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  • 1
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Journal of the American Chemical Society 114 (1992), S. 3697-3709 
    ISSN: 1520-5126
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 2
    ISSN: 1432-1432
    Keywords: Key words: Phylogenomics — Proteasome — Gene families — Duplications — Orthologues — Paralogues
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract. We employed a phylogenomic approach to study the evolution of α subunits of the proteasome gene family from early diverging eukaryotes. BLAST similarity searches of the Giardia lamblia genome identified all seven α proteasome genes characteristic of eukaryotes from the crown group. In addition, a PCR strategy for the amplification of multiple α subunit sequences generated single α proteasome products for representatives of the Kinetoplastida (Leishmania major), the Parabasalia (Trichomonas vaginalis), and the Microsporidia (Vairimorpha sp., Nosema sp., Endoreticulata sp., and Spraguea lophii). The kinetoplastid Trypanosoma cruzi and the eukaryote crown group Acanthamoeba castellanii yielded two distinct α proteasome genes each. The presence of seven distinct α proteasome genes in G. lamblia, one of the earliest-diverging eukaryotes, indicates that the α proteasome gene family evolved rapidly from a minimum of one gene in Archaea to seven or more in Eukarya. Results from the phylogenomic analysis are consistent with the idea that the Diplomonida (as represented by G. lamblia), the Kinetoplastida, the Parabasalia, and the Microsporidia diverged after the duplication events that originated the α proteasome gene family. A model for the early origin and evolution of the proteasome gene family is presented.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 21 (1995), S. 151-175 
    ISSN: 0885-6125
    Keywords: domain knowledge ; change of representation ; theory revision ; protein structure prediction ; homology modeling ; amino acid properties
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Predicting the fold, or approximate 3D structure, of a protein from its amino acid sequence is an important problem in biology. The homology modeling approach uses a protein database to identify fold-class relationships by sequence similarity. The main limitation of this method is that some proteins with similar structures appear to have very different sequences, which we call the “hidden-homology problem.” As in other real-world domains for machine learning, this difficulty may be caused by a low-level representation. Learning in such domains can be improved by using domain knowledge to search for representations that better match the inductive bias of a preferred algorithm. In this domain, knowledge of amino acid properties can be used to construct higher-level representations of protein sequences. In one experiment using a 179-protein data set, the accuracy of fold-class prediction was increased from 77.7% to 81.0%. The search results are analyzed to refine the grouping of small residues suggested by Dayhoff. Finally, an extension to the representation incorporates sequential context directly into the representation, which can express finer relationships among the amino acids. The methods developed in this domain are generalized into a framework that suggests several systematic roles for domain knowledge in machine learning. Knowledge may define both a space of alternative representations, as well as a strategy for searching this space. The search results may be summarized to extract feedback for revising the domain knowledge.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 21 (1995), S. 151-175 
    ISSN: 0885-6125
    Keywords: domain knowledge ; change of representation ; theory revision ; protein structure prediction ; homology modeling ; amino acid properties
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Predicting the fold, or approximate 3D structure, of a protein from its amino acid sequence is an important problem in biology. The homology modeling approach uses a protein database to identify fold-class relationships by sequence similarity. The main limitation of this method is that some proteins with similar structures appear to have very different sequences, which we call the “hidden-homology problem.” As in other real-world domains for machine learning, this difficulty may be caused by a low-level representation. Learning in such domains can be improved by using domain knowledge to search for representations that better match the inductive bias of a preferred algorithm. In this domain, knowledge of amino acid properties can be used to construct higher-level representations of protein sequences. In one experiment using a 179-protein data set, the accuracy of fold-class prediction was increased from 77.7% to 81.0%. The search results are analyzed to refine the grouping of small residues suggested by Dayhoff. Finally, an extension to the representation incorporates sequential context directly into the representation, which can express finer relationships among the amino acids. The methods developed in this domain are generalized into a framework that suggests several systematic roles for domain knowledge in machine learning. Knowledge may define both a space of alternative representations, as well as a strategy for searching this space. The search results may be summarized to extract feedback for revising the domain knowledge.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    The @journal of physical chemistry 〈Washington, DC〉 98 (1994), S. 5580-5586 
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Physics
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 420 (2002), S. 716-717 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The Alliance for Cellular Signaling (AfCS)–Nature Molecule Pages will be a comprehensive database of key facts about more than 3,000 proteins involved in cell signalling. Each entry will be created by invited experts and be peer-reviewed. Alongside the large-scale experiments being conducted ...
