Small molecules from antibody pharmacophores (SMAbPs) as a hit identification workflow for immune checkpoints

Abstract

Small-molecule modulators of immune checkpoints are poised to revolutionize cancer immunotherapy. However, efficient strategies for hit identification are lacking. We introduce small molecules from antibody pharmacophores (SMAbPs), a workflow leveraging cocrystal structures of checkpoints with antibodies to create pharmacophore maps for virtual screening. Applying SMAbPs to five immune checkpoints yielded hits with submicromolar potency in both cell-free and cellular assays. Notably, SMAbPs identified the most potent T cell immunoglobulin and mucin-domain containing-3 and V-domain immunoglobulin suppressor of T cell activation (VISTA) inhibitors reported to date and first-in-class modulators of B and T lymphocyte attenuator, 4-IBB, and CD27. Targeting inhibitory and costimulatory checkpoints with hits identified through SMAbPs demonstrated remarkable in vivo antitumor activity, exemplified by MG-V-53 (VISTA inhibitor) and MG-C-30 (CD27 agonist), which significantly reduced tumor volumes in MC38 and EG7-OVA mouse models, respectively.

Fig. 1.. Overview of the SMAbP workflow.

(A) Identify key interacting residues of mAb with target immune checkpoint from cocrystal structure, (B) pharmacophore-based virtual screening, and (C) hit validation. RFU, relative fluorescence intensity.

Fig. 2.. Discovery and evaluation of MG-T-19 as a TIM-3 inhibitor.

(A) Chemical structure of MG-T-19. (B) The overlay of the pharmacophore map derived from PDB ID: 6TXZ over amino acid residues of M6903 (top) and MG-T-19 (bottom). Green spheres represent hydrophobic interactions. Yellow arrows represent hydrogen bonding interactions. (C) Proliferation of Kasumi-1 cells as a single culture and coculture with PBMCs in the absence (control) and presence of M6903 (100 nM) and MG-T-19 (2.5 μM). Proliferation was analyzed by H3 thymidine uptake, and results were given as counts per minute (CPM). Error bars represent SD (n = 5). **P < 0.01 and ***P < 0.001.

Fig. 3.. Assessment of MG-V-53 as a small-molecule VISTA inhibitor.

(A) Chemical structure of MG-V-53. (B) Dose-response curve of MG-V-53 binding to VISTA using SPR. Error bars represent SD (n = 3). (C) Tumor volume in the MC38 mouse model of vehicle control, MG-V-53 (20 mg/kg, po), anti–PD-L1 mAb, and combination treatment groups of C57BL/6 mice. Error bars represent SEM (n = 8). **P < 0.01 and ***P < 0.001.

Fig. 4.. Biophysical and cellular evaluation of MG-B-28.

(A) Chemical structure of MG-B-28. (B) Dose-response curve of MG-B-28 binding to BTLA using MST. (C) Luminescence signal from the BTLA/NFAT luciferase reporter assay in the presence of anti-BTLA mAb (100 nM) and various concentrations of MG-B-28. Error bars represent SD (n = 5). **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Fig. 5.. Assessment of the therapeutic potential of small-molecule agonists of stimulatory checkpoints.

(A) Chemical structure of MG-C-30. (B) Activation of natural killer cells from PBMCs of healthy donors as revealed by the frequency of CD69⁺ cells in the presence of anti-hCD27 mAb (250 nM) and multiple concentrations of MG-C-30. Error bars represent SD (n = 5). (C) Tumor volume in the EG7-OVA mouse model of vehicle control, MG-C-30 (25 or 50 mg/kg, po), and anti-mCD27 mAbs groups of C57BL/6 mice. Error bars represent SEM (n = 8). ns denotes nonsignificant; *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 relative to control.