New Frontiers in Druggability

Abstract

A powerful early approach to evaluating the druggability of proteins involved determining the hit rate in NMR-based screening of a library of small compounds. Here we show that a computational analog of this method, based on mapping proteins using small molecules as probes, can reliably reproduce druggability results from NMR-based screening, and can provide a more meaningful assessment in cases where the two approaches disagree. We apply the method to a large set of proteins. The results show that, because the method is based on the biophysics of binding rather than on empirical parameterization, meaningful information can be gained about classes of proteins and classes of compounds beyond those resembling validated targets and conventionally druglike ligands. In particular, the method identifies targets that, while not druggable by druglike compounds, may become druggable using compound classes such as macrocycles or other large molecules beyond the rule-of-five limit.

Lessons from Hot Spot Analysis for Fragment-Based Drug Discovery

“…[23, 25, 36–38]. In particular, we have previously established that, when using 16 probes types for the mapping, the sites that are known to be druggable invariably contain a strong hot spot containing 16 or more probe clusters [24, 39]. Second, since the primary hot spot is the location with the highest binding potency for small molecules, we expect that fragment hits are most likely to bind at this site.…”

“…Targets that lack a primary hot spot of sufficient strength are not suitable for FBDD, and have poor overall prospects for inhibitor development by any means [21, 27]. The FTMap analysis used to derive these results was based on mapping the ligand-free proteins, allowing druggability to be assessed for any target that has been crystallized even before investing time or resources into lead discovery [39]. Whether a bound fragment will have a robust binding mode also depends largely on CC1.…”

“…As already mentioned, hot spots are generally less sensitive to conformational changes than binding sites are, and hence the druggability of most targets can be assessed by mapping ligand-free structures [39]. However, ligand binding may affect the location and relative strength of hot spots [34, 39, 54], and hence it is advisable to also map ligand-bound structures when they become available in the process of drug discovery.…”

“…However, ligand binding may affect the location and relative strength of hot spots [34, 39, 54], and hence it is advisable to also map ligand-bound structures when they become available in the process of drug discovery. For example, the ligand-free structure of Bcl-xL has three strong hot spots close to each other in the pocket that binds L578 of the BAK peptide [47], and it was shown that fragments of known inhibitors all bind at this single site.…”

Identification of Agents Targeting Ftsz Assembly

“…For example, Foss et al have demonstrated that small molecules which disrupt bacterial membrane function (such as cinnamaldehye, totarol and sanguinarine) produce similar phenotypes to FtsZ inhibitors. [60] The druggability of regions of this protein is also a matter for debate; Kozakov et al have used the FTMap algorithm [61] to characterize the ligand-binding hot spots of the ZipA/FtsZ protein-protein interaction and concluded that this interface is not a druggable target [62].…”