Validating the effect of drugs analyzed in this paper by experimental studies and clinical trials will expedite the drug discovery process for COVID-19. Despite COVID-19 turned into a pandemic, no approved drug for the treatment or globally available vaccine is out yet. In such a global emergency, drug repurposing approach that bypasses a costly and long-time demanding drug discovery process is an effective way in search of finding drugs for the COVID-19 treatment. Recent studies showed that SARS-CoV-2 uses neuropilin-1 (NRP1) for host entry. Here we took advantage of structural information of the NRP1 in complex with C-terminal of spike (S) protein of SARS-CoV-2 to identify drugs that may inhibit NRP1 and S protein interaction. U.S. Food and Drug Administration (FDA) approved drugs were screened using docking simulations. Among top drugs, well-tolerated drugs were selected for further analysis. Molecular dynamics (MD) simulations of drugs-NRP1 complexes were run for 100 ns to assess the persistency of binding. MM/GBSA calculations from MD simulations showed that eltrombopag, glimepiride, sitagliptin, dutasteride, and ergotamine stably and strongly bind to NRP1. In silico Alanine scanning analysis revealed that Tyr Worldometers (2020). COVID-19 Coronavirus Pandemic [online]. Website: https://www.worldometers.info/coronavirus/ [accessed 05 December 2020]. The coronavirus disease-2019 (COVID-19) has symptoms of pneumonia manifesting fever, fatigue, dyspnea, chest pain, and cough which are also observed in other viral respiratory diseases . The whole-genome analysis showed that SARS-CoV-2 belongs to the Betacoronovirus genera and has a 96% genomic sequence identity to that of bat coronavirus . Despite the high genomic similarities, SARS-CoV-2 behaves more aggressively than SARS-CoV in terms of viral load, reaching the peak RNA concentration, tissue tropism, and transmission efficiency . Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected over 40 million people and resulted in more than 1.5 million deaths around the world since December 2019.1pro) first cleaves its bounds with nsp4 and nsp6, then cleaves the ORF1a and ORF1ab at 11 sites . Besides 3CLpro, nsp3  cleaves these polyproteins at three sites and completes the production of 16 nsps . SARS-CoV-2 genome is composed of a (+) sense single-strand RNA (ssRNA) with 14 open reading frames (ORFs). SARS-CoV-2 synthesizes two polyproteins, ORF1a and ORF1ab, and four structural proteins e.g., spike (S), envelop (E), matrix (M), and nucleocapsid (N) proteins and accessory proteins  . Proteolytic cleavage of ORF1a and ORF1ab by proteases leads to the production of 16 nonstructural proteins (nsps). Among nsps, nsp5  that has been accepted as the main receptor for the entry of the virus . ACE2, a membrane protein, is expressed in lung, upper and stratified epithelial cells of the esophagus, heart, kidney, testis, colon, ileum, and intestine . Despite the attenuated expression of ACE2 in elderly people, increased or unaffected severity of COVID-19 symptoms  in these people , and high viral loads in the throat  suggest the existence of an alternative receptor for the virus entry. 682Arg-Ala-Arg685) at the S1/S2 region of S protein of the SARS-CoV-2 may explain its higher transmission rate and tissue tropism. This sequence is also conserved in the S protein of various pathogenic human viruses such as Ebola, influenza, and HIV-1 . Cleavage of the S protein within the polybasic sequence, which is primed by transmembrane serine protease 2 (TMPRSS2) via furin produces S1 and S2 . FURIN mediated cleavage of S protein results in increased tropism and the infection rate of SARS-CoV-2, most probably because of the formation of new cell surface binding regions . Knocking down FURIN gene or using its inhibitor decreases the virus entry to cells and syncytia formation in the infected cells, respectively . A polybasic sequence (Arg682Arg-Ala-Arg685) sequence is aligned with [R/K]XX[R/K] motif , named as C-end rule (CendR). CendR binds and activates cell surface receptors neuropilin  . NRP1 binds to several growth factors such as vascular endothelial growth factors (VEGFs) , hepatocyte growth factor , and transforming growth factor . Among those, the interaction between NRP1 and VEGF-A165 has been extensively studied . C-terminal arginine residue and CendR motif of VEGF-A165 critically interact with b1 domain of NRP1 (NRP1-b1) in which natural and artificial NRP1 inhibitors were explored . Having a cavity on CendR binding pocket of NRP1 made it an attractive target for designing small-molecules. Several molecules blocking NRP1-VEGF interaction were developed . First designed NRP1 inhibitor, EG00229, occupied the VEGF-A binding region by directly interacting with Tyr297, Glu348, Thr349, and Tyr353 . Based on the discovered scaffold of EG00229, a more potent molecule, EG01377 was developed . Both these molecules bind to NRP1 with a very similar mode. (Arg685) on the CendR of protein S prevented the NRP1 binding . The crystallographic analysis confirmed that the binding mode of protein S’ CendR to the NRP1 is similar to the previously resolved NRP1-VEGF-A structure . Recent studies showed that interaction between NRP1 and protein S of SARS-CoV-2 is required for the SARS-CoV-2 cell entry . While coexpression of NRP1 with ACE2 and TMRPSS2 increased the infection, monoclonal antibody targeting the b1b2 extracellular domain of NRP1 significantly inhibited the infection. The stimulating effect of NRP1 on the virus infection diminished when the furin cleavage site of SARS-CoV-2 is mutated . Analysis of direct interaction between CendR peptide of protein S and NRP1 using isothermal titration calorimetry method showed that binding affinity of the complex is between 20 and 13µM depending on the pH. Mutating the critical arginine residue (Argpro RNA-dependent RNA polymerase), virus proteins taking roles on the assembly mechanism (protein E) and the release of the virus (protein M and N) are candidates for drug development and drug repurposing . Given the crucial role of NRP1 for the SARS-CoV-2 entry into the host specifically in elderly people, this in silico study aimed to repurpose FDA-approved drugs against b1 domain of NRP1 to find a promising drug to block SARS-CoV-2 infection. For this purpose, initially docking simulations were run to find drugs with high binding affinity to b1 domain of NRP1. As a control, previously identified NRP1 inhibitor, EG01377, was docked to the same pocket. While docking binding energy of the inhibitor is around –6.0 kcal/mol, over 250 drugs have –7.4kcal/mol or lower AutoDock Vina binding energy. Drugs were sorted based on docking binding energies, and an extensive literature search was done to select well-tolerated drugs for further analysis. One hundred ns molecular dynamics simulations (MD) of drug-NRP1 complexes showed that thrombopoietin receptor agonist eltrombopag, migraine drug ergotamine, drugs for type 2 diabetes sitagliptin and glimepiride, and antiandrogen dutasteride can stably interact with NRP1. Crystal structure of NRP1 in complex with EG01377 (PDB ID: 6FMF) was simulated to compare the affinity of selected drugs with its inhibitor. Binding free energy calculation using MM/GBSA method showed that selected drugs have a comparable or better affinity to NRP1 than EG01377. Alanine scanning calculations revealed Tyr297, Trp301, and Tyr353 as the critical amino acid residues for drug-NRP1 interaction. These findings may be used in experimental studies and clinical trials to test the effect of promising drugs alone or in combination with current COVID-19 treatment protocols.To date, there is no consensus on the treatment of COVID-19 yet. Since developing a new drug is costly and requiring a long period, repurposing of U.S. Food and Drug Administration (FDA) approved drugs may provide an alternative approach to find a therapeutic for the COVID-19 treatment within a reasonable time and cost. Multiple targets are available to neutralize COVID-19. For example, virus entry proteins on the host , replication machinery of the virus  (2021). The Protein Data Bank [online]. Website www.rcsb.org [accessed 18 September 2020]. . Protein was prepared for docking simulations via Dock Prep module of UCSF Chimera as described previously . Crystal water molecules were removed and if alternate locations are available for residues, the ones with the higher occupancies were selected. Rotamer library developed by Shapovalov and Dunbrack (2011) was used to complete missing side chains of amino acids, polar hydrogens were added, and nonpolar hydrogens were merged with bound atoms. Atom charges should be defined to run docking simulations. Thus, Gasteiger charges to each atom in the protein were assigned using Auto Dock Tools (ADT) (v. 1.5.6). Structures of drugs were downloaded from Zinc15 database catalogue of FDA-approved drugs. Set of drugs used in this study were imported from the U.S. Environmental Protection Agency’s (EPA) distributed structure-searchable toxicity (DSSTox) database. The 3948 drugs and NRP1 inhibitor (EG01377) were prepared for docking by using ADT suite. Inhibitor binding pocket of NRP1 was targeted for docking simulations in which grid center was placed on the center of Tyr 297, Glu348, and Tyr353 side chains with 6400 Å3of the grid box. AutoDock Vina (version 1.1.2) was used for the docking .High-resolution human NRP1 structure (PDB ID: 6FMC) was retrieved from The Protein Data Bank25Å3. Solvated protein was neutralized and then ionized with sodium-chloride salt (Na+ and Cl-) to 150 mM final concentration to mimic the physiological conditions . Twenty thousand steps of energy minimization (via conjugate gradient) was performed. The minimized system was gradually heated and then equilibrated for 1.4 ns (NPT ensemble) with constraints on the protein. Constrains starting from 2 kcal/mol/Å2 were reduced by 0.5 kcal/mol/Å2 for each 0.4 ns equilibration run. Production simulation of 100 ns for each equilibrated drug-NRP1 complex was run using 2 fs time step at 310K and 1atm pressure. Langevin thermostat and Langevin barostat maintained the temperature and pressure, respectively. To calculate the force acting on the system van der Waals (12Å cut-off) and long-range electrostatic interactions  were calculated. NAMD  software and CHARMM36m force field  were used for all MD simulations. CHARMM-GUI server was used to generate parameters of drugs . With the aid of VMD, NRP1 structure (PDB ID: 6FMF) was solvated using TIP3P water molecules in a rectangular box with edge lengths of x = 75 Å, y = 80 Å, z = 75 Å and a size of 4.50 × 10>α atoms was calculated to verify the successful equilibration of the system. 3) Contact frequency between drug and nearby amino acid residues were carried out for determining the binding residues. 4) Binding free energy (BFE) of drugs was calculated using molecular mechanics generalized born surface area (MM/GBSA) method. 5) Amino acid residue with a high contact frequency was mutated to Alanine to calculate their contribution to BFE of drugs. All MD analyses were performed and protein figures were prepared by using VMD and Pymol, respectively . RMSD trajectory tool and timeline function in VMD were used to calculate RMSD of protein and contact frequencies between drug and protein, respectively. Unstructured and highly dynamic first 9 N-terminal amino acid residues were excluded from the RMSD calculation. Analyses of protein-drug interactions were done by following these steps: 1) MD trajectory of each drug-protein simulation was visualized to inspect the position of the drug. If the drug leaves the binding pocket, that one is eliminated. 