613
Views
0
CrossRef citations to date
0
Altmetric
Commentary

Computational analysis, Alignment and Extension of Analogue Series From Medicinal Chemistry

& ORCID Icon
Article: FSO804 | Received 09 Jun 2022, Accepted 10 Jun 2022, Published online: 28 Jun 2022

References

  • WessG , UrmannM , SickenbergerB. Medicinal chemistry: challenges and opportunities. Angew. Chem. Int. Ed.40(18), 3341–3350 (2001).
  • The Practice of Medicinal Chemistry (3rd Edition)WermuthCG ( Ed.). Academic Press-Elsevier, CA, USA (2008).
  • LillMA. Multi-dimensional QSAR in drug discovery. Drug Discov. Today12(23-24), 1013–1017 (2007).
  • CherkasovA , MuratovEN , FourchesDet al.QSAR modeling: where have you been? Where are you going to?J. Med. Chem.57(12), 4977–5010 (2014).
  • ToplissJG. A manual method for applying the Hansch approach to drug design. J. Med. Chem.20(4), 463–469 (1977).
  • LoY-C , RensiSE , TorngW , AltmanRB. Machine learning in chemoinformatics and drug discovery. Drug Discov. Today23(8), 1538–1546 (2018).
  • DavisAM , TeagueSJ , KleywegtGJ. Application and limitations of X-ray crystallographic data in structure-based ligand and drug design. Angew. Chem. Int. Ed.42(24), 2718–2736 (2003).
  • AndersonAC. The process of structure-based drug design. Chem. Biol.10(9), 787–797 (2003).
  • MunsonM , LiebermanH , TserlinEet al.Lead optimization attrition analysis (LOAA): a novel and general methodology for medicinal chemistry. Drug Discov. Today20(8), 978–987 (2015).
  • MaynardAT , RobertsCD. Quantifying, visualizing, and monitoring lead optimization. J. Med. Chem.59(9), 4189–4201 (2016).
  • ShanmugasundaramV , ZhangL , KayasthaS , dela Vega de León A , DimovaD , BajorathJ. Monitoring the progression of structure-activity relationship information during lead optimization. J. Med. Chem.59(9), 4235–4244 (2016).
  • VogtM , YonchevD , BajorathJ. Computational method to evaluate progress in lead optimization. J. Med. Chem.61(23), 10895–10900 (2018).
  • HussainJ , ReaC. Computationally efficient algorithm to identify matched molecular pairs (MMPs) in large data sets. J. Chem. Inf. Model.50(3), 339–348 (2010).
  • YoshimoriA , BajorathJ. The SAR matrix method and an artificially intelligent variant for the identification and structural organization of analog series, SAR analysis, and compound design. Mol. Inform.39(12), 2000045 (2020).
  • NavejaJJ , VogtM , StumpfeD , Medina-FrancoJL , BajorathJ. Systematic extraction of analogue series from large compound collections using a new computational compound-core relationship method. ACS Omega4(1), 1027–1032 (2019).
  • BajorathJ. State-of-the-art of artificial intelligence in medicinal chemistry. Future Sci. OA7(6), FSO702 (2021).
  • TongX , LiuX , TanXet al.Generative models for de novo drug design. J. Med. Chem.64(19), 14011–14027 (2021).
  • SkinniderMA , StaceyRG , WishartDS , FosterLJ. Chemical language models enable navigation in sparsely populated chemical space. Nat. Mach. Intell.3(9), 759–770 (2021).
  • YoshimoriA , BajorathJ. DeepAS – Chemical language model for the extension of active analogue series. Bioorg. Med. Chem.66(1), 116808 (2022).
  • WassermannAM , BajorathJ. A data mining method to facilitate SAR transfer. J. Chem. Inf. Model.51(8), 1857–1866 (2011).
  • YoshimoriA , BajorathJ. Computational method for the systematic alignment of analogue series with structure-activity relationship transfer potential across different targets. Eur. J. Med. Chem.10.1016/j.ejmech.2022.114558 (2022) ( Epub ahead of print).