T-RMSD

T-RMSD computes distance root-mean-square deviations (dRMSD) for equivalent residues identified from ungapped columns of multiple sequence alignments and uses per-position distance matrices to generate structural trees for protein classification.

Key Features:

• Tree-Based RMSD Methodology: Calculates dRMSD variations across equivalent residues defined by ungapped columns in multiple sequence alignments.
• Distance Matrix Generation: Produces a distinct distance matrix for each equivalent position to capture positional structural variation.
• Structural Tree with Support Values: Constructs structural trees that include support values at cluster nodes analogous to bootstrap values, quantifying structural distances between proteins or groups.

Scientific Applications:

• Fine-Grained Structural Clustering: Enables precise clustering of protein families or structurally related groups based on per-residue structural distances.
• Quantitative Estimation of Structural Distances: Provides a framework to estimate and compare structural distances quantitatively using tree topology and node support values.

Methodology:

Compute dRMSD variations between all pairs of equivalent residues derived from ungapped columns of multiple sequence alignments, generate per-position distance matrices, and use those matrices to construct a structural tree with support values.