2) For simulations that drug-protein interaction was maintained for 100 ns, root mean square deviation (RMSD) of CFor MM/GBSA and Alanine scanning calculations, MMPBSA.py script of AmberTools20 was used . For each calculation, 25,000 frames from 100 ns simulations were used. BFE between drug and protein is calculated based on Equation 1:binding = Gcomplex – Greceptor – Gligand (1)ΔGcomplex : Energy of protein-drug complex, Greceptor : Energy of protein only, Gligand : Energy of unbound drug.Gpro and PLpro) and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 as targets . In addition, host proteins TMPRSS2 and ACE2 which primes protein S and mediates SARS-CoV-2 entry to host, respectively, are targeted for drug repositioning as well . To discover an antiviral drug diverse targets are available from viral replication enzymes to host proteins facilitating the virus entry and to proteins responsible for the virus release . Several in silico and in vivo drug repurposing studies are carried out using proteases (3CL682-Arg-Ala-Arg685) at the C-terminal which interacts with b1 domain of NRP1  . Mutating the critical Arg685 diminishes protein S and NRP1 binding  and antibody against b1b2 domain of NRP1 relieve the SARS-CoV-2 infection . Drugs having a high affinity to CendR binding pocket of NRP1 can be used in the COVID-19 treatment by blocking SARS-CoV-2 entry into cells. NRP1 is a recently identified receptor that facilitates the SARS-CoV-2 cell entry in coordination with ACE2 and TMPRSS2 . S protein of SARS-CoV-2 attaches to the host cells for the virus entry . When the S protein is cleaved by the host protease, S1 and S2 proteins are generated. S1 has a polybasic sequence  . Docking simulations revealed that over 100 molecules have Vina binding energies –7.6 kcal/mol or lower (Table S1). Histogram representation of Vina binding energies of all drugs are provided in . Top 15 of those drugs having the Vina binding energies between –8.5 and –8.0 kcal/mol were given in (Table 1) with their ZINC IDs, structures, and types. AutoDock Vina program was used to calculate binding energy and predict the binding mode of drugs to the target pocket as described before . During the docking simulations, receptor (NRP1) was treated as a rigid body and drugs were allowed to sample different conformations in the CendR binding pocket. NRP1 inhibitor, EG01377 , was docked to NRP1 as a control to evaluate the binding affinities of drugs against NRP1. Vina binding energy of EG01377 was calculated as –6.0 kcal/mol (Table 1). The docked conformation of EG01377 is in contact with Tyr320, Ile415, Thr316, Gly414, Tyr353, Lys351, Ser346, Thr349, Tyr297, Ser298, Trp301, Glu348, and Asn300 . Among those, hydrogen bond and pi interactions between the inhibitor and Tyr297, Tyr353, and Trp301; and van der Waals interactions generated through Ser298, Ser346, Thr316, Ile415, Gly414, Thr349, Lys351, and Asn300 were reproduced in docking pose as well. However, some hydrogen bond and pi interactions between the inhibitor and amino acids such as inhibitor-Asp320 and Glu348 in the crystal could not be observed in the docking pose. Hydrogen bond interactions between the inhibitor and Ser298, Thr349, Ser346 in the crystal were generated as van der Waals type interaction in docking conformation . Note that to compare docking position of EG01377 with that of in crystal, structure with 6FMF PDB ID was used since the binding mode of inhibitor in 6FMF was stated as free of artifact in the original study . To solidify the idea of using NRP1 inhibitor as an antiviral drug, the binding mode of S protein to NRP1 was analyzed  and compared with that of EG01377. The peptide of S protein interacts with Asp320, Tyr297, Trp301, Thr349, Lys351, Tyr353, and Ser346 of NRP1 via either of hydrogen bond, pi, and van der Waals interactions. Interaction between EG01377 and all of these amino acids shows that NRP1 inhibitor has the potential to be an antiviral drug. Furthermore, the binding poses of selected drugs occupy the pocket surrounded by Tyr297, Trp301, Lys351, and Tyr353 in docking simulations which supports the idea of these drugs may behave as NRP1 inhibitors . To evaluate the persistency and strength of drug-NRP1 complexes near physiological conditions, MD simulations were run.Docking simulations showed that, according to the descriptions in DrugBank , various types of drugs such as anticancer, antipsychotics, antiinflammatory, antibiotics, antidiabetics, and estrogen hormone may bind to NRP1 (Table S1). For further analysis, widely used drugs eltrombopag , glimepiride , dutasteride , sitagliptin , ergotamine  at the top of the docking result list, and two antimalarial drugs, mefloquine  and atovaquone , having similar binding energies to top drugs were selected. Two-dimensional diagram of interaction pattern of EG01377 in the crystal showed that it can generate hydrogen bond, or interact via van der Waals or pi interactions with Aspα atoms showed that simulations reached equilibrium around 2Å after an initial jump within 1–2 ns . In short MD simulations (20 ns) eltrombopag, glimepiride, dutasteride, sitagliptin, and ergotamine stably interacted with NRP1, however, atovaquone and mefloquine did not. These two antimalarial drugs left their initial docking positions and moved to the solution even in two independent trials. Then we extended 20 ns simulations for those who could interact with the protein in these short simulations to 100 ns to assess the stability of their interaction with NRP1. In a control simulation, the EG01377-NRP1 complex obtained from crystal (6FMF) was simulated for 100 ns. Visual inspection of long simulations showed that all selected drugs and the inhibitor retained their docking positions on the NRP1 through the entire simulation. Root mean square deviation analysis (RMSD) of C297, Trp301, Thr316, Glu348, Thr349, Lys351, Tyr353. In MD simulations, EG01377 interacted frequently with Tyr297, Trp301, Thr316, and Tyr353 which have aromatic (Tyr and Trp) and polar (Thr) side chains. In addition to these highly interacting amino acids, the inhibitor interacted with Glu348 and Thr349 through 100 ns simulation . As a result, MD simulation of EG01377-NRP1 analysis verified interacting residues in the docking. Contact frequency analysis for eltrombopag-NRP1 simulation indicated that similar to EG01377, Tyr297, Trp301, Thr316, and Tyr353 are the frequently interacting residues. The same residues were also identified in docking simulation . In addition to these highly interacting amino acids, interaction between Asp320 and eltrombopag that is identified in the EG01377-NRP1 crystal structure (6FMF) makes eltrombopag drug a prime candidate. One minor difference between EG01377 and eltrombopag simulations is that while EG01377 interacted with Gly318, eltrombopag interacted more with Gly414. To examine the interaction between drugs and critical residues, the contact frequency between drugs and selected amino acids around the binding pocket were visualized. Thus, the persistency of drug-amino acid interactions observed in the initial docking position could be assessed . Docking of EG01377 showed that the inhibitor interacts with Tyr297, Trp301, Thr316, Thr349, and Tyr353  in MD simulations. To note some interactions altered throughout the simulations. For example, interaction with highly interacting amino acids Thr349 and Lys351 fluctuated as simulations progressed. Despite slight differences in their docking positions, interacting residues in docking simulations are very similar. While glimepiride interacted with Tyr297, Trp301, Thr316, Glu348, Thr349, and Tyr353, sitagliptin fitted a deeper part of the pocket and, in addition to glimepiride’s interacting amino acids, interacted with Thr316 . Overall, nearby residues observed in docking simulations of glimepiride and sitagliptin were verified by MD simulations.Glimepiride and sitagliptin frequently interacted with the same amino acids that are Tyr297, Thr349, Lys351, and Tyr353. MD simulation of dutasteride-NRP1 showed that dutasteride behaved less similarly with the inhibitor and did not interact with Trp301 and Tyr353 after a certain time . Possibly dutasteride translated in the binding pocket and started to interact with new residues such as Gly318, Glu319, Asp320, and Ile415.The docking position of dutasteride showed that the drug interacts with Tyr297, Trp301, Thr316, and Tyr353 . In addition to these, ergotamine interacted with Asp320, Thr349, and Ile415 in certain periods of the MD simulation. In docking simulation ergotamine interacted with Tyr297, Trp301, Thr316, Ser346, Glu348, Thr349, Lys351, and Tyr353. While some of the amino acids recognized in the docking lost contact with ergotamine such as Ser346 and Glu348, most of them interacted with ergotamine in the whole MD simulation.Ergotamine showed similar interaction frequency patterns with the inhibitor and constantly interacted with TyrTo determine the binding free energy (BFE) between drugs and NRP1 MM/GBSA method was used. The BFE of eltrombopag, glimepiride, dutasteride, sitagliptin, and ergotamine was calculated as –17.11, –12.55, –9.47, –13.34, and –14.95 kcal/mol, respectively (Table 2). BFE of EG01377 was calculated as –16.19 kcal/mol. pro and RdRp of SARS-CoV-2 from our group showed that eltrombopag may bind to the active site of 3CLpro and nsp8 binding site of RdRp which may attenuate the virus activity . Eltrombopag exhibits in vitro antiviral properties with IC50 lower than 10µM . This report shows that eltrombopag can strongly interact with NRP1, as well. If these in silico findings can be verified by in vitro and cell-culture experiments, eltrombopag can be a very strong antiviral drug by blocking SARS-CoV-2-NRP1 binding to host and alleviating the virus replication.A well-tolerated drug eltrombopag stimulates platelet synthesis in patients having low blood platelet . In comparison to EG01377, eltrombopag has comparable Vina binding energy  and BFE  calculated from docking and MD simulations, respectively. During the MD simulations interacting residues of EG01377 and eltrombopag with NRP1 are very similar to each other . A previous drug-repurposing study against 3CLTwo antidiabetics, glimepiride and sitagliptin are well-tolerated drugs used to treat type2 diabetes . Both drugs have the same Vina binding energies  in docking simulations and very similar BFEs calculated from MM/GBSA analysis that are –13.34 and –12.55 kcal/mol for sitagliptin and glimepiride, respectively. Interacting amino acid residues and BFEs of these antidiabetics are quite alike to EG01377 . Sitagliptin is an inhibitor of dipeptidyl-peptidase IV (DPP-4) that is the host receptor of the Middle East respiratory syndrome (MERS)-CoV  and in silico studies suggested that protein S of SARS-CoV-2 can bind to DPP4 as well . Administration of sitagliptin to patients suffering from diabetes and COVID-19 does not only help to lower the blood glucose level but may also reduce the SARS-CoV-2 entry to the cells.301 and Tyr353 as shown in contact frequency analysis . However, dutasteride has still a high affinity to the NRP1 and interacts with amino acids observed in docking simulations. Despite further in vivo analysis needed, dutasteride may be a preventive drug that shuts down the virus entry by blocking the NRP1 and downregulating the TMPRSS2. Dutasteride, another well-tolerated drug, inhibits type I and II 5α-reductase and shows antiandrogenic activity . 