1076 10 20655 http://socictopen.socict.org/files/original/ec513b97ef2f12627bb5cb05476ebd7b.pdf ffcecdcd70b11714a4db4444be9ab0c7 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In Silico Discovery of Candidate Drugs against Covid-19 Creator An entity primarily responsible for making the resource Claudia Cava, Gloria Bertoli, Isabella Castiglioni Description An account of the resource Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Bioinformatics, COVID-19, Drugs, Gene network Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/v12040404 Source A related resource from which the described resource is derived Viruses Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Microbiology Language A language of the resource EN http://socictopen.socict.org/files/original/38531f4baee688488a4eb656fe5e29c8.pdf 14463fb7bca6184655ce2a663d26719c Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico identification and validation of triarylchromones as potential inhibitor against main protease of severe acute respiratory syndrome coronavirus 2. Creator An entity primarily responsible for making the resource Seema A Nayar, Brijesh Rathi, Vaishali Chandel, Garima Tripathi, Abhijeet Kumar, Dhruv Kumar Description An account of the resource The ongoing pandemic due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused COVID-19 has emerged as a severe threat to the life of human kind. The identification and designing of appropriate and reliable drug molecule for the treatment of COVID-19 patients is the pressing need of the present time. Among different drug targets, the main protease of SARS-CoV-2 is being considered as most effective target. In addition to the drug repurposing, different compounds of natural as well as synthetic origins are being investigated for their efficacy against different drug targets of SARS-CoV-2 virus. In that context, the chromone based natural flavonols have also exhibited significant antiviral properties against different targets of SARS-CoV-2. The in silico studies presented here discloses the efficacy of triarylchromones (TAC) as potential inhibitor against main protease of SARS-CoV-2. The molecular docking and ADMET study performed using 14 arylchromones which could easily be accessed through simple synthetic protocols, revealed best binding affinities in case of TAC-3 (-11.2 kcal/mol), TAC-4 (-10.5 kcal/mol), TAC-6 (-11.2 kcal/mol), TAC-7 (-10.0 kcal/mol). Additional validation studies including molecular dynamics simulation and binding energy calculation using MMGBSA for protein ligand complex for 100 ns revealed the best binding interaction of TAC-3, TAC-4, TAC-6, TAC-7 against main protease of SARS-CoV-2. Moreover, the in vitro and preclinical validation of identified compounds will help us to understand the molecular mechanisms of regulation of TACs against SARS-CoV-2.Communicated by Ramaswamy H. Sarma. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource molecular docking, covid-19, main protease, molecular dynamics simulation, ADME, Arylchromone Identifier An unambiguous reference to the resource within a given context 10.1080/07391102.2021.1918255 Source A related resource from which the described resource is derived Journal of biomolecular structure & dynamics http://socictopen.socict.org/files/original/8fb757da4f33e6ac02ec1bbbf66aef31.pdf 1c23d9bdeb213468a8ebb87b35551a13 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico identification of vaccine targets for 2019-nCoV [version 1; peer review: 2 approved] Creator An entity primarily responsible for making the resource Chloe Hyun-Jung Lee, Hashem Koohy Description An account of the resource Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context DOI: 10.12688/f1000research.22507.1 Source A related resource from which the described resource is derived F1000Research Publisher An entity responsible for making the resource available F1000 Research Ltd Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Medicine Language A language of the resource EN http://socictopen.socict.org/files/original/8be0c28e660bd5a46490e0c5b2824a65.pdf 1c23d9bdeb213468a8ebb87b35551a13 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico identification of vaccine targets for 2019-nCoV [version 1; peer review: 2 approved] Creator An entity primarily responsible for making the resource Chloe Hyun-Jung Lee, Hashem Koohy Description An account of the resource Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context DOI: 10.12688/f1000research.22507.1 Source A related resource from which the described resource is derived F1000Research Publisher An entity responsible for making the resource available F1000 Research Ltd Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Medicine Language A language of the resource EN http://socictopen.socict.org/files/original/50adb21c3ff8d1965e2806c60e8336b6.pdf 1c23d9bdeb213468a8ebb87b35551a13 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico identification of vaccine targets for 2019-nCoV [version 2; peer review: 3 approved] Creator An entity primarily responsible for making the resource Hashem Koohy, Chloe H. Lee Description An account of the resource Background: The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (18-February-2020), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China. Methods: The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0. Results: We report in silico identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a de novo search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential. Conclusions: Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context DOI: 10.12688/f1000research.22507.2 Source A related resource from which the described resource is derived F1000Research