Back

Heparin as an Anti-Inflammatory Agent

Litov, L.; Petkov, P.; Rangelov, M.; Ilieva, N.; Lilkova, E.; Todorova, N.; Krachmarova, E.; Malinova, K.; Gospodinov, A.; Hristova, R.; Ivanov, I.; Nacheva, G.

2020-07-29 molecular biology
10.1101/2020.07.29.223859 bioRxiv
Show abstract

Timely control of the cytokine release syndrome (CRS) at the severe stage of COVID-19 is key to improving the treatment success and reducing the mortality rate. The inhibition of the activity of the two key cytokines, IFN{gamma} and IL-6, can significantly reduce or even reverse the development of the cytokine storm. The objective of our investigations is to reveal the anti-inflammatory potential of heparin for prevention and suppression of the development of CRS in acute COVID-19 patients. The effect of low-molecular-weight heparin (LMWH) on IFN{gamma} signalling inside the stimulated WISH cells was investigated by measuring its antiproliferative activity and the translocation of phosphorylated STAT1 in the nucleus. The mechanism of heparin binding to IFN{gamma} and IL-6 and therefore inhibition of their activity was studied by means of extensive molecular-dynamics simulations. We find that LMWH binds with high affinity to IFN{gamma} and is able to inhibit fully the interaction with its cellular receptor. It also influences the biological activity of IL-6 by binding to either IL-6 or IL-6/IL-6R thus preventing the formation of the IL-6/IL-6R/gp130 signaling complex. Our conclusion is that heparin is a potent anti-inflammatory agent that can be used in acute inflammatory conditions, due to its potential to inhibit both IFN {gamma} and IL-6 signalling pathways. Based on our results and available clinical observations, we suggest the administration of LMWH to COVID-19 patients in the initial stages of the acute phase. The beginning of the treatment and the dosage should be based on a careful follow-up of the platelet count and the D-dimer, IL-6, IFN, T-cells, and B-cells levels.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
PLOS ONE
5266 papers in training set
Top 16%
11.9%
2
Journal of Molecular Graphics and Modelling
17 papers in training set
Top 0.1%
9.7%
3
Journal of Biomolecular Structure and Dynamics
43 papers in training set
Top 0.2%
7.9%
4
International Journal of Molecular Sciences
494 papers in training set
Top 0.5%
7.9%
5
Scientific Reports
3612 papers in training set
Top 15%
5.5%
6
Biomolecules
100 papers in training set
Top 0.1%
4.9%
7
Computational and Structural Biotechnology Journal
242 papers in training set
Top 1%
4.1%
50% of probability mass above
8
Pharmaceuticals
34 papers in training set
Top 0.2%
3.3%
9
Frontiers in Immunology
638 papers in training set
Top 5%
2.4%
10
Viruses
332 papers in training set
Top 2%
2.4%
11
Molecules
39 papers in training set
Top 0.4%
2.4%
12
Journal of Thrombosis and Haemostasis
32 papers in training set
Top 0.2%
2.1%
13
Biochimie
25 papers in training set
Top 0.2%
2.1%
14
PLOS Computational Biology
1863 papers in training set
Top 13%
2.1%
15
Cells
249 papers in training set
Top 3%
1.7%
16
Frontiers in Molecular Biosciences
102 papers in training set
Top 0.7%
1.7%
17
International Journal of Biological Macromolecules
76 papers in training set
Top 0.9%
1.7%
18
Biomedicines
67 papers in training set
Top 1%
1.7%
19
Biochemical Pharmacology
20 papers in training set
Top 0.2%
1.3%
20
Pathogens
56 papers in training set
Top 1%
1.1%
21
Journal of Biosciences
15 papers in training set
Top 0.2%
0.8%
22
Life
29 papers in training set
Top 0.9%
0.8%
23
Biochimica et Biophysica Acta (BBA) - Biomembranes
36 papers in training set
Top 0.3%
0.8%
24
Medical Research Archives
11 papers in training set
Top 0.7%
0.6%
25
Communications Biology
993 papers in training set
Top 34%
0.6%
26
Journal of Chemical Information and Modeling
238 papers in training set
Top 3%
0.6%
27
Frontiers in Physiology
106 papers in training set
Top 3%
0.6%