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Molecular Diversity

, Volume 19, Issue 2, pp 347–356 | Cite as

Multi-output model with Box–Jenkins operators of linear indices to predict multi-target inhibitors of ubiquitin–proteasome pathway

  • Gerardo M. Casañola-Martin
  • Huong Le-Thi-Thu
  • Facundo Pérez-Giménez
  • Yovani Marrero-Ponce
  • Matilde Merino-Sanjuán
  • Concepción Abad
  • Humberto González-Díaz
Full-Length Paper

Abstract

The ubiquitin–proteasome pathway (UPP) plays an important role in the degradation of cellular proteins and regulation of different cellular processes that include cell cycle control, proliferation, differentiation, and apoptosis. In this sense, the disruption of proteasome activity leads to different pathological states linked to clinical disorders such as inflammation, neurodegeneration, and cancer. The use of UPP inhibitors is one of the proposed approaches to manage these alterations. On other hand, the ChEMBL database contains >5,000 experimental outcomes for >2,000 compounds tested as possible proteasome inhibitors using a large number of pharmacological assay protocols. All these assays report a large number of experimental parameters of biological activity like \(EC_{50}, IC_{50}\), percent of inhibition, and many others that have been determined under many different conditions, targets, organisms, etc. Although this large amount of data offers new opportunities for the computational discovery of proteasome inhibitors, the complexity of these data represents a bottleneck for the development of predictive models. In this work, we used linear molecular indices calculated with the software TOMOCOMD-CARDD and Box–Jenkins moving average operators to develop a multi-output model that can predict outcomes for 20 experimental parameters in >450 assays carried out under different conditions. This generated multi-output model showed values of accuracy, sensitivity, and specificity above 70 % for training and validation series. Finally, this model is considered multi-target and multi-scale, because it predicts the inhibition of the UPP for drugs against 22 molecular or cellular targets of different organisms contained in the ChEMBL database.

Keywords

Ubiquitin–proteasome pathway inhibitors CHEMBL Multi-target Multi-scale and multi-output models Moving averages QSAR 

Notes

Acknowledgments

Casañola-Martin, G. M. thanks the program Estades Temporals per a Investigadors Convidats for a fellowship to research at Valencia University (2013–2014). Le-Thi-Thu, H. gratefully acknowledges the support from the National Vietnam National University, Hanoi. Marrero-Ponce, Y. thanks the International Professor program for a fellowship to work at Cartagena University in the year 2013–2014. Also, thanks to Prof. Aroa Reguero from the Pontifical Catholic University of Ecuador in Esmeraldas (PUCESE) for her help in the review of the manuscript. Finally, the authors also thank the anonymous referees and editor for their useful comments that contributed to the improvement of this work.

Supplementary material

11030_2015_9571_MOESM1_ESM.xlsx (138 kb)
Supplementary material 1 (xlsx 138 KB)
11030_2015_9571_MOESM2_ESM.pdf (83 kb)
Supplementary material 2 (pdf 84 KB)

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Gerardo M. Casañola-Martin
    • 1
    • 2
    • 3
  • Huong Le-Thi-Thu
    • 4
  • Facundo Pérez-Giménez
    • 2
  • Yovani Marrero-Ponce
    • 5
  • Matilde Merino-Sanjuán
    • 6
    • 7
  • Concepción Abad
    • 1
  • Humberto González-Díaz
    • 8
    • 9
  1. 1.Departament de Bioquímica i Biologia MolecularUniversitat de ValènciaBurjassotSpain
  2. 2.Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de FarmaciaUniversitat de ValènciaValenciaSpain
  3. 3.Faculty of Environmental SciencePontifical University Catholic of Ecuador in Esmeraldas (PUCESE)EsmeraldasEcuador
  4. 4.School of Medicine and PharmacyVietnam National University Hanoi (VNU)HanoiVietnam
  5. 5.Facultad de Química FarmacéuticaUniversidad de CartagenaCartagena de IndiasColombia
  6. 6.Department of Pharmacy and Pharmaceutical TechnologyUniversity of ValenciaValenciaSpain
  7. 7.Institute of Molecular Recognition and Technological Development (IDM), Inter-Universitary Institute from Polytechnic University of Valencia and University of ValenciaValenciaSpain
  8. 8.Department of Organic Chemistry IIUniversity of the Basque Country UPV/EHULeioaSpain
  9. 9.IKERBASQUE, Basque Foundation for ScienceBilbaoSpain

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