Yang K, Zhu L, Liu C, Zhou D, Zhu Z, Xu N, et al. Current status and prospect of the DNA double-strand break repair pathway in colorectal cancer development and treatment. BBA-Mol Basis Dis. 2024;1870:167438 https://doi.org/10.1016/j.bbadis.2024.167438

Article  CAS  Google Scholar 

Pierce AJ, Stark JM, Araujo FD, Moynahan ME, Berwick M, Jasin M. Double-strand breaks and tumorigenesis. Trends Cell Biol. 2001;11:S52–S59. https://doi.org/10.1016/S0962-8924(01)02149-3

Article  CAS  PubMed  Google Scholar 

Chen XS, Pomerantz RT. DNA polymerase θ: a cancer drug target with reverse transcriptase activity. Genes. 2021;12:1146 https://doi.org/10.3390/genes12081146

Article  CAS  PubMed  PubMed Central  Google Scholar 

Barszczewska-Pietraszek G, Drzewiecka M, Czarny P, Skorski T, Śliwiński T. Polθ inhibition: an anticancer therapy for HR-deficient tumours. Int J Mol Sci. 2023;24:319 https://doi.org/10.3390/ijms24010319

Article  CAS  Google Scholar 

Schrempf A, Slyskova J, Loizou JI. Targeting the DNA repair enzyme polymerase θ in cancer therapy. Trends Cancer. 2021;7:98–111. https://doi.org/10.1016/j.trecan.2020.09.007

Article  CAS  PubMed  Google Scholar 

Drzewiecka M, Barszczewska-Pietraszek G, Czarny P, Skorski T, Śliwiński T. Synthetic lethality targeting Polθ. Genes. 2022;13:1101 https://doi.org/10.3390/genes13061101

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zatreanu D, Robinson HMR, Alkhatib O, Boursier M, Finch H, Geo L, et al. Polθ inhibitors elicit BRCA-gene synthetic lethality and target PARP inhibitor resistance. Nat Commun. 2021;12:3636 https://doi.org/10.1038/s41467-021-23463-8

Article  CAS  PubMed  PubMed Central  Google Scholar 

Pismataro MC, Astolfi A, Barreca ML, Pacetti M, Schenone S, Bandiera T, et al. Small molecules targeting DNA polymerase theta (POLθ) as promising synthetic lethal agents for precision cancer therapy. J Med Chem. 2023;66:6498–522. https://doi.org/10.1021/acs.jmedchem.2c02101

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stockley ML, Ferdinand A, Benedetti G, Blencowe P, Boyd SM, Calder M, et al. Discovery, characterization, and structure-based optimization of small-molecule in vitro and in vivo probes for human DNA polymerase theta. J Med Chem. 2022;65:13879–91. https://doi.org/10.1021/acs.jmedchem.2c01142

Article  CAS  PubMed  Google Scholar 

Bubenik M, Mader P, Mochirian P, Vallée F, Clark J, Truchon JF, et al. Identification of RP-6685, an orally bioavailable compound that inhibits the DNa polymerase activity of Polθ. J Med Chem. 2022;65:13198–215. https://doi.org/10.1021/acs.jmedchem.2c00998

Article  CAS  PubMed  PubMed Central  Google Scholar 

A Study of ART4215 for the Treatment of Advanced or Metastatic Solid Tumors. Accessed 15 Jan 2025. https://clinicaltrials.gov/study/NCT04991480

Barsanti PA, Beck HP, Fleury M, Knox JE, Mcspadden ED, Jones BT, et al. Thiadiazolyl derivatives as DNA polymerase theta inhibitors. WO 2020 243459 A1, 2020

Ito F, Li Z, Minakhin L, Chandramouly G, Tyagi M, Betsch R, et al. Structural basis for a Polθ helicase small-molecule inhibitor revealed by cryo-EM. Nat Commun. 2024;15:7003 https://doi.org/10.1038/s41467-024-51351-4

Article  CAS  PubMed  PubMed Central  Google Scholar 

Schneider P, Walters WP, Plowright AT, Sieroka N, Listgarten J, Goodnow RA, et al. Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discov. 2020;19:353–64. https://doi.org/10.1038/s41573-019-0050-3

Article  CAS  PubMed  Google Scholar 

Vijayan RSK, Kihlberg J, Cross JB, Poongavanam V. Enhancing preclinical drug discovery with artificial intelligence. Drug Discov Today. 2022;27:967–84. https://doi.org/10.1016/j.drudis.2021.11.023

