Skip to content
2000
Volume 16, Issue 3
  • ISSN: 1573-4099
  • E-ISSN: 1875-6697

Abstract

Introduction: Rheumatoid Arthritis [RA] is an autoimmune disease that can cause chronic inflammation of the joints. Human DiHydroOrotate DeHydrogenase [DHODH] is a clinically validated drug target for the treatment of Rheumatoid Arthritis. DHODH inhibition results in beneficial immunosuppressant and anti-proliferative effects. Materials and Methods: Leflunomide [LEF] and Brequinar Sodium [BREQ], drugs used in the treatment of RA, suppresses the immune cells responsible for inflammation but has several side-effects, most predominant being symptomatic liver damage and toxicity. An existing scaffold based on structural analogies with LEF and BREQ was used to screen out potent inhibitors of DHODH, in ZINC Database using 2D binary fingerprint. 10 structures similar to the scaffold were shortlisted due to their Tanimoto similarity coefficient. Selected structures were docked using the tools AutoDock, Ligand fit and iGEMDOCK with target human DHODH. High scoring compounds having similar interactions as that of scaffold were checked to evaluate their Drug-Likeliness. Results: The five shortlisted compounds were then subjected to Molecular Dynamics Simulation studies for 50ns using GROMACS. Measures of structural similarity based on 2D Fingerprint Screening and Molecular Dynamics Simulation studies can suggest good leads for drug designing. The novelty of this study is that the workflow used here yields the same results that are at par with the experimental data. Conclusion: This suggests the use of the 2D fingerprint similarity search in various databases, followed by multiple docking algorithms and dynamics as a workflow that will lead to finding novel compounds that a structurally and functionally similar to LEF and BREQ.

Loading

Article metrics loading...

/content/journals/cad/10.2174/1573409915666190528114703
2020-06-01
2025-04-23
Loading full text...

Full text loading...

/content/journals/cad/10.2174/1573409915666190528114703
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error
Please enter a valid_number test