PHOSforUS

PHOSforUS predicts phosphorylation sites within proteins by integrating biophysical parameters and a statistical thermodynamics framework to assess the roles of conformational dynamics and structural/chemical complementarity, with emphasis on disordered regions in eukaryotic proteomes.

Key Features:

• Biophysical parameter integration: Integrates structural and chemical complementarity with conformational dynamics to inform phosphorylation-site prediction, especially in disordered regions.
• Statistical thermodynamics framework: Employs a statistical thermodynamics approach to analyze substrate sequence information and energetic contributions to recognition.
• Vertical and horizontal information partitioning: Dissects sequence information into vertical (conserved kinase specificity motifs) and horizontal (distributed conformational dynamics embedded in position-specific conservation patterns) components.
• Dynamic contributions analysis: Evaluates free energy differences between phosphorylated and non-phosphorylated conformational ensembles to quantify the influence of conformational dynamics on kinase–substrate interactions.
• Conformational compaction classifier: Uses the magnitude of change in compaction of disordered protein chains upon phosphorylation as a primary classifier of substrate selectivity.
• Focus on disordered regions in eukaryotic proteomes: Targets prediction and analysis in disordered protein regions across eukaryotic proteomes.

Scientific Applications:

• Mechanistic interpretation of phosphorylation: Provides insights into the mechanistic consequences of phosphorylation in disordered proteins by linking sequence, dynamics, and energetics.
• Kinase–substrate interaction analysis: Aids analysis of substrate selectivity by partitioning chemical/structural complementarity and conformational dynamics contributions.
• Research in molecular biology, biochemistry, and pharmacology: Supports studies of protein function regulation by phosphorylation relevant to molecular biology, biochemistry, and pharmacology.

Methodology:

Integrates biophysical parameters (structural and chemical complementarity) with conformational dynamics, applies a statistical thermodynamics framework to partition sequence information into vertical and horizontal components, evaluates free energy differences between phosphorylated and non-phosphorylated conformational ensembles, and quantifies compaction changes of disordered chains as a classifier.