COVID-19 liver and gastroenterology findings: An in silico analysis of SARS-CoV-2 interactions with liver molecules

World J Hepatol. 2022 Jun 27;14(6):1131-1141. doi: 10.4254/wjh.v14.i6.1131.

Abstract

Background: Coronavirus disease 19 (COVID-19) has not only been shown to affect the respiratory system, but has also demonstrated variable clinical presentations including gastrointestinal tract disorders. In addition, abnormalities in liver enzymes have been reported indicating hepatic injury. It is known that severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) might infect cells via the viral receptor angiotensin-converting enzyme 2 (ACE2) which is expressed in several organs including the liver. The viral Spike glycoprotein binds to ACE2 and must be cleaved by Furin and Type 2 Serine Protease to enter the cells. After that, the Akt/mTOR signaling pathway is activated and several COVID-19 changes are triggered.

Aim: To analyze liver and gastrointestinal symptoms and cell signaling pathways triggered by SARS-CoV-2 infection due to virus-liver interactions in silico.

Methods: In this in silico study, the three-dimensional structures of the Akt, mTORC1 and Furin (receptors) were selected from the Protein Data Bank (PDB) and the structures of inhibitors (ligands) MK-2206, CC-223 and Naphthofluorescein were selected from PubChem and ZINC databases. Ligand files were downloaded as 2D structures and converted to optimized 3D structures using ViewerLite 4.2 software. Marvin Sketch® software was used to calculate prediction of the protonated form of inhibitors in a physiological environment (pH 7.4). AutoDock Tools (ADT) software was used to calculate and delimit the Grid box used in the molecular docking of each structure selected in the PDB. In addition, protonated ligands were prepared for molecular docking using ADT software. Molecular docking was performed using ADT software tools connected to Vina software. Analysis of the amino acid residues involved in ligand interactions, as well as ligand twists, the atoms involved in interactions, bond type and strength of interactions were performed using PyMol® and Discovery Studio® (BIOVIA) software.

Results: Molecular docking analysis showed that the mTORC1/CC-223 complex had affinity energy between the receptor and ligand of -7.7 kcal/moL with interactions ranging from 2.7 to 4.99 Å. There were four significant chemical bonds which involved two of five polypeptide chains that formed the FKBP12-Rapamycin-Binding (FRB) domain. The strongest was a hydrogen bond, the only polar interaction, and Van der Waals interactions shown to be present in 12 residues of mTORC1's FRB domain. With regard to the Akt/MK-2206 complex there were three Van der Waals interactions and 12 chemical bonds in which seven residues of Akt were involved with all five rings of the MK-2206 structure. In this way, both ASP 388 and GLN 391 bind to the same MK-2206 ring, the smaller one. However, LYS 386 had four chemical bonds with the inhibitor, one with each structure ring, while LYS 387 binds two distinct rings. One of the MK-2206 inhibitor's rings which binds to LYS 387 also binds simultaneously to ILE 367 and LEU 385 residues, and the fifth ring of the structure was involved in a bond with the ALA 382 residue. The hydrogen bonds were the shortest bonds in the complex (2.61 and 3.08 Å) and all interactions had an affinity energy of -8.8 kcal/moL. The affinity energy in the Furin/Naphhofluorescein complex was -9.8 kcal/moL and involved six interactions ranging from 2.57 to 4.98 Å. Among them, two were polar and the others were non-polar, in addition to twelve more Van der Waals interactions. Two distinct hydrogen bonds were formed between Furin and its inhibitor involving GLN 388 and ALA 532 residues. ALA 532 also binds to two distinct rings of Naphthofluorescein, while TRP 531 residue has two simultaneous bonds with the inhibitor.

Conclusion: Liver infection and signaling pathways altered by SARS-CoV-2 can be modulated by inhibitors that demonstrate significant interaction affinity with human proteins, which could prevent the development of infection and symptoms.

Keywords: Bioinformatics; COVID-19; Cell signaling pathway; Liver injury; SARS-CoV-2.