{"paper_id":"0378700f-c471-418a-bd2f-109f214dc862","body_text":"ADPDB: A Comprehensive Knowledgebase of Manually Curated Peptides Against Dengue Virus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ADPDB: A Comprehensive Knowledgebase of Manually Curated Peptides Against Dengue Virus Rajat Kumar Mondal, Ananya Anurag Anand, Sintu Kumar Samanta This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4000627/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 May, 2024 Read the published version in International Journal of Peptide Research and Therapeutics → Version 1 posted 7 You are reading this latest preprint version Abstract Recently, there have been estimates of 390 million dengue infections annually worldwide. Thus, Dengue viruses (DENV) continue to result in a severe burden on the human health all over the world. There are four different serotypes of DENV depending on antigenicity. Each can result in a life-threatening condition. For such a severe disease, present-day options of treatment are certainly limited and most patients rely on supportive care. Although there has been a dengue vaccine approved with modest efficacy, there is an urgent need for drugs that can reduce the complications that occur as a result of dengue. Some recent advances have been made in the development of drugs for combating dengue. These include some new vaccine candidates, invention of peptide-based drugs (antimicrobial peptides or AMPs), and repurposing of a few existing ones. Out of these, peptide-based drugs are recently under the limelight for their enhanced efficacy against the DENV and are being tested for their efficacy in preventing dengue in different parts of the world. In this context, we have developed a database that highlights the efforts made in the direction of peptide-based drugs against DENV. The database mentions the important features of all the anti-DENV peptides recorded up to date. These include source, target, mode of action, sequence, length, IC50, toxicity, etc. Our database also presents a holistic view of the overall situation of the peptide-based discovery for dengue. The database is accessible via any web browser at https://bblserver.org.in/adpdb/. Anti-dengue peptides Anti-Dengue Peptide Database (ADPDB) Anti-microbial peptides (AMPs) Biological Data Curation & Analysis Biological Database Development. Figures Figure 1 Figure 2 Figure 3 Introduction Dengue is an important mosquito-borne disease caused by the dengue viruses (DENVs), which is estimated to cause around 25,000 deaths per year (Reginald et al., 2018 ). Aedes albopictus and Aedes aegypti are the commonly known vectors of transmission for DENV (Guardia and Lleonart, 2014 ). At present, dengue is an endemic disease in more than 100 countries, especially in the sub-tropical and tropical regions (Chew et al., 2017 ). DENV-1-4 are the four serotypes of dengue virus, that are found to be antigenically as well as genetically distinct from each other. Surprisingly, even though they are distinct, they all cause similar sicknesses. People infected with any of these types may experience a range of symptoms, from asymptomatic fever to things like joint pain, rash, and other mild issues.It may also result in life-threatening symptoms like dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) in severe cases (Shukla et al., 2023 ). The most important thing to note regarding these serotypes is that the infection with one induces lifelong immunity against only itself and not the other three serotypes. This is why the disease becomes of utmost concern. A common strategy that has been undertaken to stop DENV infection is primarily by vector control ( Kala et al., 2023 ). The use of fog and the spreading of genetically modified (GM) mosquitoes are among the commonly known strategies that have failed to prevent the mosquito population from increasing. While active research on the development of vaccines has been ongoing for the past few decades, it has been held back by numerous challenges. The major problems faced during dengue vaccine development include the lack of appropriate animal models and the difference in antigenicity of each serotype which creates a hurdle in developing a single candidate against all four serotypes ( Kala et al., 2023 ). The first dengue vaccine, CYD-TDV (chimeric yellow fever virus-tetravalent dengue vaccine) was a live-attenuated tetravalent vaccine comprising envelope proteins of DENV (Chew et al., 2017 ). However, its overall efficacy against DENV is low, especially that against DENV-2 remaining at only 39%. The CYD-TDV vaccine has also been shown to cause risks of hospitalization in children who are less than nine years of age. Thus, the World Health Organization (WHO) recommends the usage of this vaccine only in countries with an extremely high burden of dengue. Also, there are no antiviral drugs against DENV available at present (Chew et al., 2017 ). The only therapy is supportive treatment with fluid restoration and close clinical monitoring. Although nucleoside analogs, like balapiravir, had entered preclinical and clinical trials, were terminated due to the lack of potency. Similarly, other anti-DENV drugs, such as chloroquine, celgosivir, and lovastatin, have undergone clinical trials but have failed to meet the expectations. Unlike small molecules, peptides are marked by high selectivity and specificity, along with less off-target toxicity, which makes them insightful candidates for further testing. Due to their excellent pharmacological properties, several peptides are being tested against DENV. Also, the success of the antiviral peptide, Enfuvirtide, which has been recently approved by the Food and Drug Administration (FDA) has