5α-reductase converts testosterone to dihydrotestosterone and enlarges the prostate glands. Thus, dutasteride is used to treat prostatic conditions by blocking the 5α-reductase activity . Besides the effect on the prostate gland, dutasteride suppresses the transmembrane serine protease 2 (TMPRSS2) expression  which primes protein S of the SARS-CoV-2 . Docking binding energy and MM/GBSA calculations show that dutasteride has a high affinity to NRP1 (Tables 1 and 2). Relatively higher BFE with a high standard deviation of dutasteride-NRP1 may stem from the loss of interaction between dutasteride and two aromatic residues Trppro of SARS-CoV-2 . Ergotamine has the second-best BFE among all drugs analyzed in this study (Table 2). Comparable BFEs of ergotamine and EG01377 to NRP1 suggests that ergotamine can strongly bind to NRP1, in turn, can attenuate NRP1-protein S binding. If these computational analyses can be experimentally verified, ergotamine can be used to mitigate the COVID-19. To note, it has been reported that ergotamine may cross-react with antiviral drugs . Thus, further studies related to ergotamine should be designed accordingly.Antimigraine ergotamine is a tolerable drug with mild and transient side effects . Several in silico drug repurposing studies reported that ergotamine may inhibit the RdRp and 3CLComparable BFE and interaction pattern of inhibitor and selected drugs indicate that these drugs may act as NRP1 inhibitors.297 consistently generated pi interactions, Trp301 and Tyr353 have generated either H-bond or pi interactions with all drugs. Ser298, Thr316, Glu348, and Gly414 interacted with drugs through van der Waals interactions and generated hydrophobic interactions. Ser298 formed hydrogen bonds only with EG01377 and ergotamine. Glu348 generated pi interactions and hydrogen bonds with EG01377 and glimepiride, and only pi interactions with eltrombopag. To determine the number of hydrogen bonds drug made during the MD simulation, the hydrogen bond (H-bond) generated by drugs to any amino acids through 100 ns were analyzed . Calculation of the average number of H-bonds showed that each drug, including the inhibitor, produced less than one H-bond per frame. Interaction types between selected drugs and protein were analyzed and represented in a two-dimensional diagram . Analyses showed that the inhibitor and all drugs interact with the protein through hydrophobic interactions, and conduct hydrogen bond and at least one type of pi interaction. Since drugs of interest possess aromatic rings, charged or aromatic amino acids on NRP1 generate those interactions. TyrDespite drugs suggested to behave like NRP1 inhibitor have diverse structures, they have some common properties. For example, all drugs analyzed in details have multiple ring structures at least one with aromatic. Second, all these organic compounds bear polar groups such as carbonyl group or halogen atoms that have ability to generate hydrogen bonds or pi interactions with amino acids. Third, drugs have 70 to 110 atoms in their structure that allow them to generate high number of van der Waals interaction with the protein. These common properties of drugs cause tight binding to NRP1.297, Trp301, Thr316, and Tyr353 in all drug/inhibitor-NRP1 simulations were analyzed . These residues were mutated to Alanine one by one and BFE between drugs and NRP1 was calculated using the MM/GBSA method (Table 3). Then the difference between BFEs of drugs against mutant and wild-type NRP1 is calculated (ΔΔG). ΔΔG values larger than 0 means that mutation is destabilizing the interaction, ΔΔG lower than 0 means mutation is stabilizing the interaction. Free energy change in protein-protein interaction at equilibrium is calculated by using the following formula: ΔGᵒ= –RTlnKeq where ΔGᵒ is the standard free energy change, R is the gas constant, T is the absolute temperature. Using R = 1.987 × 10-3 kcal/mol, T = 298 K in that formula gives that increase in 0.4–0.5 kcal/mol in ΔGᵒ (ΔΔG in our data), leads to 2-fold decrease in ligand bound protein state. Thus, mutations causing ΔΔG > 0.5 kcal/mol were evaluated as critical amino acid for drug-protein binding. According to ΔΔG values, Tyr297, Trp301, and Tyr353 are very critical for all drugs binding to NRP1. Interestingly, despite high interaction with drugs, Thr316 minimally contributes to BFE. Tyr297 has the highest contribution to BFE, –4.03, –4.12, –2.24 kcal/mol, in NRP1-EG01377, eltrombopag, and dutasteride simulations, respectively. Trp301 is the second highest contributor to BFE in EG01377 , eltrombopag , and sitagliptin  simulations and top contributor to BFE in ergotamine-NRP1 simulation . Tyr353 has a similar effect on the binding of eltrombopag to NRP1 with Trp301 and contributes –2.37 kcal/mol to BFE. Tyr353 has also the highest effect on BFE in sitagliptin  and glimepiride  simulations. (Table 3). The contribution of each mutated amino acid to drug-NRP1 BFE is given . To reveal the critical amino acids for drug binding and quantify their contribution to BFE, in silico Alanine scanning mutation was performed. The most frequently and commonly interacting amino acids e.g., TyrH-bond and Alanine scanning calculations provide a deeper understanding of drug-NRP1 interactions. Future structure-activity relationship (SAR) studies aim to design a more potent NRP1 inhibitor may benefit from the critical amino acids identified here. Adding an H-bond donor or acceptor to a new molecule can increase the binding affinity to NRP1. pro and Mpro) and RNA polymerase (RdRp), or virus binding receptors on the host such as ACE2 or TMPRSS2 are generally targeted in drug repurposing studies . Recent studies reported protein S binds to NRP1 which facilitates SARS-CoV-2 host entry . Here a drug repurposing study was done against NRP1 in terms of docking and MD simulations using the FDA approved drugs. Furthermore, key amino acids on NRP1 for drug binding were identified by running Alanine scanning analysis. Several well-tolerated drugs showed comparable and even better affinity to NRP1 than its inhibitor EG01377. Eltrombopag had the best binding affinity to NRP1 among all drugs. In addition to eltrombopag, two antidiabetics, sitagliptin and glimepiride stably interacted with and exhibited high affinity to NRP1. Since patients having chronic diseases such as diabetes are at more risk against COVID-19, those suffering from diabetes may benefit from sitagliptin and glimepiride not only as antidiabetics but also their preventive effects, if proven by experiment, against SARS-CoV-2 infection. Dutasteride may provide multiple benefits to COVID-19 patients. First, it reduces the expression of TMPRSS2 that primes the S-protein . Second, in silico studies reported that it may block 3CLpro . Third, this study shows that dutasteride can bind to and strongly interact with NRP1, thus, may decrease SARS-CoV-2 entry. Ergotamine is another top candidate molecule for the NRP1 binding. Previous calculations showed that ergotamine has the potential to bind to 3CLpro and RdRp of SARS-CoV-2 . Therefore, ergotamine may inhibit SARS-CoV-2 at the infection and replication stages. Alanine scanning calculations uncovered that Tyr297, Trp301, and Tyr353  are the most critical amino acid residues for drug binding to NRP1. H-bond analysis and Alanine scanning results may be exploited by further inhibitor design studies. Despite substantial progress has been made by several companies for the SARS-CoV-2 vaccine  only several governments approved for emergency use authorization. Therefore, medication is still an essential element to combat COVID-19. Vital enzymes of SARS-CoV-2 such as proteases (3CLTo expedite the discovery of therapeutics for COVID-19 drug repurposing studies may provide a rational starting point. If the findings of this study can be verified by in vitro, in vivo, and clinical trials these well-tolerated and cost-effective drugs can be adapted to current protocols used to treat COVID-19.


AR increased the expression of 6PGD indirectly via activation of sterol regulatory element binding protein 1 (SREBP1). Accordingly, loss of 6PGD, AR or SREBP1 resulted in suppression of PPP activity as revealed by 1,2-13C2 glucose metabolic flux analysis. Knockdown of 6PGD also impaired growth and elicited death of prostate cancer cells, at least in part due to increased oxidative stress. We investigated the therapeutic potential of targeting 6PGD using two specific inhibitors, physcion and S3, and observed substantial anti-cancer activity in multiple models of prostate cancer, including aggressive, therapy-resistant models of castration-resistant disease as well as prospectively collected patient-derived tumour explants. Targeting of 6PGD was associated with two important tumour-suppressive mechanisms: first, increased activity of the AMP-activated protein kinase (AMPK), which repressed anabolic growth-promoting pathways regulated by acetyl-CoA carboxylase 1 (ACC1) and mammalian target of rapamycin complex 1 (mTORC1); and second, enhanced AR ubiquitylation, associated with a reduction in AR protein levels and activity. Supporting the biological relevance of positive feedback between AR and 6PGD, pharmacological co-targeting of both factors was more effective in suppressing the growth of prostate cancer cells than single-agent therapies. Collectively, this work provides new insight into the dysregulated metabolism of prostate cancer and provides impetus for further investigation of co-targeting AR and the PPP as a novel therapeutic strategy.Alterations to the androgen receptor (AR) signalling axis and cellular metabolism are hallmarks of prostate cancer. This study provides insight into both hallmarks by uncovering a novel link between AR and the pentose phosphate pathway (PPP). Specifically, we identify 6-phosphogluoconate dehydrogenase ( Altered cellular metabolism is a hallmark of cancer. Perhaps the best characterised metabolic transformation in malignant cells is the so-called Warburg effect, in which cancer cells favour metabolism via glycolysis rather than the more efficient oxidative phosphorylation . While WA major regulator of the unique metabolism of the normal and malignant prostate is the androgen receptor (AR) . AR is aDirect alterations to AR – including mutation, amplification, alternative splicing, and altered ligand availability – have been well characterised as mechanisms of resistance in CRPC . HoweverKLK3 gene  datasets from tissues and cell lines (6PGD expression via another downstream pathway(s) or factor(s). One credible intermediary between AR and 6PGD is SREBP1, a master transcriptional regulator of genes involved in lipid and cholesterol production  and MCF7 (breast)  and then evaluated 6PGD expression in the presence or absence of DHT. Supporting our hypothesis, either knockdown (AR binds to gene enhancers or promoters to directly regulate transcription . Howeveroduction . AR enhaoduction  and by aoduction . Additiopromoter . We mine(breast) . Regulat(breast) . To testnockdown  or inhibnockdown . We valinockdown . CollectRegulation of 6PGD by the AR signalling axis supports other recent reports linking the PPP to PCa ; and alt13C2 glucose. After 48 hr of siRNA transfection, 1,2-13C2 glucose was spiked in to growth media at a ratio of 1:1 with natural glucose and PPP flux was estimated over a period of 15 min by measuring the incorporation of 13C into the immediate product of 6PGD’s catalytic activity, ribulose 5-phosphate (Ru5P). A schematic detailing the differential incorporation of 13C isotope into Ru5P by both the oxidative  and non-oxidative  branches of the PPP is shown in To more directly investigate the involvement of 6PGD, AR, and SREBP1 in the PPP, we conducted mass spectrometry tracing experiments with 1,2-Since a key role of the PPP is to regulate intracellular redox state , we alsoHaving established that 6PGD is required for efficient activity of the PPP, optimal PCa cell growth and protection against oxidative stress, we evaluated pharmacological targeting of this enzyme as a potential therapeutic strategy. Physcion, a plant-derived anthraquinone, was recently identified as an inhibitor of 6PGD using an in vitro screening assay . TreatmeIn addition to directly promoting cell growth and survival via anabolism and limiting oxidative stress, the PPP has been reported