Tapaswi Ram Khajuria,
Prof (Dr.) Atul Khajuria,
KIRAN KUMARI,
- Retd. Lecturer, Education Dept. Govt. Higher Sec School Barola Udhampur, J & K, India
- Professor, University School of Allied and Health Care Sciences Rayat Bahra Professional University VPO BOHAN, Tehsil Distt. Hoshiarpur, Punjab, India
- Retd. Govt. Master, Education Dept. Govt. High School Pachote, Chenani, Udhampur, J&K, India
Abstract
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: monoclonal antibodies; mAb developability; Fc engineering; Fab stability; antibody aggregation; structural genomics; repertoire sequencing; machine learning prediction; thermostability (Tm); aggregation propensity (SAP); self-interaction (SCM); AlphaFold3; DeepSP; OAS database; SAbDab; V(D)J recombination; somatic hypermutation; CDR-H3 loops; high-concentration formulations; subcutaneous delivery
[This article belongs to International Journal of Molecular Biotechnological Research ]
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International Journal of Molecular Biotechnological Research
| Volume | 04 | |
| Issue | 01 | |
| Received | 22/04/2026 | |
| Accepted | 24/04/2026 | |
| Published | 05/05/2026 | |
| Publication Time | 13 Days |