Comparative study of the interaction of ivermectin with proteins of interest associated with SARS-Co
Comparative study of the interaction of ivermectin with proteins of interest associated with SARS-CoV-2: A computational and biophysical approach
The SARS-CoV-2 pandemic has accelerated the study of existing drugs. The mixture of homologs called ivermectin (avermectin-B1a [HB1a] + avermectin-B1b [HB1b]) has shown antiviral activity against SARS-CoV-2 in vitro. However, there are few reports on the behavior of each homolog. We investigated the interaction of each homolog with promising targets of interest associated with SARS-CoV-2 infection from a biophysical and computational-chemistry perspective using docking and molecular dynamics. We observed a differential behavior for each homolog, with an affinity of HB1b for viral structures, and of HB1a for host structures considered. The induced disturbances were differential and influenced by the hydrophobicity of each homolog and the binding pockets. We present the first comparative analysis of the potential theoretical inhibitory effect of both avermectins on biomolecules associated with COVID-19 and suggest that ivermectin through its homologs, has a multiobjective behavior.
SARS-CoV-2 is a novel virus belonging to the β-Coronavirus genus of the 2B group of the Coronaviridae family. This interesting virus contains only 29 proteins, 26 of which have been successfully expressed for in vitro studies to determine targets of interest for drug discovery . For example, the conserved cysteine protease Mopar has been highlighted as an exciting target as it mediates the maturation cleavage of polyproteins during virus replication [2,3].
Despite great successes in the production and roll-out of vaccines against SARS-CoV-2, new variants are on the rise and there is still no globally accepted treatment for COVID-19 (https://www.who.int/publications/i/item/WHO-2019-nCoV-clinical-2021-1). During the last year, many laboratories focused on screening FDA-approved drugs for quick implementation in clinical settings [, , ]. A compound of interest from such work is the racemic mixture ivermectin, typically used to treat helminth infections. Most of the studies on the macrocyclic lactone ivermectin only consider the major constituent B1a in their dockings . However, ivermectin is an approximately 80:20 mixture of two homolog derivatives of the compound avermectin B1, called 22,23-dihydro-avermectin B1a (HB1a) and B1b (HB1b) correspondingly, which differ in the presence of a sec-butyl and isopropyl group, at the C25 position, respectively (Fig. 1). Interestingly, this mixture has demonstrated in vitro antiviral activity against several single-stranded RNA viruses, such as Zika virus, dengue virus, Chikungunya virus, avian influenza A virus, Porcine Reproductive and Respiratory Syndrome virus, human immunodeficiency virus type 1, among others, including SARS-CoV-2 .
As the nuclear import for macromolecules is facilitated by importins, the structures of importin α1 subunit (PDB: 5KLR) from Mus musculus and importin β1 subunit (PDB: 2P8Q) from Homo sapiens were used as a model for the members of the nuclear import superfamily. The host nuclear import system can be bound and sequestered by pathogens such as SARS-CoV-2 allowing the transportation of viral proteins to the host nucleus leading to increased viral replication [, , , ]. Additionally, we also consider the multi-functional helicase (nsp13) of SARS-CoV-2 responsible for viral replication (PDB: 6ZSL) [, , ], and the main protease (Mopar) of SARS-CoV-2 (PDB: 6LU7) as it is a key enzyme of coronaviruses and has a fundamental role in mediating viral replication and transcription, making it an attractive target for drugs [11,, , , ]. All structures were obtained in PDB format from the RCSB protein database (https://www.rcsb.org/). The homologs structures of HB1a (CID_6321424) and HB1b (CID_6321425) that make up ivermectin was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/) in SDF format, and the SMILES online converter was used (https://cactus.nci.nih.gov/translate/) to get a PDB format. To avoid confusion throughout the study, we only refer to ivermectin when mentioning the mixture of homologs (a mixture of approximately 80:20 of the two homologs derivatives of the compound avermectin B1, called 22,23-dihydro-avermectin B1a and B1b), while for the individual study of each homolog, the type of avermectin analyzed (HB1a or HB1b) was always indicated. For a comparison between the ADME profiles of the avermectin homologs, the PubChem databases (https://pubchem.ncbi.nlm.nih.gov/) were used; SwissADME (www.swissadme.ch/) and the Molinspiration Property Engine v2018.10 (https://www.molinspiration.com/).