to suppress AMPK activity by inhibiting its phosphorylation , therebyAR transcript levels  and that 6PGD can enhance the stability of AR protein, collectively revealing a positive feedback loop between androgen signalling and the PPP. The co-dependency of these pathways led us to speculate that a combinatorial targeting approach could be an effective PCa therapy. In support of this hypothesis, enzalutamide and S3 exhibited an additive effect in androgen-sensitive (VCaP) and CRPC (V16D) cell lines  underlying this observation are not known, given their expansive and diverse roles in PCa cell metabolism, it is plausible that AR and SREBP1 regulate other metabolic factors that stimulate the non-oxidative PPP. Importantly, regulation of the PPP by AR-SREBP1-6PGD has a broader clinical implication; therapeutic strategies that effectively suppress this pathway would impinge on the activity of three important oncogenic drivers with multifaceted cancer-promoting activities.Despite its role as a key downstream effector of androgen-regulated cellular metabolism, our data do not support a direct mode of transcriptional regulation of gnalling , is itsegnalling . Some meng FASN, . HoweverWe propose that AR-mediated activation of the PPP in PCa would yield additional advantages beyond the generation of key substrates for nucleic acid anabolism and the antioxidant NADPH. Most notably, PPP suppression of AMPK, itself a hub for cellular metabolic and growth control, results in augmentation of ACC1 and mTOR activity . The impIn addition to regulation of 6PGD by the androgen signalling axis, our work also revealed that 6PGD can act in a reciprocal manner to maintain AR protein levels and activity. Indeed, S3 was as effective as Enz at inhibiting the expression of some AR target genes, albeit at higher doses. We propose that this positive feedback would serve as an effective circuit to fuel PCa growth and enhance survival. Mechanistically, we demonstrated that targeting of 6PGD results in increased ubiquitylation of AR, explaining why it is decreased at the protein level. Precisely how 6PGD inhibition regulates processing of AR by the UPS is unclear. However, we note that S3 treatment increased ROS levels and activated AMPK signalling, both of which have been shown to promote AR degradation/turnover . Thus, wGiven the important role of the PPP in PCa growth and survival, established by this study in addition to earlier work , targetiSince AR-targeted therapies are not curative, there is intense interest in identifying combination therapies that would improve patient outcomes. Our work provides a solid rationale for co-targeting of AR and 6PGD; indeed, we observed synergistic effects of Enz and S3 in PCa models. Moreover, the existence of an AR:6PGD feedback loop enhances the appeal of such a combinatorial strategy. Although we acknowledge that physcion and S3 may not be useful clinical agents due to pharmacological issues, we expect that the future development of therapies that effectively suppress activity of 6PGD, or other components of the PPP, could have a major impact on PCa patients.16H12O5; 1,8-dihydroxy-3-methoxy-6-methyl-anthraquinone; emodin-3-methyl ether) and S3 , were obtained from Sigma-Aldrich , except for enzalutamide ; apalutamide (ARN-509), darolutamide (ODM-201), and Trolox . All chemicals/reagents were dissolved in dimethyl sulfoxide (DMSO) except dihydrotestosterone (DHT), which was dissolved in ethanol.Chemicals, solvents, and solutions, including physcion (CCVCL_1379), VCaP (RRID:CVCL_2235), PC3 (RRID:CVCL_0035), and 22Rv1 (RRID:CVCL_1045) human prostate carcinoma cells were obtained from the American Type Culture Collection . Dr. Amina Zoubeidi  kindly provided LNCaP-V16D  and LNCaP-MR49F  human PCa cells  with 12.5 nM siRNA in six-well plates using RNAiMAX transfection reagent , according to the manufacturer’s instructions. The siRNAs used in this study were AR ), 6PGD , SREBP1 , and Negative Control 2 #AM4637 .Gene-specific knockdown was achieved by reverse-transfection of PCa cell suspensions  and qPCR was done as described previously . GeNorm Whole-cell lysates were prepared using RIPA buffer containing cOmplete ULTRA protease and phosphatase inhibitor  and Western blotting was performed as described previously . A list 5 cells in six-well dishes (Corning) and treated with 1 µM Enz (or 0.1% DMSO control) or transfected with 12.5 nM AR siRNA (or scrambled siRNA control). Each treatment comprised four replicates. After 24 hr, the cells were collected in Trizol  or RIPA buffer + protease inhibitors . RNA extractions were completed using RNeasy Mini spin columns , according to the manufacturer’s instructions. RNA was eluted in 40 µl RNase-free H2O. RT-qPCR and western blotting were performed to verify the expected response of known AR-regulated proteins and genes, PSA/KLK3 and FKBP51/FKBP5. Subsequently, libraries were generated using 800 ng of RNA and NEXTflex Rapid Illumina Directional RNA-Seq Library Prep Kits , according to the manufacturer’s instructions. Sequencing was carried out at the South Australian Health and Medical Research Institute Genomics Facility using an Illumina NextSeq 500 (single read 75 bp v2 sequencing chemistry). The quality and number of reads for each sample were assessed with FastQC v0.11.3 , staining with Annexin V PE BD Pharmingen  and 1 mM 7-aminoactiomycin D (Thermo Fisher Scientific) and analysis by Flow Cytometry using a BD LSRFortessa X20.Cell growth curves were done using Trypan blue exclusion and manual counting of cells, as described previously . Cell vi5 cells per well into Nunclon D multi-dishes with poly-lysine coating (Thermo Fisher Scientific), with or without transfection with siPGD (Silencer Select s10394). At time of collection, cells were washed twice with 0.9% w/v NaCl, scraped in MeOH:H2O (1:1). Chloroform was added prior to vortexing, centrifuging, and collecting the aqueous layer. The aqueous layer was dried in a Savant SpeedVac (Thermo Fisher Scientific) without heat. Dried samples were resuspended in 60 µl LC-MS H2O, centrifuged at 15,000 × g at 4°C for 10 min, and supernatant transferred into HPLC vials for LCMS analysis. Samples were kept at 4°C on the autosampler tray. Glycolytic and pentose-phosphate pathway metabolites were measured using 1260 Infinity (Agilent)-QTRAP5500 (AB Sciex) LC-MS/MS system. Analyte separation was achieved using a Synergi 2.5 µm Hydro-RP 100A LC Column (100 × 2 mm) (Phenomenex) at ambient temperature. The pair of buffers used were 95:5 (v/v) water:acetonitrile containing 10 mM tributylamine and 15 mM acetic acid (Buffer A) and 100% acetonitrile (Buffer B) flowed at 200 µl/min; injection volume was 5 µl. Scheduled MRM acquisition was performed in negative mode . Raw data was extracted using MSConvert , with or without transfection of siRNAs . For the 13C-labelled glucose time-course experiment, cells were cultured for 46 hr before adding fresh media for a further 2 hr and then spiking in 1,2-13C2 glucose at a final concentration of 11 mM . Incorporation of the labelled glucose was allowed to proceed for 0, 10, 60, 120, 240, 480, or 900 s. This spike-in strategy (as opposed to media exchange) enabled a rapid time course with minimal disruption to glycolytic fluxes. Experiments were stopped by quenching the cells with ice-cold methanol:H2O (1:1) and placing plates at –20°C (prior to cell scraping). After completion of the time course, cell slurries in methanol:H2O were collected by scraping and transferred into microfuge tubes. Samples were identically processed and assayed as described for metabolomics samples, with the exception that MRMs were configured to quantify mass isotopologues of glycolytic and PPP intermediates. Fluxes through the oxidative and non-oxidative branches of PP pathway were estimated using the accumulation/dilution rate of m1 and m2 isotopologues of Ru5P. Assuming steady-state metabolism, the dilution rate (D) of Ru5P was calculated using the continuous stirred-tank reactor (CSTR) equation m representing Ru5P mass isotopologues m1 and m2 datapoints generated from the time-course experiment. D was estimated using a least-squares Monte Carlo fitting script in MATLAB. Since a Monte Carlo procedure was used to simulate dilution rates, empirical p-values were calculated using the equation: p=(r + 1)/(n + 1) (0: D - DsiCON ≥0) is true and n is the number of simulated replicates (n = 1000).LNCaP cells were seeded at a density of 7.5 × 10/(n + 1) , where r5 cells per well, six-well plate), the cells were treated with or without antioxidant (0.5 mM Trolox) and left to incubate for the indicated time . Cells were stained with CellROX Orange and SYTOX Red Stain and analysed by Flow Cytometry  using a BD LSRFortessa X20.Cellular ROS levels were measured using CellROX Orange Flow Cytometry Assay Kits (Life Technologies). Briefly, 24 hr post-seeding . Ethical approval for the use of human prostate tumours was obtained from the Ethics Committees of the University of Adelaide  and St Andrew’s Hospital . All experiments were performed in accordance with the guidelines of the National Health and Medical Research Council . The 8 mm core of tissue was dissected and prepared for ex vivo culturing as described previously . Tissues6 cells per 6 cm plate) were treated with indicated concentrations of S3 ±10 µM MG132, or 10 µM MG132 alone, for 24 hr. Cells were lysed in RIPA lysis buffer. After centrifugation for 10 min at 16,000 g, supernatants were incubated with 0.2 µg anti-AR antibody  for 16 hr at 4°C with constant rotation, followed by incubation with 20 µl protein G Sepharose beads (Thermo Fisher) for a further period of 2 hr at 4°C with constant rotation. Beads were washed twice with RIPA lysis buffer and then resuspended in 2× Laemmli sample buffer before samples were assessed by Western blotting.LNCaP cells . Briefly, images  were imported and converted into three panels using the Colour Deconvolution plug-in and vector haematoxylin and DAB staining (HDAB) commands. The Adjust Threshold plug-in was used on the DAB-only images to measure % area (positivity) and reciprocal intensity (RI). The final DAB intensity values were calculated by subtracting RI from maximal intensity (255) and multiplying by % area (positivity). Values from 20 to 70 images per treatment were measured and RI was kept constant for each patient.PDE tissue sections were evaluated for target antigens 6PGD, Ki67, and pS6 (Ser235/236) by IHC as described previously . The antData are displayed as the mean; error bars are standard error. Differences between groups were determined using GraphPad Prism with t tests or one-way ANOVA (with Tukey or Dunnett’s post hoc tests), as indicated in the figure legends. A p-value ≤ 0.05 was considered statistically significant. In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This article reports on the regulatory loop between androgen receptor and 6-phosphogluconate dehydrogenase which is a rate-limiting enzyme in the pentose phosphate pathway. Evidence is provided that modulation of 6-phosphogluconate dehydrogenase by androgen receptor is mediated by sterol regulatory element binding protein 1. Moreover, 6-phosphogluconate dehydrogenase appears to be essential for the survival of prostate cancer cells while its expression is elevated in prostate cancer patient specimens. Overall, it was thought that this study is of broad interest inasmuch as it highlights previously unappreciated role of androgen receptor in metabolic reprogramming in neoplasia of the prostate, thus suggesting potentially targetable metabolic vulnerabilities.