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Small-molecule glucokinase activators (GKAs) are currently being investigated as therapeutic options for the treatment of type 2 diabetes (T2D). Because liver overexpression of glucokinase is thought to be associated with altered lipid profiles, this study aimed at assessing the potential lipogenic risks linked to oral GKA administration.Nine GKA candidates were qualified for their ability to activate recombinant glucokinase and to stimulate glycogen synthesis in rat hepatocytes and insulin secretion in rat INS-1E cells. In vivo activity was monitored by plasma glucose and HbA1c measurements after oral administration in rodents. Risk-associated effects were assessed by measuring hepatic and plasma triglycerides and free fatty acids, as well as plasma aminotransferases, and alkaline phosphatase.GKAs, while efficiently decreasing glycaemia in acute conditions and HbA1c levels after chronic administration in hyperglycemic db/db mice, were potent inducers of hepatic steatosis. This adverse outcome appeared as soon as 4 days after daily oral administration at pharmacological doses and was not transient. GKA treatment similarly increased hepatic triglycerides in diabetic and normoglycaemic rats, together with a pattern of metabolic phenotypes including different combinations of increased plasma triglycerides, free fatty acids, alanine and aspartyl aminotransferases, and alkaline phosphatase. GKAs belonging to three distinct structural families induced hepatic steatosis in db/db mice, arguing in favour of a target-mediated, rather than a chemical class-mediated, effect.Given the risks associated with fatty liver disease in the general population and furthermore in patients with T2D, these findings represent a serious warning for the use of GKAs in humans.This article is commented on by Rees and Gloyn, pp. 335-338 of this issue. To view this commentary visit http://dx.doi.org/10.1111/j.1476-5381.2012.02201.x.

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.