Structural and thermodynamic characterization of allosteric transitions in human serum albumin with metadynamics simulations.

Human serum albumin (HSA) is the most prominent protein in blood plasma, responsible for the maintenance of blood viscosity and transport of endogenous and exogenous molecules. Fatty acids (FA) are the most common ligands of HSA and their binding can modify the protein's structure. The protein can assume two well-defined conformations, referred to as 'Neutral' and 'Basic'. The Neutral (N) state occurs at pH close to 7.0 and in the absence of bound FA. The Basic (B) state occurs at pH higher than 8.0 or when the protein is bound to long-chain FA. HSA's allosteric behaviour is dependent on the number on FA bound to the structure. However, the mechanism of this allosteric regulation is not clear. To understand how albumin changes its conformation, we compared a series of HSA structures deposited in the protein data bank to identify the minimum amount of FA bound to albumin, which is enough to drive the allosteric transition. Thereafter, non-biased molecular dynamics (MD) simulations were used to track protein's dynamics. Surprisingly, running an ensemble of relatively short MD simulations, we observed rapid transition from the B to the N state. These simulations revealed differences in the mobilities of the protein's subdomains, with one domain unable to fully complete its transition. To track the transition dynamics in full, we used these results to choose good geometrical collective variables for running metadynamics simulations. The metadynamics calculations showed that there was a low energy barrier for the transition from the B to the N state, while a higher energy barrier was observed for the N to the B transition. These calculations also offered valuable insights into the transition process.

Resistance to a tyrosine kinase inhibitor mediated by changes to the conformation space of the kinase.

Gilteritinib is a highly selective and effective inhibitor of the FLT3/ITD mutated protein, and is used successfully in treating acute myeloid leukaemia (AML). Unfortunately, tumour cells gradually develop resistance to gilteritinib due to mutations in the molecular drug target. The atomistic details behind this observed resistance are not clear, since the protein structure of the complex is only available in the inactive state, while the drug binds better to the active state. To overcome this limitation, we used a computer-aided approach where we docked gilteritinib to the active site of FLT3/ITD and calculated the Gibbs free energy difference between the binding energies of the parental and mutant enzymes. These calculations agreed with experimental estimations for one mutation (F691L) but not the other (D698N). To further understand how these mutations operate, we used metadynamics simulations to study the conformational landscape of the activation process. Both mutants show a lower activation energy barrier which suggests that they are more likely to adopt an active state until inhibited, making the mutant enzymes more active. This suggests that a higher efficiency of tyrosine kinases contributes to resistance not only against type 2 but also against type 1 kinase inhibitors.

Is breaking of a hydrogen bond enough to lead to drug resistance?

Drug resistance is a serious problem in cancer, viral, bacterial, fungal and parasitic diseases. Examination of crystal structures of protein-drug complexes is often not enough to explain why a certain mutation leads to drug resistance. As an example, the crystal structure of the kinase inhibitor dasatinib bound to the Abl1 kinase shows a hydrogen bond between the drug and residue Thr315 and very few contacts between the drug and residues Val299 and Phe317, yet mutations in those residues lead to drug resistance. In the first case, it is tempting to suggest that the loss of a hydrogen bond leads to drug resistance, whereas in the other two cases it is not known why mutations lead to drug resistance in the first place. We carried out extensive molecular dynamics (MD) simulations and free energy calculations to explain drug resistance to dasatinib from a molecular point of view and show that resistance is due to a multitude of subtle effects. Importantly, our calculations could reproduce the experimental values for the binding energies upon mutations in all three cases and shed light on their origin.