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Ivan Topisirovic as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Erica Golemis as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Luke Gaughan (Reviewer #3).Thank you for submitting your article "A feedback loop between the androgen receptor and 6-phosphogluoconate dehydrogenase (6PGD) drives prostate cancer growth" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.As the editors have judged that your manuscript is of interest, but as described below that additional experiments are required before it is published, we would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv  along with this decision letter and a formal designation that the manuscript is "in revision at eLife". Please let us know if you would like to pursue this option. Summary:In this article, Gillis et al. provide evidence suggesting that androgen receptor (AR) targets 6-phosphogluconate dehydrogenase (6PGD), a key enzyme in the pentose phosphate pathway (PPP). In prostate cancer cells, 6PGD levels decrease upon AR depletion but not after enzalutamide treatment. The authors further show that this AR-mediated control of 6PGD levels is regulated by SREBP1. 6PGD depletion or pharmacologic inhibition induce prostate cancer cell death, likely by increasing ROS. Moreover, the authors report that pharmacological inhibition of 6PGD coincides with AR downregulation, thus suggesting an AR/SREBP1/6PGD feedforward loop. 6PGD inhibition also appears to induce AMPK, thereby suppressing mTOR signaling and acetyl-CoA carboxylase (ACC1). Finally, the authors provide evidence that the combination of 6PGD inhibitors with AR antagonists may provide a stronger anti-neoplastic response, thereby highlighting the PPP as a potentially targetable metabolic vulnerability in prostate cancer. This is further corroborated by the findings that 6PGD is upregulated in prostate cancer patient samples. Indeed, the authors demonstrate that 6PGD inhibition impacts cell proliferation, mTOR signaling and AR in patient derived explants (PDEs). Overall, the reviewers agreed the article was of broad interest, inasmuch as it provides a hitherto unappreciated link between AR and potentially targetable metabolic reprogramming in prostate cancer. Nonetheless, several issues pertaining to insufficient understanding of the mechanistic underpinnings of observed phenomena were noted.Essential revisions:1. Although previous literature show this in breast and liver cancer cell lines, the authors should conduct ChIP-qPCR in the cell lines they are studying (LNCaP and VCaP) to confirm that SREBP1 is associated with the 6PGD promoter in prostate cancer. If SREBP1 binding to this promoter is observed, does it increase as a result of AR induction and/or decrease with AR inhibition?2. More mechanistic evidence regarding how AR controls 6PGD levels and subsequently, how 6PGD impacts on AR abundance would improve the study. The authors show that an SREBP inhibitor affects 6PGD levels, but considering potential issues with specificity of inhibitors, SREBP depletion by CRISPR or siRNA should be tested for the ability to attenuate DHT-induced 6PGD expression. Similarly, the experiments using 6PGD inhibitors  should be complemented by orthogonal genetic approaches.3. It is not clear how and at which level 6PGD may affect AR levels. Experiments using transcriptional, translational and proteasome inhibitors to address the level at which 6PGD regulates AR are required to strengthen this part of the study. As a related point, the authors should investigate whether overexpression of 6PCG lead to an increase in AR levels.4. It remains unclear whether the effects of AR on cell survival are dependent on 6PGD. Would enforced expression of 6PCG in the context of AR depletion improve cell viability through engagement of the PPP?5. A deeper investigation of the effects on PPP is warranted. Although the levels of 6-PG (the substrate of the reaction) have been measured , levels of the PPP intermediates/products (ribulose-5-phosphate or NADPH) or a final product of the pathway (e.g. ribose-5-phosphate) should be included. Isotopic tracing of 13-C glucose through the PPP following modulation of AR/SEBP1/6PGD would provide more direct evidence that PPP is indeed being affected. Essential revisions:1. Although previous literature show this in breast and liver cancer cell lines, the authors should conduct ChIP-qPCR in the cell lines they are studying (LNCaP and VCaP) to confirm that SREBP1 is associated with the 6PGD promoter in prostate cancer. If SREBP1 binding to this promoter is observed, does it increase as a result of AR induction and/or decrease with AR inhibition?SCD and LDLR genes that we used as positive controls , which was used in the ENCODE ChIP-seq studies mentioned by the Reviewers, is no longer commercially available. This led us to try an alternative antibody . However, despite optimising our experimental conditions to ensure that we selected timepoints for DHT treatment that robustly activated SREBP1 , we coulcontrols .KLK3 enhancer in the same experiment. Collectively these results are consistent with the SREBP antibody being unsuitable for ChIP and, as mentioned, the ChIP-validated antibody is unfortunately no longer available.This could not be explained by a problem with the DHT or our ChIP-qPCR protocol, as we showed the expected 40-60-fold recruitment of AR to the 2. More mechanistic evidence regarding how AR controls 6PGD levels and subsequently, how 6PGD impacts on AR abundance would improve the study. The authors show that an SREBP inhibitor affects 6PGD levels, but considering potential issues with specificity of inhibitors, SREBP depletion by CRISPR or siRNA should be tested for the ability to attenuate DHT-induced 6PGD expression.The Reviewers raise an important point about inhibitor specificity, and we now show that siRNA-mediated SREBP1 knockdown also attenuates the DHT-induced protein levels of 6PGD. These new data further strengthen the association between SREBP1 and PGD expression and have been incorporated into the revised manuscript .Similarly, the experiments using 6PGD inhibitors  should be complemented by orthogonal genetic approaches.In response to the Reviewers’ suggestion, we have repeated key functional experiments from Figures 4 and 5 using genetic knockdown via siPGD to block 6PGD signalling, instead of the S3 and Physcion inhibitors. Specifically, we have now performed growth, death and ROS assays in the absence or presence of siPGD in 2 additional cell lines (V16D and MR49F), and shown very similar effects to our results using the inhibitors; namely, reduced cell growth and induction of cell death and ROS production. These new data strengthen our conclusions and have been incorporated into the revised manuscript . We also now include new Western blot data showing that, as we observed using S3, siPGD leads to inhibition of ACC1 and mTOR signalling .3. It is not clear how and at which level 6PGD may affect AR levels. Experiments using transcriptional, translational and proteasome inhibitors to address the level at which 6PGD regulates AR are required to strengthen this part of the study. As a related point, the authors should investigate whether overexpression of 6PCG lead to an increase in AR levels.As suggested by the Reviewers, we exploited transcriptional (actinomycin D), translational (cycloheximide) and proteasome (MG132) inhibitors in our experiments with the 6PGD inhibitor, S3, and assessed the effects on AR RNA (for actinomycin D) or protein (for cycloheximide and MG132) levels. Actinomycin D and cycloheximide did not influence the effect of S3 on AR. Conversely, our experiments with MG132 provide strong evidence that S3 leads to enhanced turnover of AR by the ubiquitin proteasome system. Specifically, we immunoprecipitated AR from LNCaP cells cultured with S3 in the absence and presence of MG132. Importantly, in the presence of MG132, ubiquitinylated AR accumulated in a dose-responsive manner with S3. Accordingly, we can now confidently conclude that S3 is affecting AR at the level of protein turnover, and these new data have been incorporated into the revised manuscript .To address whether overexpression of 6PGD influences AR protein levels, we generated a LNCaP cell line stably overexpressing 6PGD via lentiviral transduction. Over multiple passages in culture, the 6PGD overexpressing line maintained similar AR levels to the control vector-transduced line . This fi4. It remains unclear whether the effects of AR on cell survival are dependent on 6PGD. Would enforced expression of 6PCG in the context of AR depletion improve cell viability through engagement of the PPP?Thank you for this suggestion; to address the dependency of AR depletion on 6PGD, we used the LNCaP cell line stably overexpressing 6PGD  and comp5. A deeper investigation of the effects on PPP is warranted. Although the levels of 6-PG (the substrate of the reaction) have been measured , levels of the PPP intermediates/products (ribulose-5-phosphate or NADPH) or a final product of the pathway (e.g. ribose-5-phosphate) should be included. Isotopic tracing of 13-C glucose through the PPP following modulation of AR/SEBP1/6PGD would provide more direct evidence that PPP is indeed being affected.13C glucose after knockdown of AR/SREBP1/6PGD. PPP flux was estimated over a period of 15 minutes by measuring the incorporation of 13C into the immediate product of 6PGD catalytic activity, ribulose-5-phosphate (Ru-5-P). Our new data conclusively show that flux through the oxidative (irreversible) branch of the PPP (i.e. through 6PGD) significantly decreased with knockdown of 6PGD, AR or SREBP1 . Interestingly, knockdown of AR and SREBP1 (but not 6PGD) also had a significant impact on flux through the non-oxidative (reversible) branch of the PPP, as determined by evaluating m2 (doubly labelled) Ru5P production via F6P/GAP . Collectively, these glucose tracing data show that targeting 6PGD significantly suppresses PPP activity through the oxidative pathway, an effect that is also evident when targeting the upstream signalling factors AR and SREBP1. We thank the Reviewers for this suggestion, which has markedly strengthened our manuscript’s conclusions.We agree with the need to more directly relate our effects on PGD modulation to PPP activity in prostate cancer cells. Accordingly, we have followed the suggestion to perform isotopic tracing with 1,2-


