bioRxivBiophysicsPreprint
A mechanism-aware stoichiometry platform resolves functional viral thresholds and induces antiviral hypersensitivity
Gabe Clinger, Haley DurdeniD, Aaron Daurelle, Benjamin PreeceiD, Wiley Peppel, Rodrigo Gallegos, Abdul A. WaheediD, Nicole Bohne, Brian MacArthur, Abby PetersoniD, Ahmet YıldıziD, Eric O. FreediD, Saveez SaffarianiD
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Abstract
Antiviral discovery is frequently hindered by a stoichiometric blind spot--a lack of resolution regarding the functional density of viral enzymes required for replication. Traditional screening pipelines rely on target-based or phenotypic assays that cannot distinguish between simple molecular binding and the crossing of a functional stoichiometric cliff. Here, we present a mechanism-aware platform that resolves these enzymatic requirements with single-virion precision. By integrating quantitative cryo-electron microscopy and genomic validation with Monte Carlo modeling, we map the stoichiometric landscapes of HIV-1 Protease (PR) and Reverse Transcriptase (RT). We uncover a striking disparity in enzymatic demand: a high-redundancy buffering capacity for PR ([~]40 monomers) contrasted with a high-threshold requirement for RT ([~]95 subunits). We demonstrate that by systematically de-buffering the virion, our platform induces a state of antiviral hypersensitivity, enabling the detection of therapeutic activity in novel and clinical inhibitors that remain invisible to traditional workflows. Furthermore, this multiplexed profiling enables de novo target identification, as inhibitors trigger failure exclusively on their respective stoichiometric arms. This platform provides a deterministic roadmap for de-risking drug discovery and identifying viral sub-stoichiometric vulnerabilities.
- organism: human
- assay: cryo-EM
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
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