HIV-derived peptide mimics

Moebius, Kalle; Eichler, Jutta

doi:10.1016/j.ddtec.2009.09.001

Cited by 6 publications

(5 citation statements)

References 54 publications

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“…Peptides mimicking the binding sites of the involved proteins are not only valuable tools to explore the respective interactions at the molecular level, but also candidates for therapeutic intervention through specific inhibition of these interactions (5). HIV-1 enters its host cell by using its envelope (Env), which is composed of the two glycoproteins gp120 and gp41.…”

Section: Introductionmentioning

confidence: 99%

Mimicking Protein–Protein Interactions through Peptide–Peptide Interactions: HIV-1 gp120 and CXCR4

Gross¹,

Möbius²,

Haußner³

et al. 2013

Front. Immunol.

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We have recently designed a soluble synthetic peptide that functionally mimics the HIV-1 coreceptor CXCR4, which is a chemokine receptor that belongs to the family of seven-transmembrane GPCRs. This CXCR4 mimetic peptide, termed CX4-M1, presents the three extracellular loops (ECLs) of the receptor. In binding assays involving recombinant proteins, as well as in cellular infection assays, CX4-M1 was found to selectively recognize gp120 from HIV-1 strains that use CXCR4 for cell entry (X4 tropic HIV-1). Furthermore, anti-HIV-1 antibodies modulate this interaction in a molecular mechanism related to that of their impact on the gp120–CXCR4 interaction. We could now show that the selectivity of CX4-M1 pertains not only to gp120 from X4 tropic HIV-1, but also to synthetic peptides presenting the V3 loops of these gp120 proteins. The V3 loop is thought to be an essential part of the coreceptor binding site of gp120 that contacts the second ECL of the coreceptor. We were able to experimentally confirm this notion in binding assays using substitution analogs of CX4-M1 and the V3 loop peptides, respectively, as well as in cellular infection assays. These results indicate that interactions of the HIV-1 Env with coreceptors can be mimicked by synthetic peptides, which may be useful to explore these interactions at the molecular level in more detail.

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Section: Introductionmentioning

confidence: 99%

Mimicking Protein–Protein Interactions through Peptide–Peptide Interactions: HIV-1 gp120 and CXCR4

Gross¹,

Möbius²,

Haußner³

et al. 2013

Front. Immunol.

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“…For example, they contain a positive charge for binding to Asp 189 in the S1 pocket. [36,37] We tested the 20 top-ranked compounds (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) for trypsin inhibition in an in vitro assay at a concentration of 100 lM (Supporting Information, Fig. S4 and Table S6).…”

Section: Epitope Screeningmentioning

confidence: 99%

“…[1] They represent the basis of diverse macromolecular recognition events and signal transduction such as various kinase cascades [2,3] and virus entry into cells. [4] PPI up-and down-regulation can result in severe medical conditions as shown for the interaction of p53 and MDM2, where misregulation of the MDM2 protein level results in tumor formation. [5] With an estimated number of 5000-10,000 functionally relevant PPIs in the human organism, it is apparent that PPI inhibition bears great potential for rational drug discovery.…”

Section: Introductionmentioning

confidence: 99%

Virtual screening for compounds that mimic protein–protein interface epitopes

et al. 2011

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Modulation of protein-protein interactions (PPI) has emerged as a new concept in rational drug design. Here, we present a computational protocol for identifying potential PPI inhibitors. Relevant regions of interfaces (epitopes) are predicted for three-dimensional protein models and serve as queries for virtual compound screening. We present a computational screening protocol that incorporates two different pharmacophore models. One model is based on the mathematical concept of autocorrelation vectors and the other utilizes fuzzy labeled graphs. In a proof-of-concept study, we were able to identify serine protease inhibitors using a predicted trypsin epitope as query. Our virtual screening framework may be suited for rapid identification of PPI inhibitors and suggesting bioactive tool compounds.

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“…Entry and replication of human immunodeficiency virus type 1 (HIV‐1), the causative agent of the acquired immunodeficiency syndrome (AIDS), into its host cell is mediated by numerous interactions between viral and host cell proteins 1. Peptides mimicking the binding sites of the involved proteins are not only valuable tools to explore the respective interactions at the molecular level but also candidates for therapeutic intervention through specific inhibition of these interactions 2. HIV‐1 enters its host cell by using its envelope (Env), which is composed of the two glycoproteins gp120 and gp41.…”

Section: Introductionmentioning

confidence: 99%

Lipid bilayer arrays: Cyclically formed and measured

Lü

Kocharyan

Schmidt

2013

Biotechnology Journal

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Artificial lipid bilayers have many uses. They are well established for scientific studies of reconstituted ion channels, used to host engineered pore proteins for sensing, and can potentially be applied in DNA sequencing. Droplet bilayers have significant technological potential for enabling many of these applications due to their compatibility with automation and array platforms. To further develop this potential, we have simplified the formation and electrical measurement of droplet bilayers using an apparatus that only requires fluid dispensation. We achieved simultaneous bilayer formation and measurement over a 32-element array with ~80% yield and no operator input following fluid addition. Cycling these arrays resulted in the formation and measurement of 96 out of 120 possible bilayers in 80 minutes, a sustainable rate that could significantly increase with automation and greater parallelization. This turn-key, high-yield approach to making artificial lipid bilayers requires no training, making the capability of creating and measuring lipid bilayers and ion channels accessible to a much wider audience. In addition, this approach is low-cost, parallelizable, and automatable, allowing high-throughput studies of ion channels and pore proteins in lipid bilayers for sensing or screening applications.

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HIV-derived peptide mimics

Cited by 6 publications

References 54 publications

Mimicking Protein–Protein Interactions through Peptide–Peptide Interactions: HIV-1 gp120 and CXCR4

Mimicking Protein–Protein Interactions through Peptide–Peptide Interactions: HIV-1 gp120 and CXCR4

Virtual screening for compounds that mimic protein–protein interface epitopes

Lipid bilayer arrays: Cyclically formed and measured

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