Drug repurposing for targeting fibronectin in treatment of endometriosis and cancers.

Increased concentrations of the fibronectin glycoprotein can cause ectopic tissue growth patients with endometriosis and the formation of various cancerous tumors. Furthermore, fibronectin binding to its receptors from the EDA (Extra Domain A) region contributes to promote tumorigenesis, metastasis and vasculogenesis. Thus, the EDA region can be considered a unique target for therapeutic intervention. Therefore, the present study used computational methods to identify the best fibronectin inhibitor(s) among FDA-approved drugs. First, docking-based virtual screening was performed using PyRx 0.8. Next, FDA-approved drugs that obtained favorable results in the docking phase were selected for further studies and analysis using molecular dynamics (MD) simulation. The preliminary findings of the virtual screening showed that 17 FDA-approved drugs (from 2471) had more favorable energy with their binding energy less than -9 kcal/mol. The MD simulation results of these 17 drugs showed that Avapritinib had a lower RMSD value and higher binding energy and hydrogen bonding than the other complexes in the EDA domain. Also, analyses related to the second structure changes displayed that Avapritinib in the EDA domain led to more changes in the second structure. According to the results, the anticancer drug Avapritinib forms a more stable complex with fibronectin than other FDA-approved drugs. Furthermore, this drug leads to more changes in the second EDA structure, which may have more serious potential for inhibiting EDA fibronectin.Communicated by Ramaswamy H. Sarma.

Correction to: Drug repurposing using computational methods to identify therapeutic options for COVID-19.

[This corrects the article DOI: 10.1007/s40200-020-00546-9.].

Corrigendum to ?Repurposing FDA-approved drugs to fight COVID-19 using in silico methods: Targeting SARS-CoV-2 RdRp enzyme and host cell receptors (ACE2, CD147) through virtual screening and molecular dynamic simulationsË® [Inform. Med. Unlocked 23 (2021) 1-9/100541].

[This corrects the article DOI: 10.1016/j.imu.2021.100541.].

Rational approaches to discover SARS-CoV-2/ACE2 interaction inhibitors: Pharmacophore-based virtual screening, molecular docking, molecular dynamics and binding free energy studies.

The lack of effective treatment remains a bottleneck in combating the current coronavirus family pandemic, particularly coronavirus 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The infection of host cells by SARS-CoV-2 is mediated by the binding of its receptor-binding domain (RBD) on the spike (S) glycoprotein to the host angiotensin-converting enzyme (ACE2) receptor. As all developed and available vaccines against COVID-19 do not provide long-term immunity, the creation of an effective drug for the treatment of COVID-19 is necessary and cannot be ignored. Therefore, the aim of this study is to present a computational screening method to identify potential inhibitor candidates with a high probability of blocking the binding of RBD to the ACE2 receptor. Pharmacophore mapping, molecular docking, molecular dynamics (MD) simulations, and binding free-energy analyses were performed to identify potential inhibitor candidates against ACE2/SARS-CoV-2. In conclusion, we propose the compound PubChem-84280085 as a potential inhibitor of protein-protein interactions to disrupt the binding of the SARS-CoV-2-RBD to the ACE2 receptor.

Carotenoids as potential inhibitors of TNFα in COVID-19 treatment.

Tumor necrosis factor-alpha (TNF-α) is a multifunctional pro-inflammatory cytokine, responsible for autoimmune and inflammatory disorders. In COVID-19 patients, increased TNF-α concentration may provoke inflammatory cascade and induce the initiation of cytokine storm that may result in fatal pneumonia and acute respiratory distress syndrome (ADRS). Hence, TNFα is assumed to be a promising drug target against cytokine storm in COVID-19 patients. In the present study, we focused on finding novel small molecules that can directly block TNF-α-hTNFR1 (human TNF receptor 1) interaction. In this regards, TNF-α-inhibiting capacity of natural carotenoids was investigated in terms of blocking TNF-α-hTNFR1 interaction in COVID-19 patients with the help of a combination of in silico approaches, based on virtual screening, molecular docking, and molecular dynamics (MD) simulation. A total of 125 carotenoids were selected out of 1204 natural molecules, based on their pharmacokinetics properties and they all met Lipinski's rule of five. Among them, Sorgomol, Strigol and Orobanchol had the most favorable ΔG with the best ADME (absorption, distribution, metabolism, excretion) properties, and were selected for MD simulation studies, which explored the complex stability and the impact of ligands on protein conformation. Our results showed that Sorgomol formed the most hydrogen bonds, resulting in the highest binding energy with lowest RMSD and RMSF, which made it the most appropriate candidate as TNF-α inhibitor. In conclusion, the present study could serve to expand possibilities to develop new therapeutic small molecules against TNF-α.

