Integrative Structural-Functional Genomics of Fc and Fab: Precision Models for Monoclonal Antibody Stability and Anti-Aggregation Engineering - Tapaswi Ram Khajuria; Prof (Dr.) Atul Khajuria; KIRAN KUMARI (International Journal of Molecular Biotechnological Research, 2026)
Monoclonal antibodies (mAbs) represent the cornerstone of biotherapeutics, yet aggregation propensity compromises up to 50% of candidates during development, driven by Fab hypervariability and Fc vulnerabilities.(1,2) This review integrates functional genomics from OAS (4B+ sequences)(5) and structural databases (SAbDab: 10K+ structures)(6) with machine learning models achieving R=0.97 for SAP prediction.(11) We dissect biophysical mechanisms, benchmark predictive tools (DeepSP, ESM2), and engineering strategies (YTE, FW mutations) that enhance Tm by 5-10°C while preserving affinity.(14,25) Case studies from trastuzumab variants and COVID mAbs demonstrate 30-55% aggregation reduction.(7,11) Integrative pipelines fuse repertoire mining, AlphaFold3 structures, and MD- featurized ML to de-risk developability, slashing attrition by 35%.(7) Future directions emphasize multi- task models for high-conc. subcutaneous delivery (200 mg/mL).(22)
Keywords: AlphaFold3; CDR-H3 loops; DeepSP; Fab stability; Fc engineering; OAS database; SAbDab; V(D)J recombination; aggregation propensity (SAP); antibody aggregation; high-concentration formulations; mAb developability; machine learning prediction; monoclonal antibodies; repertoire sequencing; self-interaction (SCM); somatic hypermutation; structural genomics; subcutaneous delivery; thermostability (Tm)