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Molecular modeling to investigate the binding of Congo red toward GNNQQNY protofibril and in silico virtual screening for the identification of new aggregation inhibitors.

Authors :
Zhao JH
Liu HL
Elumalai P
Chen WH
Men LC
Liu KT
Source :
Journal of molecular modeling [J Mol Model] 2013 Jan; Vol. 19 (1), pp. 151-62. Date of Electronic Publication: 2012 Jul 27.
Publication Year :
2013

Abstract

Understanding the nature of the recognition between amyloid protofibrils and dye molecules at the molecular level is essential to improving instructive guides for designing novel molecular probes or new inhibitors. However, the atomic details of the binding between dyes and amyloid fibrils are still not fully understood. In this study, molecular docking, consensus scoring, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) analyses were integrated to investigate the binding between Congo red (CR) and the GNNQQNY protofibril from yeast prion protein Sup35 and to further evaluate their binding stabilities and affinities. Our results reveal that there are four CR binding sites located on GNNQQNY protofibril surface. These four CR binding sites adopt dual binding modes by which CR binding with its long axis parallel and perpendicular to the long axis of the protofibril. In addition, CR was also found to bind to the edge of the protofibril via hydrophobic/aromatic and hydrogen-bonding interactions, which is inferred as the possible inhibition mechanism to prevent the elongation of the protofibril from the addition of incoming peptides. Virtual screening from National Cancer Institute (NCI) database obtained three hit compounds with higher binding affinity than CR to the edge of the protofibril due to the fact that the central parts of these compounds are able to form additional hydrogen bonds with the protofibril. The results of the study could be useful for the development of new molecular probes or inhibitors for clinical applications.

Details

Language :
English
ISSN :
0948-5023
Volume :
19
Issue :
1
Database :
MEDLINE
Journal :
Journal of molecular modeling
Publication Type :
Academic Journal
Accession number :
22836831
Full Text :
https://doi.org/10.1007/s00894-012-1532-y