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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Vydáno v:	International journal of molecular sciences Ročník 22; číslo 20; s. 11191
Hlavní autoři:	Islam, Md Ataul, Rallabandi, V. P. Subramanyam, Mohammed, Sameer, Srinivasan, Sridhar, Natarajan, Sathishkumar, Dudekula, Dawood Babu, Park, Junhyung
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 17.10.2021 MDPI
Témata:	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
On-line přístup:	Získat plný text
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Shrnutí:	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 (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	1422-0067 1661-6596 1422-0067
DOI:	10.3390/ijms222011191