biostudies-literatureAdenekan OKnut och Alice Wallenbergs StiftelseNational Institute of General Medical SciencesNIGMS NIH HHSNational Science Foundation4356-4367https://www.ebi.ac.uk/biostudies/studies/S-EPMC12709397biostudies-literatureUnknown124(23)Single-event completion times, such as are estimated in viral entry, offer both promise and challenge to kinetic interpretation. The promise is that they constrain underlying kinetic models much more efficiently than bulk kinetics, but the challenge is that completion times alone can incompletely determine complex reaction topologies. Gamma distributions or mechanistic models have often been used to estimate kinetic parameters for such data, but the gamma distribution relies on homogenous processes to explain the rate-limiting behavior of the system. Here, we introduce hypoexponential analysis to estimate heterogeneous kinetic processes. We demonstrate that hypoexponential models can indeed estimate rate constants separated by two to three orders of magnitude. We then apply this approach tBiophysical journalUnmasking complex kinetics in viral entry by inferring hypoexponential models.PMC127093972021791KAW 2020.0209R01GM138444R01 GM138444Adenekan OKasson PMfalseUnmasking complex kinetics in viral entry by inferring hypoexponential models.Single-event completion times, such as are estimated in viral entry, offer both promise and challenge to kinetic interpretation. The promise is that they constrain underlying kinetic models much more efficiently than bulk kinetics, but the challenge is that completion times alone can incompletely determine complex reaction topologies. Gamma distributions or mechanistic models have often been used to estimate kinetic parameters for such data, but the gamma distribution relies on homogenous processes to explain the rate-limiting behavior of the system. Here, we introduce hypoexponential analysis to estimate heterogeneous kinetic processes. We demonstrate that hypoexponential models can indeed estimate rate constants separated by two to three orders of magnitude. We then apply this approach t2025-01-01T00:00:00Z2025 Dec2026-06-09T04:49:02.737Z2026-06-09T03:07:28.326ZS-EPMC127093974113995610.1016/j.bpj.2025.10.035