DynaMine

DynaMine predicts protein backbone dynamics from amino-acid sequences to quantify residue-level backbone mobility for functional and structural analysis.

Key Features:

• Sequence-Based Predictions: Predicts backbone dynamics using only protein amino-acid sequence information without requiring tertiary structure or prior disorder annotations.
• Distinguishing Structural Regions: Identifies folded domains, disordered linkers, molten globules, and pre-structured binding motifs of varying sizes within proteins.
• Disorder Identification: Detects intrinsically disordered regions with accuracy comparable to state-of-the-art disorder predictors.
• Residue-Level Resolution: Produces per-residue profiles describing the statistical potential for fast backbone movements.
• Absolute Scale Predictions: Outputs values that are meaningful on an absolute scale for comparative analyses.
• Experimentally Calibrated Predictions: Integrates experimental data sets from proteins in solution to calibrate predictions.
• Fast Computation: Uses a rapid computational approach for high-throughput generation of backbone dynamics profiles.

Scientific Applications:

• Protein functional analysis: Enables exploration of protein function, stability, and interactions by providing residue-level backbone mobility information.
• Study of intrinsically disordered proteins (IDPs): Facilitates identification and characterization of IDRs and pre-structured motifs relevant to IDP biology.
• Comparative dynamics studies: Supports comparative analyses of dynamics between different protein regions and across proteins using absolute-scale values.
• Case studies: Has been applied to proteins such as human p53 and E1A from human adenovirus 5 to demonstrate applicability to well-studied and novel proteins.

Methodology:

Predictions are produced by integrating experimentally derived data sets for proteins in solution and applying a fast computational approach to generate per-residue statistical-potential profiles of backbone movement.