Publications in collaboration with researchers from Universidad Central de Las Villas (15)

2016

  1. Topological sub-structural molecular design (TOPS-MODE): a useful tool to explore key fragments of human A3adenosine receptor ligands

    Molecular Diversity, Vol. 20, Núm. 1, pp. 55-76

2008

  1. New QSAR combined strategy for the design of A1 adenosine receptor agonists

    Bioorganic and Medicinal Chemistry, Vol. 16, Núm. 4, pp. 1658-1675

  2. Search for new antagonist ligands for adenosine receptors from QSAR point of view. How close are we?

    Medicinal Research Reviews, Vol. 28, Núm. 3, pp. 329-371

2007

  1. ANN-QSAR model for selection of anticancer leads from structurally heterogeneous series of compounds

    European Journal of Medicinal Chemistry, Vol. 42, Núm. 5, pp. 580-585

  2. QSAR studies using radial distribution function for predicting A 1 adenosine receptors agonists

    Bulletin of Mathematical Biology, Vol. 69, Núm. 1, pp. 347-359

2006

  1. Quantitative structure activity relationships as useful tools for the design of new adenosine receptor ligands. 1. Agonist

    Current Medicinal Chemistry, Vol. 13, Núm. 19, pp. 2253-2266

  2. Radial distribution function descriptors: An alternative for predicting A2 A adenosine receptors agonists

    European Journal of Medicinal Chemistry, Vol. 41, Núm. 1, pp. 56-62

2005

  1. A radial distribution function approach to predict A 2B agonist effect of adenosine analogues

    Bioorganic and Medicinal Chemistry, Vol. 13, Núm. 3, pp. 601-608

  2. A topological sub-structural approach to the mutagenic activity in dental monomers. 3. Heterogeneous set of compounds

    Polymer, Vol. 46, Núm. 8, pp. 2783-2790

  3. BCUT descriptors to predicting affinity toward A3 adenosine receptors

    Bioorganic and Medicinal Chemistry Letters, Vol. 15, Núm. 15, pp. 3491-3495

  4. GETAWAY descriptors to predicting A2A adenosine receptors agonists

    European Journal of Medicinal Chemistry, Vol. 40, Núm. 11, pp. 1080-1086

  5. Geometry, topology, and atom-weights assembly descriptors to predicting A1 adenosine receptors agonists

    Bioorganic and Medicinal Chemistry Letters, Vol. 15, Núm. 10, pp. 2641-2645

2004

  1. A TOPS-MODE approach to predict adenosine kinase inhibition

    Bioorganic and Medicinal Chemistry Letters, Vol. 14, Núm. 12, pp. 3077-3079

  2. A TOPS-MODE approach to predict affinity for A1 adenosine receptors. 2-(Arylamino)adenosine analogues

    Bioorganic and Medicinal Chemistry, Vol. 12, Núm. 11, pp. 2985-2993

  3. QSAR study of N6-(substituted-phenylcarbamoyl) adenosine-5′-uronamides as agonist for A1 adenosine receptors

    Bulletin of Mathematical Biology, Vol. 66, Núm. 4, pp. 907-920