An efficient computational protocol for template-based design of peptides that inhibit interactions involving SARS-CoV-2 proteins.

The RNA-dependent RNA polymerase (RdRp) complex of SARS-CoV-2 lies at the core of its replication and transcription processes. The interfaces between holo-RdRp subunits are highly conserved, facilitating the design of inhibitors with high affinity for the interaction interface hotspots. We, therefore, take this as a model protein complex for the application of a structural bioinformatics protocol to design peptides that inhibit RdRp complexation by preferential binding at the interface of its core subunit nonstructural protein, nsp12, with accessory factor nsp7. Here, the interaction hotspots of the nsp7-nsp12 subunit of RdRp, determined from a long molecular dynamics trajectory, are used as a template. A large library of peptide sequences constructed from multiple hotspot motifs of nsp12 is screened in-silico to determine sequences with high geometric complementarity and interaction specificity for the binding interface of nsp7 (target) in the complex. Two lead designed peptides are extensively characterized using orthogonal bioanalytical methods to determine their suitability for inhibition of RdRp complexation. Binding affinity of these peptides to accessory factor nsp7, determined using a surface plasmon resonance (SPR) assay, is slightly better than that of nsp12: dissociation constant of 133nM and 167nM, respectively, compared to 473nM for nsp12. A competitive ELISA is used to quantify inhibition of nsp7-nsp12 complexation, with one of the lead peptides giving an IC50 of 25µM . Cell penetrability and cytotoxicity are characterized using a cargo delivery assay and MTT cytotoxicity assay, respectively. Overall, this work presents a proof-of-concept of an approach for rational discovery of peptide inhibitors of SARS-CoV-2 protein-protein interactions.

How helpful were molecular dynamics simulations in shaping our understanding of SARS-CoV-2 spike protein dynamics?

The SARS-CoV-2 spike protein (S) represents an important viral component that is required for successful viral infection in humans owing to its essential role in recognition of and entry to host cells. The spike is also an appealing target for drug designers who develop vaccines and antivirals. This article is important as it summarizes how molecular simulations successfully shaped our understanding of spike conformational behavior and its role in viral infection. MD simulations found that the higher affinity of SARS-CoV-2-S to ACE2 is linked to its unique residues that add extra electrostatic and van der Waal interactions in comparison to the SARS-CoV S. This illustrates the spread potential of the pandemic SARS-CoV-2 relative to the epidemic SARS-CoV. Different mutations at the S-ACE2 interface, which is believed to increase the transmission of the new variants, affected the behavior and binding interactions in different simulations. The contributions of glycans to the opening of S were revealed via simulations. The immune evasion of S was linked to the spatial distribution of glycans. This help the virus to escape the immune system recognition. This article is important as it summarizes how molecular simulations successfully shaped our understanding of spike conformational behavior and its role in viral infection. This will pave the way to us preparing for the next pandemic as the computational tools are tailored to help fight new challenges.

Drug Discovery in Real Life: An Online Learning Activity for Bioinformatics Students

During COVID-19 lockdowns, online learning activities had to be developed for the Undergraduate and Masters by Coursework Bioinformatics students at RMIT University. Therefore, we designed an integrative, industry-based research assignment, which guided the students through a drug discovery project from target identification to lead optimization. The students were able to utilize this real-life scenario to apply multiple diverse but complementary bioinformatic principles to analyze biological and chemical data leading to meaningful predictions. This activity was utilized as a final assessment of the students' knowledge. © 2023 American Chemical Society and Division of Chemical Education, Inc.

Structural similarities between SARS-CoV2 3CLpro and other viral proteases suggest potential lead molecules for developing broad spectrum antivirals.