Article  CAS  PubMed  Google Scholar 

Pillai N, Dasgupta A, Sudsakorn S, Fretland J, Mavroudis PD. Machine learning guided early drug discovery of small molecules. Drug Discov Today. 2022;27:2209–15. https://doi.org/10.1016/j.drudis.2022.03.017

Article  CAS  PubMed  Google Scholar 

Qin Z, Liu L, Gao M, Feng W, Huang C, Liu W Molecular generation, QSAR, and molecular dynamic simulation studies for virtual screening of DNA polymerase theta inhibitors. Curr Comput-Aid Drug. 2024. https://doi.org/10.2174/0115734099305142240508051830

Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, et al. QSAR modeling: where have you been? Where are you going to? J Med Chem. 2014;57:4977–5010. https://doi.org/10.1021/jm4004285

Article  CAS  PubMed  PubMed Central  Google Scholar 

Brown N, Ertl P, Lewis R, Luksch T, Reker D, Schneider N. Artificial intelligence in chemistry and drug design. J Comput Aided Mol Des. 2020;34:709–15. https://doi.org/10.1021/jm4004285

Article  CAS  PubMed  Google Scholar 

Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, et al. Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening. J Chem Inf Model. 2013;53:475–92. https://doi.org/10.1021/ci300421n

Article  CAS  PubMed  PubMed Central  Google Scholar 

Huo D, Sun Z, Wang M, Yan A. Ligand and structure based hierarchical virtual screening cascade for finding novel epidermal growth factor receptor inhibitors. Chem Biol Drug Des. 2024;103:e14375 https://doi.org/10.1111/cbdd.14375

Article  CAS  PubMed  Google Scholar 

Kong Y, Bender A, Yan A. Identification of novel aurora kinase A (AURKA) inhibitors via hierarchical ligand-based virtual screening. J Chem Inf Model. 2018;58:36–47. https://doi.org/10.1021/acs.jcim.7b00300

Article  CAS  PubMed  Google Scholar 

Huo D, Wang S, Kong Y, Qin Z, Yan A. Discovery of novel Epidermal Growth Factor Receptor (EGFR) inhibitors using computational approaches. J Chem Inf Model. 2022;62:5149–64. https://doi.org/10.1021/acs.jcim.1c00884

Article  CAS  PubMed  Google Scholar 

Amabilino S, Pogány P, Pickett SD, Green DVS. Guidelines for recurrent neural network transfer learning-based molecular generation of focused libraries. J Chem Inf Model. 2020;60:5699–713. https://doi.org/10.1021/acs.jcim.0c00343

Article  CAS  PubMed  Google Scholar 

Hawkins PCD, Skillman AG, Nicholls A. Comparison of shape-matching and docking as virtual screening tools. J Med Chem. 2007;50:74–82. https://doi.org/10.1021/jm0603365

Article  CAS  PubMed  Google Scholar 

Li N, Wang J, Wu H, Zheng Z, Liu W, Qin Z. Design and discovery of monopolar spindle kinase 1 (MPS1/TTK) inhibitors by computational approaches. Med Chem Res. 2024;33:1861–86. https://doi.org/10.1007/s00044-024-03286-0

Article  CAS  Google Scholar 

Barsanti PA, Beck HP, Fluery M, Jones BT, Mcspadden ED, Pei Z, et al. Substituted thiadiazolyl derivatives as DNA polymerase theta inhibitors. WO 2022 118210 A1, 2022

Barsanti PA, Jaipuri FA, Severance DL, Wang C, Duffy KJ, Lawhorn BG, et al. O-linked thiadiazolyl compounds as DNA polymerase theta inhibitors. WO 2022 259204 A1, 2022

Rogers D, Hahn M. Extended-connectivity fingerprints. J Chem Inf Model. 2010;50:742–54. https://doi.org/10.1021/ci100050t

Article  CAS  PubMed  Google Scholar 

Breiman L. Random forests. Mach Learn. 2001;45:5–32. https://doi.org/10.1023/A:1010933404324

Article  Google Scholar 

Roos K, Wu C, Damm W, Reboul M, Stevenson JM, Lu C, et al. OPLS3e: extending force field coverage for drug-like small molecules. J Chem Theory Comput. 2019;15:1863–74. https://doi.org/10.1021/acs.jctc.8b01026

Article  CAS  PubMed  Google Scholar 

MacroModel, a versatile, full-featured molecular modeling program. Schrödinger Release 2020-3: MacroModel, Schrödinger, LLC, New York, NY, 2020. https://www.schrodinger.com/platform/products/macromodel/

LigPrep, a versatile ligand preparation tool for structure-based workflows. Schrödinger Release 2020-3: LigPrep, Schrödinger, LLC, New York, NY, 2020. https://www.schrodinger.com/platform/products/ligprep/