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Company
    Nature biotechnology 14 (1996), S. 323-328 
    ISSN: 1546-1696
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: [Auszug] Immunoglobulin (Ig) amino acid sequences are highly conserved and often have sequence homology ranging from 70 to 95%. Antigen binding fragments (Fab), variable region fragments (Fv), and single chain Fv (scFv) of more than 50 myeloma proteins and monoclonal antibodies (mAb) have been crystallized ...
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Photosynthesis research 56 (1998), S. 229-254 
    ISSN: 1573-5079
    Keywords: accessory chlorophylls ; bicarbonate ; β-carotene ; computer-modelling ; heme ; manganese cluster ; Photosystem II reaction center ; reaction center chlorophyll P680
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract In this Minireview, a comparison of the binding niches of the PS II cofactors from several existing models of the PS II reaction center is provided. In particular, it discusses a three dimensional model of the Photosystem II (PS II) reaction center including D1, D2 and cytochrome b559 proteins from the green alga Chlamydomonas reinhardtii that was specifically generated for this Minireview. This model is the most complete to date and includes accessory chlorophyllzs, a manganese cluster, two molecules of β-carotene and cytochrome b559, all of which are essential components of the PS II reaction center. The modeling of the D1 and D2 proteins was primarily based on homology with the L and M subunits of the anoxygenic purple bacterial photosynthetic reaction centers. The non-homologous loop regions were built using a sequence specific approach by searching for the best-matched protein segments in the Protein Data Bank, and by imposing the matching conformations on the corresponding D1 and D2 regions. Cytochrome b559 which is in close proximity to D1 and D2 was tentatively modeled in α/β conformation and docked on the QB side of the PS II reaction center according to experimental suggestions. An alternate docking on the QA side is also shown for comparison. The cofactors in the PS II reaction center were modeled either by adopting the structures from the bacterial counterparts, when available, with modifications based on existing experimental data or by de novo modeling and docking in the most probable positions in the reaction center complex. The specific features of this model are the inclusion of the tetramanganese cluster (with calcium and chloride ions) in a open, C-shaped structure modeled within the D1/D2/cytochrome b559 complex with D1-D170, D1-E189, D1-D342 and D1-A344 as putative ligands; and the modeling of two cis β-carotenes and two accessory chlorophyllzs liganded by D1-H118 and D2-H117. We also analyzed residues in the model which may be involved in the D1 and D2 inter-protein interactions, as well as residues which may be involved in putative bicarbonate and water binding and transport.
    Type of Medium: Electronic Resource
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  • 9
    ISSN: 0952-3499
    Keywords: Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Medicine
    Notes: The ligand binding site of a monoclonal antibody (185), which binds the neuroleptic drug haloperidol, has been modelled using canonical structures and energy minimization techniques. This refined modelling protocol has allowed us to predict the variable region loop conformation. Three key residues, H:50(W), H:100a(D) and L:96(Y) appear to create the basis of the electrostatic, π-π stacking interactions and hydrogen bonding required for the high affinity binding site characteristics present in this antibody. The use of computer-aided graphics techniques and appropriate three-dimensional modelling permits inspection of the predicted molecular recognition features of the ligand binding site.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    New York, NY [u.a.] : Wiley-Blackwell
    Journal of Computational Chemistry 11 (1990), S. 346-350 
    ISSN: 0192-8651
    Keywords: Computational Chemistry and Molecular Modeling ; Biochemistry
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Computer Science
    Notes: Atomic partial charges for three model systems that mimic the metal-ligand moiety of the active site in the enzyme Cu, Zn superoxide dismutase (SOD) have been calculated at the ab initio level. The model systems include copper and zinc complexes with imidazole, formate and ammonia ligands. The partial charges thus obtained have been incorporated into force fields for molecular simulations. Simulations carried out with these force fields justify the need for specialized charge assignments for the metals and their ligands.
    Additional Material: 3 Ill.
    Type of Medium: Electronic Resource
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