<i>In silico</i> discovery of novel calcineurin inhibitors using ligand-based 3-D pharmacophore modelling and molecular dynamics simulation
Creators: name: M, Nivya R.
name: Joy, Amitha
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Molecular Biology
subject: Neuroscience
subject: Physiology
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Cancer

description: Calcineurin is a serine-threonine protein phosphatase that is activated with the binding of calmodulin in the presence of increased calcium concentration and has a major role in various signaling pathways. Its role in regulating homeostasis, developmental processes, and different disease progression has already been reported. The dysregulated Ca<sup>2+</sup>/calcineurin/NFAT1-4 pathway is observed in Autoimmune disorders and hence the use of Calcineurin inhibitors like Cyclosporin A (CsA) and Tacrolimus (FK506) is widely done in such cases. Recent studies indicate the uncontrolled overexpression of the Calcineurin protein in the pathophysiological pathway of neurodegenerative diseases. The <i>in vitro</i> and animal model studies with standard calcineurin inhibitors (CnIs), which are widely labeled as immunosuppressant drugs, have shown a significant reduction of neurodegeneration in respective models. These results compel the identification of novel calcineurin inhibitors against neurodegenerative diseases. With this scenario, the present work focuses on the computer-aided identification of novel CnIs <i>via</i> ligand-based 3-D pharmacophore modelling. Known CnIs, CsA, and FK506, were used to build the pharmacophore models which were validated and screened against external databases to retrieve possible hits. Docking investigations, pharmacokinetic properties, and molecular dynamics simulations along with toxicity predictions were performed on the hits that were obtained. According to the study, a total of 5 molecules ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of −9.7 to −9.0 Kcal/mol with 1MF8 (PDB). The stability of interactions of these molecules was further validated <i>via</i> Molecular dynamics simulation studies to confirm these to be the potential calcineurin-inhibiting molecules. HIGHLIGHTSCalcineurin inhibitors can be a novel therapeutic candidate against neurodegenerative diseases.The identification of novel Calcineurin inhibitors was done in silico using ligand-based 3-D pharmacophore modelling using Ligand Scout Essential 4.4. software.The model could identify 440 hits from various external databases like PubChem (2432 molecules), ChemSpider, MayBridge, DrugBank, and e-Drug 3D by Cheminformatic Tools and Databases for Pharmacology.Out of which 5 molecules: ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of –9.7 to –9.0 Kcal/mol with 1MF8 (PDB) which were further confirmed to be the best CnI candidates via Molecular dynamics simulation studies. Calcineurin inhibitors can be a novel therapeutic candidate against neurodegenerative diseases. The identification of novel Calcineurin inhibitors was done in silico using ligand-based 3-D pharmacophore modelling using Ligand Scout Essential 4.4. software. The model could identify 440 hits from various external databases like PubChem (2432 molecules), ChemSpider, MayBridge, DrugBank, and e-Drug 3D by Cheminformatic Tools and Databases for Pharmacology. Out of which 5 molecules: ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of –9.7 to –9.0 Kcal/mol with 1MF8 (PDB) which were further confirmed to be the best CnI candidates via Molecular dynamics simulation studies. Communicated by Ramaswamy H. Sarma