Considering the significant impact of the recent COVID-19 outbreak, development of broad-spectrum antivirals is a high priority goal to prevent future global pandemics. Antiviral development processes generally emphasize targeting a specific protein from a particular virus. However, some antiviral agents developed for specific viral protein targets may exhibit broad spectrum antiviral activity, or at least provide useful lead molecules for broad spectrum drug development. There is significant potential for repurposing a wide range of existing viral protease inhibitors to inhibit the SARS-CoV2 3C-like protease (3CLpro). If effective even as relatively weak inhibitors of 3CLpro, these molecules can provide a diverse and novel set of scaffolds for new drug discovery campaigns. In this study, we compared the sequence- and structure-based similarity of SARS-CoV2 3CLpro with proteases from other viruses, and identified 22 proteases with similar active-site structures. This structural similarity, characterized by secondary-structure topology diagrams, is evolutionarily divergent within taxonomically related viruses, but appears to result from evolutionary convergence of protease enzymes between virus families. Inhibitors of these proteases that are structurally similar to the SARS-CoV2 3CLpro protease were identified and assessed as potential inhibitors of SARS-CoV2 3CLpro protease by virtual docking. Several of these molecules have docking scores that are significantly better than known SARS-CoV2 3CLpro inhibitors, suggesting that these molecules are also potential inhibitors of the SARS-CoV2 3CLpro protease. Some have been previously reported to inhibit SARS-CoV2 3CLpro. The results also suggest that established inhibitors of SARS-CoV2 3CLpro may be considered as potential inhibitors of other viral 3C-like proteases.

VTR: A Web Tool for Identifying Analogous Contacts on Protein Structures and Their Complexes.

Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of the inter-residues contacts for the protein structure has been the target of many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular structures such as proteins. Here we show VTR, a new method for the detection of analogous contacts in protein pairs. The VTR web tool performs structural alignment between proteins and detects interactions that occur in similar regions. To evaluate our tool, we proposed three case studies: we 1) compared vertebrate myoglobin and truncated invertebrate hemoglobin; 2) analyzed interactions between the spike protein RBD of SARS-CoV-2 and the cell receptor ACE2; and 3) compared a glucose-tolerant and a non-tolerant ß-glucosidase enzyme used for biofuel production. The case studies demonstrate the potential of VTR for the understanding of functional similarities between distantly sequence-related proteins, as well as the exploration of important drug targets and rational design of enzymes for industrial applications. We envision VTR as a promising tool for understanding differences and similarities between homologous proteins with similar 3D structures but different sequences. VTR is available at http://bioinfo.dcc.ufmg.br/vtr.

Hydroxychloroquine (HCQ) Exhibits Better Binding to the Main Protease (Mpro) Compared to Spike Protein (S protein) of SARS-CoV-2: An In-silico Analysis

Background: Despite various efforts in preventing and treating SARS-CoV-2 infec-tions;transmission and mortality have been increasing at alarming rates globally. Since its first oc-currence in Wuhan, China, in December 2019, the number of cases and deaths due to SARS-CoV--2 infection continues to increase across 220 countries. Currently, there are about 228 million cases and 4.6 million deaths recorded globally. Although several vaccines/drugs have been reported to prevent or treat SARS-CoV-2, their efficacy to protect against emerging variants and duration of protection are not fully known. Hence, more emphasis is given to repurpose the existing pharmacological agents to manage the infected individuals. One such agent is hydroxychloroquine (HCQ), which is a more soluble derivative of antimalarial drug chloroquine. HCQ has been tested in clinical trials to mitigate SARS-CoV-2 infection-induced complications while reducing the time to clinical recovery (TTCR). However, several concerns and questions about the utility and efficacy of HCQ for treating SARS-CoV-2 infected individuals still persist. Identifying key proteins regulated by HCQ is likely to provide vital clues required to address these concerns. Objective: The objective of this study is to identify the ability of HCQ for binding to the most wide-ly studied molecular targets of SARS-CoV-2 viz., spike glycoprotein (S protein), and main pro-tease (Mpro, also referred as chymotrypsin like protease) using molecular docking approaches and correlate the results with reported mechanisms of actions of HCQ. Methods: X-ray crystallographic structures of spike glycoprotein and main protease of SARS-CoV-2 were retrieved from Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank (PDB). The structure of Hydroxychloroquine was retrieved from the PubChem compound database. The binding interactions of the HCQ with target proteins were predicted using C-Docker algorithm, and visualized using Discovery studio visualizer. Results: Data from molecular docking studies showed very strong binding of HCQ to the main pro-tease compared to spike glycoprotein. Conclusion: The antiviral activity of HCQ is attributed to its ability to bind to the main protease compared to surface glycoprotein. Therefore, future studies should focus more on developing a combination agent/strategy for targeting surface glycoprotein and main protease together.

