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1. |
10th BRAT symposium: Abstracts |
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Journal of Molecular Recognition,
Volume 6,
Issue 1,
1993,
Page 1-22
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ISSN:0952-3499
DOI:10.1002/jmr.300060102
出版商:John Wiley&Sons, Ltd.
年代:1993
数据来源: WILEY
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2. |
Chiral separation using molecularly imprinted heteroaromatic polymers |
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Journal of Molecular Recognition,
Volume 6,
Issue 1,
1993,
Page 25-29
Maria Kempe,
Klaus Mosbach,
Lutz Fischer,
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PDF (490KB)
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摘要:
AbstractNovel molecularly imprinted polymer systems utilizing 4‐vinylpyridine and 1‐vinylimidazole as functional monomers have been developed for enantioselective recognition of carboxylic and N‐protected amino acids. Non‐covalent interactions between the functional monomers and the template molecules were the source of the subsequent recognition sites in the resultant polymers. The capacity of the polymers for molecular recognition was investigated by using them as stationary phases in the HPLC mode. Polymers prepared with 4‐vinylpyridine were found to be more efficient in racemic resolution than those prepared with 1‐vinylimidazole. When applying a racemic mixture of the template molecule, the polymers showed highest affinity for the enantiomer used as template. Imprints of a racemic template molecule, as expected, did not exhibit enantioselectivity. The optimal molar ratio of 4‐vinylpyridine to the template Cbz‐L‐Asp‐OH in the polymerization mixture was determined to be 12:1. In addition to enantioselectivity, the investigated polymers demonstrated ‘ligand selectivity’ e.g., a Cbz‐L‐Asp‐OH‐imprinted polymer was able to separate Cbz‐D,L‐Asp‐OH, but
ISSN:0952-3499
DOI:10.1002/jmr.300060103
出版商:John Wiley&Sons, Ltd.
年代:1993
数据来源: WILEY
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3. |
Design of novel cationic ligands for the purification of trypsin‐like proteases by affinity chromatography |
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Journal of Molecular Recognition,
Volume 6,
Issue 1,
1993,
Page 31-40
Nicolas P. Burton,
Christopher R. Lowe,
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摘要:
AbstractA number on new cationic ligands have been designed and synthesized for the selective resolution an purification of the trypszin‐like proteases. A series of ligands based on 4‐[2′‐methyl‐4′‐(2″,4″‐dichloro‐1″,3″,5″‐triazin‐6‐ylamino) phenylazo]benzamidine were able to bind to trypsin and the trypsin‐like proteases, thrombin and urokinase, but bound pancreatic kallikrein only weakly. Ligands possessing a second cationic group (either 4‐aminophenyltrimethylammonium or 4‐aminobenzamidine) substituted onto the triazine ring displayed higher affinities than the parent compound for trypsin in solution but bound the enzyme weakly or not at all after immobilization. In contrast, these bis‐cationic ligands bound pancreatic kallikrein in solution ad following immobilization. The presence of the second cationic group was crucial, since its replacement by neutral or anionic groups led to loss of affinity for pancreatic kallikrein. One of the bis‐cationic ligands was used to purify pancreatic kallikrein 9.5‐fold from a crude pancreatic extract in 79% yield, to generate a product
ISSN:0952-3499
DOI:10.1002/jmr.300060104
出版商:John Wiley&Sons, Ltd.
年代:1993
数据来源: WILEY
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4. |
Using a neural network to identify potential HLA‐DR1 binding sites within proteins |
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Journal of Molecular Recognition,
Volume 6,
Issue 1,
1993,
Page 41-48
Leslie R Bisset,
Walter Fierz,
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摘要:
AbstractThe presentation by antigen‐presenting cells of immunodominant peptide segments in association with major histocompatibility complex (MHC) encoded proteins is fundamental to the efficacy of a specific immune response. One approach used to identify immunodominant segments within proteins has involved the development of predictive algorithms which utilize amino acid sequence data to identify structural characteristics or motifs associated within vivoantigenicity. The parallel‐computing technique termed ‘neural networking’ has recently been shown to be remarkably efficient at addressing the problem of pattern recognition and can be applied to predict protein secondary structure attributes directly from amino acid sequence data. In order to examine the potential of a neural network to generalize peptide structural feature related to binding within class II MHC‐encoded proteins, we have trained a neural network to determine whether or not any given amino acid of a protein is part of a peptide segment capable of binding to HLA‐DR1. We report that a neural network trained on a data base consisting of peptide segments known to bind to HLA‐DR1 is able to generalize features relating to HLA‐DR1‐binding capacity (r= 0
ISSN:0952-3499
DOI:10.1002/jmr.300060105
出版商:John Wiley&Sons, Ltd.
年代:1993
数据来源: WILEY
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5. |
Masthead |
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Journal of Molecular Recognition,
Volume 6,
Issue 1,
1993,
Page -
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PDF (96KB)
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ISSN:0952-3499
DOI:10.1002/jmr.300060101
出版商:John Wiley&Sons, Ltd.
年代:1993
数据来源: WILEY
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