Nedyalka Radeva

Structure‐Based Design of Inhibitors of the Aspartic Protease Endothiapepsin by Exploiting Dynamic Combinatorial Chemistry

Structure-based design (SBD) can be used for the design and/or optimization of new inhibitors for a biological target. Whereas de novo SBD is rarely used, most reports on SBD are dealing with the optimization of an initial hit. Dynamic combinatorial chemistry (DCC) has emerged as a powerful strategy to identify bioactive ligands given that it enables the target to direct the synthesis of its strongest binder. We have designed a library of potential inhibitors (acylhydrazones) generated from five aldehydes and five hydrazides and used DCC to identify the best binder(s). After addition of the aspartic protease endothiapepsin, we characterized the protein-bound library member(s) by saturation-transfer difference NMR spectroscopy. Cocrystallization experiments validated the predicted binding mode of the two most potent inhibitors, thus demonstrating that the combination of de novo SBD and DCC constitutes an efficient starting point for hit identification and optimization.

Six Biophysical Screening Methods Miss a Large Proportion of Crystallographically Discovered Fragment Hits: A Case Study

Fragment-based lead discovery (FBLD) has become a pillar in drug development. Typical applications of this method comprise at least two biophysical screens as prefilter and a follow-up crystallographic experiment on a subset of fragments. Clearly, structural information is pivotal in FBLD, but a key question is whether such a screening cascade strategy will retrieve the majority of fragment-bound structures. We therefore set out to screen 361 fragments for binding to endothiapepsin, a representative of the challenging group of aspartic proteases, employing six screening techniques and crystallography in parallel. Crystallography resulted in the very high number of 71 structures. Yet alarmingly, 44% of these hits were not detected by any biophysical screening approach. Moreover, any screening cascade, building on the results from two or more screening methods, would have failed to predict at least 73% of these hits. We thus conclude that, at least in the present case, the frequently applied biophysical prescreening filters deteriorate the number of possible X-ray hits while only the immediate use of crystallography enables exhaustive retrieval of a maximum of fragment structures, which represent a rich source guiding hit-to-lead-to-drug evolution.

One Question, Multiple Answers: Biochemical and Biophysical Screening Methods Retrieve Deviating Fragment Hit Lists.

Fragment‐based lead discovery is gaining momentum in drug development. Typically, a hierarchical cascade of several screening techniques is consulted to identify fragment hits which are then analyzed by crystallography. Because crystal structures with bound fragments are essential for the subsequent hit‐to‐lead‐to‐drug optimization, the screening process should distinguish reliably between binders and non‐binders. We therefore investigated whether different screening methods would reveal similar collections of putative binders. First we used a biochemical assay to identify fragments that bind to endothiapepsin, a surrogate for disease‐relevant aspartic proteases. In a comprehensive screening approach, we then evaluated our 361‐entry library by using a reporter‐displacement assay, saturation‐transfer difference NMR, native mass spectrometry, thermophoresis, and a thermal shift assay. While the combined results of these screening methods retrieve 10 of the 11 crystal structures originally predicted by the biochemical assay, the mutual overlap of individual hit lists is surprisingly low, highlighting that each technique operates on different biophysical principles and conditions.

Fragment Linking and Optimization of Inhibitors of the Aspartic Protease Endothiapepsin : Fragment-Based Drug Design Facilitated by Dynamic Combinatorial Chemistry

Abstract Fragment‐based drug design (FBDD) affords active compounds for biological targets. While there are numerous reports on FBDD by fragment growing/optimization, fragment linking has rarely been reported. Dynamic combinatorial chemistry (DCC) has become a powerful hit‐identification strategy for biological targets. We report the synergistic combination of fragment linking and DCC to identify inhibitors of the aspartic protease endothiapepsin. Based on X‐ray crystal structures of endothiapepsin in complex with fragments, we designed a library of bis‐acylhydrazones and used DCC to identify potent inhibitors. The most potent inhibitor exhibits an IC50 value of 54 nm, which represents a 240‐fold improvement in potency compared to the parent hits. Subsequent X‐ray crystallography validated the predicted binding mode, thus demonstrating the efficiency of the combination of fragment linking and DCC as a hit‐identification strategy. This approach could be applied to a range of biological targets, and holds the potential to facilitate hit‐to‐lead optimization.

Experimental Active-Site Mapping by Fragments - Hot Spots Remote from the Catalytic Center of Endothiapepsin

Successful optimization of a given lead scaffold requires thorough binding-site mapping of the target protein particular in regions remote from the catalytic center where high conservation across protein families is given. We screened a 361-entry fragment library for binding to the aspartic protease endothiapepsin by crystallography. This enzyme is frequently used as a surrogate for the design of renin and β-secretase inhibitors. A hit rate of 20% was achieved, providing 71 crystal structures. Here, we discuss 45 binding poses of fragments accommodated in pockets remote from the catalytic dyad. Three major hot spots are discovered in remote binding areas: Asp81, Asp119, and Phe291. Compared to the dyad binders, bulkier fragments occupy these regions. Many of the discovered fragments suggest an optimization concept on how to grow them into larger ligands occupying adjacent binding pockets that will possibly endow them with the desired selectivity for one given member of a protein family.

Structure-Based Optimization of Inhibitors of the Aspartic Protease Endothiapepsin.

Aspartic proteases are a class of enzymes that play a causative role in numerous diseases such as malaria (plasmepsins), Alzheimer’s disease (β-secretase), fungal infections (secreted aspartic proteases), and hypertension (renin). We have chosen endothiapepsin as a model enzyme of this class of enzymes, for the design, preparation and biochemical evaluation of a new series of inhibitors of endothiapepsin. Here, we have optimized a hit, identified by de novo structure-based drug design (SBDD) and DCC, by using structure-based design approaches focusing on the optimization of an amide–π interaction. Biochemical results are in agreement with SBDD. These results will provide useful insights for future structure-based optimization of inhibitors for the real drug targets as well as insights into molecular recognition.

A False-Positive Screening Hit in Fragment-Based Lead Discovery: Watch out for the Red Herring

With the rising popularity of fragment-based approaches in drug development, more and more attention has to be devoted to the detection of false-positive screening results. In particular, the small size and low affinity of fragments drives screening techniques to their limit. The pursuit of a false-positive hit can cause significant loss of time and resources. Here, we present an instructive and intriguing investigation into the origin of misleading assay results for a fragment that emerged as the most potent binder for the aspartic protease endothiapepsin (EP) across multiple screening assays. This molecule shows its biological effect mainly after conversion into another entity through a reaction cascade that involves major rearrangements of its heterocyclic scaffold. The formed ligand binds EP through an induced-fit mechanism involving remarkable electrostatic interactions. Structural information in the initial screening proved to be crucial for the identification of this false-positive hit.