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1.
Chemistry ; 28(9): e202103910, 2022 Feb 16.
Artículo en Inglés | MEDLINE | ID: mdl-35045197

RESUMEN

This work investigates the addition of monosaccharides to marketed drugs to improve their pharmacokinetic properties for oral absorption. To this end, a set of chloromethyl glycoside synthons were developed to prepare a variety of glycosyloxymethyl-prodrugs derived from 5-fluorouracil, thioguanine, propofol and losartan. Drug release was studied in vitro using ß-glucosidase confirming rapid conversion of the monosaccharide prodrugs to release the parent drug, formaldehyde and the monosaccharide. To showcase this prodrug approach, a glucosyloxymethyl conjugate of the tetrazole-containing drug losartan was used for in vivo experiments and showed complete release of the drug in a dog-model.


Asunto(s)
Profármacos , Animales , Perros , Glicósidos
2.
Nat Commun ; 12(1): 7024, 2021 12 02.
Artículo en Inglés | MEDLINE | ID: mdl-34857733

RESUMEN

The sugar fucose is expressed on mammalian cell membranes as part of glycoconjugates and mediates essential physiological processes. The aberrant expression of fucosylated glycans has been linked to pathologies such as cancer, inflammation, infection, and genetic disorders. Tools to modulate fucose expression on living cells are needed to elucidate the biological role of fucose sugars and the development of potential therapeutics. Herein, we report a class of fucosylation inhibitors directly targeting de novo GDP-fucose biosynthesis via competitive GMDS inhibition. We demonstrate that cell permeable fluorinated rhamnose 1-phosphate derivatives (Fucotrim I & II) are metabolic prodrugs that are metabolized to their respective GDP-mannose derivatives and efficiently inhibit cellular fucosylation.


Asunto(s)
Inhibidores Enzimáticos/farmacología , Fucosa/química , Guanosina Difosfato Fucosa/antagonistas & inhibidores , Hidroliasas/antagonistas & inhibidores , Profármacos/farmacología , Animales , Secuencia de Carbohidratos , Línea Celular Tumoral , Membrana Celular/efectos de los fármacos , Diseño de Fármacos , Inhibidores Enzimáticos/síntesis química , Expresión Génica , Glicosilación/efectos de los fármacos , Guanosina Difosfato Fucosa/biosíntesis , Halogenación , Humanos , Hidroliasas/genética , Hidroliasas/metabolismo , Células Jurkat , Linfocitos/citología , Linfocitos/efectos de los fármacos , Linfocitos/metabolismo , Ratones , Profármacos/síntesis química , Relación Estructura-Actividad , Células THP-1
3.
Biomolecules ; 10(6)2020 06 16.
Artículo en Inglés | MEDLINE | ID: mdl-32560074

RESUMEN

When Oleg Ptitsyn and his group published the first secondary structure prediction for a protein sequence, they started a research field that is still active today. Oleg Ptitsyn combined fundamental rules of physics with human understanding of protein structures. Most followers in this field, however, use machine learning methods and aim at the highest (average) percentage correctly predicted residues in a set of proteins that were not used to train the prediction method. We show that one single method is unlikely to predict the secondary structure of all protein sequences, with the exception, perhaps, of future deep learning methods based on very large neural networks, and we suggest that some concepts pioneered by Oleg Ptitsyn and his group in the 70s of the previous century likely are today's best way forward in the protein secondary structure prediction field.


Asunto(s)
Bioquímica/historia , Biología Computacional/historia , Biología Computacional/tendencias , Estructura Secundaria de Proteína , Proteínas/química , Bioquímica/métodos , Bioquímica/tendencias , Biología Computacional/métodos , Historia del Siglo XX , Historia del Siglo XXI , Relación Estructura-Actividad
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