Structural analysis of in silico mutant experiments of human inner-kinetochore structure

Henze, Richard; Huwald, Jan; Mostajo, Nelly; Dittrich, Peter; Ibrahim, Bashar

doi:10.1016/j.biosystems.2014.11.004

Cited by 7 publications

(2 citation statements)

References 60 publications

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“…NetLogo allows users to write their own extensions. However, it cannot incorporate formal rule-based languages such as BNGL (BioNetGen language) [10] or Kappa [16], nor molecular structure and geometry (for details, see [47,49,50,54,55,71,126]). In addition, it is challenging to handle very large network models or very low concentrations of agents with stochastic rules [68,74,75].…”

Section: Spatial Propertiesmentioning

confidence: 99%

Trends in mathematical modeling of host–pathogen interactions

Ewald

Sieber

Garde

et al. 2019

Cell. Mol. Life Sci.

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Pathogenic microorganisms entail enormous problems for humans, livestock, and crop plants. A better understanding of the different infection strategies of the pathogens enables us to derive optimal treatments to mitigate infectious diseases or develop vaccinations preventing the occurrence of infections altogether. In this review, we highlight the current trends in mathematical modeling approaches and related methods used for understanding host-pathogen interactions. Since these interactions can be described on vastly different temporal and spatial scales as well as abstraction levels, a variety of computational and mathematical approaches are presented. Particular emphasis is placed on dynamic optimization, game theory, and spatial modeling, as they are attracting more and more interest in systems biology. Furthermore, these approaches are often combined to illuminate the complexities of the interactions between pathogens and their host. We also discuss the phenomena of molecular mimicry and crypsis as well as the interplay between defense and counter defense. As a conclusion, we provide an overview of method characteristics to assist non-experts in their decision for modeling approaches and interdisciplinary understanding.

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Section: Spatial Propertiesmentioning

confidence: 99%

Trends in mathematical modeling of host–pathogen interactions

Ewald

Sieber

Garde

et al. 2019

Cell. Mol. Life Sci.

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“…In addition to SAC activation, BubR1 might also have additional functions to promote fast MCC disassembly and APC/C activation when the checkpoint needs to be silenced. 59 From a systems biology point of view, there are elaborated studies for understanding SAC signaling and activation 14,15,17,[19][20][21][22][23][24][65][66][67][68][69][70][71] while it is not the case for SAC silencing. 72 The presented work can be extended as future work to include SAC silencing which similarly requires both spatial and temporal understanding from a systems-level point of view.…”

Section: Spindle Assembly Checkpoint Silencingmentioning

confidence: 99%

In silico spatial simulations reveal that MCC formation and excess BubR1 are required for tight inhibition of the anaphase-promoting complex

Ibrahim

2015

Mol. BioSyst.

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In response to the activation of the mitotic spindle assembly checkpoint (SAC), distinct inhibitory pathways control the activity of the anaphase-promoting complex (APC/C). It remains unclear whether the different regulatory mechanisms function in separate pathways or as part of an integrated signalling system. Here, five variant models of APC/C regulation were constructed and analysed. The simulations showed that all variant models were able to reproduce the wild type behaviour of the APC. However, only one model, which included both the mitotic checkpoint complex (MCC) as well as BubR1 as direct inhibitors of the APC/C, was able to reproduce both wild and mutant type behaviour of APC/C regulation. Interestingly, in this model, the MCC as well as the BubR1 binding rate to the APC/C was comparable to the known Cdc20-Mad2 binding rate and could not be made higher. Mad2 active transport towards the spindle mid-zone accelerated the inhibition speed of the APC/C but not its concentration level. The presented study highlights the principle that a systems biology approach is critical for the SAC mechanism and could also be used for predicting hypotheses to design future experiments. The presented work has successfully distinguished between five potent inhibitors of the APC/C using a systems biology approach. Here, the favoured model contains both BubR1 and MCC as direct inhibitors of the APC/C.

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