Abstract
Protein flexibility is often implied in binding with different partners and is essential for protein function. The growing number of macromolecular structures in the Protein Data Bank entries and their redundancy has become a major source of structural knowledge of the protein universe. The analysis of structural variability through available redundant structures of a target, called multiple target conformations (MTC), obtained using experimental or modeling methods and under different biological conditions or different sources is one way to explore protein flexibility. This analysis is essential to improve the understanding of various mechanisms associated with protein target function and flexibility. In this study, we explored structural variability of three biological targets by analyzing different MTC sets associated with these targets. To facilitate the study of these MTC sets, we have developed an efficient tool, SA-conf, dedicated to capturing and linking the amino acid and local structure variability and analyzing the target structural variability space. The advantage of SA-conf is that it could be applied to divers sets composed of MTCs available in the PDB obtained using NMR and crystallography or homology models. This tool could also be applied to analyze MTC sets obtained by dynamics approaches. Our results showed that SA-conf tool is effective to quantify the structural variability of a MTC set and to localize the structural variable positions and regions of the target. By selecting adapted MTC subsets and comparing their variability detected by SA-conf, we highlighted different sources of target flexibility such as induced by binding partner, by mutation and intrinsic flexibility. Our results support the interest to mine available structures associated with a target using to offer valuable insight into target flexibility and interaction mechanisms. The SA-conf executable script, with a set of pre-compiled binaries are available at http://www.mti.univ-paris-diderot.fr/recherche/plateformes/logiciels.
Highlights
Proteins are highly flexible macromolecules and their dynamic properties are crucial to many biological processes
The different structures associated with a target, referred as multiple target conformations (MTC), can correspond to available Protein Data Bank (PDB) structures obtained under different conditions using nuclear magnetic resonance (NMR) models and X-ray crystallography or to theoretical models obtained using homology modeling or to dynamic series of 3D views obtained using molecular dynamics simulations that sample exhaustively the target conformation landscape
structural alphabet (SA)-conf tool was applied to different MTC subsets associated with three targets urokinase-type plasminogen activator (uPA), p53 and protease of the immunodeficiency virus type 1 (PR1) (Table 1) with the aims of i) mining the available 3D conformations associated with each target and selecting pertinent MTC subset(s), ii) identifying the variable regions of interest of MTC subsets in terms of the 3D local structures, secondary structures and sequence, and iii) providing insights into flexibility of each target by combining the SA-conf variability results obtained using its different MTC subsets
Summary
Proteins are highly flexible macromolecules and their dynamic properties are crucial to many biological processes. Because most newly solved structures fall within existing families, a large number of structures exhibit high redundancy, i.e., more than half share at least 95% sequence identity Even if this redundancy is considered valuable as in investigating families of homologous sequences [7,8], the dominant approach for the data mining of the PDB considers redundancy as non-informative [9], resulting in an artificial reduction in the variability of the structural space. The different structures associated with a target, referred as multiple target conformations (MTC), can correspond to available PDB structures obtained under different conditions using nuclear magnetic resonance (NMR) models and X-ray crystallography or to theoretical models obtained using homology modeling or to dynamic series of 3D views obtained using molecular dynamics simulations that sample exhaustively the target conformation landscape These ensembles of 3D view of one target correspond to different MTC subsets when obtained by different sources and approaches
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