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Characterizing structural features of cuticle-degrading proteases from fungi by molecular modeling.

ABSTRACT: BACKGROUND: Serine proteases secreted by nematode and insect pathogenic fungi are bio-control agents which have commercial potential for developing into effective bio-pesticides. A thorough understanding of the structural and functional features of these proteases would significantly assist with targeting the design of efficient bio-control agents. RESULTS: Structural models of serine proteases PR1 from entomophagous fungus, Ver112 and VCP1 from nematophagous fungi, have been modeled using the homology modeling technique based on the crystal coordinate of the proteinase K. In combination with multiple sequence alignment, these models suggest one similar calcium-binding site and two common disulfide bridges in the three cuticle-degrading enzymes. In addition, the predicted models of the three cuticle-degrading enzymes present an essentially identical backbone topology and similar geometric properties with the exception of a limited number of sites exhibiting relatively large local conformational differences only in some surface loops and the N-, C termini. However, they differ from each other in the electrostatic surface potential, in hydrophobicity and size of the S4 substrate-binding pocket, and in the number and distribution of hydrogen bonds and salt bridges within regions that are part of or in close proximity to the S2-loop. CONCLUSION: These differences likely lead to variations in substrate specificity and catalytic efficiency among the three enzymes. Amino acid polymorphisms in cuticle-degrading enzymes were discussed with respect to functional effects and host preference. It is hoped that these structural models would provide a further basis for exploitation of these serine proteases from pathogenic fungi as effective bio-control agents.

SUBMITTER: Liu SQ

PROVIDER: S-EPMC1890553 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Characterizing structural features of cuticle-degrading proteases from fungi by molecular modeling.

Liu Shu-Qun SQ Meng Zhao-Hui ZH Yang Jin-Kui JK Fu Yun-Xin YX Zhang Ke-Qin KQ

BMC structural biology 20070518

<h4>Background</h4>Serine proteases secreted by nematode and insect pathogenic fungi are bio-control agents which have commercial potential for developing into effective bio-pesticides. A thorough understanding of the structural and functional features of these proteases would significantly assist with targeting the design of efficient bio-control agents.<h4>Results</h4>Structural models of serine proteases PR1 from entomophagous fungus, Ver112 and VCP1 from nematophagous fungi, have been modele ...[more]

PMID: 17511867

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Project description:BACKGROUND: Serine proteases account for over a third of all known proteolytic enzymes; they are involved in a variety of physiological processes and are classified into clans sharing structural homology. The PA clan of endopeptidases is the most abundant and over two thirds of this clan is comprised of the S1 family of serine proteases, which bear the archetypal trypsin fold and have a catalytic triad in the order Histidine, Aspartate, Serine. These proteases have been studied in depth and many three dimensional structures have been experimentally determined. However, these structures mostly consist of bacterial and animal proteases, with a small number of plant and fungal proteases and as yet no structures have been determined for protozoa or archaea. The core structure and active site geometry of these proteases is of interest for many applications. This study investigated the structural properties of different S1 family serine proteases from a diverse range of taxa using molecular modeling techniques. RESULTS: Our predicted models from protozoa, archaea, fungi and plants were combined with the experimentally determined structures of 16 S1 family members and used for analysis of the catalytic core. Amino acid sequences were submitted to SWISS-MODEL for homology-based structure prediction or the LOOPP server for threading-based structure prediction. Predicted models were refined using INSIGHT II and SCRWL and validated against experimental structures. Investigation of secondary structures and electrostatic surface potential was performed using MOLMOL. The structural geometry of the catalytic core shows clear deviations between taxa, but the relative positions of the catalytic triad residues were conserved. Some highly conserved residues potentially contributing to the stability of the structural core were identified. Evolutionary divergence was also exhibited by large variation in secondary structure features outside the core, differences in overall amino acid distribution, and unique surface electrostatic potential patterns between species. CONCLUSIONS: Encompassing a wide range of taxa, our structural analysis provides an evolutionary perspective on S1 family serine proteases. Focusing on the common core containing the catalytic site of the enzyme, this analysis is beneficial for future molecular modeling strategies and structural analysis of serine protease models.

Project description:Cancer is a complex disease resulting from the uncontrolled proliferation of cell signaling events. Protein kinases have been identified as central molecules that participate overwhelmingly in oncogenic events, thus becoming key targets for anticancer drugs. A majority of studies converged on the idea that ligand-binding pockets of kinases retain clues to the inhibiting abilities and cross-reacting tendencies of inhibitor drugs. Even though these ideas are critical for drug discovery, validating them using experiments is not only difficult, but also in some cases infeasible. To overcome these limitations and to test these ideas at the molecular level, we present here the results of receptor-focused in-silico docking of nine marketed drugs to 19 different wild-type and mutated kinases chosen from a wide range of families. This investigation highlights the need for using relevant models to explain the correct inhibition trends and the results are used to make predictions that might be able to influence future experiments. Our simulation studies are able to correctly predict the primary targets for each drug studied in majority of cases and our results agree with the existing findings. Our study shows that the conformations a given receptor acquires during kinase activation, and their micro-environment, defines the ligand partners. Type II drugs display high compatibility and selectivity for DFG-out kinase conformations. On the other hand Type I drugs are less selective and show binding preferences for both the open and closed forms of selected kinases. Using this receptor-focused approach, it is possible to capture the observed fold change in binding affinities between the wild-type and disease-centric mutations in ABL kinase for Imatinib and the second-generation ABL drugs. The effects of mutation are also investigated for two other systems, EGFR and B-Raf. Finally, by including pathway information in the design it is possible to model kinase inhibitors with potentially fewer side-effects.

Dataset Information

Characterizing structural features of cuticle-degrading proteases from fungi by molecular modeling.

Publications

Characterizing structural features of cuticle-degrading proteases from fungi by molecular modeling.

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