Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning...

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Veröffentlicht in:	International journal of molecular sciences Jg. 22; H. 20; S. 11191
Hauptverfasser:	Islam, Md Ataul, Rallabandi, V. P. Subramanyam, Mohammed, Sameer, Srinivasan, Sridhar, Natarajan, Sathishkumar, Dudekula, Dawood Babu, Park, Junhyung
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 17.10.2021 MDPI
Schlagworte:	Adrenergic receptors Amino acids Binding sites Crystal structure Drug Discovery Humans Kinases Ligands Machine Learning Molecular Dynamics Simulation Protein Binding Proteins R&D Receptors, Adrenergic, beta-1 - chemistry Receptors, Adrenergic, beta-2 - chemistry Research & development Signal transduction MD simulation similarity search cardiovascular diseases virtual screening machine learning β-adrenergic receptors
ISSN:	1422-0067, 1661-6596, 1422-0067
Online-Zugang:	Volltext
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