NIpredict

NIpredict predicts nuclear import activity by characterizing interactions between nuclear localization signals (NLS) and import receptors using molecular interaction energy components (MIECs).

Key Features:

• Prediction of Nuclear Import Activity: Predicts changes in nuclear import activity resulting from alterations in the NLS by characterizing NLS–import receptor interactions.
• Molecular Interaction Energy Components (MIECs): Employs MIECs to quantify and analyze the binding affinity between an NLS and its import receptor.
• Support Vector Regression (SVR) Integration: Incorporates support vector regression (SVR) to model the relationship between characterized interactions (MIECs) and nuclear import activity.
• Identification of PTM-Based Regulation Mechanisms: Facilitates systematic identification of post-translational modification (PTM)-based regulatory mechanisms, with emphasis on phosphorylation effects in human and yeast proteins.

Scientific Applications:

• Protein Nuclear Transport Analysis: Enables study of protein transport into the nucleus by predicting how NLS modifications affect import activity.
• PTM Regulatory Mechanism Discovery: Supports identification of PTM-based regulatory mechanisms that modulate nuclear import, including phosphorylation-driven regulation.
• Protein-Specific Phosphorylation Studies: Applies to analysis of phosphorylation effects on specific proteins such as SF1 and ORC6 in human and yeast.

Methodology:

Characterizing NLS–import receptor interactions using molecular interaction energy components (MIECs); applying support vector regression (SVR) to correlate MIECs with nuclear import activity; and developing a computational framework to identify PTM-based regulatory mechanisms, including phosphorylation.