drugs are more effective than others or unveil the molecular aspects that make some drugs work better in one molecular target. Here, the protein kinases Aurora A/B, complexed with its inhibitor Danusertib, were studied using conventional and enhanced molecular dynamics (MD) simulations to estimate the dissociation paths and, therefore, the computational τ values and their comparison with experimental ones. Using classical molecular dynamics (cMD), three differential residues within the Aurora A/B active site, which seems to play an essential role in the observed experimental Danusertib's residence time against these kinases, were characterized. Then, using WT-MetaD, the relative Danusertib's residence times against Aurora A/B kinases were measured in a nanosecond time scale and were compared to those τ values observed experimentally. In addition, the potential dissociation paths of Danusertib in Aurora A and B were characterized, and differences that might be explained by the differential residues in the enzyme's active sites were found. In perspective, it is expected that this computational protocol can be applied to other protein-ligand complexes to understand, at the molecular level, the differences in residence times and amino acids that may contribute to it.
Assuntos
Aurora Quinase A , Aurora Quinase B , Simulação de Dinâmica Molecular , Aurora Quinase B/metabolismo , Aurora Quinase B/química , Aurora Quinase B/antagonistas & inibidores , Aurora Quinase A/metabolismo , Aurora Quinase A/química , Aurora Quinase A/antagonistas & inibidores , Pirazóis/química , Pirazóis/metabolismo , Conformação Proteica , Inibidores de Proteínas Quinases/química , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/metabolismo , Ligação Proteica , Humanos , Benzamidas/química , Benzamidas/metabolismo , Benzamidas/farmacologia , TermodinâmicaRESUMO
FLT3 and dual Aurora B/FLT3 inhibitors have shown relevance in the search for promising new anticancer compounds, mainly for acute myeloid leukemia (AML). This study was designed to investigate the interactions between human FLT3 in the kinase domain with several indolin-2-one derivatives, structurally similar to Sunitinib. Molegro Virtual Docker (MVD) software was utilized in docking analyses. The predicted model of the training group, considering nineteen amino acid residues, performed in Chemoface, achieved an R2 of 0.82, suggesting that the binding conformations of the ligands with FLT3 are reasonable, and the data can be used to predict the interaction energy of other FLT3 inhibitors with similar molecular patterns. The MolDock Score for energy for compound 1 showed more stable interaction energy (-233.25 kcal mol-1) than the other inhibitors studied, while Sunitinib presented as one of the least stable (-160.94 kcal mol-1). Compounds IAF70, IAF72, IAF75, IAF80, IAF84, and IAF88 can be highlighted as promising derivatives for synthesis and biological evaluation against FLT3. Furthermore, IAF79 can be considered to be a promising dual Aurora B/FLT3 inhibitor, and its molecular pattern can be exploited synthetically to search for new indolin-2-one derivatives that may become drugs used in the treatment of cancers, including AML.