Extracting binding energies and binding modes from biomolecular simulations of fragment binding to endothiapepsin.

Fragment-based drug discovery (FBDD) aims to discover a set of small binding fragments that may be subsequently linked together. Therefore, in-depth knowledge of the individual fragments' structural and energetic binding properties is essential. In addition to experimental techniques, the direct simulation of fragment binding by molecular dynamics (MD) simulations became popular to characterize fragment binding. However, former studies showed that long simulation times and high computational demands per fragment are needed, which limits applicability in FBDD. Here, we performed short, unbiased MD simulations of direct fragment binding to endothiapepsin, a well-characterized model system of pepsin-like aspartic proteases. To evaluate the strengths and limitations of short MD simulations for the structural and energetic characterization of fragment binding, we predicted the fragments' absolute free energies and binding poses based on the direct simulations of fragment binding and compared the predictions to experimental data. The predicted absolute free energies are in fair agreement with the experiment. Combining the MD data with binding mode predictions from molecular docking approaches helped to correctly identify the most promising fragments for further chemical optimization. Importantly, all computations and predictions were done within 5 days, suggesting that MD simulations may become a viable tool in FBDD projects.

How good are state-of-the-art docking tools in predicting ligand binding modes in protein-protein interfaces?

Protein-protein interfaces (PPIs) are an important class of drug targets. We report on the first large-scale validation study on docking into PPIs. DrugScore-adapted AutoDock3 and Glide showed good success rates with a moderate drop-off compared to docking to "classical targets". An analysis of the binding energetics in a PPI allows identifying those interfaces that are amenable for docking. The results are important for deciding if structure-based design approaches can be applied to a particular PPI.

Interactions of gallic acid, resveratrol, quercetin and aspirin at the platelet cyclooxygenase-1 level. Functional and modelling studies.

While resveratrol and quercetin possess antiplatelet activity, little is known on the effect of gallic acid on platelets. We studied the interactions of these three different polyphenols among themselves and with aspirin, at the level of platelet cyclooxygenase-1 (COX-1). Both functional (in vitro and in vivo) and molecular modelling approaches were used. All three polyphenols showed comparable antioxidant activity (arachidonic acid [AA]-induced intraplatelet ROS production); however, resveratrol and quercetin, but not gallic acid, inhibited AA-induced platelet aggregation. Gallic acid, similarly to salicylic acid, the major aspirin metabolite, prevented inhibition of AA-induced platelet function by aspirin but, at variance with salicylic acid, also prevented inhibition by the other two polyphenols. Molecular modelling studies, performed by in silico docking the polyphenols into the crystal structure of COX-1, suggested that all compounds form stable complexes into the COX-1 channel, with slightly different but functionally relevant interaction geometries. Experiments in mice showed that gallic acid administered before aspirin, resveratrol or quercetin fully prevented their inhibitory effect on serum TxB(2). Finally, a mixture of resveratrol, quercetin and gallic acid, at relative concentrations similar to those contained in most red wines, did not inhibit platelet aggregation, but potentiated sub-inhibitory concentrations of aspirin. Gallic acid interactions with other polyphenols or aspirin at the level of platelet COX-1 might partly explain the complex, and possibly contrasting, effects of wine and other components of the Mediterranean diet on platelets and on the pharmacologic effect of low-dose aspirin.

Glucocorticoid receptor interactions with glucocorticoids: evaluation by molecular modeling and functional analysis of glucocorticoid receptor mutants.

In the treatment of inflammatory skin diseases, there are some glucocorticoid (GC) double esters combining pronounced antiinflammatory activity and minor atrophogenic side effects. The reason, however, is only poorly understood. To investigate interactions of GCs with the ligand-binding domain of the glucocorticoid receptor (GR), we measured receptor-binding potency of a series of GC esters including their metabolites and performed a molecular modeling study using progesterone receptor crystal structure data. Ligand docking to the GR-binding pocket showed good fitting of GC 17-esters corresponding to their high receptor-binding affinity, and unfavorable sterical interactions for GC 21-esters with substituents larger than propionate. Molecular dynamics simulations served to visualize induced fit procedures. Ligand docked GC conformations after dynamics simulations were used for generation of a 3D quantitative structure-activity relationship model. Using a set of 11 steroids, this model showed a correlation coefficient (r(2)) of 0.98, a leave-one-out cross validation (q(2)) of 0.79 and was able to predict binding affinity of further six ligands with a standard error of prediction of 0.33. Moreover, interactions of Asn-564 and Met-639 with the steroids were investigated by studying GR mutants of these amino acids. Met-639 participates in hydrophobic interactions mainly with GC side chains, while Asn-564 forms a hydrogen bond to the C11-OH group of the steroid. Asn-564 is shown to be very important for ligand binding and even more for target gene activation and transcription factor repression.