Chloroquine and COVID-19—A systems biology model uncovers the drug’s detrimental effect on autophagy and explains its failure
OrsolyaKapuy ,Tamás Korcsmáros
Abstract
The COVID-19 pandemic caused by SARS-CoV-2 has resulted in an urgent need for identifying potential therapeutic drugs. In the first half of 2020 tropic antimalarial drugs, such as chloroquine (CQ) or hydroxochloroquine (HCQ) were the focus of tremendous public attention. In the initial periods of the pandemic, many scientific results pointed out that CQ/HCQ could be very effective for patients with severe COVID. While CQ and HCQ have successfully been used against several diseases (such as malaria, autoimmune disease and rheumatic illnesses); long term use of these agents are associated with serious adverse effects (i.e. inducing acute kidney injury, among many others) due to their role in blocking autophagy-dependent self-degradation. Recent experimental and clinical trial data also confirmed that there is no sufficient evidence about the efficient usage of CQ/HCQ against COVID-19. By using systems biology techniques, here we show that the cellular effect of CQ/HCQ on autophagy during endoplasmic reticulum (ER) stress or following SARS-CoV-2 infection results in upregulation of ER stress. By presenting a simple mathematical model, we claim that although CQ/HCQ might be able to ameliorate virus infection, the permanent inhibition of autophagy by CQ/HCQ has serious negative effects on the cell. Since CQ/HCQ promotes apoptotic cell death, here we confirm that addition of CQ/HCQ cannot be really effective even in severe cases. Only a transient treatment seemed to be able to avoid apoptotic cell death, but this type of therapy could not limit virus replication in the infected host. The presented theoretical analysis clearly points out the utility and applicability of systems biology modelling to test the cellular effect of a drug targeting key major processes, such as autophagy and apoptosis. Applying these approaches could decrease the cost of pre-clinical studies and facilitate the selection of promising clinical trials in a timely fashion.
Introduction
The recent coronavirus infection related disease (COVID-19) has rapidly became a global pandemic by March 2020 [1, 2]. Due to the severity of the pandemic, there was an urgent need for finding effective treatments using medicines already on the market [3, 4]. Alongside the development of vaccines against COVID-19, there have been intensive attempts to discover effective drugs that slow down the spread of disease or decrease its severity [5, 6].
COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [7]. The illness might be mild or severe, often depending on the consequence of age associated diseases or other chronic diseases (i.e. cardiovascular pulmonary, diabetes or immune compromised conditions) [8, 9]. COVID-19 patients with more severe disease have also been found to experience a so-called cytokine storm leading to severe lung damage with fatal consequences [10, 11].
Materials and methods
A systems-level view can be developed by bringing together the components and interactions reported in the literature. The schematic description about building up our mathematical model is seen on Fig 1. Our wiring diagrams are independent of identity of molecular players including only the relevant systems-level feedback loops.
Results and discussion
A control network models the CQ/HCQ treatment related inhibition of autophagy regulation with respect to ER stress We created mathematical models to understand the dynamic characteristic of the regulatory network of the ER cellular stress response mechanism. Although we know that there are three sensors of the ER stress induced signal transduction pathway, for simplicity, in this analysis, according to our previous model [18, 51], we claim that ER stress is induced via two ER stress sensors (see Fig 1A). The two ER stress sensors help each other through a positive feedback loop. While one sensor more powerfully activates autophagy-dependent survival, the other is more supportive of apoptosis. However, to better understand the dynamic behaviour of the autophagy-dependent survival mechanism following CQ/HCQ treatment, here we also considered the steps of autophagosome formation. In our reductionist model we state that ER stress sensors promote a so-called autophagy controller (this includes all the cellular elements which can induce the stress response mechanism, such as Beclin1, Atg14, Vps34). This autophagy controller is able to form an active autophagosome by making a complex with an autophagy inducer. This autophagy inducer includes all the components that are essential for the autophagosome formation but not directly activated by the stress response mechanism, i.e. ATG12 and LC3. The active autophagosome can induce the survival process in our model via a so-called autophagy effector (see Fig 2A). For simplicity we assume that this apoptosis effector includes all the components which are crucial for a fatal decision (for details about the references of the regulatory connections and codes and software used for simulations see the Materials and Methods and S1-S2 Text, S1 Table in S1 File).
Conclusions
The COVID-19 pandemic caused by SARS-CoV-2 has turned into a worldwide public health priority. In the last year, hundreds of papers have been published focusing on the development of effective treatments against COVID-19 [63]. In addition, many experimental studies have tried to identify both novel or existing drugs to slow down the pandemic. However, theoretical analyses have been largely overlooked. An excellent example of this scientific problem is the case of CQ and HCQ, two well-known antimalarial drugs [20, 38]. They were quickly started to be used in the clinics as an effective drug for treating SARS-CoV-2 in early 2020. Although CQ/HCQ seems to be an important therapeutical option for several autoimmune diseases, recently it has revealed that these drugs had too many negative side effects to use against COVID-19 [6, 38]. Corresponding to various diseases (such as rheumatism and malaria) the slow pharmacokinetics of CQ/HCQ suggest a long-treatment during SARS-CoV-2 infection, too [64]. While novel scientific results show the importance of CQ/HCQ treatment at an early stage of infection [36], the dynamical characteristic of this treatment has not been studied.
Citation: Kapuy O, Korcsmáros T (2022) Chloroquine and COVID-19—A systems biology model uncovers the drug’s detrimental effect on autophagy and explains its failure. PLoS ONE 17(4): e0266337. https://doi.org/10.1371/journal.pone.0266337
Editor: Vladimir Trajkovic, Faculty of Medicine, University of Belgrade, SERBIA
Received: August 12, 2021; Accepted: March 19, 2022; Published: April 7, 2022
Copyright: © 2022 Kapuy, Korcsmáros. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting information files.
Funding: The work of O.K. was financially supported by the National Research, Development and Innovation Fund of Hungary under Grant FK 134267. The work of T.K. was supported by the Earlham Institute (Norwich, UK) in partnership with the Quadram Institute (Norwich, UK) and strategically supported by a UKRI BBSRC UK grant (BB/CSP17270/1). T.K. was also supported by a BBSRC ISP grant for Gut Microbes and Health BB/R012490/1 and its constituent projects, BBS/E/F/000PR10353 and BBS/E/F/000PR10355. The authors thank Dr. John Thomas for critical reading of the revised version of the manuscript. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0266337#abstract0