Effectiveness of Remdesivir in Comparison with Five Approved Antiviral Drugs for Inhibition of RdRp in Combat with SARS-CoV-2.

The treatment of COVID-19 disease has been one of the most critical essential concerns of researchers in recent years. One of the most exciting and potential therapeutic targets for SARS-CoV-2 therapy progression is RNA-dependent RNA polymerase (RdRP), a viral enzyme for viral RNA replication throughout host cells. According to some research, Remdesivir suppresses RdRp. The nucleoside medication remdesivir has been authorized under an Emergency Use Authorization to treat COVID-19. Given the role of this enzyme in virus replication, our scientific question is whether Remdesivir is the most appropriate antiviral drug to inhibit this enzyme or not. Accordingly, this study aimed to repurpose antiviral drugs to inhibition of RdRp using virtual screening and Molecular Dynamics simulation methods. Five FDA-approved antiviral medications, including Elbasvir, Glecaprevir, Ledipasvir, Paritaprevir, and Simeprevir, had good interaction potential with RdRp. Also, the results show that the number of H-bonds and contacts and ∆G interactions between the protein and ligand in the Remdesivir complex is less than those of other complexes. According to the given data which shows the tendency of binding with RdRp for Paritaprevir, Simeprevir, Glecaprevir, and Ledipasvir and Elbasvir is more than Remdesivir and due to the fact that these five drugs have a high tendency to bind to other targets in the SARS-CoV-2, the use of Remdesivir as an antiviral drug in the treatment of COVID-19 should be considered more sensitively.

In silico evidence for prednisone and progesterone efficacy in recurrent implantation failure treatment.

Increased expression and activation of tumor necrosis factor-α (TNF-α) could lead to recurrent implantation failure (RIF). Therefore, TNF-α inhibition may be a strategic way to enhance the implantation rate in women with RIF. Nowadays, monoclonal antibodies are considered an effective therapeutic method for TNF-α inhibition. Unfortunately, monoclonal antibody treatments have several disadvantages. Thus, the design of small molecules capable of inhibiting TNF-α has become critical in recent years. In silico drug repurposing of FDA-approved drugs for TNF-α inhibition was used in this study. PyRx tools were employed for virtual screening. Additionally, the free energy of binding, the number of hydrogen bonds, and the number of drug contacts with the protein were calculated using the molecular dynamics (MD) simulation method. Virtual screening results reveal that 17 of 2471 FDA-approved drugs benefited from favorable binding energy with TNF-α (delta G < - 10 kcal/mol). Two of the 17 drugs, progesterone and prednisone, were the most frequently used without adverse effects during pregnancy. As a result, MD simulation was used to investigate these two drugs further. According to the MD simulation results, prednisone appears to have a higher affinity for TNF-α than progesterone, and consequently, the prednisone complex stability is higher. For the first time, this study examined the possible role of prednisone and progesterone in inhibiting TNF-α using in silico methods.

Identification of FDA approved drugs against SARS-CoV-2 RNA dependent RNA polymerase (RdRp) and 3-chymotrypsin-like protease (3CLpro), drug repurposing approach.

The RNA-dependent RNA polymerase (RdRp) and 3C-like protease (3CLpro) from SARS-CoV-2 play crucial roles in the viral life cycle and are considered the most promising targets for drug discovery against SARS-CoV-2. In this study, FDA-approved drugs were screened to identify the probable anti-RdRp and 3CLpro inhibitors by molecular docking approach. The number of ligands selected from the PubChem database of NCBI for screening was 1760. Ligands were energy minimized using Open Babel. The RdRp and 3CLpro protein sequences were retrieved from the NCBI database. For Homology Modeling predictions, we used the Swiss model server. Their structure was then energetically minimized using SPDB viewer software and visualized in the CHIMERA UCSF software. Molecular dockings were performed using AutoDock Vina, and candidate drugs were selected based on binding affinity (∆G). Hydrogen bonding and hydrophobic interactions between ligands and proteins were visualized using Ligplot and the Discovery Studio Visualizer v3.0 software. Our results showed 58 drugs against RdRp, which had binding energy of - 8.5 or less, and 69 drugs to inhibit the 3CLpro enzyme with a binding energy of - 8.1 or less. Six drugs based on binding energy and number of hydrogen bonds were chosen for the next step of molecular dynamics (MD) simulations to investigate drug-protein interactions (including Nilotinib, Imatinib and dihydroergotamine for 3clpro and Lapatinib, Dexasone and Relategravir for RdRp). Except for Lapatinib, other drugs-complexes were stable during MD simulation. Raltegravir, an anti-HIV drug, was observed to be the best compound against RdRp based on docking binding energy (-9.5 kcal/mole) and MD results. According to the MD results and binding energy, dihydroergotamine is a suitable candidate for 3clpro inhibition (-9.6 kcal/mol). These drugs were classified into several categories, including antiviral, antibacterial, anti-inflammatory, anti-allergic, cardiovascular, anticoagulant, BPH and impotence, antipsychotic, antimigraine, anticancer, and so on. The common prescription-indications for some of these medication categories appeared somewhat in line with manifestations of COVID-19. We hope that they can be beneficial for patients with certain specific symptoms of SARS-CoV-2 infection, but they can also probably inhibit viral enzymes. We recommend further experimental evaluations in vitro and in vivo on these FDA-approved drugs to assess their potential antiviral effect on SARS-CoV-2.

