AMPK-derived peptides reduce blood glucose levels but lead to fat retention in the liver of obese mice

Pharmacological Targeting of AMP-Activated Protein Kinase and Opportunities for Computer-Aided Drug Design

As a central regulator of metabolism, the AMP-activated protein kinase (AMPK) is an established therapeutic target for metabolic diseases. Beyond the metabolic area, the number of medical fields that involve AMPK grows continuously, expanding the potential applications for AMPK modulators. Even though indirect AMPK activators are used in the clinics for their beneficial metabolic outcome, the few described direct agonists all failed to reach the market to date, which leaves options open for novel targeting methods. As AMPK is not actually a single molecule and has different roles depending on its isoform composition, the opportunity for isoform-specific targeting has notably come forward, but the currently available modulators fall short of expectations. In this review, we argue that with the amount of available structural and ligand data, computer-based drug design offers a number of opportunities to undertake novel and isoform-specific targeting of AMPK.

AnchorDock: Blind and Flexible Anchor-Driven Peptide Docking

The huge conformational space stemming from the inherent flexibility of peptides is among the main obstacles to successful and efficient computational modeling of protein-peptide interactions. Current peptide docking methods typically overcome this challenge using prior knowledge from the structure of the complex. Here we introduce AnchorDock, a peptide docking approach, which automatically targets the docking search to the most relevant parts of the conformational space. This is done by precomputing the free peptide's structure and by computationally identifying anchoring spots on the protein surface. Next, a free peptide conformation undergoes anchor-driven simulated annealing molecular dynamics simulations around the predicted anchoring spots. In the challenging task of a completely blind docking test, AnchorDock produced exceptionally good results (backbone root-mean-square deviation ≤ 2.2Å, rank ≤15) for 10 of 13 unbound cases tested. The impressive performance of AnchorDock supports a molecular recognition pathway that is driven via pre-existing local structural elements.