<i>In silico</i>-guided identification of potential inhibitors against β<sub>2</sub>m aggregation in dialysis-related amyloidosis
Creators: name: Simranjeet Singh Narang
name: Suniba Shuaib
name: Goyal, Deepti
name: Bhupesh Goyal
Publisher: name: Taylor & Francis
Year: 2019
Subjects: subject: Biophysics
subject: Biochemistry
subject: 29999 Physical Sciences not elsewhere classified
subject: FOS: Physical sciences
subject: FOS: Physical sciences
subject: Genetics
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: Pharmacology
subject: Biotechnology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: Cancer

description: In dialysis-related amyloidosis (DRA), misfolding of β<sub>2</sub>-microglobulin (β<sub>2</sub>m) leads to amyloid fibril deposition mainly in the skeletal joints seriously affecting their functionality. The identification and characterization of small-molecules that bind β<sub>2</sub>m 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 β<sub>2</sub>m 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 (C<sub>1</sub>), ChEMBL360190 (C<sub>2</sub>) and ZINC3091144 (C<sub>3</sub>), displaying excellent binding free energies of –51.29, –36.51 and –34.36 kcal/mol, respectively, with β<sub>2</sub>m were subjected to MD simulations to get insights into the binding locations, key interactions and structural stability of the β<sub>2</sub>m-ligand complexes. The hydrogen bond analysis highlight higher structural stability and reduced flexibility of the loop regions of β<sub>2</sub>m in presence of C<sub>1</sub>, C<sub>2</sub> and C<sub>3</sub>. The integrated computational approach employed in the present study identify promising lead compounds against β<sub>2</sub>m aggregation in DRA. Abbreviationsβ<sub>2</sub>mβ<sub>2</sub>-microglobulin3Dthree dimensionalADAlzheimer’s diseaseADTAutoDock ToolsDRADialysis-related amyloidosisDSSPdictionary of secondary structure of proteinsFELfree energy landscapeGROMACSGROningen MAchine for Chemical SimulationsLGALamarckian Genetic AlgorithmLINCSLINear Constraint SolverMCmain chainMDmolecular dynamicsMHC–Imajor histocompatibility complex class IMM–PBSAmolecular mechanics Poisson–Boltzmann surface areaPMEnanometer (nm); particle mesh ewaldPCAprincipal component analysisPDBprotein data bank<i>R</i><sub>g</sub>radius–of–gyrationRSVrifamycin SVRMSDroot–mean–square deviationRMSFroot–mean–square fluctuationSCside chainSPCsimple point chargeSASASolvent accessible surface areaVMDvisual molecular dynamics β<sub>2</sub>-microglobulin three dimensional Alzheimer’s disease AutoDock Tools Dialysis-related amyloidosis dictionary of secondary structure of proteins free energy landscape GROningen MAchine for Chemical Simulations Lamarckian Genetic Algorithm LINear Constraint Solver main chain molecular dynamics major histocompatibility complex class I molecular mechanics Poisson–Boltzmann surface area nanometer (nm); particle mesh ewald principal component analysis protein data bank radius–of–gyration rifamycin SV root–mean–square deviation root–mean–square fluctuation side chain simple point charge Solvent accessible surface area visual molecular dynamics Communicated by Ramaswamy H. Sarma A ligand-based virtual screening approach and molecular dynamics (MD) simulations were employed to explore potent small-molecule inhibitors against β<sub>2</sub>–microglobulin (β<sub>2</sub>m) 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 (C<sub>1</sub>), ChEMBL360190 (C<sub>2</sub>) and ZINC3091144 (C<sub>3</sub>), displaying excellent binding free energies of –51.29, –36.51 and –34.36 kcal/mol, respectively, with β<sub>2</sub>m were subjected to MD simulations to get insights into the binding locations, key interactions and structural stability of the β<sub>2</sub>m-ligand complexes. The integrated computational approach employed in the present study identify promising lead compounds against β<sub>2</sub>m aggregation in DRA.