SimpLogo

SimpLogo analyzes variability of amino acid sequences of protein domains within their parent protein architectures to assess evolutionary outcomes and infer potential functional differences.

Key Features:

• Domain Architecture Analysis: Assesses how individual protein domains vary when embedded in different parent protein architectures to relate sequence variability to architectural context.
• Evolutionary Insights: Distinguishes alternative evolutionary outcomes of a single protein domain to inform the transferability of functional annotations to uncharacterized proteins.
• Application to CheW-like Domains (PF01584): Applied to CheW-like domains (PF01584), which mediate protein/protein interactions in bacterial chemotaxis and occur in CheW scaffolding proteins, CheA kinases, and CheV proteins.
• Class Identification: Analyzes 16 domain architectures encompassing 94% of naturally occurring CheW-like domains and identifies six distinct domain classes with putative functional differences, including Class 1 in CheV and most CheW proteins; Class 6 (~20%) and Class 2 (~1%) in some CheW proteins; most CheA proteins containing Class 3; CheA proteins with multiple Hpt domains containing Class 4; and CheA proteins with two CheW-like domains containing one Class 3 and one Class 5 domain.
• Visualization Method: Implements a novel visualization approach for analyzing amino acid composition across extensive multiple sequence alignments as an alternative to traditional sequence logos.

Scientific Applications:

• Functional Hypothesis Generation: Supports generation of functional hypotheses for uncharacterized proteins by revealing domain-specific sequence variability and evolutionary trajectories.
• Experimental Guidance: Guides prioritization of experimental investigations by highlighting domain classes and positions with distinct sequence features.
• Comparative Analysis: Enables comparison of amino acid composition across large datasets to investigate domain-specific evolutionary pressures and functional correlations.

Methodology:

Uses a novel visualization method to analyze amino acid composition across large multiple sequence alignments, facilitating comparison of related protein sequences regardless of length and providing an alternative to traditional sequence logos.