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
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:1422-0067
1661-6596
1422-0067
DOI:10.3390/ijms222011191