A large-scale Boolean model of the rheumatoid arthritis fibroblast-like synoviocytes predicts drug synergies in the arthritic joint

Abstract

Rheumatoid arthritis (RA) is a complex autoimmune disease with an unknown aetiology. However, rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS) play a significant role in initiating and perpetuating destructive joint inflammation by expressing immuno-modulating cytokines, adhesion molecules, and matrix remodelling enzymes. In addition, RA-FLS are primary drivers of inflammation, displaying high proliferative rates and an apoptosis-resistant phenotype. Thus, RA-FLS-directed therapies could become a complementary approach to immune-directed therapies by predicting the optimal conditions that would favour RA-FLS apoptosis, limit inflammation, slow the proliferation rate and minimise bone erosion and cartilage destruction. In this paper, we present a large-scale Boolean model for RA-FLS that consists of five submodels focusing on apoptosis, cell proliferation, matrix degradation, bone erosion and inflammation. The five-phenotype-specific submodels can be simulated independently or as a global model. In silico simulations and perturbations reproduced the expected biological behaviour of the system under defined initial conditions and input values. The model was then used to mimic the effect of mono or combined therapeutic treatments and predict novel targets and drug candidates through drug repurposing analysis.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

“…Lastly, integrating both pathway and cell models in a multicellular-multiscale model helped reveal the impact of mutations of FADD and p38 on the cellular death of epithelial cells upon infection and the recruitment of immune cells. Whereas these results demonstrate the value of COVID-19 disease logical models for generating new hypotheses and understanding of disease mechanisms, they also provide an important tool set for preclinical discovery and testing of targeted drugs and drug combinations, as demonstrated in several studies (7,(66)(67)(68). Insilico model simulations can prescreen many drug combinations, with the best-performing candidates advancing to further preclinical testing.…”

“…The map is an entry point for analytical and modelling workflows to identify actionable targets for novel or repurposed compounds that can mitigate the viral infection or alleviate COVID-19 symptoms. Similar workflows have been used to study immune and chronic diseases (6,(7)(8)(9), focusing either on omic data analysis and integration, network analysis, mathematical modelling or drug repurposing (Figure 1). This work presents a full range of potential analyses enabled by C19DMap.…”