ICM Web

ICM Web computes nucleosome energy landscapes, predicts nucleosome positioning, and generates structural representations and helical parameter profiles from DNA sequences composed of adenine (A), cytosine (C), guanine (G), and thymine (T).

Key Features:

• DNA sequence input: Accepts DNA sequences composed of adenine (A), cytosine (C), guanine (G), and thymine (T).
• Nucleosome Energy Level Diagram: Produces an energy landscape diagram for assessing nucleosome stability and identifying regions likely to form or retain nucleosomes.
• Coarse-Grained Representations: Generates simplified models of free DNA and chromatin showing spatial arrangements of DNA wrapped around histone proteins.
• Helical Parameter Plots: Plots helical parameters Tilt, Roll, Twist, Shift, Slide, and Rise versus position along the DNA sequence.
• Multiple energy models and nucleosome structures: Supports multiple energy models, nucleosome structural variants, and methods for positioning nucleosomes within the energy landscape.
• Experimental footprint incorporation: Incorporates experimental nucleosome footprint data to construct nucleosome arrays.
• Validation and benchmarking: Default energy model correlates 0.7 with 100 experimentally determined stability values and accurately predicts the positioning of six nucleosomes in the mouse mammary tumor virus (MMTV) promoter.
• Sequence length support: Applicable to analyses of sequences up to tens of kilobases in length.

Scientific Applications:

• Nucleosome stability analysis: Quantifies and maps relative nucleosome stability across DNA sequences using computed energy landscapes.
• Nucleosome positioning prediction: Predicts nucleosome positions within genomic regions based on energy models and positioning methods.
• Chromatin folding and structure investigation: Models coarse-grained chromatin structures to study chromatin organization and folding across sequences up to tens of kilobases.
• Conformational dynamics assessment: Analyzes local DNA conformational changes relevant to nucleosome-DNA interactions via helical parameter profiles (Tilt, Roll, Twist, Shift, Slide, Rise).
• Model validation and benchmarking: Enables comparison of computational energy models against experimental nucleosome stability and footprinting data, including validation on the MMTV promoter.

Methodology:

Computes nucleosome energy landscapes using selectable energy models, positions nucleosomes within those landscapes using available positioning methods, plots helical parameters (Tilt, Roll, Twist, Shift, Slide, Rise) along the sequence, generates coarse-grained representations of free DNA and chromatin, and incorporates experimental nucleosome footprint data to construct nucleosome arrays.