Dr. Miguel Angel Cabrera-Perez

Professor
Central University of Las Villas, Cuba

Highest Degree
Ph.D. in Pharmaceutical Sciences from Central University of Las Villas, Cuba

My URL
https://livedna.org/53.6088

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Area of Interest:

Pharmacology and Toxicology
Molecular Modeling
Information Modeling
Medical Chemistry
Chemical Engineering

Selected Publications

  1. Saiz-Urra, L., M.A.C. Perez and M. Froeyen, 2013. Thermodynamic computational approach to capture molecular recognition in the binding of different inhibitors to the DNA gyrase B subunit from Escherichia coli. J. Mol. Model., 19: 3187-3200.
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  2. Pham-The, H., T. Garrigues, M. Bermejo, I. Gonzalez-Alvarez, M.C. Monteagudo and M.A. Cabrera-Perez, 2013. Provisional classification and in silico study of biopharmaceutical system based on Caco-2 cell permeability and dose number. Mol. Pharmaceut., 10: 2445-2461.
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  3. Pham-The, H., I. Gonzalez-Alvarez, M. Bermejo, T. Garrigues, H. Le-Thi-Thu and M.A. Cabrera-Perez, 2013. The use of rule-based and QSPR approaches in ADME profiling: A case study on Caco-2 permeability. Mol. Inform., 32: 459-479.
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  4. Castillo-Gonzalez, D., G. Perez-Machado, A. Guedin, J.L. Mergny and M.A. Cabrera-Perez, 2013. FDA-approved drugs selected using virtual screening bind specifically to G-quadruplex DNA. Curr. Pharm. Des., 19: 2164-2173.
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  5. Perez-Castillo, Y., C. Lazar, J. Taminau, M. Froeyen, M.A. Cabrera-Perez and A. Nowee, 2012. GA(M)E-QSAR: A novel, fully automatic genetic-algorithm-(meta)-ensembles approach for binary classification in ligand-based drug design. J. Chem. Inform. Model., 52: 2366-2386.
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  6. Castillo-Gonzalez, D., G. Perez-Machado, F. Pallardo, T.M. Garrigues-Pelufo and M.A. Cabrera-Perez, 2012. Computational tools in the discovery of new G-quadruplex ligands with potential anticancer activity. Curr. Top. Med. Chem., 12: 2843-2856.
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  7. Cabrera-Perez, M.A., H. Pham-The, M. Bermejo, I.G. Alvarez, M.G. Alvarez and T.M. Garrigues, 2012. QSPR in oral bioavailability: Specificity or integrality? Mini-Rev. Med. Chem., 12: 534-550.
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  8. Saiz-Urra, L., M.A.C. Perez, A.M. Helguera and M. Froeyen, 2011. Combining molecular docking and QSAR studies for modelling the antigyrase activity of cyclothialidine derivatives. Eur. J. Med. Chem., 46: 2736-2747.
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  9. Saiz-Urra, L., M.A. Cabrera, M. Froeyen, 2011. Exploring the conformational changes of the ATP binding site of gyrase B from Escherichia coli complexed with different established inhibitors by using molecular dynamics simulation: Protein-ligand interactions in the light of the alanine scanning and free energy decomposition methods. J. Mol. Graph. Modell., 29: 726-739.
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  10. Pham-The, H., I. Gonzalez-Alvarez, M. Bermejo, V.M. Sanjuan, I. Centelles, T.M. Garrigues and M.A. Cabrera-Perez, 2011. In silico prediction of Caco-2 cell permeability by a classification QSAR approach. Mol. Inform., 30: 376-385.
    CrossRef  |  Direct Link  |  

