期刊
BIOMOLECULES
卷 11, 期 2, 页码 -出版社
MDPI
DOI: 10.3390/biom11020334
关键词
constant-pH molecular dynamics; molecular simulations; antibody; anti-TNF alpha; Gaussian accelerated molecular dynamics
资金
- Kaohsiung Medical University, Taiwan [KMU-TC108A03-1, NCTUKMU108-IF-02, NCTUKMU109-DR-01]
- Ministry of Science and Technology, Taiwan [MOST 109-2113-M-037-015]
The study developed an engineered version of Humira (W1-Humira) that can bind to TNF alpha at neutral pH and dissociate from TNF alpha at acidic pH. The engineered Humira showed pH-dependent affinity in vitro, with predicted results closely matching experimental findings. The approach demonstrated high accuracy in predicting antibody pH-dependent binding characteristics, potentially aiding in antibody drug design with advancements in computational methods and computing power.
Humira is a monoclonal antibody that binds to TNF alpha, inactivates TNF alpha receptors, and inhibits inflammation. Neonatal Fc receptors can mediate the transcytosis of Humira-TNF alpha complex structures and process them toward degradation pathways, which reduces the therapeutic effect of Humira. Allowing the Humira-TNF alpha complex structures to dissociate to Humira and soluble TNF alpha in the early endosome to enable Humira recycling is crucial. We used the cytoplasmic pH (7.4), the early endosomal pH (6.0), and pK(a) of histidine side chains (6.0-6.4) to mutate the residues of complementarity-determining regions with histidine. Our engineered Humira (W1-Humira) can bind to TNF alpha in plasma at neutral pH and dissociate from the TNF alpha in the endosome at acidic pH. We used the constant-pH molecular dynamics, Gaussian accelerated molecular dynamics, two-dimensional potential mean force profiles, and in vitro methods to investigate the characteristics of W1-Humira. Our results revealed that the proposed Humira can bind TNF alpha with pH-dependent affinity in vitro. The W1-Humira was weaker than wild-type Humira at neutral pH in vitro, and our prediction results were close to the in vitro results. Furthermore, our approach displayed a high accuracy in antibody pH-dependent binding characteristics prediction, which may facilitate antibody drug design. Advancements in computational methods and computing power may further aid in addressing the challenges in antibody drug design.
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