Преодоление разрыва между генотипом и фенотипом: интеграция полногеномных ассоциативных исследований и вычислительной структурной биологии для расшифровки механизмов неправильного фолдинга белков, вызванного однонуклеотидными полиморфизмами, при заболеваниях человека
Table 1 - Summary of Key Computational Tools for nsSNP Analysis
Analysis Type | Tool Name | Methodology | Key Output |
Pathogenicity | SIFT | Sequence homology-based | Score (0.0 deleterious - 1.0 tolerated) |
PolyPhen-2 | Machine learning-based | Score (Benign, Possibly, Probably Damaging) | |
CADD | Integration of multiple annotations | C-score (Higher = more deleterious) | |
Conservation | ConSurf | Evolutionary analysis | Score (1–9, 9 most conserved) |
Stability (ΔΔG) | FoldX | Empirical force field | ΔΔG (kcal/mol) |
mCSM | Machine learning & graph-based | ΔΔG (kcal/mol) | |
SDM | Statistical potential | Stability score | |
Structure | SWISS-MODEL | Homology modeling | 3D Protein Structure |
AlphaFold2 | Deep learning (AI) | 3D Protein Structure | |
Dynamics | GROMACS | Molecular Dynamics | Trajectories (RMSD, RMSF, SASA) |
AMBER | Molecular Dynamics | Trajectories (RMSD, RMSF, SASA) | |
Docking | AutoDock Vina | Docking simulation | Binding affinity (kcal/mol) |