Bioinformatics-Based Approaches to Study Virus-Host Interactions During SARS-CoV-2 Infection.

As the knowledge of biomolecules is increasing from the last decades, it is helping the researchers to understand the unsolved issues regarding virology. Recent technologies in high-throughput sequencing are providing the swift generation of SARS-CoV-2 genomic data with the basic inside of viral infection. Owing to various virus-host protein interactions, high-throughput technologies are unable to provide complete details of viral pathogenesis. Identifying the virus-host protein interactions using bioinformatics approaches can assist in understanding the mechanism of SARS-CoV-2 infection and pathogenesis. In this chapter, recent integrative bioinformatics approaches are discussed to help the virologists and computational biologists in the identification of structurally similar proteins of human and SARS-CoV-2 virus, and to predict the potential of virus-host interactions. Considering experimental and time limitations for effective viral drug development, computational aided drug design (CADD) can reduce the gap between drug prediction and development. More research with respect to evolutionary solutions could be helpful to make a new pipeline for virus-host protein-protein interactions and provide more understanding to disclose the cases of host switch, and also expand the virulence of the pathogen and host range in developing viral infections.

Large-Scale Structure-Based Screening of Potential T Cell Cross-Reactivities Involving Peptide-Targets From BCG Vaccine and SARS-CoV-2.

Although not being the first viral pandemic to affect humankind, we are now for the first time faced with a pandemic caused by a coronavirus. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been responsible for the COVID-19 pandemic, which caused more than 4.5 million deaths worldwide. Despite unprecedented efforts, with vaccines being developed in a record time, SARS-CoV-2 continues to spread worldwide with new variants arising in different countries. Such persistent spread is in part enabled by public resistance to vaccination in some countries, and limited access to vaccines in other countries. The limited vaccination coverage, the continued risk for resistant variants, and the existence of natural reservoirs for coronaviruses, highlight the importance of developing additional therapeutic strategies against SARS-CoV-2 and other coronaviruses. At the beginning of the pandemic it was suggested that countries with Bacillus Calmette-Guérin (BCG) vaccination programs could be associated with a reduced number and/or severity of COVID-19 cases. Preliminary studies have provided evidence for this relationship and further investigation is being conducted in ongoing clinical trials. The protection against SARS-CoV-2 induced by BCG vaccination may be mediated by cross-reactive T cell lymphocytes, which recognize peptides displayed by class I Human Leukocyte Antigens (HLA-I) on the surface of infected cells. In order to identify potential targets of T cell cross-reactivity, we implemented an in silico strategy combining sequence-based and structure-based methods to screen over 13,5 million possible cross-reactive peptide pairs from BCG and SARS-CoV-2. Our study produced (i) a list of immunogenic BCG-derived peptides that may prime T cell cross-reactivity against SARS-CoV-2, (ii) a large dataset of modeled peptide-HLA structures for the screened targets, and (iii) new computational methods for structure-based screenings that can be used by others in future studies. Our study expands the list of BCG peptides potentially involved in T cell cross-reactivity with SARS-CoV-2-derived peptides, and identifies multiple high-density "neighborhoods" of cross-reactive peptides which could be driving heterologous immunity induced by BCG vaccination, therefore providing insights for future vaccine development efforts.

Boosting the analysis of protein interfaces with multiple interface string alignments: Illustration on the spikes of coronaviruses.

We introduce multiple interface string alignment (MISA), a visualization tool to display coherently various sequence and structure based statistics at protein-protein interfaces (SSE elements, buried surface area, ΔASA , B factor values, etc). The amino acids supporting these annotations are obtained from Voronoi interface models. The benefit of MISA is to collate annotated sequences of (homologous) chains found in different biological contexts, that is, bound with different partners or unbound. The aggregated views MISA/SSE, MISA/BSA, MISA/ΔASA, and so forth, make it trivial to identify commonalities and differences between chains, to infer key interface residues, and to understand where conformational changes occur upon binding. As such, they should prove of key relevance for knowledge-based annotations of protein databases such as the Protein Data Bank. Illustrations are provided on the receptor binding domain of coronaviruses, in complex with their cognate partner or (neutralizing) antibodies. MISA computed with a minimal number of structures complement and enrich findings previously reported. The corresponding package is available from the Structural Bioinformatics Library (http://sbl.inria.frand https://sbl.inria.fr/doc/Multiple_interface_string_alignment-user-manual.html).

