Machine Learning Prediction of Mycobacterial Cell Wall Permeability of Drugs and Drug-like Compounds.

Radchenko, Eugene V; Antonyan, Grigory V; Ignatov, Stanislav K; Palyulin, Vladimir A

Radchenko, Eugene V; Antonyan, Grigory V; Ignatov, Stanislav K; Palyulin, Vladimir A.

Afiliación

Radchenko EV; Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Antonyan GV; Department of Chemistry, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia.
Ignatov SK; Department of Chemistry, Lomonosov Moscow State University, 119991 Moscow, Russia.
Palyulin VA; Department of Chemistry, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia.

Molecules ; 28(2)2023 Jan 07.

Article en En | MEDLINE | ID: mdl-36677691

Asunto(s)

Antituberculosos; Mycobacterium tuberculosis; Antituberculosos/farmacología; Pared Celular; Aprendizaje Automático; Permeabilidad

Palabras clave

Mycobacterium tuberculosis; cell wall; fragmental descriptors; machine learning; neural networks; penetration; permeability; resistance; tuberculosis

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Mycobacterium tuberculosis / Antituberculosos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Molecules Asunto de la revista: BIOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Rusia

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