Mechanistic and Predictive QSAR Analysis of Diverse Molecules to Capture Salient and Hidden Pharmacophores for Anti-Thrombotic Activity.

Zaki, Magdi E A; Al-Hussain, Sami A; Masand, Vijay H; Sabnani, Manoj K; Samad, Abdul

Zaki, Magdi E A; Al-Hussain, Sami A; Masand, Vijay H; Sabnani, Manoj K; Samad, Abdul.

Afiliación

Zaki MEA; Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia.
Al-Hussain SA; Department of Chemistry, Faculty of Science, Imam Mohammad Ibn Saud Islamic University, Riyadh 13318, Saudi Arabia.
Masand VH; Department of Chemistry, Vidya Bharati Mahavidyalaya, Amravati 444 601, Maharashtra, India.
Sabnani MK; Department of Biology, The University of Texas at Arlington, Arlington, TX 76019, USA.
Samad A; Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Tishk International University, Erbil 44001, Kurdistan Region, Iraq.

Int J Mol Sci ; 22(15)2021 Aug 03.

Article en En | MEDLINE | ID: mdl-34361118

Asunto(s)

Fibrinolíticos/farmacología; Compuestos Heterocíclicos/farmacología; Trombosis/tratamiento farmacológico; Fibrinolíticos/química; Compuestos Heterocíclicos/química; Humanos; Modelos Moleculares; Relación Estructura-Actividad Cuantitativa

Palabras clave

QSAR; factor Xa; machine learning; pharmacophores; thrombosis

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Trombosis / Fibrinolíticos / Compuestos Heterocíclicos Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Int J Mol Sci Año: 2021 Tipo del documento: Article País de afiliación: Arabia Saudita

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