Oscar Méndez-Lucio

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Obesity and the metabolic syndrome are pandemic diseases with high morbidity and mortality. With the aim of discovering novel therapies for those diseases, the cannabinoid receptor 1 (CB1), which has been validated as a target for treating appetitive disorders, is now considered a novel target for the design of anti-obesity compounds. Our main goal was to(More)
Activity cliffs have large impact in drug discovery; therefore, their detection and quantification are of major importance. This work introduces the metric activity cliff enrichment factor and expands the previously reported activity cliff generator concept by adding chemotype information to representations of the activity landscape. To exemplify these(More)
Predicting novel drug side-effects, or Adverse Drug Reactions (ADRs), plays an important role in the drug discovery process. Existing methods consider mainly the chemical and biological characteristics of each drug individually, thereby neglecting information hidden in the relationships among drugs. Complementary to the existing individual methods, in this(More)
The interaction of the envelope glycoprotein of HIV-1 (gp120/gp41) with coreceptor molecules has important implications for specific cellular targeting and pathogenesis. Experimental and theoretical evidences have shown a role for gp41 in coreceptor tropism, although there is no consensus about the positions involved. Here we analyze the association of(More)
Activity landscape modeling is mostly a descriptive technique that allows rationalizing continuous and discontinuous SARs. Nevertheless, the interpretation of some landscape features, especially of activity cliffs, is not straightforward. As the nature of activity cliffs depends on the ligand and the target, information regarding both should be included in(More)
Inhibitors of human DNA methyltransferases (DNMT) are of increasing interest to develop novel epi-drugs for the treatment of cancer and other diseases. As the number of compounds with reported DNMT inhibition is increasing, molecular docking is shedding light to elucidate their mechanism of action and further interpret structure-activity relationships.(More)
The emerging concept of the activity landscape has been widely applied for structureactivity relationships (SAR) characterization. Since chemical space representation plays a crucial role in activity landscape modeling, an adequate selection of similarity measures is desirable. Herein a set of 658 cyclooxygenase inhibitors were structurally analyzed using(More)
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