title: Structure prediction of LDLR-HNP1 complex based on docking enhanced by LDLR binding 3D motif.
abstract: Human antimicrobial peptides (AMPs), including defensins, have come under intense scrutiny owing to their key multiple roles as antimicrobial agents. Not only do they display direct action on microbes, but also recently they have been shown to interact with the immune system to increase antimicrobial activity. Unfortunately, since mechanisms involved in the binding of AMPs to mammalian cells are largely unknown, their potential as novel anti-infective agents cannot be exploited yet. Following the reported interaction of Human Neutrophil Peptide 1 dimer (HNP1) with a low density lipoprotein receptor (LDLR), a computational study was conducted to discover their putative mode of interaction. State-of-the-art docking software produced a set of LDLR-HNP1 complex 3D models. Creation of a 3D motif capturing atomic interactions of the LDLR binding interface allowed selection of the most plausible configurations. Eventually, only two models were in agreement with the literature. Binding energy estimations revealed that only one of them is particularly stable, but also interaction with LDLR weakens significantly bonds within the HNP1 dimer. This may be significant since it suggests a mechanism for internalisation of HNP1 in mammalian cells. In addition to a novel approach for complex structure prediction, this study proposes a 3D model of the LDLR-HNP1 complex which highlights the key residues which are involved in the interactions. The putative identification of the receptor binding mechanism should inform the future design of synthetic HNPs to afford maximum internalisation, which could lead to novel anti-infective drugs.
authors.affiliation: Faculty of Science, Engineering and Computing, Kingston University, Kingston-upon-Thames, KT1 2EE, UK. r.esmaielbeiki@kingston.ac.uk
authors.forename: Reyhaneh
authors.initials: R
authors.lastname: Esmaielbeiki
authors.forename: Declan P
authors.initials: DP
authors.lastname: Naughton
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Nebel
mesh_terms: D000890:Anti-Infective Agents; D001665:Binding Sites; D003198:Computer Simulation; D006801:Humans; D054730:Protein Interaction Domains and Motifs; D055503:Protein Multimerization; D017434:Protein Structure, Tertiary; D011973:Receptors, LDL / Q000737:chemistry* / Q000378:metabolism; D012984:Software; D023084:alpha-Defensins / Q000737:chemistry* / Q000378:metabolism
chemical_list: D000890:Anti-Infective Agents; C573412:LDLR protein, human; D011973:Receptors, LDL; D023084:alpha-Defensins; C406413:human neutrophil peptide 1