The androgen receptor (AR) signalling pathway is the key driver in most prostate cancers (PCa), and is underpinned by several kinases both upstream and downstream of the AR. Many popular therapies for PCa that target the AR directly, however, have been circumvented by AR mutation, such as androgen receptor variants. Some upstream kinases promote AR signalling, including those which phosphorylate the AR and others that are AR-regulated, and androgen regulated kinase that can also form feed-forward activation circuits to promotes AR function. All of these kinases represent potentially druggable targets for PCa. There has generally been a divide in reviews reporting on pathways upstream of the AR and those reporting on AR-regulated genes despite the overlap that constitutes the promotion of AR signalling and PCa progression. In this review, we aim to elucidate which kinases—both upstream and AR-regulated—may be therapeutic targets and require future investigation and ongoing trials in developing kinase inhibitors for PCa. The biological effects of male sex hormones, androgens, on the target tissues are manifested by the androgen receptor (AR) to achieve a wide range of developmental as well as physiological responses. Thus, androgens play a crucial role in the differentiation and maturation of the male reproductive organs and androgens are the major regulators of cell proliferation and cell death of the epithelial cells within the prostate gland ,2. It isTherefore, to combat PCa, the AR and AR signalling pathways have been considered a key target, and androgen deprivation therapy (ADT) is the current standard of care for advanced PCa. Whilst some ADT reduce androgen synthesis, such as Abiraterone, other drugs, including enzalutamide, target the AR directly. However, in metastatic patients, ADT resistance due to transition to hormone-insensitive castration resistant PCa (CRPC) usually occurs within 18–36 months . NotablyOwing to the fact that AR is a very dynamic phosphoprotein, it is unsurprising that its stability, activity, and cellular localisation are all differentially regulated by phosphorylation by specific signalling kinases ,11,12. AThe AR is overexpressed in PCa as a function of disease progression, with ADT providing a selection pressure to overcome androgen dependence and develop into advanced disease such as castration-resistant prostate cancer (CRPC) . Thus, tIn addition to its primary role as a transcription factor, a few non-genomic (transcription-independent) functions of the AR have been revealed in the recent years, including the binding of AR with a scaffold protein filamin A in prostate fibroblasts to promote oncogenesis , and steThe functionality of the AR is primarily split into three well-defined functionally critical domains; the amino terminus transactivation domain (NTD), the DNA binding domain (DBD), and the ligand-binding domain (LBD), with a hinge region connecting the LBD and DBD . All theAnother layer of intricacy to AR-dependent transcription is the involvement of the co-regulatory proteins, such as coactivators that can bind to the AR to enhance the rate of AR-mediated transcription, and transcriptional corepressors—which usually bind to the NTD—which can dampen AR transactivation function causing a reduction in AR target gene expression. Two main conformations of the AR have been proposed by which AR can regulate, which co-regulatory molecules bind: the ligand-bound conformation of the LBD and post-translational modifications, such as phosphorylation ,34. The Phosphorylation of the AR by kinases is known to occur in at least 15 amino acid residues within the AR protein  and can Components of several key signal transduction pathways have been shown to interact with androgen signalling, including direct phosphorylation of the AR, through their kinase components. These include the IL-6 and EGF extracellular signal-mediated pathways and the PI3K/Akt and MAPK transduction networks, which are often found to be implicated in hormone-independent aggressive PCa such as CRPC . LikewisInterleukin 6 (IL-6) is a pleiotropic cytokine that is involved in the regulation of the growth of the majority of malignant tumours , includiThere is also crosstalk between several growth factors signalling pathways and the AR signalling pathway, with the epidermal growth factor (EGF) receptor family amongst the most described in the literature. EGF pathways play a pivotal role in regulating AR signalling, e.g., ERBB1 (EGFR) expression is enhanced as a function of tumour severity, whilst the expression of ERBB2 (HER2) increases during and following androgen ablation, thus ensuring sustained survival of PCa cells ,61.There is functional redundancy in the activation of downstream signalling by IL-6 and EGF signal transduction pathways. Like IL-6, EGF signalling can also promote phosphorylation of STAT3 at Tyr705, although this occurs via the EGFR and Src ,63. EGFREGF stimulation of the EGFR and HER2 receptors results in phosphorylation and activation of activated Cdc42-associated tyrosine kinase 1 (ACK1) ,67, whicIn normal prostate epithelia, the EGF pathway mediated phosphorylation of ACK1 results in the degradation of ACK1 and EGFR in a negative feedback mechanism, mediated via the interaction of E3 ligases with the ubiquitin association (UBA) domain of the ACK1. This appears to be overcome in CRPC, as both ACK1 and EGFR protein levels are increased, presumably due to changes in phosphorylation and protein interactions in the ACK1 UBA domain . The redDue to the role of ACK1 in AR transactivation and PCa genomic integrity, several inhibitors have been designed that show potential to overcome CRPC . NotablyThe PI3K/Akt signalling network is involved in complex crosstalk between several cell signalling cascades, some of which have the potential to be oncogenic and have already been mentioned earlier. Two key points in the signalling network are mTOR1 and mTOR2 both of which are functionally distinct complexes downstream of PI3K/Akt, which regulate many cellular processes that promote tumour progression and drug resistance . The intPI3K/Akt/mTOR and AR signalling pathways have a complex relationship containing several redundancies, and downregulation of one can promote the other; this can occur during AR inhibitor therapy, where downregulation of AR-regulated genes can result in increased AKT-mTOR signalling and lead to therapeutic resistance . ConditiGrowth factor and cytokine pathways mentioned previously activate kinases, such as Src and ACK1, which positively regulate the activity of both the AR and Akt, and therefore, activation of these membrane-associated receptors may be key in the development of therapeutic resistance and progression to CRPC. However, under low androgen conditions, the AR and Akt can also directly interact, with Akt phosphorylating the AR at Ser213 and Ser791 .The activation of the MAPK signal transduction pathway is yet another mechanism that growth factors employ to activate PCa growth. The MAPK pathway is split into four parts, the extracellular signal-regulated ERK1/2 pathway, the EGF- and oxidative stress-associated ERK5 pathway, and the stress-activated JNK and p38 MAPK pathways. Androgen-mediated AR signalling can induce the ERK1/2 and p38 MAPK pathways , which cExpression and activation of p38 MAPK and some of its associated upstream kinases occurs in PCa, making this pathway another possible therapeutic target . InteresAR signalling results in the proliferation of PCa epithelial cells via regulating the transition between the G1 and S phases ,90. At tMany ADT rely on Rb ,92, and CIP1, an inhibitor of CDK2/3/4/6 [AR activity is also modulated through phosphorylation by other CDK throughout the cell cycle. Firstly, Ser81 of AR can be phosphorylated by CDK1, CDK2, CDK5, and CDK9 ,95. PhosK2/3/4/6 ,102. CDKK2/3/4/6 , and CDKK2/3/4/6 . The othK2/3/4/6 ,106. TheK2/3/4/6 . HoweverK2/3/4/6 . This woK2/3/4/6 , and thuK2/3/4/6 ,111. HowK2/3/4/6 , and sevK2/3/4/6 , and hasNormally, the AR acts as a transactivator for target genes leading to their increased expression. The AR can also repress gene expression by acting as a transrepressor. These target genes code for proteins with a variety of roles, including mediation of cell proliferation and metabolism. Some AR target genes code for downstream kinases which can reinforce AR signalling by interaction with the AR to change its stability, location, and transactivation by phosphorylation of key serine, threonine, and tyrosine residues. On the other hand, androgen-repressed kinases are also therapeutically important, as these may function as backup pathways that are activated in response to AR-targeting therapies and can mediate therapeutic resistance. We identified 49 androgen-regulated kinase genes in LNCaP cells, of which 25 were upregulated and 24 were downregulated , which aCell metabolism is a broad term for biochemical reactions that are required to sustain a cell and consists of several overlapping groups of enzymes. A number of these enzymes are kinases, several of which are androgen regulated . Whilst AR signalling has been shown to upregulate aerobic glycolysis and anabolic synthesis through upregulation of several enzymes including key rate-limiting kinases in the glycolytic pathway . HexokinCalcium/Calmodulin Dependent Protein Kinase Kinase 2 (CAMKK2) is a metabolic regulator, which is targeted by the AR in both androgen-dependent and androgen-independent PCa cell lines . In PCa,Calcium/calmodulin-dependent protein kinase type 1 (CAMK1) is a transcriptional target of AR ,14. HoweCholine kinase alpha (CHKA) is an androgen-upregulated kinase that has roles in lipid metabolism and positive regulation of AR activity ,127. In However, CHKA is of particular therapeutic interest in PCa due to its interactions with AR both directly and indirectly. CHKA acts as an AR chaperone by binding to the LBD and maintaining AR stability and results in a feed-forward signalling loop that maintains AR activity . HoweverCoenzyme A synthase (COASY) was identified as upregulated by AR signalling . COASY iAs mentioned previously, growth factor signalling can crosstalk with AR signalling and can contribute to progression to androgen-independent and even AR-independent PCa. AR signalling increases EGFR and IGF1R transcription ,143, andOne of the functional clusters identified in Asim et al. was MAPK signalling . MAPK siAR signalling potentiates ERK1/2 MAPK activity by inducing and enhancing the ERK1/2 MAPK pathway, partially through genomic transactivation and repression. Firstly, EGFR and IGF1R—which transduce signals via ERK1/2 signalling—are upregulated ,143. TheThe ERK5 MAPK pathway is also activated by growth factors—as well by mitogenic signals and oxidative stress —however,The AR-mediated genomic regulation of the pro-survival p38 MAPK appears to be varied. MAP2K3 and MAP2K6 are the primary activators of p38 and are downregulated. Conversely, the AR-mediated increase in Homeodomain Interacting Protein Kinase 2 (HIPK2) ,14 and SDuring ADT, the genomic repression of the p38 MAPK pathway would be ablated and reversed. One of the results would be increased hsp27, which would be predicted to increase stability and nuclear translocation of the AR ,88, as wMAP2K4 is another key MAPK gene that we and others have found to be transcriptionally regulated by the AR ,14,171. Although targeting MEK4 may have limited effects in modulating the JNK MAPK pathway, MEK4 is still targeted for the activation of the p38 MAPK pathway, which increases AR stability by hsp27 expression and metastasis via matrix metalloproteinase-2 (MMP-2) expression. However, chronic overexpression of MAP2K4 in the LNCaP cell line indicated MEK4 can also bypass p38 MAPK and increase the stability of hsp27 and MMP-2 expression . Phase ICDK8 has been identified as an AR-repressed gene ,181. WhiIn the VCaP cell line—which is androgen-dependent and represents primary PCa —the inhiGO analysis of the kinases we previously found to be downregulated  showed eIndeed, SRPK2 overexpression in PCa is associated with high Gleason grade and metastasis in AR-dependent and AR-independent cell lines, indicating SRPK2 may have a role in the progression of PCa and initiation of metastasis . In andrclinicaltrial.gov database (accessed on 30 January 2022) with the terms “prostate cancer” and “kinase inhibitor” returned 106 clinical trials that were either recruiting, active, or completed. Looking forward, Several kinase inhibitors have been tested for in a large range of human malignancies, and a search on the Kinases are heavily involved in the regulation and biological effects of AR activation and are interrelated in a complex robust network, where AR-responsive genes also affect cascades upstream of the AR and the AR directly. Kinases upstream of the AR, such as ACK1 and Src, present as therapeutic targets to reduce androgen-independent activation of the AR due to extracellular signalling by EGF and IL-6. Androgen-responsive kinases, which are upregulated, present as targets to reduce the proliferation of AR-dependent prostate cancer, and downregulated kinases imply changes that can occur during ADT and, thus, may be therapeutic targets for reducing the progression of androgen independence of prostate cancer. Some of the androgen-responsive kinases are under-researched and could present as therapeutic targets, such as COASY and SRPK2.


