Mechanism of ribonuclease inhibition by ribonuclease inhibitor protein based on the crystal structure of its complex with ribonuclease A

We describe the mechanism of ribonuclease inhibition by ribonuclease inhibitor, a protein built of leucine-rich repeats, based on the crystal structure of the complex between the inhibitor and ribonuclease A. The structure was determined by molecular replacement and refined to an R(cryst) of 19.4% at 2.5 Angstrom resolution. Ribonuclease A binds to the concave region of the inhibitor protein comprising its parallel beta-sheet and loops. The inhibitor covers the ribonuclease active site and directly contacts several active-site residues. The inhibitor only partially mimics the RNase-nucleotide interaction and does not utilize the pi phosphate-binding pocket of ribonuclease A, where a sulfate ion remains bound. The 2550 Angstrom(2) of accessible surface area buried upon complex formation may be one of the major contributors to the extremely tight association (K-i = 5.9 x 10(-14) M). The interaction is predominantly electrostatic; there is a high chemical complementarity with 18 putative hydrogen bonds and salt links, but the shape complementarity is lower than in most other protein-protein complexes. Ribonuclease inhibitor changes its conformation upon complex formation; the conformational change is unusual in that it is a plastic reorganization of the entire structure without any obvious hinge and reflects the conformational flexibility of the structure of the inhibitor. There is a good agreement between the crystal structure and other biochemical studies of the interaction. The structure suggests that the conformational flexibility of RI and an unusually large contact area that compensates for a lower degree of complementarity may be the principal reasons for the ability of RI to potently inhibit diverse ribonucleases. However, the inhibition is lost with amphibian ribonucleases that have substituted most residues corresponding to inhibitor-binding residues in RNase A, and with bovine seminal ribonuclease that prevents inhibitor binding by forming a dimer. (C) 1996 Academic Press Limited

MHCPEP, a database of MHC-binding peptides: Update 1996

MHCPEP is a curated database comprising over 9000 peptide sequences known to bind MHC molecules. Entries are compiled from published reports as well as from direct submissions of experimental data. Each entry contains the peptide sequence, its MHC specificity and, when available, experimental method, observed activity, binding affinity, source protein, anchor positions and publication references. The present format of the database allows text string matching searches but can easily be converted for use in conjunction with sequence analysis packages. The database can be accessed via Internet using WWW, FTP or Gopher.

Modeling the optical constants of solids using acceptance-probability-controlled simulated annealing with an adaptive move generation procedure

The acceptance-probability-controlled simulated annealing with an adaptive move generation procedure, an optimization technique derived from the simulated annealing algorithm, is presented. The adaptive move generation procedure was compared against the random move generation procedure on seven multiminima test functions, as well as on the synthetic data, resembling the optical constants of a metal. In all cases the algorithm proved to have faster convergence and superior escaping from local minima. This algorithm was then applied to fit the model dielectric function to data for platinum and aluminum.

Bioactivation of Phenytoin by Human Cytochrome P450: Characterization of the Mechanism and Targets of Covalent Adduct Formation

The cytochrome P450-dependent covalent binding of radiolabel derived fi om phenytoin (DPH) and its phenol and catechol metabolites, 5-(4'-hydroxyphenyl)-5-phenylhydantoin (HPPH) and 5-(3',4'-dihydroxyphenyl)-5-phenylhydantoin (CAT), was examined in liver microsomes. Radiolabeled HPPH and CAT and unlabeled CAT were obtained from microsomal incubations and isolated by preparative HPLC. NADPH-dependent covalent binding was demonstrated in incubations of human liver microsomes with HPPH. When CAT was used as substrate, covalent adduct formation was independent of NADPH, was enhanced in the presence of systems generating reactive oxygen species, and was diminished under anaerobic conditions or in the presence of cytoprotective reducing agents. Fluorographic analysis showed that radiolabel derived from DPH and HPPH was selectively associated with proteins migrating with approximate relative molecular weights of 57-59 kDa and at the dye front (molecular weights < 23 kDa) on denaturing gels. Lower levels of radiolabel were distributed throughout the molecular weight range. In contrast, little selectivity was seen in covalent adducts formed from CAT. HPPH was shown to be a mechanism-based inactivator of P450, supporting the contention that a cytochrome P450 is one target of covalent binding. These results suggest that covalent binding of radiolabel derived from DPH in rat and human Liver microsomes occurs via initial P450-dependent catechol formation followed by spontaneous oxidation to quinone and semiquinone derivatives that ultimately react with microsomal protein. Targets for covalent binding may include P450s, though the catechol appears to be sufficiently stable to migrate out of the P450 active site to form adducts with other proteins. In conclusion, we have demonstrated that DPH can be bioactivated in human liver to metabolites capable of covalently binding to proteins. The relationship of adduct formation to DPH-induced hypersensitivity reactions remains to be clarified.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Aspects of adaptive management of coastal wetlands: Case studies of processes, conservation, restoration, impacts and assessment

Coastal wetlands are dynamic and include the freshwater-intertidal interface. In many parts of the world such wetlands are under pressure from increasing human populations and from predicted sea-level rise. Their complexity and the limited knowledge of processes operating in these systems combine to make them a management challenge.Adaptive management is advocated for complex ecosystem management (Hackney 2000; Meretsky et al. 2000; Thom 2000;National Research Council 2003).Adaptive management identifies management aims,makes an inventory/environmental assessment,plans management actions, implements these, assesses outcomes, and provides feedback to iterate the process (Holling 1978;Walters and Holling 1990). This allows for a dynamic management system that is responsive to change. In the area of wetland management recent adaptive approaches are exemplified by Natuhara et al. (2004) for wild bird management, Bunch and Dudycha (2004) for a river system, Thom (2000) for restoration, and Quinn and Hanna (2003) for seasonal wetlands in California. There are many wetland habitats for which we currently have only rudimentary knowledge (Hackney 2000), emphasizing the need for good information as a prerequisite for effective management. The management framework must also provide a way to incorporate the best available science into management decisions and to use management outcomes as opportunities to improve scientific understanding and provide feedback to the decision system. Figure 9.1 shows a model developed by Anorov (2004) based on the process-response model of Maltby et al. (1994) that forms a framework for the science that underlies an adaptive management system in the wetland context.