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Classification of protein domains based on their three-dimensional shapes (CPD3DS) 被引量:1
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作者 Zhaochang Yang Mingkang Liu +1 位作者 Bin Wang Beibei Wang 《Synthetic and Systems Biotechnology》 SCIE 2021年第3期224-230,共7页
Protein design has become a powerful method to expand the number of natural proteins and design customized proteins according to demands.Domain-based protein design spares the need to create novel elements from scratc... Protein design has become a powerful method to expand the number of natural proteins and design customized proteins according to demands.Domain-based protein design spares the need to create novel elements from scratch,which makes it a more efficient strategy than scratch-based protein design in designing multi-domain proteins,protein complexes and biomaterials.As the surface shape plays a central role in domain-domain and protein-protein interactions,a global map of the surface shapes of all domains should be very beneficial for domain-based protein design.Therefore,in this study,we characterized the surface shapes of protein domains,collected from CATH and SCOP databases,with their 3D-Zernike descriptors(3DZDs).Then similarities of domain shape features were identified,and all domains were classified accordingly.The preferences of the combinations of domains between different clusters were analyzed in natural proteins from the Protein Data Bank.A user-friendly website,termed CPD3DS,was also developed for storage,retrieval,analyses and visualization of our results.This work not only provides an overall view of protein domain shapes by showing their variety and similarities,but also opens up a new avenue to understand the properties of protein structural domains,and design principles of protein architectures. 展开更多
关键词 3D-zernike descriptors K-MEANS Shape similarity Domain surface shapes Structural similarity
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