IPK to inhibit PKR. The activity of P58IPK is normally restricted in cells by the formation of an inactive complex with its negative regulator Hsp40. On the other hand, PKR remains associated with the 40S ribosomal subunit, a unique strategic location that facilitates its free access to the downstream target eIF2α. Although both NP and Hsp40 bind to P58IPK, the binding affinity of NP is much stronger compared to Hsp40. P58IPK harbors an NP binding site, spanning to N-terminal TPR subdomains I and II. The Hsp40 binding site on P58IPK was mapped to the TPR subdomain II. The high affinity binding of NP to P58IPK and the overlap between NP and Hsp40 binding sites releases the P58IPK from its negative regulator by competitive inhibition. The NP-P58IPK complex is selectively recruited to the 40S ribosomal subunit by direct interaction between NP and the ribosomal protein S19 (RPS19), a structural component of the 40S ribosomal subunit. NP has distinct binding sites for P58IPK and RPS19, enabling it to serve as bridge between P58IPK and the 40S ribosomal subunit. NP mutants deficient in binding to either P58IPK or RPS19 fail to inhibit PKR, demonstrating that selective engagement of P58IPK to the 40S ribosomal subunit is required for PKR inhibition. Cells deficient in P58IPK mount a rapid PKR antiviral response and establish an antiviral state, observed by global translational shutdown and rapid decline in viral load. These studies reveal a novel viral strategy in which NP releases P58IPK from its negative regulator and selectively engages it on the 40S ribosomal subunit to promptly combat the PKR antiviral responses.Hantavirus nucleocapsid protein (NP) inhibits protein kinase R (PKR) dimerization by an unknown mechanism to counteract its antiviral responses during virus infection. Here we demonstrate that NP exploits an endogenous PKR inhibitor P58 IPK to combat the PKR antiviral response. The PKR remains associated with the host ribosomes to gain free access for eIF2α that enables the prompt shutdown of host translation apparatus during virus infection. The studies reported here reveal a novel mechanism by which hantavirus NP prevents PKR induced host translation shutoff in virus infected cells. NP dissociates the inactive Hsp40-P58IPK complex and recruits the released P58IPK to the 40S ribosomal subunit, a strategic PKR location. This tactic recruitment of P58IPK rapidly inhibits PKR and prevents host interference in viral protein synthesis.Activation of PKR during virus infection shuts down the host translation machinery and creates an antiviral state to create obstacles for viral protein synthesis. Our results demonstrate that hantaviruses hijack an endogenous PKR inhibitor P58 Hantaviridae family, Bunyavirales order. Their genome is composed of three RNA segments S, M and L, which encode nucleocapsid protein (NP), glycoprotein precursor (GPC) and RNA dependent RNA polymerase (RdRp), respectively [Hantaviruses are zoonotic negative sense RNA viruses in the ectively . The GPCectively . Recentlectively . Hantaviectively . AlthougThe virus-host interaction determines the outcome of a viral disease. The host type I interferon (IFN) response stimulates the expression of interferon stimulated genes (ISGs) . The antIPK [Protein kinase R (PKR), one of the classical ISGs from the eIF2α-kinase family has a C-terminal kinase domain (KD) and an N-terminal dsRNA binding domain (dsRBD), composed of two tandem dsRNA binding motifs. The intermolecular interaction between dsRBD and KD maintains this enzyme in the latent form. Upon binding to dsRNA or its activator PACT protein, PKR undergoes a conformational change and forms a homo-dimer ,13. The IPK .IPK, an endogenous PKR inhibitor [IPK a member of the HSP family of proteins [IPK inhibits PKR by direct binding and interruption in PKR dimerization [IPK has been mapped to its TPR6 motif [IPK is itself negatively regulated by its own inhibitor Hsp40, which forms an inactive complex with P58IPK (22). We have previously reported that hantavirus NP interrupts PKR dimerization by an unknown mechanism to ensure continuous synthesis of viral proteins in the host cell [IPK from the clutches of Hsp40 and recruits it to the 40S ribosomal subunit to inhibit PKR dimerization. Our results demonstrate that NP binds to P58IPK with higher affinity as compared to Hsp40. Both NP and Hsp40 share a common binding site on P58IPK. Our results suggest that NP competes with Hsp40 for binding to P58IPK, leading to the dissociation of Hsp40-P58IPK complex. The resulting NP-P58IPK complex is selectively recruited to the 40S ribosomal subunit by the direct interaction between NP and the ribosomal protein S19 (RPS19), a structural component of the 40S ribosomal subunit. NP has distinct binding sites for RPS19 and P58IPK. The simultaneous binding of NP to both the P58IPK and RPS19 facilitates the prompt recruitment of P58IPK to the 40S ribosomal subunit. Interruption in the recruitment process prevents PKR inhibition in cells. Collectively, our studies reveal a novel mechanism by which hantavirus NP releases P58IPK from the clutches of its negative regulator and recruits it on the 40S ribosomal subunit to efficiently counteract the PKR antiviral responses.The P58nhibitor  from theproteins . The P58rization . The PKRR6 motif . Interesost cell . Here weIPK to inhibit the activation of PKR, we knocked down P58IPK by shRNA in HEK293T cells, stably expressing either NP from SNV (Sin Nombre virus) or EGFP as negative control. The cells were transfected with poly I:C three hours before harvesting to trigger PKR activation, and were examined by western blot analysis for the phosphorylation of PKR. It is evident from (IPK (compare lanes 6 and 8). The results were confirmed by using another shRNA targeted to a different region of P58IPK mRNA  or Hantaan virus or Myc tagged SUFU (suppressor of fused homolog) protein of chicken origin as negative control  is consistent with their previously reported PKR inhibition [We previously reported that hantavirus NP inhibits PKR activation by inhibiting its dimerization and subsequent autophosphorylation. The inactive PKR fails to phosphorylate its downstream targets, such as, eIF2α. To determine whether NP uses P58ent from  that cel pathway ,26, suggan virus . The revhibition .IPK-NP interaction, HUVECs were infected with either ANDV or Hazara virus (HZV), a tick borne orthonairovirus having tri-segmented negative sense RNA genome similar to hantaviruses. HZV is used as model virus for the study of Crimean congo hemorrhagic fever virus (CCHFV), a BSL 4 orthonairovirus that causes significant human disease. HUVECs were used because these cells are permissive to both hantavirus and HZV infection. The cell lysates were immunoprecipitated using either anti-ANDV NP antibody or IgG or anti-CCHFV NP antibody that cross reacts with HZV NP due to significant sequence homology between CCHFV and HZV NPs. We confirmed the cross reactivity of anti-CCHFV NP antibody with bacterially expressed and purified HZV NP  instrument, as previously reported [IPK and GST (control) with the immobilized protein  of ~ 0.8 μM and ~ 204 μM, respectively . The structural motifs TPR1-TPR3, TPR4-TPR6, TPT7-TPR9 comprise three subdomains I, II and III, respectively (IPK deletion mutants lacking either subdomain I (TPR1-TPR3) or both subdomains I and II (TPR1-TPR6) were expressed as N-terminally Myc tagged fusion proteins in HEK293T cells along with FLAG tagged NP. Cell lysates were immunoprecipitated with anti-Myc antibody and the binding of FLAG-NP was determined by western blot analysis using anti-FLAG antibody. It is evident from IPK to NP, which was further compromised by the deletion of both the subdomain I and II (ΔTPR1-6). This observation suggests that NP binding site is located in the subdomains I and II, although the subdomain I might play a major role in the binding. A similar experiment was performed to map the binding site of Hsp40 on P58IPK. It is evident from IPK to Hsp40. However, the binding was significantly compromised by the deletion of both the subdomains I and II, suggesting that Hsp40 binding site is most likely located in the subdomain II. Taken together, the results from IPK. Since NP binds to P58IPK with higher affinity as compared to Hsp40  or C-terminal 175–428 amino acids (NP175-428) or C-terminal 230–428 amino acids (NP230-428). The cell lysates were immunoprecipitated using anti-Myc antibody. Western blot analysis of immunoprecipitated material by anti-FLAG antibody revealed that N-terminal 175 amino acids didn’t bind to P58IPK  bound to P58IPK similar to wild type NP , its parental cytoplasmic morphology was retained. These observations suggest that wild type NP likely targets mCherry-P58IPK to the 40S ribosomal subunit.We next used confocal microscopy to visualize the location of P58 mutants . Wild typression . NP mutaIPK was sufficient to inhibit PKR, HEK293T stable cell lines expressing either wild type NP or NP truncation mutants were transfected with poly I:C three hours before harvesting to trigger PKR activation. Cell lysates were examined by western blot analysis to monitor PKR autophosphorylation   . The 40Sm (A260) . The PKRm (A260) . InteresIPK lead to the hypothesis that P58IPK deficient cells would activate PKR upon hantavrius infection and undergo translational shutdown to establish an antiviral state. To test this hypothesis, P58IPK was knockdown in HUVEC cells using lentivirus shRNA delivery system. Since lentivirus transduction at higher MOI induces PKR activation, a careful titration revealed that lentivirus transduction up to an MOI of 3.0 knocks down P58IPK without affecting the phosphorylation of eIF2α  [IPK binds to misfolded proteins and aids their proper folding during unfolded protein response (UPR) in the ER [IPK inhibits PERK, another eIF2α kinase that regulates protein synthesis during ER stress [IPK promotes the translation of influenza virus mRNA by shutting down the PKR antiviral response in virus infected cells by an unknown mechanism [IPK to restrict its activity [IPK and PKR is mediated by one of the nine tandemly arranged TPR domains of P58IPK [IPK contains a J-domain at its C-terminus, which is required for PKR inhibition in vivo [IPK via its C-terminal J-domain [IPK has been reported to stimulate the ATPase activity of Hsp70 [IPK likely uses Hsp70 to refold PKR and interrupt its dimerization. Interestingly, PKR remains associated with the 40S ribosomal subunit in the cell. While this strategic location likely promotes the easy access of PKR upon activation to its downstream target eIF2α, it remains unclear how P58IPK gains access to this strategic location to interrupt PKR dimerization. Moreover, the lack of molecular mechanism for the release of P58IPK from its negative regulator Hsp40 shows clear gaps in the mechanism of PKR inhibition by P58IPK.Despite being a PKR inhibitor , the P58lum (ER) ,40. The n the ER ,40. In aR stress ,40. It hechanism . Interesactivity . The intf P58IPK . Also, P in vivo . The heaJ-domain . Similarof Hsp70 . These oIPK knockdown cells, suggesting that NP requires P58IPK for activity. Further studies revealed that NP binds to P58IPK and the binding site spans to the TPR subdomain I and II at the N-terminus of P58IPK. The Hsp40 binding site on P58IPK was mapped to the TRP subdomain II, clearly demonstrating that NP binding site overlaps with the binding site of Hsp40. Since NP binds to P58IPK with higher affinity as compared to Hsp40, it is likely that