Publisher An entity responsible for making the resource available F1000 Research Ltd Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Medicine http://socictopen.socict.org/files/original/05c227e4192b8542d6b7927b8d6a3de0.pdf a186cf573066089972f2b683179277a3 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico Molecular Docking Analysis Targeting SARSCoV-2 Spike Protein and Selected Herbal Constituents Creator An entity primarily responsible for making the resource Pallab Chaudhuri, Raj Kumar Singh, Kuldeep Dhama, Yashpal S. Malik, Prasad Thomas, Muthu Sankar, Shiv Varan Singh, Karthikeyan Ravichandran, Anbazhagan Subbaiyan Description An account of the resource In modern drug discovery, molecular docking analysis is routinely used to understand and predictthe interaction between a drug molecule and a target protein from a microbe. Drugs identified inthis way may inhibit the entry and replication of pathogens in host cells. The SARS-CoV-2 associatedcoronavirus disease, COVID-19, has become the most contagious and deadly pandemic disease in theworld today. In abeyance of any specific vaccine or therapeutic against SARS-CoV-2, the burgeoningsituation urges a need for effective drugs to treat the virus-infected patients. Herbal medicines havebeen used as natural remedies for treating various infectious diseases since ancient times. The spike(S) protein of SARS-CoV-2 is important for the attachment and pathogenesis of the virus. Therefore,this study focused on the search of useful ligands for S protein among active constituents present incommon herbs that could serve as efficient remedies for COVID-19. We analysed the binding efficiencyof twelve compounds present in common herbs with the S protein of SARS-CoV-2 through moleculardocking analysis and also results are validated with two different docking tools. The binding efficiencyof ligands was scored based on their predicted pharmacological interactions coupled with bindingenergy estimates. In docking analysis, compound “I” (Epigallocatechin gallate (EGCG)) was found tohave the highest binding affinity with the viral S protein, followed by compounds, “F” (Curcumin),“D”(Apigenin) and “E” (Chrysophanol). The present study corroborates that compound “I” (EGCG) mostlypresent in the integrants of green tea, shows the highest potentiality for acting as an inhibitor of SARSCoV-2. Further, characterization of the amino acid residues comprising the viral binding site and thenature of the hydrogen bonding involved in the ligand-receptor interaction revealed significant findingswith herbal compound “I” (EGCG) binding to the S protein at eight amino acid residues. The bindingsites are situated near to the amino acids which are required for virus pathogenicity. The findings ofthe present study need in vivo experiments to prove the utility of “I”, “F”,“D” and “E” compounds andtheir further use in making herb-based anti-SARS-CoV-2 product in near future. This analysis may helpto create a new ethno-drug formulation for preventing or curing the COVID-19. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource molecular docking, spike protein, Herbal medicine, Ligands, in silico, SARS-CoV-2, COVID-19 Identifier An unambiguous reference to the resource within a given context DOI: 10.22207/JPAM.14.SPL1.37 Source A related resource from which the described resource is derived Journal of Pure and Applied Microbiology Publisher An entity responsible for making the resource available Journal of Pure and Applied Microbiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Microbiology http://socictopen.socict.org/files/original/220007106919e6de174c10c03c1cd161.pdf 4fcc6f3937dc891a2e966eaea413ba6b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico prediction of structure and function for a large family of transmembrane proteins that includes human Tmem41b [version 2; peer review: 1 approved, 2 approved with reservations] Creator An entity primarily responsible for making the resource Shahram Mesdaghi, David L. Murphy, Filomeno Sánchez Rodríguez, J. Javier Burgos-Mármol, Daniel J. Rigden Description An account of the resource Background: Recent strides in computational structural biology have opened up an opportunity to understand previously uncharacterised proteins.  The under-representation of transmembrane proteins in the Protein Data Bank highlights the need to apply new and advanced bioinformatics methods to shed light on their structure and function.  This study focuses on a family of transmembrane proteins containing the Pfam domain PF09335 ('SNARE_ASSOC'/ ‘VTT ‘/’Tvp38’/'DedA'). One prominent member, Tmem41b, has been shown to be involved in early stages of autophagosome formation and is vital in mouse embryonic development as well as being identified as a viral host factor of SARS-CoV-2. Methods: We used evolutionary covariance-derived information to construct and validate ab initio models, make domain boundary predictions and infer local structural features.  Results: The results from the structural bioinformatics analysis of Tmem41b and its homologues showed that they contain a tandem repeat that is clearly visible in evolutionary covariance data but much less so by sequence analysis.  Furthermore, cross-referencing of other prediction data with covariance analysis showed that the internal repeat features two-fold rotational symmetry.  Ab initio modelling of Tmem41b and homologues reinforces these structural predictions.  Local structural features predicted to be present in Tmem41b were also present in Cl-/H+ antiporters.  Conclusions: The results of this study strongly point to Tmem41b and its homologues being transporters for an as-yet uncharacterised substrate and possibly using H+ antiporter activity as its mechanism for transport. