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Stochastic approaches are required for the simulation of biochemical systems like signal transduction networks, since high fluctuations and extremely low particle numbers of some species are ubiquitous. Computational problems arise from the huge differences among the timescales on which the reactions occur, causing high cost for stochastically exact simulations. Here, we demonstrate a general hybrid method combining the exact Gillespie algorithm with a system of stochastic differential equations (SDEs). This technique provides a smooth and correct transition between subsets of ’slow’ and ’fast’ reactions instead of abruptly cutting the stochastic effects above a certain particle number. The method was successfully applied to mitochondrial Cytochrome C release in the CD95-induced apoptosis pathway. Moreover, this approach can also be used for other kinds of Markov processes.

Purpose For 30 years nature has provided a plethora of natural products with potential meaningful anti-cancer activity. Fusarochromanone (FC101a) is a small molecule fungal metabolite exhibiting potent in-vitro growth inhibitory effects and is capable of inducing apoptosis, suppressing angiogenesis and tumorigenesis, and inhibiting endothelial cell growth in multiple cancer cell lines. Despite all we know regarding FC101a, the mechanism of action and molecular target(s) of this compound have remained an enigma. Furthermore, modest in-vivo activity has been documented and requires addressing. Method Early stage pharmacokinetics (PK) assessment is vital to successful drug development. Herein, we aimed to use in-silico assays to i) characterize an in-depth ADMET profile of FC101a and ii) to probe for possible therapeutic targets. Two-dimensional SDF files of FC101a and 13 analogs were introduced into ADMET Predictor Version 7.1 that parses the structures in order to calculate molecular descriptors, which are used to estimate ADMET properties. Calculated ADMET values were analyzed and subjected to multiple drug-like indices, delivering a PK profile of each analog. To probe for possible targets, a total of 49 proteins were introduced into SYBYL-X Version 2.0 platform and the deepest binding pocket of each protein was virtually docked with parent compound, FC101a; with the negative control, FC101b; and with the model compound, kynurenine. Results Each analog showed promising ADMET qualities, although FC101 Oxazole was identified as the most optimized analog. Despite FC101a having a desirable ADME and toxicity profile, areas of concern were identified and must be addressed in-vitro. These include potential mutagenic properties and estrogen receptor toxicity. We provide potential avenues medicinal chemists could use to achieve higher effective permeation, higher blood brain barrier (BBB) penetration, and higher aqueous solubility in FC101a. Molecular docking assays revealed procaspase-8 - cFLIP(L) complex as a potential biological target and led to proposed mechanisms of action by which FC101a facilitates procaspase-8 heterodimerization, thereby increasing proteolytic activity and up regulating extrinsic apoptosis. Conclusion Our data revealed both potential mechanisms of action and a promising ADMET profile of FC101a. These attributes render FC101a a promising lead candidate for development into a low toxic anti-cancer agent effective against a broad range of cancers.