Pyrroline-5-carboxylate reductase (PYCR) is the final enzyme in proline biosynthesis, catalyzing the NAD(P)H-dependent reduction of Δ-pyrroline-5-carboxylate (P5C) to proline. Mutations in the gene alter mitochondrial function and cause the connective tissue disorder cutis laxa. Furthermore, PYCR1 is overexpressed in multiple cancers, and the knock-out suppresses tumorigenic growth, suggesting that PYCR1 is a potential cancer target. However, inhibitor development has been stymied by limited mechanistic details for the enzyme, particularly in light of a previous crystallographic study that placed the cofactor-binding site in the C-terminal domain rather than the anticipated Rossmann fold of the N-terminal domain. To fill this gap, we report crystallographic, sedimentation-velocity, and kinetics data for human PYCR1. Structures of binary complexes of PYCR1 with NADPH or proline determined at 1.9 Å resolution provide insight into cofactor and substrate recognition. We see NADPH bound to the Rossmann fold, over 25 Å from the previously proposed site. The 1.85 Å resolution structure of a ternary complex containing NADPH and a P5C/proline analog provides a model of the Michaelis complex formed during hydride transfer. Sedimentation velocity shows that PYCR1 forms a concentration-dependent decamer in solution, consistent with the pentamer-of-dimers assembly seen crystallographically. Kinetic and mutational analysis confirmed several features seen in the crystal structure, including the importance of a hydrogen bond between Thr-238 and the substrate as well as limited cofactor discrimination.

Pyrroline-5-carboxylate reductase 1 (PYCR1) catalyzes the biosynthetic half-reaction of the proline cycle by reducing Δ1-pyrroline-5-carboxylate (P5C) to proline through the oxidation of NAD(P)H. Many cancers alter their proline metabolism by upregulating the proline cycle and proline biosynthesis, and knockdowns of PYCR1 lead to decreased cell proliferation. Thus, evidence is growing for PYCR1 as a potential cancer therapy target. Inhibitors of cancer targets are useful as chemical probes for studying cancer mechanisms and starting compounds for drug discovery; however, there is a notable lack of validated inhibitors for PYCR1. To fill this gap, we performed a small-scale focused screen of proline analogs using X-ray crystallography. Five inhibitors of human PYCR1 were discovered: L-tetrahydro-2-furoic acid, cyclopentanecarboxylate, L-thiazolidine-4-carboxylate, L-thiazolidine-2-carboxylate, and N-formyl L-proline (NFLP). The most potent inhibitor was NFLP, which had a competitive (with P5C) inhibition constant of 100 mM. The structure of PYCR1 complexed with NFLP shows that inhibitor binding is accompanied by conformational changes in the active site, including the translation of an a-helix by 1 Å. These changes are unique to NFLP and enable additional hydrogen bonds with the enzyme. NFLP was also shown to phenocopy the PYCR1knockdown in MCF10A H-RASV12 breast cancer cells by inhibiting de novo proline biosynthesis and impairing spheroidal growth. In summary, we generated the first validated chemical probe of PYCR1 and demonstrated proof-of-concept for screening proline analogs to discover inhibitors of the proline cycle.

Protein biochemistry protocols typically include disulfide bond reducing agents to guard against unwanted thiol oxidation and protein aggregation. Commonly used disulfide bond reducing agents include dithiothreitol, β-mercaptoethanol, glutathione, and the tris(alkyl)phosphine compounds tris(2-carboxyethyl)phosphine (TCEP) and tris(3-hydroxypropyl)phosphine (THPP). While studying the catalytic activity of the NAD(P)H-dependent enzyme Δ 1 -pyrroline-5-carboxylate reductase, we unexpectedly observed a rapid non-enzymatic chemical reaction between NAD + and the reducing agents TCEP and THPP. The product of the reaction exhibits a maximum ultraviolet absorbance peak at 334 nm and forms with an apparent association rate constant of 231−491 M −1 s −1 . The reaction is reversible, and nuclear magnetic resonance characterization ( 1 H, 13 C, and 31 P) of the product revealed a covalent adduct between the phosphorus of the tris(alkyl)phosphine reducing agent and the C4 atom of the nicotinamide ring of NAD + . We also report a 1.45 Å resolution crystal structure of short-chain dehydrogenase/reductase with the NADP + −TCEP reaction product bound in the cofactor binding site, which shows that the adduct can potentially inhibit enzymes. These findings serve to caution researchers when using TCEP or THPP in experimental protocols with NAD(P) + . Because NAD(P) + -dependent oxidoreductases are widespread in nature, our results may be broadly relevant.

Metabolism within the tumor microenvironment, where a complex mixture of different cell types resides in a nutrient-deprived surrounding, is not fully understood due to difficulties in measuring metabolic fluxes and exchange of metabolites between different cell types in vivo. Genome-scale metabolic modeling enables estimation of such exchange fluxes as well as an opportunity to gain insight into the metabolic behavior of individual cell types. Here, we estimated the availability of nutrients and oxygen within the tumor microenvironment using concentration measurements from blood together with a metabolite diffusion model. In addition, we developed an approach to efficiently apply enzyme usage constraints in a comprehensive metabolic model of human cells. The combined modeling reproduced severe hypoxic conditions and the Warburg effect, and we found that limitations in enzymatic capacity contribute to cancer cells' preferential use of glutamine as a substrate to the citric acid cycle. Furthermore, we investigated the common belief that some stromal cells are exploited by cancer cells to produce metabolites useful for the cancer cells. We identified a total of 233 potential metabolites that could support collaboration between cancer cells and cancer associated fibroblasts, but when limiting to metabolites previously identified to participate in such collaboration, no growth advantage was observed. Our work highlights the importance of enzymatic capacity limitations for cell behaviors and exemplifies the utility of enzyme constrained models for accurate prediction of metabolism in cells and tumor microenvironments.

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