Identification and Validation of New DNA-PKcs Inhibitors through High-Throughput Virtual Screening and Experimental Verification

Abstract

DNA-PKcs is a crucial protein target involved in DNA repair and response pathways, with its abnormal activity closely associated with the occurrence and progression of various cancers. In this study, we employed a deep learning-based screening and molecular dynamics (MD) simulation-based pipeline, identifying eight candidates for DNA-PKcs targets. Subsequent experiments revealed the effective inhibition of DNA-PKcs-mediated cell proliferation by three small molecules (5025-0002, M769-1095, and V008-1080). These molecules exhibited anticancer activity with IC₅₀ (inhibitory concentration at 50%) values of 152.6 μM, 30.71 μM, and 74.84 μM, respectively. Notably, V008-1080 enhanced homology-directed repair (HDR) mediated by CRISPR/Cas9 while inhibiting non-homologous end joining (NHEJ) efficiency. Further investigations into the structure-activity relationships unveiled the binding sites and critical interactions between these small molecules and DNA-PKcs. This is the first application of DeepBindGCN_RG in a real drug screening task, and the successful discovery of a novel DNA-PKcs inhibitor demonstrates its efficiency as a core component in the screening pipeline. Moreover, this study provides important insights for exploring novel anticancer therapeutics and advancing the development of gene editing techniques by targeting DNA-PKcs.

Keywords: CRISPR/Cas9; DNA-PKcs; HDR; anticancer activity; deep learning; virtual screening.

Figure 1

The virtual screening procedure integrates DeepBindGCN models with other methods to identify highly reliable drug candidates for DNA-PKcs. (a) The screening inhibitors against the Chemdiv dataset for DNA-PKcs using a combination of DeepBindGCN_BC/RG, Schrödinger docking, MD simulation, and experimental methods. (b) The last frame from the 40 ns pocket MD simulation of the three identified active compounds, showing both 3D and 2D interaction details.

Figure 2

The calculated free energy landscape from metadynamics simulation for those candidates with favorable binding with DNA-PKcs. (a) The calculated free energy landscape for DNA-PKcs with candidates 4290-0112, 5025-0002, 5795-0108, 7238-1541, and 8601-0106. (b) The calculated free energy landscape for DNA-PKcs with candidates C163-0038, C163-0039, C163-0087, C200-6885, and C684-0025. (c) The calculated free energy landscape for DNA-PKcs with candidates E208-0020, G744-0225, L102-0385, M769-1095 and S431-0991. (d) The calculated free energy landscape for DNA-PKcs with candidates SA50-0140, V001-2119, V008-1080 and V014-8131.

Figure 3

The RMSD value and number of hydrogen bonds of selected compounds with DNA-PKcs during the MD simulation. (a) The RMSD value over the 40 ns MD simulation for the eight selected protein–compound complexes. (b) The number of hydrogen bonds between DNA-PKcs and the eight selected compounds.

Figure 4

DNA-PKcs inhibitors induce proliferation inhibition in 786-O RCC cells. (a,b) 786-O RCC cells were treated with M3814, other small molecules (10 μM, 100 μM) or vehicle control (0.1% DMSO) for applied time; cell inhibition was analyzed by CCK8 assay. (c–o) the cell viability IC₅₀ values of different small molecules against 786-O cells. All p-values were obtained by comparing to the DMSO group at the same concentration. ns denotes not significant, * denotes p < 0.05, ** denotes p < 0.01, *** denotes p < 0.001, **** denotes p < 0.0001.

Figure 5

Evaluation of HDR-mediated gene targeting efficiency by treatment with different small molecules. (a) Schematics of the donor plasmid and targeting strategy for HDR-mediated knock-in of the ires-GFP reporter at GAPDH 3-UTR. (b,c) FACS analysis of HEK293T cells treated with different small molecules or vehicles showing HDR-mediated integration of ires-GFP in the presence of RNP mixture and ires-GFP donor. The cells were co-transfected with donor/RNP by nucleofection and analyzed two days post transfection.

Figure 6

Evaluation of NHEJ efficiency in HEK293T cells treated with different small molecules using modified TLR reporter. (a) Schematic depicting the outcome after the induction of a site-specific double-strand break (DSB). If the break undergoes NHEJ mediated repair, eGFP will be translated out of frame and iRFP will be expressed, producing far-red fluorescent cells. (b) HEK293T cells overexpressing the TLR reporter (BFP positive) were nucleofected with Cas9 and sgRNA plasmids, then treated with different small molecules or vehicle. NHEJ efficiency was evaluated by detecting iRFP expression 48 h post-treatment using a flow cytometer.

Figure 7

Interaction analysis of DNA-PKcs with newly discovered and known active compounds with docked conformation. (A) Compound 5025-0002 binding to the DNA-PKcs pocket, displaying both 3D detailed interactions above and 2D representation below. (B) Interaction between M769-1095 and DNA-PKcs pocket. (C) Interaction between V008-1080 and DNA-PKcs pocket. (D) Interaction between M3814 and DNA-PKcs pocket. (E) Interaction between NU7441 and DNA-PKcs pocket. Residues in all 3D visualizations are color-coded by B-Factor in PyMOL, with distances for crucial interactions (depicted with dotted lines) measured. The 2D diagrams employ colors and symbols as standardized by the Schrödinger 2D interaction plots.