NP competitively inhibits the binding of Hsp40 to P58IPK. The competitive inhibition releases P58IPK from the clutches of Hsp40 and the resulting NP-P58IPK complex was found to interact with the 40S ribosomal subunit via RPS19. Hantaviruses have evolved P58IPK and RPS19 binding domains in NP that enable it to serve as a bridge between P58IPK and the 40S ribosomal subunit. The selective engagement of P58IPK with the 40S ribosomal subunit, with the assistance of NP, facilitates the free access of P58IPK to the PKR. This is supported by the observations that NP mutants lacking either P58IPK or RPS19 binding domains failed to inhibit PKR autophosphorylation in cells. These studies have provided a molecular mechanism by which NP dissociates the P58IPK-Hsp40 complex in virus infected cells and recruits the released P58IPK to the 40S ribosomal subunit for the prompt inhibition of PKR. The significance of this unique PKR inhibition strategy in hantavirus replication is evident by the induction of rapid host translation shutoff and establishment of antiviral state in P58IPK deficient cells.Interestingly, NP failed to inhibit PKR autophosphorylation in P58IPK that favors virus replication in the host by the inhibition of PKR antiviral responses. Recent studies have shown that P58IPK also plays a role in the host antiviral defense in vivo [IPK knockout mice during influenza virus infection undoubtedly controlled the virus replication, however the elevated inflammatory response due to PKR activation caused sever lung pathology and apoptosis that increased the mortality rates in infected mice [IPK function would be to calm down PKR antiviral response in the host after virus replication has been controlled. However, hantaviruses exploit P58IPK to prevent PKR activation in virus infected cells to ensure continuous replication without the interruption from PKR antiviral responses.Based on these observations it appears surprising that mammalian cells harbor a PKR inhibitor P58 in vivo . PKR act in vivo . The vigted mice . These oDue to their small genome size, virus encoded proteins containing multifunctional domains enabling them to interact with numerous host cell factors during the course of viral infection. Hantavirus NP is one of such multifunctional proteins playing diverse roles in hantavirus replication cycle. NP is involved in cap-snatching in conjunction with RdRp , translaIPK and pFLAG-P58IPK were constructed by inserting the P58IPK open reading frame (ORF) into pcDNA3.1-Myc and pcDNA3.1-FLAG backbones, respectively. The P58IPK ORF was amplified from cDNA generated by the reverse transcription of an RNA sample purified from HUVEC cells in culture. The plasmid pGST-P58IPK was cloned by the insertion of P58IPK ORF into pGEX-4T-3 vector. The P58IPK truncation mutants were constructed by PCR amplification and insertion of appropriate gene sequence into pcDNA3.1-Myc backbone. The plasmids pMyc-Hsp40 and pFLAG-Hsp40 were constructed by the insertion of Hsp40 ORF into pcDNA3.1-Myc and pcDNA3.1-FLAG backbones, respectively. The Hsp40 ORF was also amplified from cDNAs generated by the reverse transcription of an RNA sample from HUVEC cells. The plasmid pcDNA3.1 myc his Su(fu) (Addgene plasmid # 13855), expressing the Myc tagged SUFU protein was a gift from Cliff Tabin [IPK shRNAs were constructed by inserting the hairpin sequence into pLKO.1 - TRC cloning vector, a gift from David Root (Addgene # 10878) [IPK were: 5’—CAG TCG CAG AAA CGA GAT TAT -3’ and 5’—GAG CCA AGC ATT GCT GAA TAT -3’.The plasmids pMyc-ANDVNP, pMyc-SNVNP and pMyc-HTNVNP expressing Myc tagged nucleocapsid proteins from Andes virus, Sin nombre virus and Hantan virus were constructed as previously reported . The NP ff Tabin . The plaff Tabin . The pLK# 10878) . The tarHuman embryonic kidney 293T (HEK293T) and HeLa cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) (Hyclone) supplemented with 10% heat-inactivated fetal bovine serum (Gibco), 2 mM glutamine, 100 U/ml penicillin and 100 μg/ml streptomycin at 37°C under humidified air containing 5% CO2. Human umbilical vein endothelial cells (HUVECs) were purchased from Lonza and cultured in EGM BulletKit medium from Lonza CC-3124). The propagation of Andes virus (strain Chile-9717869) in cell culture has been previously described [. The proIPK (2940S) were from Cell Signaling Technologies. The primary antibody for phosphorylated PKR was from Abcam. The primary antibodies for FLAG tag (F1804), β-actin (A5441) and GFP(G1546) were from Sigma. The primary antibody for c-Myc tag, RPS19(sc-100836) were from Santa Cruz. The primary antibody for Hsp40 (ADI-SPA-400) was from Enzo Life Science. The primary antibody for RPL4(11302-1-AP) was from proteintech. The polyclonal antibody for ANDV and SNV NP was produced in our lab. The antibody for CCHFV NP (ab190657) was from abcam.Cells were washed once with phosphate buffered saline (PBS) and lysed with radioimmunoprecipitation assay buffer (RIPA buffer) supplemented with protease and phosphatase inhibitor cocktails (Roche). Clarified cell extracts were mixed with equal volume of 2× SDS loading buffer and boiled at 95°C for 5 min. Proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore). The membrane was blocked with 5% non-fat milk in PBST buffer  followed by incubating with primary and secondary antibodies diluted in blocking buffer. The blots were developed with ECL (enhanced chemiluminescence) and exposed to X-ray film. The primary antibodies for PKR (12297S), eIF2α(5324S), phosphorylated eIF2α (Ser51)(9721S) and P58IPK along with either Myc-NP or Myc-NP mutants for thirty-six hours using TurboFect Transfection Reagent. Cells were washed once with PBS and fixed with 4% paraformaldehyde in PBS for 15 min at room temperature. The excess paraformaldehyde was neutralized with 0.1 M glycine in PBS, followed by extensive washing with PBS. The fixed cells were permeabilized with 0.5% TritonX-100 in PBS for 5 min and blocked with 3% BSA for 2 hours at room temperature. The cells were sequentially incubated with anti-Myc and Alexa Fluor 488 Goat Anti-Mouse IgG (H+L) antibody (life technologies). The coverslips were mounted in mounting medium containing DAPI (vector labs). The confocal images were recorded with Nikon Digital Eclipse C1 Microscope.HeLa cells grown on coverslips were co-transfected with mCherry-P58Coimmunoprecipitation was carried out as previously described . Briefly2, 1.5 mM KCl) supplemented with 1x protease inhibitor cocktail (Roche), 100 μg/ml Cycloheximide, 2 mM DTT, 100 units of RNAase inhibitor, followed by the addition of Triton X-100 and sodium deoxycholate to a final concentration of 0.5% to solubilize ribosomes for 20 min at 4°C. Cell lysates were centrifuged at 16000x g for 15 min at 4°C and supernatants were layered on linear sucrose gradient (5%-40%) centrifuged at 37000 rpm for 3.5 hours at 4°C using SW41 rotor. Fractions of 300 μl sucrose gradient were collected using biocomp fractionator and optical density at 260 nm was measured.Ribosomal subunits and polysomes were fractionated on sucrose density gradient. Briefly, HEK293T cells seeded in 10 cm dish were transfected with EGFP, NP or NPΔ151–175 mutant. Cells were treated with Cycloheximide  for 5 min at 48 hours post-transfection. Cells were washed twice with ice-cold PBS containing 100 μg/ml Cycloheximide. Cells were scraped in 5 ml of ice-cold PBS containing 100 μg/ml cycloheximide and centrifuged at 500 xg for 5 min. Cell pellet was resuspended in 500 μl of hypotonic buffer pLysS bacterial cells (Novagen). Briefly, the bacteria were grown in 500 ml cultures at 37°C with vigorous shaking until the optical density at 600 nm (OD 600) reached 0.6. The recombinant protein expression was induced by the addition of isopropyl β-D-1-thiogalactopyranoside (IPTG) to the media at a final concentration of 1 mM. The media was shaken at 25°C for additional 5 hours. The bacterial pellets were suspended in lysis buffer  and sonicated. The clarified cell lysates were loaded on Glutathione HiCap matrix (Qiagen), followed by washing and elution of bound proteins with reduced glutathione following the manufacturer’s instructions. The eluted protein were dialyzed against , concentrated and saved at -80°C. For GST pull-down assay, 20 μg of GST or GST-P58IPK were incubated with 50 μl Glutathione HiCap matrix (50% slurry) in 500 μl GST pull-down binding and wash buffer  for 2 hours at 4°C. The Glutathione HiCap matrix was washed and saved as bait. On the other hand, HEK293T cells expressing the proteins of our interest were lysed using GST pull-down binding and wash buffer. The HEK293T cell lysates were clarified and mixed with the bait for one hour at 4°C. The Glutathione HiCap matrix was washed four times with wash buffer and resuspended in 1× SDS loading buffer and boiled at 95°C for 5 min. After brief centrifugation the supernatants were loaded into SDS PAGE gel.GST and GST-P5835S methionine and cysteine (PerkinElmer). Cells were washed with PBS before lysis with 100 μl of RIPA buffer. The cell lysates were mixed with 2× SDS loading buffer, boiled at 95°C for 5 min and separated on 10% SDS-PAGE gel. The gels was stained with coomassie brilliant blue dye, dried on filter paper and exposed to X-ray film over night at -80°C.Cells grown in 6-well plates were washed twice with starvation medium (DMEM deficient in methionine and cysteine) and cultured in the same medium for 30 min to consume intracellular pools of methionine and cysteine. Cells were then incubated for 40 min with 1 ml of starvation medium containing 300 μCi Total cellular RNA was purified using RNeasy Kit (Qiagen) and reverse transcribed using M-MLV Reverse Transcriptase (invitrogen) according to manufacturer’s instructions. Real time PCR reactions were performed on ABI 7500 real time PCR system (Applied Biosystems), using SYBR green PCR master mix (Roche). Each reaction was performed in triplicates. The mRNA levels of a housekeeping gene β-actin were quantified as an internal control. The relative quantification method was used for data analysis as previously reported . The priIPK and GST with His tagged protein loaded on NiNTA biosensor for 420s, followed by dissociation phase of 600 seconds. The kinetic parameters Kass (association rate constant), Kdis (dissociation rate constant) and the binding affinities (Kd = Kdis/Kass) were calculated with the help of inbuilt data analysis software (BLItZ Pro), as previously reported [Biolayer interferometry (BLI) was used to monitor the binding affinities of His tagged NP and HSP40 with GST-P58IPK fusion protein and GST tag using the BLItz system (ForteBio Inc.), as previously reported ,52,53. Breported ,52,53.Sucrose gradients were used to examine the oligomeric forms of wild type NP and its deletion mutants. Forty microliters of purified protein containing a C-terminal His tag (110 μM) were layered onto linear gradients containing 5 to 50% (wt/vol) sucrose in 1x PBS and centrifuged at 90,000 rpm in an S120AT3-0098 rotor at 4°C for 6 hours, using a Sorvall Discovery M120SE analytical ultracentrifuge. Gradient fractions of 30 μl were collected. The protein molecular mass markers bovine serum albumin , alcohol dehydrogenase (ADH) (150 kDa), and glutathione S-transferase (GST) (27 kDa) were similarly fractionated. Fraction were analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The wild type NP and its deletion mutants were analyzed by western blot analysis using anti His-tag primary antibody. The elution profile of GST, BSA and ADH  was used