Automated high throughput pK<sub>a</sub> and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge.

Bahr, Matthew N; Nandkeolyar, Aakankschit; Kenna, John K; Nevins, Neysa; Da Vià, Luigi; Isik, Mehtap; Chodera, John D; Mobley, David L

Automated high throughput pK_a and distribution coefficient measurements of pharmaceutical compounds for the SAMPL8 blind prediction challenge.

Bahr, Matthew N; Nandkeolyar, Aakankschit; Kenna, John K; Nevins, Neysa; Da Vià, Luigi; Isik, Mehtap; Chodera, John D; Mobley, David L.

Afiliación

Bahr MN; Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA. matthew.n.bahr@gsk.com.
Nandkeolyar A; Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA.
Kenna JK; Drexel University, 3141 Chestnut Street, Philadelphia, PA, 19104, USA.
Nevins N; Department of Pharmaceutical Sciences and Department of Chemistry, University of California, Irvine, Irvine, CA, 92697, USA.
Da Vià L; Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA.
Isik M; Pharmaceutical Research and Development, GlaxoSmithKline, 1250 South Collegeville Road, Collegeville, PA, 19426, USA.
Chodera JD; Pharmaceutical Research and Development, GlaxoSmithKline, Gunnels Wood Road, Stevenage, SG1 2NY, UK.
Mobley DL; Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.

J Comput Aided Mol Des ; 35(11): 1141-1155, 2021 11.

Article en En | MEDLINE | ID: mdl-34714468

Asunto(s)

Modelos Químicos; Preparaciones Farmacéuticas/química; Proteínas/química; Automatización; Descubrimiento de Drogas; Ligandos; Estructura Molecular

Palabras clave

Acid dissociation constants; Blind prediction challenge; Distribution coefficients; High throughput experimentation; SAMPL; pH-solubility profiles

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Preparaciones Farmacéuticas / Proteínas / Modelos Químicos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Comput Aided Mol Des Asunto de la revista: BIOLOGIA MOLECULAR / ENGENHARIA BIOMEDICA Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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