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.12688/f1000research.27676.2 Source A related resource from which the described resource is derived Biotemas Publisher An entity responsible for making the resource available Universidade Federal de Santa Catarina Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine http://socictopen.socict.org/files/original/14090ac0a128053b74fedf69ab270576.pdf e73494539af876705be6c06f58e3a480 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico screening of potent bioactive compounds from honeybee products against COVID-19 target enzymes. Creator An entity primarily responsible for making the resource Mohamed M. Abdel-DAIM, Moataz A Shaldam, Galal Yahya, Nashwa H Mohamed, Yahya Al Naggar Description An account of the resource After the early advent of the Coronavirus Disease 2019 (COVID-19) pandemic, myriads of FDA-approved drugs have been massively repurposed for COVID-19 treatment based on molecular docking against selected protein targets that play fundamental roles in the replication cycle of the novel coronavirus. Honeybee products are well known of their nutritional values and medicinal effects. Bee products contain bioactive compounds in the form of a collection of phenolic acids, flavonoids, and terpenes of natural origin that display wide spectrum antiviral effects. We revealed by molecular docking the profound binding affinity of 14 selected phenolics and terpenes present in honey and propolis (bees glue) against the main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) enzymes of the novel SARS-CoV-2 virus (the causative agent of COVID-19) using AutoDock Vina software. Of these compounds, p-coumaric acid, ellagic acid, kaempferol, and quercetin have the strongest interaction with the SARS-CoV-2 target enzymes, and it may be considered an effective COVID-19 inhibitor. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource molecular docking, covid-19, drug repurposing, Phenolic compounds, Natural products, Honeybee products Identifier An unambiguous reference to the resource within a given context 10.1007/s11356-021-14195-9 Source A related resource from which the described resource is derived Environmental science and pollution research international http://socictopen.socict.org/files/original/32f442794af968575b701720ce574df4.pdf 1da17dff95069ae06f48b458ad96a876 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico study of dynamic level interaction between CLF36 peptide and coronavirus surface protein in Bovine coronaviruses Creator An entity primarily responsible for making the resource Mojtaba Tahmoorespur, Abdulaziz Hamadalahmad, Marjan Azghandi, Zana Pirkhezranian Description An account of the resource Considering the fact that coronavirus is one of the major causes of calf diarrhea syndrome, this study aimed to investigate the interaction between the peptide cLF36 and the coronavirus protein by utilizing computational methods. Coronavirus amino acid sequence was obtained and molecular docking between coronavirus and the engineered camel lactoferrin was performed. The simulation model was conducted using PROMX model. The results showed that the highest bond length was 2.5 Å and the lowest 1.7Å which makes the connection between the two proteins strong, robust, and close to reality. According to the obtained results, cLF36 is a promising potential drug in the treatment of calf diarrhea. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource coronavirus, calf diarrhea, Molecular Docking Simulation, camel lactoferrin Identifier An unambiguous reference to the resource within a given context 10.30493/dls.2020.235579 Source A related resource from which the described resource is derived Dysona. Life Science Publisher An entity responsible for making the resource available E-NAMTILA Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Biology (General) http://socictopen.socict.org/files/original/679e298d97535f581c06bf27f130e766.pdf fc648fea843d70e8a10fa41e4d1d739e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource In silico Study of Pharmacological Treatments against SARS-CoV2 Main Protease Creator An entity primarily responsible for making the resource Youness Kadil, Mohamed Mouhcine, Houda Filali Description An account of the resource The COVID-19 caused by a new type of coronavirus has emerged from China and led to thousands ofdeath globally. Despite the efforts engaged in studying this newly emerged virus and searching for itstreatment, the understanding of the COVID-19 drug and target protein interactions still represent a keychallenge. Several molecules have demonstrated In-Vitro activity against the SARS-CoV-2 virus and/or potential clinical benefit in observational and non-randomized studies. Randomized clinical trialsof an appropriate size are currently ongoing to establish the efficacy of these therapeutic proposals.Herein, concerning these diverse guidelines and therapeutic suggestions of different approaches to thetreatment, this research aims to provide a molecular analysis of the interaction between the principalmolecules cited in bibliography and the active protease site of the virus. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource protease, docking, pharmacological treatment, SARS-CoV-2, COVID-19 Identifier An unambiguous reference to the resource within a given context DOI: 10.22207/JPAM.14.SPL1.45 Source A related resource from which the described resource is derived Journal of Pure and Applied Microbiology Publisher An entity responsible for making the resource available Journal of Pure and Applied Microbiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Microbiology