altMOD

altMOD enhances protein homology modeling in MODELLER by integrating interatomic distance-based statistical potentials into the objective function to improve three-dimensional structural model accuracy.

Key Features:

• Statistical Potential Integration: Incorporates interatomic distance-based statistical potentials, including DOPE (Discrete Optimized Protein Energy) and DFIRE, into the MODELLER objective function to guide homology model optimization.
• Improved Structural Model Quality: Enhances homology model accuracy, demonstrated by improvements in GDT-HA (Global Distance Test – High Accuracy), lDDT (local Distance Difference Test), and reduced MolProbity scores.
• Refined Structural Variability Estimation: Improves estimation of σ values representing structural divergence between target proteins and templates during modeling.

Scientific Applications:

• Protein Structure Prediction: Generates improved three-dimensional protein models for structural biology studies.
• Functional and Structural Annotation: Supports investigation of protein structure–function relationships and molecular interactions.
• Structure-Based Research: Facilitates studies in areas such as drug discovery and protein interaction analysis using refined homology models.

Methodology:

altMOD refines σ values describing structural variability between targets and templates and integrates interatomic distance-based statistical potentials such as DOPE and DFIRE into the MODELLER objective function to improve homology model optimization.