SHARK enables sensitive detection of evolutionary homologs and functional analogs in unalignable and disordered sequences.

Autor:	Chow CFW; Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany.; Center for Systems Biology Dresden, Dresden 01307, Germany.; Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden 01062, Germany., Ghosh S; Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany.; Center for Systems Biology Dresden, Dresden 01307, Germany., Hadarovich A; Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany.; Center for Systems Biology Dresden, Dresden 01307, Germany., Toth-Petroczy A; Max Planck Institute of Molecular Cell Biology and Genetics, Dresden 01307, Germany.; Center for Systems Biology Dresden, Dresden 01307, Germany.; Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden 01062, Germany.
Jazyk:	angličtina
Zdroj:	Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2024 Oct 15; Vol. 121 (42), pp. e2401622121. Date of Electronic Publication: 2024 Oct 09.
DOI:	10.1073/pnas.2401622121
Abstrakt:	Intrinsically disordered regions (IDRs) are structurally flexible protein segments with regulatory functions in multiple contexts, such as in the assembly of biomolecular condensates. Since IDRs undergo more rapid evolution than ordered regions, identifying homology of such poorly conserved regions remains challenging for state-of-the-art alignment-based methods that rely on position-specific conservation of residues. Thus, systematic functional annotation and evolutionary analysis of IDRs have been limited, despite them comprising ~21% of proteins. To accurately assess homology between unalignable sequences, we developed an alignment-free sequence comparison algorithm, SHARK (Similarity/Homology Assessment by Relating K-mers). We trained SHARK-dive, a machine learning homology classifier, which achieved superior performance to standard alignment-based approaches in assessing evolutionary homology in unalignable sequences. Furthermore, it correctly identified dissimilar but functionally analogous IDRs in IDR-replacement experiments reported in the literature, whereas alignment-based tools were incapable of detecting such functional relationships. SHARK-dive not only predicts functionally similar IDRs at a proteome-wide scale but also identifies cryptic sequence properties and motifs that drive remote homology and analogy, thereby providing interpretable and experimentally verifiable hypotheses of the sequence determinants that underlie such relationships. SHARK-dive acts as an alternative to alignment to facilitate systematic analysis and functional annotation of the unalignable protein universe. Competing Interests: Competing interests statement:The authors declare no competing interest.
Databáze:	MEDLINE
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