Repurposing FDA-approved drugs to fight COVID-19 using in silico methods: Targeting SARS-CoV-2 RdRp enzyme and host cell receptors (ACE2, CD147) through virtual screening and molecular dynamic simulations.

BACKGROUND: Different approaches have been proved effective for combating the COVID-19 pandemic. Accordingly, in silico drug repurposing strategy, has been highly regarded as an accurate computational tool to achieve fast and reliable results. Considering SARS-CoV-2's structural proteins and their interaction the host's cell-specific receptors, this study investigated a drug repurposing strategy aiming to screen compatible inhibitors of FDA-approved drugs against viral entry receptors (ACE2 and CD147) and integral enzyme of the viral polymerase (RdRp). METHODS: The study screened the FDA-approved drugs against ACE2, CD147, and RDRP by virtual screening and molecular dynamics (MD) simulation. RESULTS: The results of this study indicated that five drugs with ACE2, four drugs with RDRP, and seven drugs with CD147 achieved the most favorable free binding energy (ΔG < -10). This study selected these drugs for MD simulation investigation whose results demonstrated that ledipasvir with ACE2, estradiol benzoate with CD147, and vancomycin with RDRP represented the most favorable ΔG. Also, paritaprevir and vancomycin have good binding energy with both targets (ACE2 and RdRp). CONCLUSIONS: Ledipasvir, estradiol benzoate, and vancomycin and paritaprevir are potentially suitable candidates for further investigation as possible treatments of COVID-19 and novel drug development.

Platelet-activating factor and antiphospholipid antibodies in recurrent implantation failure.

Recurrent implantation failure (RIF) refers to cases in which women have had the failure of the embryo implantation after several in vitro fertilization (IVF). The success rate for IVF depends on many different factors. Implantation is a complex step in a successful pregnancy. Antiphospholipid antibodies (aPLs) and platelet-activating factor (PAF) can be considered as effective factors in the embryo implantation. The first purpose of this study is to compare the levels of aPLs and PAF among RIF and fertile control women. The second purpose is evaluating correlations between the blood levels of these factors in this two groups. The levels of twelve types of aPL and PAF in peripheral blood samples of RIF and fertile control women were checked with ELISA method. The results showed that levels of Anti Cardiolipin antibody IgG was above the normal level in 3% of RIF patients. This study examined for the first time the correlation between twelve types of aPLs and PAF in RIF and fertile women. The results of these correlations show that the serum levels of aPLs affects themselves and the serum levels of PAF. The correlation of aPLs levels and PAF levels was different in the two groups. Differences in the correlations of aPLs levels and PAF levels in two groups show that the equal changes in the level of variables examined can have different effects in RIF and the fertile control groups. It is suggested that the correlation between these variables be evaluated in other studies.

COVID-19 Mediated by Basigin Can Affect Male and Female Fertility.

Coronavirus disease 2019 (COVID-19) prevalence has caused many problems in society and disrupted many regular aspects of life. COVID-19 contains major structural proteins that among them, S protein can promote fusion of the viral and cellular membranes and facilitate the entry of coronavirus into the host cells. Basigin (BSG) is one of the most important receptors for COVID-19 that mediates its entry to host cells. Also, Basigin has an important role in male and female reproduction. Basigin is expressed in the uterus and plays an important role during embryo implantation and needed for successful implantation. Therefore, disruption or inhibition of Basigin causes to a weakness in embryo implantation. Therefore, if a woman or a man is infected with COVID-19, it is recommended that they do not attempt to conception until their treatment is complete. It is also recommended tests for COVID-19 be performed on infertile couples before using assisted reproductive technology (ART).

Drug repurposing using computational methods to identify therapeutic options for COVID-19.

