DisEMBL

DisEMBL predicts disordered and unstructured regions within protein sequences to identify segments that influence protein function and inform construct design for proteomics and structural studies.

Key Features:

• Prediction of disorder: Identifies intrinsically disordered or unstructured regions within protein sequences.
• Alternative definitions of disorder: Implements multiple definitions of disorder to enhance prediction accuracy.
• Hot-loops definition: Uses a "hot loops" criterion that classifies coils with high temperature factors as disordered regions.
• Detection of short linear motifs: Highlights disordered segments that often contain short linear peptide motifs such as SH3 ligands and targeting signals.
• Construct-design guidance: Identifies potentially disordered segments to guide selection of expression constructs to improve expression, foldability, and stability.

Scientific Applications:

• Structural biology and genomics: Facilitates target selection and construct design for structural analysis and structural genomics projects.
• Biochemical studies: Aids optimization of experimental constructs and conditions by identifying disordered regions that affect protein expression and stability.

Methodology:

Predicts disorder from protein sequences using multiple alternative definitions of disorder, including a "hot loops" approach that designates coils with high temperature factors as disordered.