High-throughput screen for inhibitors of protein-protein interactions in a reconstituted heat shock protein 70 (Hsp70) complex.

Protein-protein interactions (PPIs) are an important category of putative drug targets. Improvements in high-throughput screening (HTS) have significantly accelerated the discovery of inhibitors for some categories of PPIs. However, methods suitable for screening multiprotein complexes (e.g. those composed of three or more different components) have been slower to emerge. Here, we explored an approach that uses reconstituted multiprotein complexes (RMPCs). As a model system, we chose heat shock protein 70 (Hsp70), which is an ATP-dependent molecular chaperone that interacts with co-chaperones, including DnaJA2 and BAG2. The PPIs between Hsp70 and its co-chaperones stimulate nucleotide cycling. Thus, to re-create this ternary protein system, we combined purified human Hsp70 with DnaJA2 and BAG2 and then screened 100,000 diverse compounds for those that inhibited co-chaperone-stimulated ATPase activity. This HTS campaign yielded two compounds with promising inhibitory activity. Interestingly, one inhibited the PPI between Hsp70 and DnaJA2, whereas the other seemed to inhibit the Hsp70-BAG2 complex. Using secondary assays, we found that both compounds inhibited the PPIs through binding to allosteric sites on Hsp70, but neither affected Hsp70's intrinsic ATPase activity. Our RMPC approach expands the toolbox of biochemical HTS methods available for studying difficult-to-target PPIs in multiprotein complexes. The results may also provide a starting point for new chemical probes of the Hsp70 system.

A Fragment-Based Ligand Screen Against Part of a Large Protein Machine: The ND1 Domains of the AAA+ ATPase p97/VCP.

The ubiquitous AAA+ ATPase p97 functions as a dynamic molecular machine driving several cellular processes. It is essential in regulating protein homeostasis, and it represents a potential drug target for cancer, particularly when there is a greater reliance on the endoplasmic reticulum-associated protein degradation pathway and ubiquitin-proteasome pathway to degrade an overabundance of secreted proteins. Here, we report a case study for using fragment-based ligand design approaches against this large and dynamic hexamer, which has multiple potential binding sites for small molecules. A screen of a fragment library was conducted by surface plasmon resonance (SPR) and followed up by nuclear magnetic resonance (NMR), two complementary biophysical techniques. Virtual screening was also carried out to examine possible binding sites for the experimental hits and evaluate the potential utility of fragment docking for this target. Out of this effort, 13 fragments were discovered that showed reversible binding with affinities between 140 µM and 1 mM, binding stoichiometries of 1:1 or 2:1, and good ligand efficiencies. Structural data for fragment-protein interactions were obtained with residue-specific [U-(2)H] (13)CH3-methyl-labeling NMR strategies, and these data were compared to poses from docking. The combination of virtual screening, SPR, and NMR enabled us to find and validate a number of interesting fragment hits and allowed us to gain an understanding of the structural nature of fragment binding.

A high throughput screen identifies potent and selective inhibitors to human epithelial 15-lipoxygenase-2.

Lipoxygenase (LOX) enzymes catalyze the hydroperoxidation of arachidonic acid and other polyunsaturated fatty acids to hydroxyeicosatetraenoic acids with varying positional specificity to yield important biological signaling molecules. Human epithelial 15-lipoxygenase-2 (15-LOX-2) is a highly specific LOX isozyme that is expressed in epithelial tissue and whose activity has been correlated with suppression of tumor growth in prostate and other epithelial derived cancers. Despite the potential utility of an inhibitor to probe the specific role of 15-LOX-2 in tumor progression, no such potent/specific 15-LOX-2 inhibitors have been reported to date. This study employs high throughput screening to identify two novel, specific 15-LOX-2 inhibitors. MLS000545091 is a mixed-type inhibitor of 15-LOX-2 with a Ki of 0.9+/-0.4 µM and has a 20-fold selectivity over 5-LOX, 12-LOX, 15-LOX-1, COX-1, and COX-2. MLS000536924 is a competitive inhibitor with a Ki of 2.5+/-0.5 µM and also possesses 20-fold selectivity toward 15-LOX-2 over the other oxygenases, listed above. Finally, neither compound possesses reductive activity towards the active-site ferrous ion.

Divergent evolution in enolase superfamily: strategies for assigning functions.

Nature's strategies for evolving catalytic functions can be deciphered from the information contained in the rapidly expanding protein sequence databases. However, the functions of many proteins in the protein sequence and structure databases are either uncertain (too divergent to assign function based on homology) or unknown (no homologs), thereby limiting the utility of the databases. The mechanistically diverse enolase superfamily is a paradigm for understanding the structural bases for evolution of enzymatic function. We describe strategies for assigning functions to members of the enolase superfamily that should be applicable to other superfamilies.

Binding-site assessment by virtual fragment screening.

The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock approximately 11,000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.

Physics-based scoring of protein-ligand complexes: enrichment of known inhibitors in large-scale virtual screening.

We demonstrate that using an all-atom molecular mechanics force field combined with an implicit solvent model for scoring protein-ligand complexes is a promising approach for improving inhibitor enrichment in the virtual screening of large compound databases. The rescoring method is evaluated by the extent to which known binders for nine diverse, therapeutically relevant enzymes are enriched against a background of approximately 100,000 drug-like decoys. The improvement in enrichment is most robust and dramatic within the top 1% of the ranked database, that is, the first thousand compounds; below the first few percent of the ranked database, there is little overall improvement. The improved early enrichment is likely due to the more realistic treatment of ligand and receptor desolvation in the rescoring procedure. We also present anecdotal but encouraging results assessing the ability of the rescoring method to predict specificity of inhibitors for structurally related proteins.