  11. Perez-Castillo, Y., M. Froeyen, M.A. Cabrera-Perez and A. Nowe, 2011. Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling. J. Comput.-Aided Mol. Des., 25: 371-393.
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  12. Castillo-Gonzalez, D., M.A. Cabrera-Perez, M. Perez-Gonzalez, A.M. Helguera and A. Duran-Martinez, 2009. Prediction of telomerase inhibitory activity for acridinic derivatives based on chemical structure. Eur. J. Med. Chem., 44: 4826-4840.
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  13. Cabrera-Perez, M., D. Castillo-Gonzalez, M. Perez-Gonzalez and A. Duran-Martinez, 2009. Telomerase inhibitory activity of acridinic derivatives: A 3D-QSAR approach. QSAR Combinatorial Sci., 28: 526-536.
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  14. Perez, M.A.C. and Y.P. Castillo, 2008. Bacterial β-ketoacyl-acyl carrier protein synthase III (FabH): An attractive target for the design of new Broad-spectrum antimicrobial agents. Mini-Rev. Med. Chem., 8: 36-45.
    CrossRef  |  PubMed  |  Direct Link  |  

  15. Helguera, A.M., M.P. Gonzalez, M.N.D.S. Cordeiro and M.A.C. Perez, 2008. Quantitative structure-carcinogenicity relationship for detecting structural alerts in nitroso compounds: Species, rat; sex, female; route of administration, Gavage. Chem. Res. Toxicol., 21: 633-642.
    CrossRef  |  Direct Link  |  

  16. Helguera, A.M., M.N.D.S. Cordeiro, M.A.C. Perez, R.D. Combes and M.P. Gonzalez, 2008. Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds: Species: Rat; Sex: Male; Route of administration: Water. Toxicol. Applied Pharmacol., 231: 197-207.
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  17. Helguera, A.M., M.N.D.S. Cordeiro, M.A.C. Perez, R.D. Combes and M.P. Gonzalez, 2008. QSAR modeling of the rodent carcinogenicity of nitrocompounds. Bioorg. Med. Chem., 16: 3395-3407.
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  18. Gonzalez-Diaz, H., M.A. Cabrera-Perez, G. Aguero-Chapin, M. Cruz-Monteagudo, N. Castaneda-Cancio, M.A. del Rio and E. Uriarte, 2008. Multi-target QSPR assemble of a complex network for the distribution of chemicals to biphasic systems and biological tissues. Chemometrics Intell. Lab. Syst., 94: 160-165.
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  19. Helguera, A.M., M.P. Gonzalez, M.N.D.S. Cordeiro and M.A.C. Perez, 2007. Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds. Toxicol. Applied Pharmacol., 221: 189-202.
    CrossRef  |  Direct Link  |  

  20. Morales, A.H., P.R. Duchowicz, M.A.C. Perez, E.A. Castro, M.N.D.S. Cordeiro and M.P. Gonzalez, 2006. Application of the replacement method as a novel variable selection strategy in QSAR. 1. Carcinogenic potential. Chemometrics Intell. Lab. Syst., 81: 180-187.
    CrossRef  |  Direct Link  |  

  21. Morales, A.H., M.A.C. Perez, R.D. Combes and M.P. Gonzalez, 2006. Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity. Toxicology, 220: 51-62.
    CrossRef  |  Direct Link  |  

  22. Helguera, A.M., M.A.C. Perez and M.P. Gonzalez, 2006. A radial-distribution-function approach for predicting rodent carcinogenicity. J. Mol. Model., 12: 769-780.
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  23. Cabrera, M.A., I. Gonzalez, C. Fernandez, C. Navarro and M. Bermejo, 2006. A topological substructural approach for the prediction of P-glycoprotein substrates. J. Pharm. Sci., 95: 589-606.
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  24. Ponce, Y.M., M.A.C. Perez, V.R. Zaldivar, M.B. Sanz, D.S. Mota and F. Torrens, 2005. Prediction of intestinal epithelial transport of drug in (Caco-2) cell culture from molecular structure using in silico approaches during early drug discovery. Internet Electronic J. Mol. Des., 4: 124-150.
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  25. Helguera, A.M., M.A.C. Perez, R.D. Combes and M.P. Gonzalez, 2005. The prediction of carcinogenicity from molecular structure. Curr. Comput.-Aided Drug Des., 1: 237-255.
    CrossRef  |  Direct Link  |  

