Protein Structure Modeling - Neorabio

● Hybrid modeling strategy: Combines template-based modeling, deep learning predictions, and ab initio reconstruction where templates are insufficient.
● Geometric and energetic refinement: Minimization and relaxation steps ensure that predicted structures adopt physically reasonable conformations.
● Comprehensive validation: Ramachandran statistics, clash analysis, model confidence scoring, and domain-resolution checks are included.
● Flexible modeling options: Customized strategies for membrane proteins, multi-domain architectures, enzyme active sites, or disordered regions.
● Transparent interpretation: Deliverables include residue-level confidence metrics, alternative conformations, and binding-site annotations when applicable.

● Structure-based drug design: Binding-site mapping, pocket characterization, and ligand-interaction hypothesis generation.
● Functional annotation: Predicting molecular roles, active residues, or structural motifs.
● Protein engineering: Assessing mutation impacts on stability, folding, or functional domains.
● Mechanistic and structural biology studies: Supporting hypothesis development for conformational changes or regulatory mechanisms.
● Preparation for downstream simulations: Providing optimized coordinates for MD, QM/MM, docking, and free-energy calculations.