2.2. Comparative molecular docking
We performed a comparative analysis using five popular molecular docking models for a rigorous prediction of the standard free energy (ΔG) of binding of ligand-protein complexes. The complexes were built in the programs MTiAutoDock (https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::MTiAutoDock), webinar (https://durrantlab.pitt.edu/webina/), DINC 2.0 (http://dinc.kavrakilab.org/), COACH-D (https://yanglab.nankai.edu.cn/COACH-D/) and doctor (https://dockthor.lncc.br/v2/) were used. They all represent some of the basic, improved, and more advanced versions of molecular docking associated with the efficient AutoDock algorithm either in the sampling stage, blind docking, or in the scoring function. To increase accuracy, a minimum of 10 runs per program was performed which implied approximately 106 evaluations per run. The rest of the parameters were considered by default. Additionally, to validate the docking results, the Pose&Rank server (https://modbase.compbio.ucsf.edu/poseandrank/) was used to score the protein-ligand complexes, using the statistical scoring function dependent on the atomic distance RankScore. As usual, all the water molecules were removed and the PDB files were separated into two different files, one containing the protein and the other containing the ligand structure. Only the three runs with the most favorable berth were considered in the sampling of the probabilistically most feasible and thermodynamically most favorable positions in the complexes. This criterion was used to discriminate the complexes that would be subjected to further analysis, including potential theoretical inhibition and molecular dynamics.
2.3. Comparative analysis of the hydrophobic characteristics
We use PockDrug-Server that predicts the drug delivery capacity in the pockets considering the Kyte-Doolittle Pocket Hydrophobicity Scale . The hydrophobic characteristics of the binding sites were also analyzed using Biovia Discovery Studio 2021 .
2.4. Comparative analysis of theoretical Inhibition
The binding constant K from the binding free energy was calculated as described [11,25] from the following equation:(1)K=e−∆G/RT
Results and discussion
3.1. Molecular Docking of HB1a and HB1b
Most of the computational studies aimed at predicting the best molecular docking for SARS-CoV-2 proteins have focused on the use of algorithms based on AutoDock Vina (ADV). ADV has an improved scoring function of the knowledge-based AutoDock (AD) method that uses a variant of X-Score, with an adjustment using PDBbind, and also considering the inter-and intramolecular contributions, its sampling technique is based on the Iterative Local Search global optimizer, in its Broyden - Fletcher - Goldfarb - Shanno variant (BFGS) [4,, , , , , , , , , , ]. The use of the DockThor server was further proposed, which implements a grid-based method that employs a steady-state genetic algorithm for multiple solutions as a search engine and the MMFF94S force field as the scoring function for pose evaluation. This scoring function is obtained by linear regression and more sophisticated machine learning techniques for nonlinear problems using the refined set PDBbind . the doctor has demonstrated a higher success rate than exhibited by AD and ADV-based methods [55,56].
A marked energetic differential docking was observed between each homolog with each of the tested structures. All methods predicted thermodynamically favorable docking between each of the homologs and the proteins considered in this study (Table 1). Specifically, and as predicted by highly efficient and discriminatory algorithms used in the literature such as Webinar , DINC [58,59], COACH-D , and doctor [55,56,61], the existing homolog in the smallest proportion, HB1b, was the compound with the most thermodynamically favorable docking compared to Mopar followed by the helicase, while the thermodynamic union of the majority HB1a was more oriented to Importins (α1 and β1). Ivermectin has been reported to exert its antiviral effect by interfering with nuclear transport after binding with IMPα, affecting the recognition of important substrates, as well as binding to IMPβ .
There are several studies on possible targets for the controversial ivermectin, but there are few comparative reports on the behavior of avermectin homologs. Our objective was to investigate from a biophysical and computational chemical perspective the ligand-protein interactions, and the effect of these interactions on the kinetics and dynamics of the complexes predicted with each homolog. In this sense, after analysis of molecular dynamics and docking, as well as inhibitory kinetics, hydrophobicity studies, interactions between residues, RMSD, RMSF, Rg, ROG, and preliminary results under crowding, we found that each of the homologs of ivermectin could establish thermodynamically favorable dockings with each of the proteins tested in this study. Each homolog produced different changes in the thermodynamic stability of the complexes, affecting the degrees of freedom of energy transitions by mediating minimum energy conformations, with fluctuations different from those of the free proteins. We also found at a global level a theoretical individual affinity of the HB1b for the viral structures and of the HB1a for the host structures. This corresponds to the predicted inhibition kinetics which, in turn, is influenced by the hydrophobicity of the cavities in the binding pockets and by the affinity of the differential chemical groups of each homolog. The theoretical behavior of these homologs could contribute to the possible reported multi-target ivermectin activity. However, it is necessary to carry out experimental demonstrations to corroborate this differential behavior, as well as its clinical relevance.
Credited to LeninGonzález-Paz (email@example.com)
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