  26. Helguera, A.M., M.A.C. Perez, M.P. Gonzalez, R.M. Ruiz and H.G. Diaz, 2005. A topological substructural approach applied to the computational prediction of rodent carcinogenicity. Bioorg. Med. Chem., 13: 2477-2488.
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  27. Gonzalez-Diaz, H., G. Aguero, M.A. Cabrera, R. Molina and L. Santana et al., 2005. Unified markov thermodynamics based on stochastic forms to classify drugs considering molecular structure, partition system and biological species: Distribution of the antimicrobial G1 on rat tissues. Bioorg. Med. Chem. Lett., 15: 551-557.
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  28. Gonzalez, M.P., A.M. Helguera and M.A. Cabrera, 2005. Quantitative structure-activity relationship to predict toxicological properties of benzene derivative compounds. Bioorg. Med. Chem., 13: 1775-1781.
    CrossRef  |  Direct Link  |  

  29. Ponce, Y.M., M.A.C. Perez, V.R. Zaldivar, H.G. Diaz and F. Torrens, 2004. A new topological descriptors based model for predicting intestinal epithelial transport of drugs in Caco-2 cell culture. J. Pharm. Pharmaceut. Sci., 7: 186-199.
    PubMed  |  Direct Link  |  

  30. Perez, M.A.C., M.B. Sanz, L.R. Torres, R.G. Avalos, M.P. Gonzalez and H.G. Diaz, 2004. A topological sub-structural approach for predicting human intestinal absorption of drugs. Eur. J. Med. Chem., 39: 905-916.
    CrossRef  |  Direct Link  |  

  31. Perez, M.A.C. and M.B. Sanz, 2004. In silico prediction of central nervous system activity of compounds. Identification of potential pharmacophores by the TOPS-MODE approach. Bioorganic Med. Chem., 12: 5833-5843.
    CrossRef  |  Direct Link  |  

  32. Gonzalez, M.P., H.G. Diaz, M.A. Cabrera and R.M. Ruiz, 2004. A novel approach to predict a toxicological property of aromatic compounds in the Tetrahymena pyriformis. Bioorg. Med. Chem., 12: 735-744.
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  33. Cabrera, M.A., M. Bermejo, M. Perez and R. Ramos, 2004. TOPS-MODE approach for the prediction of blood-brain barrier permeation. J. Pharmaceut. Sci., 93: 1701-1717.
    CrossRef  |  Direct Link  |  

  34. Ponce, Y.M., M.A.C. Perez, V.R. Zaldivar, E. Ofori and L.A. Montero, 2003. Total and local quadratic indices of the molecular Pseudograph's atom adjacency matrix. Application to prediction of Caco-2 permeability of drugs. Int. J. Mol. Sci., 4: 512-536.
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  35. Perez, M.A.C., A.R. Garcia, C.F. Teruel, I.G. Alvarez and M.B. Sanz, 2003. A topological-substructural molecular design (TOPS-MODE) approach to determining pharmacokinetics and pharmacological properties of 6-fluoroquinolone derivatives. Eur. J. Pharmaceut. Biopharmaceut., 56: 197-206.
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  36. Gonzalez, M.P., H.G. Diaz, R.M. Ruiz, M.A. Cabrera and R.R. de Armas, 2003. TOPS-MODE based QSARs derived from heterogeneous series of compounds. Applications to the design of new herbicides. J. Chem. Inform. Comput. Sci., 43: 1192-1199.
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  37. Gonzales-Diaz, H., O. Gia, E. Uriarte, I. Hernadez and R. Ramos et al., 2003. Markovian chemicals in silico design (MARCH-INSIDE), a promising approach for computer-aided molecular design I: Discovery of anticancer compounds. J. Mol. Model., 9: 395-407.
    CrossRef  |  Direct Link  |  

  38. Diaz, H.G., Y. Marrero, I. Hernandez, I. Bastida and E. Tenorio et al., 2003. 3D-MEDNEs:  An alternative in silico technique for chemical research in toxicology. 1. Prediction of chemically induced agranulocytosis. Chem. Res. Toxicol., 16: 1318-1327.
    CrossRef  |  Direct Link  |  

  39. Perez, M.A.C., H.G. Diaz, C.F. Teruel, J.M. Pla-Delfina and M.B. Sanz, 2002. A novel approach to determining physicochemical and absorption properties of 6-fluoroquinolone derivatives: Experimental assessment. Eur. J. Pharmaceut. Biopharmaceut., 53: 317-325.
    CrossRef  |  Direct Link  |  
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