PURPOSE: Recently, the world has been dealing with a new type of coronavirus called COVID-19 that in terms of symptoms is similar to the SARS coronavirus. Unfortunately, researchers could not find a registered therapy to treat the infection related to the virus yet. Regarding the fact that drug repurposing is a good strategy for epidemic viral infection, we applied the drug repurposing strategy using virtual screening to identify therapeutic options for COVID-19. For this purpose, five proteins of COVID-19 (3-chymotrypsin-like protease (3CLpro), Papain-Like protease (PLpro), cleavage site, HR1 and RBD in Spike protein) were selected as target proteins for drug repositioning. METHODS: First, five proteins of COVID-19 were built by homology modeling. Then FDA-approved drugs (2471 drugs) were screened against cleavage site and RBD in Spike protein via virtual screening. One hundred and twenty-eight FDA-approved drugs with the most favorable free-binding energy were attached to the cleavage site and RBD in Spike protein. Of these 128 drugs, 18 drugs have either been used currently as antiviral or have been reported to possess antiviral effects. Virtual screening was then performed for the 18 selected drugs with ACE2, 3CLpro and PLpro and HR1 and TMPRSS2. RESULTS: According to the results, glecaprevir, paritaprevir, simeprevir, ledipasvir, glycyrrhizic acid, TMC-310911, and hesperidin showed highly favorably free binding energies with all tested target proteins. CONCLUSION: The above-mentioned drugs can be regarded as candidates to treat COVID-19 infections, but further study on the efficiency of these drugs is also necessary.

In silico identification of new inhibitors for ßeta-2-glycoprotein I as a major antigen in antiphospholipid antibody syndrome.

Beta 2 glycoprotein I (ß2GPI) is a major antigen for autoantibodies present in antiphospholipid antibody syndrome (APS). ß2GPI is a single polypeptide with five repeated domains and different conformations. The activated J-shaped conformation of ß2GPI binds to negatively charged phospholipids in the membrane via the fifth domain and causes blood clotting reactions. We applied a drug repurposing strategy using virtual screening and molecular dynamics to find the best FDA drugs against the fifth domain of ß2GPI. In the first phase, FDA drugs that had the most favorable ΔG with the fifth domain of ß2GPI were selected by virtual screening. Among these drugs that had the most favorable ΔG, Vorapaxar and Antrafenine were selected for molecular dynamics (MD) simulation studies. MD simulation was performed to evaluate the stability of Vorapaxar and Antrafenine complexes and the effect of the two drugs on protein conformation. Also, MD simulation was done to investigate the effect of Antrafenine and Vorapaxar on the binding of ß2GPI to the platelet model membrane. According to the results, Vorapaxar and Antrafenine were bound to the protein with the favorable binding energy (Vorapaxar and Antrafenine binding energies are - 49.641 and - 38.803 kcal/mol, respectively). In this study, it was shown that unlike protein alone and protein in the Antrafenine complex, the protein in the Vorapaxar complex was completely separated from the model membrane after 350 ns. Moreover, Vorapaxar led to more changes in the activated J-shape of ß2GPI. Thus, Vorapaxar can be a suitable candidate for further investigations on the treatment of APS.

Macrophage migration inhibitory factor as a potential biomarker of endometriosis.

OBJECTIVE: To evaluate the expression of MIF, CD74, and COX-2 in normal, ectopic, and eutopic endometrium during the menstrual cycle and to assess MIF level in peripheral blood. DESIGN: The expressions of MIF, CD74, and COX-2 in normal, ectopic, and eutopic endometrium were evaluated with the use of real-time polymerase chain reaction. MIF protein in peripheral blood samples was checked with the use of ELISA. SETTING: Reproductive biomedicine research center. PATIENT(S): Sixteen normal women and 20 women with endometriosis. INTERVENTION(S): Ectopic biopsies were obtained with the use of laparoscopic procedure, and eutopic and control biopsies were obtained with the use of Pipelle. Peripheral blood samples were collected before laparoscopy. MAIN OUTCOME MEASURE(S): The expression of MIF, CD74, and COX-2 in normal, ectopic and eutopic endometrium during the menstrual cycle and the expression level of MIF in peripheral blood samples. RESULT(S): Relative mRNA expression of MIF, CD74, and COX-2 were significantly higher in ectopic endometrium than in eutopic and control endometrium. Also, there were significant differences in expression of these genes in normal, ectopic, and eutopic endometrium during the menstrual cycle. Moreover, women with endometriosis had significantly higher circulating levels of MIF compared with control subjects. CONCLUSION(S): Dynamic expression of MIF, CD74, and COX-2 during the menstrual cycle could play an essential role in reproduction, inflammation, and endometrium reconstruction. A higher expression of these genes in ectopic endometrium can be considered as a molecular biomarker for endometriosis development and pathophysiology. Also, a high level of MIF in blood serum can act as a biomarker in the diagnosis of endometriosis.