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Research Articles

In silico-guided identification of potential inhibitors against β2m aggregation in dialysis-related amyloidosis

, , &
Pages 3927-3941 | Received 11 Jun 2019, Accepted 10 Sep 2019, Published online: 27 Sep 2019
 

Abstract

In dialysis-related amyloidosis (DRA), misfolding of β2-microglobulin (β2m) leads to amyloid fibril deposition mainly in the skeletal joints seriously affecting their functionality. The identification and characterization of small-molecules that bind β2m and possibly inhibit its aggregation remain unexplored. In the present study, a ligand-based virtual screening approach and molecular dynamics (MD) simulations were employed to explore potent small-molecule inhibitors against β2m aggregation. The compounds were screened from various small-molecule databases by applying ligand-based virtual screening with rifamycin SV (RSV) as a reference compound. The molecular docking analysis was performed to filter out lead compounds with a higher binding affinity than RSV from a library of ∼800 compounds. Three compounds, ChEBI68321 (C1), ChEMBL360190 (C2) and ZINC3091144 (C3), displaying excellent binding free energies of –51.29, –36.51 and –34.36 kcal/mol, respectively, with β2m were subjected to MD simulations to get insights into the binding locations, key interactions and structural stability of the β2m-ligand complexes. The hydrogen bond analysis highlight higher structural stability and reduced flexibility of the loop regions of β2m in presence of C1, C2 and C3. The integrated computational approach employed in the present study identify promising lead compounds against β2m aggregation in DRA.

Abbreviations
β2m=

β2-microglobulin

3D=

three dimensional

AD=

Alzheimer’s disease

ADT=

AutoDock Tools

DRA=

Dialysis-related amyloidosis

DSSP=

dictionary of secondary structure of proteins

FEL=

free energy landscape

GROMACS=

GROningen MAchine for Chemical Simulations

LGA=

Lamarckian Genetic Algorithm

LINCS=

LINear Constraint Solver

MC=

main chain

MD=

molecular dynamics

MHC–I=

major histocompatibility complex class I

MM–PBSA=

molecular mechanics Poisson–Boltzmann surface area

PME=

nanometer (nm); particle mesh ewald

PCA=

principal component analysis

PDB=

protein data bank

Rg=

radius–of–gyration

RSV=

rifamycin SV

RMSD=

root–mean–square deviation

RMSF=

root–mean–square fluctuation

SC=

side chain

SPC=

simple point charge

SASA=

Solvent accessible surface area

VMD=

visual molecular dynamics

Communicated by Ramaswamy H. Sarma

Graphical abstract

A ligand-based virtual screening approach and molecular dynamics (MD) simulations were employed to explore potent small-molecule inhibitors against β2–microglobulin (β2m) aggregation. The compounds were screened from various small-molecule databases by applying ligand-based virtual screening with rifamycin SV (RSV) as a reference compound. The molecular docking analysis was performed to filter out lead compounds with a higher binding affinity than RSV from a library of ∼800 compounds. Three compounds, ChEBI68321 (C1), ChEMBL360190 (C2) and ZINC3091144 (C3), displaying excellent binding free energies of –51.29, –36.51 and –34.36 kcal/mol, respectively, with β2m were subjected to MD simulations to get insights into the binding locations, key interactions and structural stability of the β2m-ligand complexes. The integrated computational approach employed in the present study identify promising lead compounds against β2m aggregation in DRA.

Acknowledgements

The authors acknowledge C-DAC, Pune for providing the C-DAC's supercomputing resources (PARAM Yuva-II) for the computational facilities. The authors acknowledge School of Chemistry & Biochemistry, Thapar Institute of Engineering & Technology, Patiala, Punjab and Department of Chemistry, Sri Guru Granth Sahib World University, Fatehgarh Sahib, Punjab, India for providing the research facilities.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Simranjeet Singh Narang acknowledges University Grants Commission (UGC) and Ministry of Minority Affairs, Government of India for the award of Maulana Azad National Fellowship (MANF) (Code No: MANF-2014-15-SIK-HIM-32950).

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