Combined administration of a small-molecule inhibitor of TRAF6 and Docetaxel reduces breast cancer skeletal metastasis and osteolysis

Bishop, Ryan T.; Marino, Silvia; Carrasco, Giovana; Li, Boya; Allen, Richard; Sparatore, Anna; Ottewell, Penelope D.; Mollat, Patrick; Sims, Andrew H.; Capulli, Mattia; Wang, Ning; Idris, Aymen I.

doi:10.1016/j.canlet.2020.05.021

Cited by 22 publications

(24 citation statements)

References 93 publications

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“…We focused on the TRAF domain, which binds to the cytoplasmic tails of cell‐surface receptors. Inhibiting the protein interactions of this domain has been associated with decreased osteoclastogenesis, 37 increased insulin sensitivity, 38 and reduced breast cancer metastasis 39 . Structures of TRAF6 in complex with natural peptide ligands have revealed a conserved binding mode 40 …”

Section: Resultsmentioning

confidence: 99%

“…Inhibiting the protein interactions of this domain has been associated with decreased osteoclastogenesis, 37 increased insulin sensitivity, 38 and reduced breast cancer metastasis. 39 Structures of TRAF6 in complex with natural peptide ligands have revealed a conserved binding mode. 40 To obtain a structural model of TRAF6 alone, we removed the peptide ligand from the TRAF6-CD40 structure (PDB ID: 1LB6) and targeted a single, monomeric domain.…”

Section: Designing Peptide Binders Of Traf6mentioning

confidence: 99%

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Tertiary motifs as building blocks for the design of protein‐binding peptides

et al. 2022

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Despite advances in protein engineering, the de novo design of small proteins or peptides that bind to a desired target remains a difficult task. Most computational methods search for binder structures in a library of candidate scaffolds, which can lead to designs with poor target complementarity and low success rates. Instead of choosing from pre‐defined scaffolds, we propose that custom peptide structures can be constructed to complement a target surface. Our method mines tertiary motifs (TERMs) from known structures to identify surface‐complementing fragments or “seeds.” We combine seeds that satisfy geometric overlap criteria to generate peptide backbones and score the backbones to identify the most likely binding structures. We found that TERM‐based seeds can describe known binding structures with high resolution: the vast majority of peptide binders from 486 peptide‐protein complexes can be covered by seeds generated from single‐chain structures. Furthermore, we demonstrate that known peptide structures can be reconstructed with high accuracy from peptide‐covering seeds. As a proof of concept, we used our method to design 100 peptide binders of TRAF6, seven of which were predicted by Rosetta to form higher‐quality interfaces than a native binder. The designed peptides interact with distinct sites on TRAF6, including the native peptide‐binding site. These results demonstrate that known peptide‐binding structures can be constructed from TERMs in single‐chain structures and suggest that TERM information can be applied to efficiently design novel target‐complementing binders.

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Section: Resultsmentioning

confidence: 99%

Section: Designing Peptide Binders Of Traf6mentioning

confidence: 99%

Tertiary motifs as building blocks for the design of protein‐binding peptides

et al. 2022

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“…While little is known regarding the association of TRAF6 in breast cancer, it was found over-expressed in triple negative BC and it expression correlates with metastatic outcome [53]. In addition, a recent study reported that a molecule, an inhibitor of TRAF6, decreases metastasis in mouse BC models [54].…”

Section: Discussionmentioning

confidence: 99%

Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

Cava

Sabetian

Castiglioni

2021

Entropy

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The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

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“…To increase the frequency of bone metastases and reduce the need for intra-cardiac injections, bone seeking sub-lines of MDA-MB-231 cells have been produced via repeated in vivo passaging through mouse bones [7,15,19,28] ; MDA-MB-231-B02, MDA-MB-231-B and MDA-MB-231-bone cells form tumours in up to 90% of mice following injection into the caudal artery, whereas MDA-IV cells form tumours in 80%-90% of mice after injection into the lateral tail vein [7,15,19,[28][29][30][31] . Via a similar mechanism, of in vivo passaging, researchers have also produced a bone seeking MCF7 breast cancer cell line that predominantly forms osteolytic lesions after 10-12 weeks [26] .…”

Section: Immortalised Breast Cancer Cell Linesmentioning

confidence: 99%