Rational Design of Selective Allosteric Inhibitors of PHGDH and Serine Synthesis with Anti-tumor Activity

Abstract

Metabolic reprogramming in cancer cells facilitates growth and proliferation. Increased activity of the serine biosynthetic pathway through the enzyme phosphoglycerate dehydrogenase (PHGDH) contributes to tumorigenesis. With a small substrate and a weak binding cofactor, (NAD⁺), inhibitor development for PHGDH remains challenging. Instead of targeting the PHGDH active site, we computationally identified two potential allosteric sites and virtually screened compounds that can bind to these sites. With subsequent characterization, we successfully identified PHGDH non-NAD⁺-competing allosteric inhibitors that attenuate its enzyme activity, selectively inhibit de novo serine synthesis in cancer cells, and reduce tumor growth in vivo. Our study not only identifies novel allosteric inhibitors for PHGDH to probe its function and potential as a therapeutic target, but also provides a general strategy for the rational design of small-molecule modulators of metabolic enzyme function.

Keywords: PHGDH; allosteric inhibitor; anti-tumor; cancer cell metabolism; de novo serine synthesis; in vivo; rational design; virtual screen.

Figure 1. Identification of Novel Allosteric Inhibitors of PHGDH

(A) Potential allosteric sites in PHGDH (PDB code: 2G76). The sites were predicted by the program of CAVITY and illustrated by the surface mode.The cofactor NAD⁺ was indicated in sticks. PHGDH forms a dimer in the crystal structure, site I and II exist in each monomer, and only one site I and one site II is shown in the figure for clarity. (B) Chemical structures of PHGDH inhibitors. (C) Enzyme inhibition dose-response curve of PKUMDL-WQ-2101. (D) SPR dose-response curve of PKUMDL-WQ-2101. (E) Cofactor competiton curve of PKUMDL-WQ-2101. The percentage inhibition did not obviously change along with the increase of NADH concentration, indicating that there are no significant interactions between PKUMDL-WQ-2101 and the cofactor binding site. (F-G) Predicted binding mode of PKUMDL-WQ-2101. The compound and key residues in sites I are shown in stick representation. Site I is shown in suface mode (F). Enzymatic activities and responses to PKUMDL-WQ-2101 of PHGDH mutants (G). (H-I) Predicted binding mode of PKUMDL-WQ-2201. The compound and key residues in sites II are shown in stick representation. Site II is shown in surface mode (H). Enzymatic activities and responses to PKUMDL-WQ-2201 of PHGDH mutants (I). (J) Inhibitors in different sites synergize to induce PHGDH inhibition. The concentration of PKUMDL-WQ-2101 and PKUMDL-WQ-2202 was kept at 25 μM for enzyme inhibition assay, while PKUMDL-WQ-2201 concentration varies. CI values <1 indicates synergistic interaction. Data shown represent the mean ± SD (n = 3). See Figure S1 for dose-response curves of PKUMDL-WQ-2201 to 2203 and Figure S2 for synergytic matrix.

Figure 2. Bioactivities of PKUMDL-WQ-2101 and PKUMDL-WQ-2201 in cell based assays

(A-B) Growth inhibition activity of PKUMDL-WQ-2101 (A) and PKUMDL-WQ-2201 (B) in MDA-MB-468, HCC70, MCF-7, MDA-MB-231, ZR-75-1 and MCF-10A cells, respectively. Cells were exposed to vehcile or various concentrations of PKUMDL-WQ-2101 for 72h followed by MTT assay. The EC₅₀ value of PKUMDL-WQ-2201 for MCF-7 and MDA-MB-231 was larger than 200 μM, so the corresponding dose-response curve was not presented here. (C-D) Percentage of MDA-MB-468 cells in different phases of the cell cycle after respectively treatment with 2.5, 5.0, 20 and 40 μM PKUMDL-WQ-2101 (C), and 10, 80 and 160 μM PKUMDL-WQ-2201 (D) for 24 hours. DMSO was used as vehcile. Data represent the mean ± SD independent experiments. Difference is significant by two-tailed multiple t-test, *p < 0.05, **p < 0.01, ***p < 0.001. See Figure S3 for cell bioactivities of PKUMDL-WQ-2202 and 2203.

Figure 3. CRISPR-Cas9 mediated PHGDH KO and PHGDH inhibition by PKUMDL-WQ-2101 and PKUMDL-WQ-2201

(A)Overview of LentiCRISPR system and sgRNA design generated for targeted PHGDH deletion in SKOV3 ovarian cancer cells. (B) Western blot analysis for SKOV3 GFP KO control and SKOV3 PHGDH KO cells with actin as a loading control. (C) Growth curve comparing SKOV3 GFP KO control and PHGDH KO over 6 days. (D) Growth curves of SKOV3 GFP KO control and (E) PHGDH KO cells after 6 days of treatment with vehicle or 10μM PKUMDL-WQ-2101 followed by cell counting. (F) Growth curves of SKOV3 GFP KO control or (G) PHGDH KO cells after 6 days of treatment with vehicle or 50μM PKUMDL-WQ-2201 followed by cell counting. All values represent the mean ± SEM from n=3 biological replicates. P values were obtained from a two-tailed student's t-test, *P< 0.05, **p<0.01, ***P<0.001. See Figure S4 for PKUMDL-WQ-2101 and 2201 bioactivies on SKOV3 GFP KO cells and results of PKUMDL-WQ-2101 pull down assays.

Figure 4. PKUMDL-WQ-2101 and PKUMDL-WQ-2201 inhibit the serine biosynthesis pathway in cells

(A) Schematic of U-¹³C-glucose stable isotope labeling used to detect carbon labeling from glucose (red) in metabolites part of the serine metabolic network. (B) 13C-serine and 13C-glycine labeling from glucose in SKOV3 GFP KO control cells compared to SKOV3 PHGDH KO cells after 24 hours. (C)13C-serine and (D) ¹³C-glycine labeling from glucose in SKOV3 GFP KO cells after 24 hour treatment with 37 μM PKUMDL-WQ-2101 and 291 μM PKUMDL-WQ-2201, followed by subsequent U-¹³C-glucose labeling. (E) Mass isotopomer distribution (MID) of UTP and (F) ATP after 24 hour treatment with 37 μM PKUMDL-WQ-2101 and 291 μM PKUMDL-WQ-2201, followed by subsequent U-¹³C-glucose labeling. (G) Glutathione after 24 hour treatment with 37 μM PKUMDL-WQ-2101 and 291 μM PKUMDL-WQ-2201, followed by subsequent U-13C-glucose labeling. All values represent the mean ± SEM from n=3 biological replicates. Difference is significant by One-Way ANOVA, *P< 0.05, **p<0.01, ***P<0.001.

Figure 5. Bioactivities of PKUMDL-WQ-2101 and PKUMDL-WQ-2201 in vivo.

(A-F) After 30 days of drug delivery, treatment with PKUMDL-WQ-2101 (A-C) or PKUMDL-WQ-2201 (D-F) significantly suppressed the growth of tumors compared with control-treated group. Data represent the mean ± SEM independent experiments. Difference is significant by two-tailed multiple t-test, *p < 0.05. See Figure S5 for PKUMDL-WQ-2101 and 2201 biactivities on MDA-MB-231 xenografts and mice growth curves.