PairK: Pairwise k-mer alignment for quantifying protein motif conservation in disordered regions

Area of Science:

• Computational Biology
• Bioinformatics
• Evolutionary Biology

Background:

• Protein-protein interactions are crucial for biological functions.
• Short linear motifs (SLiMs) within intrinsically disordered regions (IDRs) mediate these interactions.
• IDRs evolve rapidly, posing challenges for traditional alignment methods in assessing SLiM conservation.

Purpose of the Study:

• To develop a new method for aligning and quantifying the conservation of subsequences within IDRs.
• To assess the evolutionary conservation of short linear motifs (SLiMs) in intrinsically disordered regions (IDRs).
• To improve the identification of biologically important SLiMs.

Main Methods:

• Developed PairK, a pairwise k-mer alignment method that is independent of multiple sequence alignment (MSA).
• Assessed PairK's performance by distinguishing biologically important motifs from background motifs.
• Compared PairK's conservation scores against MSA-based scores and a large language model (LLM)-based predictor.

Main Results:

• PairK accurately quantifies local subsequence conservation within IDRs without relying on MSAs.
• The method successfully distinguishes biologically important SLiMs from background motifs.
• PairK outperforms both standard MSA-based conservation scores and an LLM-based predictor.
• PairK can assess conservation across wider phylogenetic distances than MSAs, suggesting higher SLiM conservation than previously estimated.

Conclusions:

• PairK offers a more sensitive and accurate approach to quantifying SLiM conservation in IDRs.
• The findings indicate that many functionally important SLiMs are more conserved than traditional methods suggest.
• PairK provides a valuable tool for studying motif evolution and function in disordered protein regions.