These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

165 related articles for article (PubMed ID: 38633987)

  • 1. Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an
    Evteev S; Ivanenkov Y; Semenov I; Malkov M; Mazaleva O; Bodunov A; Bezrukov D; Sidorenko D; Terentiev V; Malyshev A; Zagribelnyy B; Korzhenevskaya A; Aliper A; Zhavoronkov A
    Front Chem; 2024; 12():1382512. PubMed ID: 38633987
    [No Abstract]   [Full Text] [Related]  

  • 2. Recent Advances in Automated Structure-Based De Novo Drug Design.
    Tang Y; Moretti R; Meiler J
    J Chem Inf Model; 2024 Mar; 64(6):1794-1805. PubMed ID: 38485516
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Deep Learning Applied to Ligand-Based De Novo Drug Design.
    Palazzesi F; Pozzan A
    Methods Mol Biol; 2022; 2390():273-299. PubMed ID: 34731474
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Reaction-driven de novo design, synthesis and testing of potential type II kinase inhibitors.
    Schneider G; Geppert T; Hartenfeller M; Reisen F; Klenner A; Reutlinger M; Hähnke V; Hiss JA; Zettl H; Keppner S; Spänkuch B; Schneider P
    Future Med Chem; 2011 Mar; 3(4):415-24. PubMed ID: 21452978
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases.
    Muller C; Rabal O; Diaz Gonzalez C
    Methods Mol Biol; 2022; 2390():383-407. PubMed ID: 34731478
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Protein ligand interaction analysis against new CaMKK2 inhibitors by use of X-ray crystallography and the fragment molecular orbital (FMO) method.
    Takaya D; Niwa H; Mikuni J; Nakamura K; Handa N; Tanaka A; Yokoyama S; Honma T
    J Mol Graph Model; 2020 Sep; 99():107599. PubMed ID: 32348940
    [TBL] [Abstract][Full Text] [Related]  

  • 7. In silico fragment-based drug discovery: setup and validation of a fragment-to-lead computational protocol using S4MPLE.
    Hoffer L; Renaud JP; Horvath D
    J Chem Inf Model; 2013 Apr; 53(4):836-51. PubMed ID: 23537132
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Structure-based
    Li Y; Pei J; Lai L
    Chem Sci; 2021 Oct; 12(41):13664-13675. PubMed ID: 34760151
    [TBL] [Abstract][Full Text] [Related]  

  • 9. GENERA: A Combined Genetic/Deep-Learning Algorithm for Multiobjective Target-Oriented De Novo Design.
    Lamanna G; Delre P; Marcou G; Saviano M; Varnek A; Horvath D; Mangiatordi GF
    J Chem Inf Model; 2023 Aug; 63(16):5107-5119. PubMed ID: 37556857
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Quantitative structure-activity relationship: promising advances in drug discovery platforms.
    Wang T; Wu MB; Lin JP; Yang LR
    Expert Opin Drug Discov; 2015 Dec; 10(12):1283-300. PubMed ID: 26358617
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Quantum computing for near-term applications in generative chemistry and drug discovery.
    Pyrkov A; Aliper A; Bezrukov D; Lin YC; Polykovskiy D; Kamya P; Ren F; Zhavoronkov A
    Drug Discov Today; 2023 Aug; 28(8):103675. PubMed ID: 37331692
    [TBL] [Abstract][Full Text] [Related]  

  • 12.
    de Souza Neto LR; Moreira-Filho JT; Neves BJ; Maidana RLBR; Guimarães ACR; Furnham N; Andrade CH; Silva FP
    Front Chem; 2020; 8():93. PubMed ID: 32133344
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Deep generative models for ligand-based de novo design applied to multi-parametric optimization.
    Perron Q; Mirguet O; Tajmouati H; Skiredj A; Rojas A; Gohier A; Ducrot P; Bourguignon MP; Sansilvestri-Morel P; Do Huu N; Gellibert F; Gaston-Mathé Y
    J Comput Chem; 2022 Apr; 43(10):692-703. PubMed ID: 35218219
    [TBL] [Abstract][Full Text] [Related]  

  • 14. De novo molecular design and generative models.
    Meyers J; Fabian B; Brown N
    Drug Discov Today; 2021 Nov; 26(11):2707-2715. PubMed ID: 34082136
    [TBL] [Abstract][Full Text] [Related]  

  • 15. FastGrow: on-the-fly growing and its application to DYRK1A.
    Penner P; Martiny V; Bellmann L; Flachsenberg F; Gastreich M; Theret I; Meyer C; Rarey M
    J Comput Aided Mol Des; 2022 Sep; 36(9):639-651. PubMed ID: 35989379
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Linkers in fragment-based drug design: an overview of the literature.
    Grenier D; Audebert S; Preto J; Guichou JF; Krimm I
    Expert Opin Drug Discov; 2023; 18(9):987-1009. PubMed ID: 37466331
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.
    Kao PY; Yang YC; Chiang WY; Hsiao JY; Cao Y; Aliper A; Ren F; Aspuru-Guzik A; Zhavoronkov A; Hsieh MH; Lin YC
    J Chem Inf Model; 2023 Jun; 63(11):3307-3318. PubMed ID: 37171372
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Generative Recurrent Networks for De Novo Drug Design.
    Gupta A; Müller AT; Huisman BJH; Fuchs JA; Schneider P; Schneider G
    Mol Inform; 2018 Jan; 37(1-2):. PubMed ID: 29095571
    [TBL] [Abstract][Full Text] [Related]  

  • 19. BuildAMol: a versatile Python toolkit for fragment-based molecular design.
    Kleinschmidt N; Lemmin T
    J Cheminform; 2024 Aug; 16(1):104. PubMed ID: 39183293
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Training recurrent neural networks as generative neural networks for molecular structures: how does it impact drug discovery?
    D'Souza S; Kv P; Balaji S
    Expert Opin Drug Discov; 2022 Oct; 17(10):1071-1079. PubMed ID: 36216812
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.