Identification of SARS-CoV-2 RNA-dependent RNA polymerase inhibitors from the major phytochemicals of Nigella sativa: An in silico approach.

The coronavirus disease 2019 (COVID-19), which emerged in December 2019, continues to be a serious health concern worldwide. There is an urgent need to develop effective drugs and vaccines to control the spread of this disease. In the current study, the main phytochemical compounds of Nigella sativa were screened for their binding affinity for the active site of the RNA-dependent RNA polymerase (RdRp) enzyme of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The binding affinity was investigated using molecular docking methods, and the interaction of phytochemicals with the RdRp active site was analyzed and visualized using suitable software. Out of the nine phytochemicals of N. sativa screened in this study, a significant docking score was observed for four compounds, namely α-hederin, dithymoquinone, nigellicine, and nigellidine. Based on the findings of our study, we report that α-hederin, which was found to possess the lowest binding energy (-8.6 kcal/mol) and hence the best binding affinity, is the best inhibitor of RdRp of SARS-CoV-2, among all the compounds screened here. Our results prove that the top four potential phytochemical molecules of N. sativa, especially α-hederin, could be considered for ongoing drug development strategies against SARS-CoV-2. However, further in vitro and in vivo testing are required to confirm the findings of this study.

The impact of structural bioinformatics tools and resources on SARS-CoV-2 research and therapeutic strategies.

SARS-CoV-2 is the causative agent of COVID-19, the ongoing global pandemic. It has posed a worldwide challenge to human health as no effective treatment is currently available to combat the disease. Its severity has led to unprecedented collaborative initiatives for therapeutic solutions against COVID-19. Studies resorting to structure-based drug design for COVID-19 are plethoric and show good promise. Structural biology provides key insights into 3D structures, critical residues/mutations in SARS-CoV-2 proteins, implicated in infectivity, molecular recognition and susceptibility to a broad range of host species. The detailed understanding of viral proteins and their complexes with host receptors and candidate epitope/lead compounds is the key to developing a structure-guided therapeutic design. Since the discovery of SARS-CoV-2, several structures of its proteins have been determined experimentally at an unprecedented speed and deposited in the Protein Data Bank. Further, specialized structural bioinformatics tools and resources have been developed for theoretical models, data on protein dynamics from computer simulations, impact of variants/mutations and molecular therapeutics. Here, we provide an overview of ongoing efforts on developing structural bioinformatics tools and resources for COVID-19 research. We also discuss the impact of these resources and structure-based studies, to understand various aspects of SARS-CoV-2 infection and therapeutic development. These include (i) understanding differences between SARS-CoV-2 and SARS-CoV, leading to increased infectivity of SARS-CoV-2, (ii) deciphering key residues in the SARS-CoV-2 involved in receptor-antibody recognition, (iii) analysis of variants in host proteins that affect host susceptibility to infection and (iv) analyses facilitating structure-based drug and vaccine design against SARS-CoV-2.

TMEM106B in humans and Vac7 and Tag1 in yeast are predicted to be lipid transfer proteins.

TMEM106B is an integral membrane protein of late endosomes and lysosomes involved in neuronal function, its overexpression being associated with familial frontotemporal lobar degeneration, and point mutation linked to hypomyelination. It has also been identified in multiple screens for host proteins required for productive SARS-CoV-2 infection. Because standard approaches to understand TMEM106B at the sequence level find no homology to other proteins, it has remained a protein of unknown function. Here, the standard tool PSI-BLAST was used in a nonstandard way to show that the lumenal portion of TMEM106B is a member of the late embryogenesis abundant-2 (LEA-2) domain superfamily. More sensitive tools (HMMER, HHpred, and trRosetta) extended this to predict LEA-2 domains in two yeast proteins. One is Vac7, a regulator of PI(3,5)P2 production in the degradative vacuole, equivalent to the lysosome, which has a LEA-2 domain in its lumenal domain. The other is Tag1, another vacuolar protein, which signals to terminate autophagy and has three LEA-2 domains in its lumenal domain. Further analysis of LEA-2 structures indicated that LEA-2 domains have a long, conserved lipid-binding groove. This implies that TMEM106B, Vac7, and Tag1 may all be lipid transfer proteins in the lumen of late endocytic organelles.

Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses.

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism and druggability of the virus. Peptide and epitope motifs have been detected on coronavirus spike proteins using sequence homology approaches; however, comparing the three-dimensional shape of the protein has been shown as more informative in predicting mimicry than sequence-based comparisons. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known protein models with the receptor-binding motifs and verify potential mimicked interactions with protein docking simulations. Both human and non-human proteins were returned for all three receptor-binding motifs. For example, all three were similar to several proteins containing EGF-like domains: some of which are endogenous to humans, such as thrombomodulin, and others exogenous, such as Plasmodium falciparum MSP-1. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.

Phytoconstituents from ten natural herbs as potent inhibitors of main protease enzyme of SARS-COV-2: In silico study.

Background: Lack of treatment of novel Coronavirus disease led to the search of specific antivirals that are capable to inhibit the replication of the virus. The plant kingdom has demonstrated to be an important source of new molecules with antiviral potential. Purpose: The present study aims to utilize various computational tools to identify the most eligible drug candidate that have capabilities to halt the replication of SARS-COV-2 virus by inhibiting Main protease (Mpro) enzyme. Methods: We have selected plants whose extracts have inhibitory potential against previously discovered coronaviruses. Their phytoconstituents were surveyed and a library of 100 molecules was prepared. Then, computational tools such as molecular docking, ADMET and molecular dynamic simulations were utilized to screen the compounds and evaluate them against Mpro enzyme. Results: All the phytoconstituents showed good binding affinities towards Mpro enzyme. Among them laurolitsine possesses the highest binding affinity i.e. -294.1533 kcal/mol. On ADMET analysis of best three ligands were simulated for 1.2 ns, then the stable ligand among them was further simulated for 20 ns. Results revealed that no conformational changes were observed in the laurolitsine w.r.t. protein residues and low RMSD value suggested that the Laurolitsine-protein complex was stable for 20 ns. Conclusion: Laurolitsine, an active constituent of roots of Lindera aggregata, was found to be having good ADMET profile and have capabilities to halt the activity of the enzyme. Therefore, this makes laurolitsine a good drug candidate for the treatment of COVID-19.

Recognition through GRP78 is enhanced in the UK, South African, and Brazilian variants of SARS-CoV-2; An in silico perspective.

New SARS-CoV-2 variants emerged in the United Kingdom and South Africa in December 2020 in concomitant with the Brazillian variant in February 2021 (B.1.1.248 lineage) and currently sparking worldwide during the last few months. The new strain 501.V2 in South Africa bears three mutations in the spike receptor-binding domain (RBD); K417 N, E484K, and N501Y, while the Brazilian B.1.1.248 lineage has 12 mutations. In the current study, we simulate the complex ACE2-SARS-CoV-2 spike RBD system in which the RBD is in the wild-type and mutated isoforms. Additionally, the cell-surface Glucose Regulated Protein 78 (CS-GRP78) associated with the ACE2-SARS-CoV-2 spike RBD complex (ACE2-S RBD) is modeled at the presence of these mutant variants of the viral spike. The results showed that E484K and N501Y are critical in viral spike recognition through either ACE2 or CS-GRP78. The mutated variants (the UK, South African, and Brazilian) of the spike RBD tightly bind to GRP78 more than in the case of the wild-type RBD. These results point to the potent role of GRP78 with ACE2 in the attachment of the new variants, which could be a key for the design of inhibitors to block SARS-CoV-2 attachment and entry to the host cell.

Arthropod Ectoparasites Have Potential to Bind SARS-CoV-2 via ACE.

Coronavirus-like organisms have been previously identified in Arthropod ectoparasites (such as ticks and unfed cat flea). Yet, the question regarding the possible role of these arthropods as SARS-CoV-2 passive/biological transmission vectors is still poorly explored. In this study, we performed in silico structural and binding energy calculations to assess the risks associated with possible ectoparasite transmission. We found sufficient similarity between ectoparasite ACE and human ACE2 protein sequences to build good quality 3D-models of the SARS-CoV-2 Spike:ACE complex to assess the impacts of ectoparasite mutations on complex stability. For several species (e.g., water flea, deer tick, body louse), our analyses showed no significant destabilisation of the SARS-CoV-2 Spike:ACE complex, suggesting these species would bind the viral Spike protein. Our structural analyses also provide structural rationale for interactions between the viral Spike and the ectoparasite ACE proteins. Although we do not have experimental evidence of infection in these ectoparasites, the predicted stability of the complex suggests this is possible, raising concerns of a possible role in passive transmission of the virus to their human hosts.

