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Sökning: WFRF:(Hu XC)

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  • Ding, HT, et al. (författare)
  • Parallel cloning, expression, purification and crystallization of human proteins for structural genomics
  • 2002
  • Ingår i: Acta Crystallographica. Section D: Biological Crystallography. - 1399-0047. ; 58, s. 2102-2108
  • Tidskriftsartikel (refereegranskat)abstract
    • 54 human genes were selected as test targets for parallel cloning, expression, purification and crystallization. Proteins from these genes were selected to have a molecular weight of between 14 and 50 kDa, not to have a high percentage of hydrophobic residues (i.e. more likely to be soluble) and to have no known crystal structures and were not known to be subunits of heterocomplexes. Four proteins containing transmembrane regions were selected for comparative tests. To date, 44 expression clones have been constructed with the Gateway(TM) cloning system (Invitrogen, The Netherlands). Of these, 35 clones were expressed as recombinant proteins in Escherichia coli strain BL21 (DE3)-pLysS, of which 12 were soluble and four have been purified to homogeneity. Crystallization conditions were screened for the purified proteins in 96-well plates under oil. After further refinement with the same device or by the hanging-drop method, crystals were grown, with needle, plate and prism shapes. A 2.12 Angstrom data set was collected for protein NCC27. The results provide insights into the high-throughput target selection, cloning, expression and crystallization of human genomic proteins.
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  • Menden, MP, et al. (författare)
  • Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
  • 2019
  • Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
  • Tidskriftsartikel (refereegranskat)abstract
    • The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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