Publicaciones en colaboración con investigadores/as de Universidad Central de Las Villas (73)

2024

  1. Ligand and structure-based discovery of phosphorus-containing compounds as potential metalloproteinase inhibitors

    SAR and QSAR in Environmental Research, Vol. 35, Núm. 3, pp. 219-240

2023

  1. A Review of Computational Approaches Targeting SARS-CoV-2 Main Protease to the Discovery of New Potential Antiviral Compounds

    Current Topics in Medicinal Chemistry, Vol. 23, Núm. 1, pp. 3-16

  2. Anti-inflammatory Activity: In silico and in vivo of Sapogenins Present in Agave brittoniana subsp. brachypus (Trel.)

    Anti-Inflammatory and Anti-Allergy Agents in Medicinal Chemistry, Vol. 22, Núm. 1, pp. 42-48

2022

  1. Ligand-based discovery of new potential acetylcholinesterase inhibitors for Alzheimer’s disease treatment

    SAR and QSAR in Environmental Research, Vol. 33, Núm. 1, pp. 49-61

  2. Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases

    Molecular Diversity, Vol. 26, Núm. 3, pp. 1383-1397

2020

  1. Computational approach to the discovery of potential neprilysin inhibitors compounds for cardiovascular diseases treatment

    Medicinal Chemistry Research, Vol. 29, Núm. 5, pp. 897-909

  2. Thorough evaluation of OECD principles in modelling of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine derivatives using QSARINS

    SAR and QSAR in Environmental Research, Vol. 31, Núm. 10, pp. 741-759

2019

  1. An approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking

    Arabian Journal of Chemistry, Vol. 12, Núm. 8, pp. 4861-4877

2018

  1. Computational identification of chemical compounds with potential activity against leishmania amazonensis using nonlinear machine learning techniques

    Current Topics in Medicinal Chemistry, Vol. 18, Núm. 27, pp. 2347-2354

2017

  1. Larvicidal activity prediction against Aedes aegypti mosquito using computational tools

    Journal of Vector Borne Diseases, Vol. 54, Núm. 2, pp. 164-171

  2. State of the art review and report of new tool for drug discovery

    Current Topics in Medicinal Chemistry, Vol. 17, Núm. 26, pp. 2957-2976

2016

  1. Generalized molecular descriptors derived from event-based discrete derivative

    Current Pharmaceutical Design, Vol. 22, Núm. 33, pp. 5095-5113

  2. Prediction of caco-2 cell permeability using bilinear indices and multiple linear regression

    Letters in Drug Design and Discovery, Vol. 13, Núm. 2, pp. 161-169

2015

  1. Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening

    European Journal of Medicinal Chemistry, Vol. 96, pp. 238-244

  2. Extending graph (discrete) derivative descriptors to N-tuple atom-relations

    Match, Vol. 73, Núm. 2, pp. 397-420

  3. In silico antibacterial activity modeling based on the TOMOCOMD-CARDD approach

    Journal of the Brazilian Chemical Society, Vol. 26, Núm. 6, pp. 1218-1226

  4. QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents

    SAR and QSAR in Environmental Research, Vol. 26, Núm. 11, pp. 943-958

2014

  1. Analysis of proteasome inhibition prediction using atom-based quadratic indices enhanced by machine learning classification techniques

    Letters in Drug Design and Discovery, Vol. 11, Núm. 6, pp. 705-711

  2. Discrete derivatives for atom-pairs as a novel graph-theoretical invariant for generating new molecular descriptors: Orthogonality, interpretation and QSARs/QSPRs on benchmark databases

    Molecular Informatics, Vol. 33, Núm. 5, pp. 343-368

  3. Tyrosinase enzyme: 1. An overview on a pharmacological target

    Current Topics in Medicinal Chemistry, Vol. 14, Núm. 12, pp. 1494-1501