An interpretable machine learning approach to identify the mechanism of action of antibiotics

  • World Health Organisation et al. Lack of new antibiotics threatens global efforts to contain drug-resistant infections. (2020).

  • Neill, JO Antimicrobial Resistance: Addressing a Crisis for the Health and Wealth of Nations Chair of Antimicrobial Resistance Review. In Review Paper Addressing a Crisis for Nations Health and Prosperity1–20 (HM Government Wellcome Trust, 2014).

  • Pence, HE, & Williams A. Chemspider: An Online Chemical Information Resource (2010).

  • Kim, s. et al. Pubchem substance and composite databases. null. Acids Res. 44(D1), D1202-D1213 (2016).

    CAS
    Article

    google scholar

  • Irwin, JJ & Shoichet, BK Zinc – A free database of commercially available compounds for virtual screening. J. Chem. info. Fashion model. 45(1), 177-182 (2005).

    CAS
    Article

    google scholar

  • Ashby, J. The value and limitations of short-term genotoxicity testing and the inadequacy of current chemical selection criteria for cancer bioassays. Ann. NY Acad. science 534(1), 133-138 (1988).

    ADS
    CAS
    Article

    google scholar

  • King, RD, Muggleton, S., Lewis, RA & Sternberg, M. Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogs that bind to dihydrofolate reductase. proc. wet. academy. science 89(23), 11322-11326 (1992).

    ADS
    CAS
    Article

    google scholar

  • Hirst, JD, King, RD & Sternberg, MJ Quantitative structure-activity relationships through neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines. J. Computer-assisted Mol. des. 8(4), 405-420 (1994).

    ADS
    CAS
    Article

    google scholar

  • Bronstein, MM, Bruna, J., LeCun, Y., Szlam, A. & Vandergheynst, P. Geometric deep learning: going beyond Euclidean data. IEEE signal process. Allowed. 34(4), 18-42 (2017).

    ADS
    Article

    google scholar

  • Stokes, JM et al. An in-depth learning approach to antibiotic discovery. Cell 180(4), 688–702 (2020).

    CAS
    Article

    google scholar

  • Dai, H., Dai, B., & Song, L. Discriminatory embedding of latent variable models for structured data. In International Machine Learning Conference2702-2711 (PMLR, 2016).

  • Yang, K. et al. Analysis of learned molecular representations for property prediction. J. Chem. info. Fashion model. 59(8), 3370-3388 (2019).

    CAS
    Article

    google scholar

  • Desk et al. Design, synthesis and structure-activity relationship of substrate-competitive, selective and in vivo active triazole and thiadiazole inhibitors of the c-jun n-terminal kinase. J. Med. Chem. 52(7), 1943-1952 (2009).

    CAS
    Article

    google scholar

  • Chen, X.-W., & Jeong, JC Enhanced elimination of recursive functions. In Sixth International Conference on Machine Learning and Applications (ICMLA 2007)429-435 (IEEE, 2007).

  • Kursa, MB & Rudnicki, WR Feature selection with the Boruta pack. J.Stat. soft 361-13 (2010).

    Article

    google scholar

  • Tibshirani, R. Regression shrinkage and lasso selection. J.R. State. soc. ser. B method. 58(1), 267-288 (1996).

    MathematicsSciNet
    MATH

    google scholar

  • Pope, PE, Kolouri, S., Rostami, M., Martin, CE, & Hoffmann, H. Explainability methods for graphical convolutional neural networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition10772-10781 (2019).

  • Kojima, R. et al. kgcn: a graph-based deep learning framework for chemical structures. J. Cheminform. 12(1), 1-10 (2020).

    Article

    google scholar

  • Baldassarre, F., & Azizpour, H. Explainability techniques for graphical convolutional networks. CoRR, full. abs/1905.13686, (2019).

