Identification of selective Lyn inhibitors from the chemical databases through integrated molecular modelling approaches. Issue 1 (2nd January 2021)
- Record Type:
- Journal Article
- Title:
- Identification of selective Lyn inhibitors from the chemical databases through integrated molecular modelling approaches. Issue 1 (2nd January 2021)
- Main Title:
- Identification of selective Lyn inhibitors from the chemical databases through integrated molecular modelling approaches
- Authors:
- Shetve, V.V.
Bhowmick, S.
Alissa, S.A.
Alothman, Z.A.
Wabaidu, S.M.
Asmary, F.A.
Alhajri, H.M
Islam, M.A. - Abstract:
- ABSTRACT: In the current study, the Asinex and ChEBI databases were virtually screened for the identification of potential Lyn protein inhibitors. Therefore, a multi-steps molecular docking study was carried out using the VSW utility tool embedded in Maestro user interface of the Schrödinger suite. On initial screening, molecules having a higher XP-docking score and binding free energy compared to Staurosporin were considered for further assessment. Based on in silico pharmacokinetic analysis and a common-feature pharmacophore mapping model developed from the Staurosporin, four molecules were proposed as promising Lyn inhibitors. The binding interactions of all proposed Lyn inhibitors revealed strong ligand efficiency in terms of energy score obtained in molecular modelling analyses. Furthermore, the dynamic behaviour of each molecule in association with the Lyn protein-bound state was assessed through an all-atoms molecular dynamics (MD) simulation study. MD simulation analyses were confirmed with notable intermolecular interactions and consistent stability for the Lyn protein-ligand complexes throughout the simulation. High negative binding free energy of identified four compounds calculated through MM-PBSA approach demonstrated a strong binding affinity towards the Lyn protein. Hence, the proposed compounds might be taken forward as potential next-generation Lyn kinase inhibitors for managing numerous Lyn associated diseases or health complications after experimentalABSTRACT: In the current study, the Asinex and ChEBI databases were virtually screened for the identification of potential Lyn protein inhibitors. Therefore, a multi-steps molecular docking study was carried out using the VSW utility tool embedded in Maestro user interface of the Schrödinger suite. On initial screening, molecules having a higher XP-docking score and binding free energy compared to Staurosporin were considered for further assessment. Based on in silico pharmacokinetic analysis and a common-feature pharmacophore mapping model developed from the Staurosporin, four molecules were proposed as promising Lyn inhibitors. The binding interactions of all proposed Lyn inhibitors revealed strong ligand efficiency in terms of energy score obtained in molecular modelling analyses. Furthermore, the dynamic behaviour of each molecule in association with the Lyn protein-bound state was assessed through an all-atoms molecular dynamics (MD) simulation study. MD simulation analyses were confirmed with notable intermolecular interactions and consistent stability for the Lyn protein-ligand complexes throughout the simulation. High negative binding free energy of identified four compounds calculated through MM-PBSA approach demonstrated a strong binding affinity towards the Lyn protein. Hence, the proposed compounds might be taken forward as potential next-generation Lyn kinase inhibitors for managing numerous Lyn associated diseases or health complications after experimental validation. … (more)
- Is Part Of:
- SAR and QSAR in environmental research. Volume 32:Issue 1(2021)
- Journal:
- SAR and QSAR in environmental research
- Issue:
- Volume 32:Issue 1(2021)
- Issue Display:
- Volume 32, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 32
- Issue:
- 1
- Issue Sort Value:
- 2021-0032-0001-0000
- Page Start:
- 1
- Page End:
- 27
- Publication Date:
- 2021-01-02
- Subjects:
- Lyn protein -- virtual screening -- molecular docking -- molecular dynamics -- MM-PBSA
Structure-activity relationships (Biochemistry) -- Periodicals
QSAR (Biochemistry) -- Periodicals
572.4 - Journal URLs:
- http://www.tandfonline.com/toc/gsar20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/1062936X.2020.1799433 ↗
- Languages:
- English
- ISSNs:
- 1062-936X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8075.965500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24344.xml