Assigned from data sets measured in water at 2, 25, and 60 °C containing 13C=O NMR chemical shifts and [θ]222 ellipticities, helical propensities are reported for the twenty genetically coded amino acids, as well as for norvaline and norleucine. These have been introduced by chemical synthesis at central sites within length-optimized, spaced, solubilized Ala19 hosts. The resulting polyalanine-derived, quantitative propensity sets express for each residue its temperature-dependent but context-independent tendency to forgo a coil state and join a preexisting helical conformation. At 2 °C their rank ordering is: P ⪡ G < H < C, T, N < S < Y, F, W < V, D < K < Q < I < R, M < L < E < A; at 60 °C the rank becomes: H, P < G < C < R, K < T, Y, F < N, V < S < Q < W, D < I, M < E < A < L. The ΔΔ G values, kcal/mol, relative to alanine, for the cluster T, N, S, Y, F, W, V, D, Q, imply that at 2 °C all are strong breakers: ΔΔ Gmean = +0.63 ± 0.11, but at 60 °C their breaking tendencies are dramatically attenuated and converge toward the mean: ΔΔ Gmean = +0.25 ± 0.07. Accurate modeling of helix-rich proteins found in thermophiles, mesophiles, and organisms that flourish near 0 °C thus requires appropriately matched propensity sets. Comparisons are offered between the temperature-dependent propensity assignments of this study and those previously assigned by the Scheraga group; the special problems that attend propensity assignments for charged residues are illustrated by lysine guest data; and comparisons of errors in helicity assignments from shifts and ellipticity data show that the former provide superior precision and accuracy.

The discovery and development of new antibiotics capable of curing infections due to multidrug-resistant and pandrug-resistant Gram-negative bacteria are a major challenge with fundamental importance to our global healthcare system. Part of our broad program at Novartis to address this urgent, unmet need includes the search for new agents that inhibit novel bacterial targets. Here we report the discovery and hit-to-lead optimization of new inhibitors of phosphopantetheine adenylyltransferase (PPAT) from Gram-negative bacteria. Utilizing a fragment-based screening approach, we discovered a number of unique scaffolds capable of interacting with the pantetheine site of E. coli PPAT and inhibiting enzymatic activity, including triazolopyrimidinone 6. Structure-based optimization resulted in the identification of two lead compounds as selective, small molecule inhibitors of bacterial PPAT: triazolopyrimidinone 53 and azabenzimidazole 54 efficiently inhibited E. coli and P. aeruginosa PPAT and displayed modest cellular potency against the efflux-deficient E. coli Δ tolC mutant strain.

In the preceding manuscript [ Moreau et al. 2018 , 10.1021/acs.jmedchem.7b01691 ] we described a successful fragment-based lead discovery (FBLD) strategy for discovery of bacterial phosphopantetheine adenylyltransferase inhibitors (PPAT, CoaD). Following several rounds of optimization two promising lead compounds were identified: triazolopyrimidinone 3 and 4-azabenzimidazole 4. Here we disclose our efforts to further optimize these two leads for on-target potency and Gram-negative cellular activity. Enabled by a robust X-ray crystallography system, our structure-based inhibitor design approach delivered compounds with biochemical potencies 4-5 orders of magnitude greater than their respective fragment starting points. Additional optimization was guided by observations on bacterial permeability and physicochemical properties, which ultimately led to the identification of PPAT inhibitors with cellular activity against wild-type E. coli.

Drug-resistant Gram-negative bacteria are of increasing concern worldwide. Novel antibiotics are needed, but their development is complicated by the requirement to simultaneously optimize molecules for target affinity and cellular potency, which can result in divergent structure-activity relationships (SARs). These challenges were exemplified during our attempts to optimize inhibitors of the bacterial enzyme CoaD originally identified through a biochemical screen. To facilitate lead optimization, we developed mass spectroscopy assays based on the hypothesis that levels of CoA metabolites would reflect the cellular enzymatic activity of CoaD. Using these methods, we were able to monitor the effects of cellular enzyme inhibition at compound concentrations up to 100-fold below the minimum inhibitory concentration (MIC), a common metric of growth inhibition. Furthermore, we generated a panel of efflux pump mutants to dissect the susceptibility of a representative CoaD inhibitor to efflux. These approaches allowed for a nuanced understanding of the permeability and efflux liabilities of the series and helped guide optimization efforts to achieve measurable MICs against wild-type E. coli.

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