  • Montavon, G., Lapuschkin, S., Binder, A., Samek, W. & Müller, K.-R. Explain nonlinear classification decisions with deep Taylor decomposition. Recognize pattern. 65211-222 (2017).

    ADS
    Article

    google scholar

  • Ying, R., Bourgeois, D., You, J., Zitnik, M., & Leskovec, J. Gnn explanation: a tool for post-hoc explanation of graph neural networks. arXiv preprint arXiv:1903.03894(2019).

  • Corsello, SM et al. The drug reuse hub: a next-generation drug library and resource. wet. med. 23(4), 405-408 (2017).

    CAS
    Article

    google scholar

  • Zuegg, J., Hansford, KA, Elliott, AG, Cooper, MA & Blaskovich, MA How to stimulate and facilitate the discovery of antibiotics at an early stage. ACS infection. this. 6(6), 1302-1304 (2020).

    CAS
    Article

    google scholar

  • Blaskovich, MA, Zuegg, J., Elliott, AG & Cooper, MA Helping chemists discover new antibiotics. ACS infection. this. 1(7), 285-287 (2015).

    CAS
    Article

    google scholar

  • Reeve, SM, Lombardo, MN & Anderson, AC Understanding the structural mechanisms of antibiotic resistance provides the platform for new discoveries. Future Microbiology. 10(11), 1727-1733 (2015).

    CAS
    Article

    google scholar

  • Cho, H., Uehara, T. & Bernhardt, TG Beta-lactam antibiotics induce a lethal malfunction of the bacterial cell wall synthesis machinery. Cell 159(6), 1300-1311 (2014).

    CAS
    Article

    google scholar

  • Pham, TD, Ziora, ZM & Blaskovich, MA Quinolone antibiotics. MedChemComm 10(10), 1719-1739 (2019).

    CAS
    Article

    google scholar

  • Pearson, G. et al. Mitogen-activated protein (MAP) kinase pathways: regulation and physiological functions. endocr. Rev. 22(2), 153-183 (2001).

    CAS
    PubMed

    google scholar

  • Fleman, R. et al. Combinatorial libraries to aid the discovery of novel, broad-spectrum antibacterial agents targeting the ESKAPE pathogens. J. Med. Chem. 58(8), 3340-3355 (2015).

    CAS
    Article

    google scholar

  • Wang, b. et al. Antibacterial diamines target bacterial membranes. J. Med. Chem. 59(7), 3140-3151 (2016).

    CAS
    Article

    google scholar

  • Qian, L., Guan, Y., He, B. & Xiao, H. Modified guanidine polymers: synthesis and antimicrobial mechanism revealed by AFM. Polymer 49(10), 2471-2475 (2008).

    CAS
    Article

    google scholar

  • Olender, D., Żwawiak, J. & Zaprutko, L. Multidirectional efficacy of biologically active nitro compounds in drugs. Medicines 11(2), 54 (2018).

    Article

    google scholar

  • Witt, J. et al. Synthesis of hydrazone derivatives of 4-[4-formyl-3-(2-oxochromen-3-yl) pyrazol-1-yl] benzoic acid as potent growth inhibitors of antibiotic-resistant Staphylococcus aureus and Acinetobacter baumanniiMolecules 24(11), 2051 (2019).

    Article

    google scholar

  • Lv, Q.-Z. et al. A new antifungal (4-phenyl-1,3-thiazol-2-yl)hydrazine induces oxidative damage in candida albicansFront side. Cell. Infect. microbiologically. 10557 (2020).

    Article

    google scholar

  • Landrum, G. et al.† Rdkit: open source chemistry. (2006).

  • Weininger, D. Smiles, A chemical language and information system. 1. Introduction to methodology and coding rules. J. Chem. info. Calculate. science 28(1), 31-36 (1988).

    CAS
    Article

    google scholar

  • He, H. & Ma, Y. Unbalanced Learning: Fundamentals, Algorithms and Applications (Wiley, 2013).

    Book

    google scholar

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