Identification of anti-TNFα peptides with consensus sequence

Zhang, Jie; Li, Zheng; An, Zhen; Gao, Bo; Liu, Nongle; Wang, Fang; Dong, Jing; Xin, Zhong-Tao; Shao, Ningsheng; Wang, Huixin; Xue, Yongbiao

doi:10.1016/j.bbrc.2003.09.141

Cited by 12 publications

(5 citation statements)

References 29 publications

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“…TNF-α is a high-value target for which several antibody and small molecule therapeutics have been developed [26], [27]. TNF-α affinity reagents have been isolated by other procedures [28]–[30], and this is useful for comparison. If successful, a ligand for TNF-α could be used as an affinity reagent by itself or as a component of a multivalent ligand [31].…”

Section: Resultsmentioning

confidence: 99%

“…General applicability to several protein targets has been shown, and binding dissociation constant (K d ) enhancements of nearly 250-fold were achieved with this algorithm (Table S3 in File S1). In one specific example, the TNF4-opt peptide developed with this algorithm is one of the highest affinity TNF-α binding peptides/small-molecules reported to-date [28]–[30], [41].…”

Section: Discussionmentioning

confidence: 99%

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Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

et al. 2010

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BackgroundThere is a significant need for affinity reagents with high target affinity/specificity that can be developed rapidly and inexpensively. Existing affinity reagent development approaches, including protein mutagenesis, directed evolution, and fragment-based design utilize large libraries and/or require structural information thereby adding time and expense. Until now, no systematic approach to affinity reagent development existed that could produce nanomolar affinity from small chemically synthesized peptide libraries without the aid of structural information.Methodology/Principal FindingsBased on the principle of additivity, we have developed an algorithm for generating high affinity peptide ligands. In this algorithm, point-variations in a lead sequence are screened and combined in a systematic manner to achieve additive binding energies. To demonstrate this approach, low-affinity lead peptides for multiple protein targets were identified from sparse random sequence space and optimized to high affinity in just two chemical steps. In one example, a TNF-α binding peptide with Kd = 90 nM and high target specificity was generated. The changes in binding energy associated with each variation were generally additive upon combining variations, validating the basis of the algorithm. Interestingly, cooperativity between point-variations was not observed, and in a few specific cases, combinations were less than energetically additive.Conclusions/SignificanceBy using this additivity algorithm, peptide ligands with high affinity for protein targets were generated. With this algorithm, one of the highest affinity TNF-α binding peptides reported to date was produced. Most importantly, high affinity was achieved from small, chemically-synthesized libraries without the need for structural information at any time during the process. This is significantly different than protein mutagenesis, directed evolution, or fragment-based design approaches, which rely on large libraries and/or structural guidance. With this algorithm, high affinity/specificity peptide ligands can be developed rapidly, inexpensively, and in an entirely chemical manner.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

et al. 2010

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“…The peptides isolated in these selections have been subjected to a variety of analyses. In biological systems, selections against a particular target often identify a consensus, or a short sequence that can direct binding to the target regardless of where it is in the selected peptide. − Sequencing of the peptides selected by inorganic materials and nanostructures has thus far revealed what appear to be hints at a few consensus sequences for a particular target. ,,− However, in some publications it is not clear whether the authors have discovered an actual consensus sequence or whether a single bacteriophage has been isolated multiple times. Other selections seem to isolate peptides with unrelated sequences. , The absence of clear consensus sequences is surprising and may indicate that there is a multitude of mechanisms by which peptides bind to these targets.…”

Section: 4 Binding To Inorganic Materials and Nanostructuresmentioning

confidence: 99%

Filamentous Phage Display in the New Millennium

2005

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“…In particular, mRNA display and ribosome display, using a cell-free translation system, have the advantage that the diversity of the library is not limited by T. Kobayashi Á M. Kakui Á T. Shibui Á Y. Kitano ZoeGene Corporation, 1000 Kamoshida-cho, Aoba-ku, Yokohama, Kanagawa 227-8502, Japan the transformation efficiency of bacterial cells. So far, many functional short peptides, binding to EPOR [14], TNFa [15,16], ErbB-2 [17,18], KDR [19], and IL-6R [20], have been obtained mainly by phage display. Thus, it could be possible to select these functional peptides using cell-free translation-based display technology.…”

Section: Introductionmentioning

confidence: 99%

In Vitro Selection of a Peptide Inhibitor of Human IL-6 Using mRNA Display

et al. 2010

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Interleukin-6 (IL-6) plays a crucial role in malignant diseases, such as rheumatoid arthritis, Castleman disease, and multiple myeloma, and as such, is an attractive therapeutic target. Here, the authors isolated a novel IL-6 inhibitor peptide by in vitro selection using mRNA display. The authors first used a random-primed human cDNA library to isolate IL-6-binding peptides. After four rounds of selection, a 19-amino acid peptide named CA11 was selected and confirmed to specifically interact with IL-6. The authors then performed an alanine scan analysis of CA11 and determined the amino acid residues necessary to interact with IL-6. Next, the authors constructed a CA11-based partially randomized library and after ten more rounds of selection, isolated several groups of peptides. The most frequently occurring sequence, RA07, bound to IL-6 with 3 to 4-fold higher affinity than CA11. Furthermore, RA07 inhibited IL-6-dependent KT-3 cell proliferation in a dose-dependent manner. ELISAs revealed that RA07 could not inhibit IL-6 from binding to the IL-6 receptor (IL-6R), but could inhibit the IL-6/IL-6 complex binding to gp130.

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Identification of anti-TNFα peptides with consensus sequence

Cited by 12 publications

References 29 publications

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

Thermodynamic Additivity of Sequence Variations: An Algorithm for Creating High Affinity Peptides Without Large Libraries or Structural Information

Filamentous Phage Display in the New Millennium

In Vitro Selection of a Peptide Inhibitor of Human IL-6 Using mRNA Display

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