PCOILS

PCOILS predicts coiled-coil regions in protein sequences using profile-based inputs to improve detection accuracy and reduce highly charged false positives.

Key Features:

• Profile-based prediction: Incorporates sequence profile inputs to capture more detailed sequence information for coiled-coil detection.
• Weighting option: Implements a sequence-weighting mechanism to mitigate highly charged false positives.
• Coiled-coil target: Detects coiled-coil structural motifs characterized by helical strands forming superhelices.
• Comparative performance: Demonstrated superior performance relative to COILS and PairCoil/MultiCoil and competitive results versus Marcoil (which employs hidden Markov models).
• Benchmarking dataset: Performance was evaluated against a database comprising proteins with known structural information.

Scientific Applications:

• Protein domain annotation: Identification of coiled-coil domains within protein sequences for structural annotation.
• Interaction site prediction: Localization of potential protein–protein interaction sites mediated by coiled-coil regions.
• Structural analysis: Support for studies of the structural basis of protein complexes involving coiled-coil motifs.
• Comparative method evaluation: Use in benchmarking and comparing coiled-coil prediction methods.

Methodology:

PCOILS uses profile-based sequence inputs and an optional sequence-weighting scheme to reduce highly charged false positives, and its performance was assessed against a database of proteins with known structural information.