Repurposing biomedical informaticians for COVID-19.

The COVID-19 pandemic is an unprecedented challenge to the biomedical research community at the intersection of great uncertainty due to the novelty of the virus and extremely high stakes due to the large global death count. The global quarantine shut-downs complicated scientific matters because many laboratories were closed down unless they were actively doing COVID-19 related research, making repurposing of activities difficult for many biomedical researchers. Biomedical informaticians, who have been primarily able to continue their research through remote work and video conferencing, have been able to maintain normal activities. In addition to continuing ongoing studies, there has been great grass roots interest in helping in the fight against COVID-19. In this commentary, we describe several projects that arose from this desire to help, and the lessons that the authors learned along the way. We then offer some insights into how these lessons might be applied to make scientific progress be more efficient in future crisis scenarios.

Naltrexone a potential therapeutic candidate for COVID-19.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the cause of Coronavirus Disease (COVID-19) that has resulted in a global pandemic. At the time of writing, approximately 16.06 million cases have been reported worldwide. Like other coronaviruses, SARS-CoV-2 relies on the surface Spike glycoprotein to access the host cells, mainly through the interaction of its Receptor Binding Domain (RBD) with the host receptor Angiotensin-Converting Enzyme2 (ACE2). SARS-CoV-2 infection induces a profound downstream pro-inflammatory cytokine storm. This release of the pro-inflammatory cytokines is underpinning lung tissue damage, respiratory failure, and eventually multiple organ failure in COVID-19 patients. The phosphorylation status of ERK1/2 is positively correlated with virus load and ERK1/2 inhibition suppressed viral replication and viral infectivity. Therefore, molecular entities able to interfere with binding of the SARS-CoV-2 Spike protein to ACE2, or damping hyperinflammatory cytokines storm, blocking ERK1/2 phosphorylation have a great potential to inhibit viral entry along with viral infectivity. Herein, we report that the FDA-approved non-peptide opioid antagonist drug, naltrexone suppresses high fat/LPS induced pro-inflammatory cytokine release both from macrophage cells and Adipose Tissue Macrophage. Moreover, Low Dose Naltrexone (LDN) also showed its activity as an ERK1/2 inhibitor. Notably, virtual docking and simulation data also suggest LDN may disrupt the interaction of ACE2 with RBD. LDN may be considered as a target as the treatment and (or) adjuvant therapy for coronavirus infection. Clinical toxicity measurements may not be required for LDN since naltrexone was previously tested and is an approved drug by the FDA.Communicated by Ramaswamy H. Sarma.

Structure-based drug repositioning over the human TMPRSS2 protease domain: search for chemical probes able to repress SARS-CoV-2 Spike protein cleavages.

In December 2019, a new coronavirus was identified in the Hubei province of central china and named SARS-CoV-2. This new virus induces COVID-19, a severe respiratory disease with high death rate. A putative target to interfere with the virus is the host transmembrane serine protease family member II (TMPRSS2). This enzyme is critical for the entry of coronaviruses into human cells by cleaving and activating the spike protein (S) of SARS-CoV-2. Repositioning approved, investigational and experimental drugs on the serine protease domain of TMPRSS2 could thus be valuable. There is no experimental structure for TMPRSS2 but it is possible to develop quality structural models for the serine protease domain using comparative modeling strategies as such domains are highly structurally conserved. Beside the TMPRSS2 catalytic site, we predicted on our structural models a main exosite that could be important for the binding of protein partners and/or substrates. To block the catalytic site or the exosite of TMPRSS2 we used structure-based virtual screening computations and two different collections of approved, investigational and experimental drugs. We propose a list of 156 molecules that could bind to the catalytic site and 100 compounds that may interact with the exosite. These small molecules should now be tested in vitro to gain novel insights over the roles of TMPRSS2 or as starting point for the development of second generation analogs.