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

Author:

Liu Shu-Qun,Meng Zhao-Hui,Yang Jin-Kui,Fu Yun-Xin,Zhang Ke-Qin

Abstract

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.

Publisher

Springer Science and Business Media LLC

Subject

Structural Biology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3