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Updated: Oct 26, 2026

Conformational Evaluation of HIV-1 Trimeric Envelope Glycoproteins Using a Cell-based ELISA Assay
Published on: September 14, 2014
Optimal combination of broadly neutralizing antibodies for HIV: Sensitivity ranking determines efficacy
Ting Guo1, Qi Deng2, Zhaozong Zhang1
1Aliyun School of Big Data, Changzhou University, Changzhou, 213159, China.
Abstract:
Combination therapy with broadly neutralizing antibodies (bNAbs) holds great promise for human immunodeficiency virus (HIV) functional cure, yet a critical question remains: when multiple bNAbs with distinct pharmacokinetic and pharmacodynamic properties are available, which combinations are most effective, and what determines their performance? To address this, we develop an impulsive differential equation model that incorporates three bNAb mechanisms, namely blocking viral entry, enhancing viral clearance, and stimulating cytotoxic T lymphocyte (CTL) proliferation. We derive the basic reproduction number R0 and establish it as a threshold. Specifically, R0 < 1 ensures virus eradication, while R0 > 1 leads to persistent infection. Global sensitivity analysis ranks the six antibody-related parameters, with the dosing interval and clearance rate being the most influential, followed by dose, maximum efficacy, half-maximal concentration, and Hill coefficient. Guided by this ranking, we design antibody combinations and find that the dual regimen (long-half-life + high-efficacy) achieves clearance probabilities and delays viral rebound comparable to the triple combination (with the high-affinity antibody added). In contrast, combinations lacking the long-half-life antibody rebound earliest, confirming that the most sensitive parameters dominate treatment durability. Mechanistically, neutralization of viral entry is the primary driver of sustained suppression. CTL enhancement contributes only marginally when neutralization is intact, but provides a compensatory protective effect when neutralization is partially compromised. These findings establish a quantitative framework for rational bNAb combination design, showing that optimizing the most sensitive parameters matters more than simply increasing the number of antibodies.