further led to gaining more insight on the use of antiviral peptides as an alternative to small molecule-based therapy or other treatment strategies (Lee et al., 2023 ). It is crucial to note that any research depends on the existence of certain resources, without which it either slows down or ends up lacking clarity. For the same reason, several specialized databases have been made in the past that contain different AMPs against various target organisms specifically. Some of the most recent examples are ANTISTAPHYBASE (Zouhir et al., 2017 ), ANTIPSEUDOBASE (Zouhir et al., 2023 ), ACovPepDB (Zhang et al., 2022 ), and HIPdb (Qureshi et al., 2013 ) which contain peptide-based drugs against Staphylococcus species, Pseudomonas species , Coronavirus, and HIV respectively. To date, there is no single database specifically developed for anti-dengue virus peptides. The entire scenario of the spread of dengue worldwide and the limited treatment options, we were provoked to create a database specialized for anti-dengue peptides, named as Anti-Dengue Peptide Database (ADPDB). All the known antimicrobial peptides (AMPs) against DENV and related information has been curated in this crucial database. Hopefully, this database will aid in the further research of anti-dengue peptides. Material & Method 4.1. Data curation & compilation 4.1.1. Curation of anti-dengue peptides PubMed literature database ( https://pubmed.ncbi.nlm.nih.gov/ ) was used as a source database for curating the data. In PubMed, we used the following queries to curate the PubMed IDs of those articles which contain the information about anti-dengue peptides. Query 1: ((((dengue virus) OR breakbone fever)) AND ((peptide) OR peptides)) AND ((inhibit*) OR block*) Query 2: ((((dengue virus) OR dengue)) AND ((peptide) OR peptides)) AND ((inhibit*) OR block*) The search of both the above queries was done on the 14th of October, 2023. Both queries returned 819 PubMed IDs each (total:1638). Further, all PubMed IDs were listed and the duplicate IDs were removed using Microsoft Excel. After getting rid of redundancy, we got 820 unique PubMed IDs. After this, each article of respective PMID was thoroughly studied one by one and data was curated for the following fields: ‘anti-dengue peptide name’, ‘sequence’, ‘source’, ‘taxonomy’, ‘target organism with strain’, ‘inhibition concentration’, ‘target component’, ‘target process’, ‘mode of action (MoA)’, ‘toxicity’, ‘hemolytic activity’, and ‘validation’. It is important to note that in some peptide sequences, we did not find a linear sequence. These sequences were put as it is in the dataset. Moreover, in some cases ‘anti-dengue peptide name’ was missing and only the ‘sequence’ was available in the article and vice-versa. The missing values fields were filled up with a ‘not available’ string. After curating the data, we got our master anti-dengue peptide dataset with 606 peptides. 4.1.2. Compositional details and physicochemical properties computation We utilized our custom Python package named proteinAnalysis2 ( https://github.com/rajat-kumar-mondal/proteinAnalysis2 ) to calculate the compositional details and physicochemical properties of peptides. This package is developed in pure Python language (version 3.12.1) ( https://www.python.org/ ) , and an upgraded version of the original proteinAnalysis package (version 1) (Mondal et al., 2023 ). It incorporates functionalities from the proteinAnalysis class of the proteinAnalysis package (version 1) (Mondal et al., 2023 ), the ProteinAnalysis class of the ProtParam module of the Bio package (version 1.82) ( https://biopython.org/ ) , and the Peptide class of the peptides package (version 0.3.1) ( https://pypi.org/project/peptides/ ). The proteinAnalysis2 package ( https://github.com/rajat-kumar-mondal/proteinAnalysis2 ) is enormously capable of computing various basic details and properties of a peptide which are shown in Table 1 . Table 1 Table of compositional details and physicochemical properties that can be calculated by proteinAnalysis2 ( https://github.com/rajat-kumar-mondal/proteinAnalysis2 ). Compositional details Physicochemical properties Length Molecular weight Molecular formula Aliphatic index Amino acid counts Instability index Amino acid frequencies GRAVY Missing amino acid Hydrophilicity Most occurring amino acid Hydrophobic moment Less occurring amino acid Net charge Hydrophobic amino acid counts Isoelectric point Hydrophilic amino acid counts Structural class Basic amino acid counts Mass shift Acidic amino acid counts Aromaticity Modified amino acid counts Secondary structure fraction Modified amino acid frequencies Molar extinction coefficient (cysteine|cysteine) By invoking the ‘all_comp_physP’ function from proteinAnalysis2 class of the proteinAnalysis2 package ( https://github.com/rajat-kumar-mondal/proteinAnalysis2 ) , users can effortlessly obtain a dictionary containing all the compositional details and physicochemical properties of a given peptide sequence. This function was specifically employed to compute these details for anti-dengue peptides. As we mentioned earlier in some cases of peptide sequence, we did not find the straightforward sequence and in some cases peptide sequence was unavailable, in those cases, we put the following information as a string. If the peptide sequence is unavailable, we put “The peptide sequence is unavailable. Unable to calculate compositional details and physicochemical properties”. If the peptide sequence contains some special characteristics (e.g., benzoyl compound), we put “Some special compound(s) is/are present with the peptide sequence. Unable to calculate compositional details and physicochemical properties”. In this way, the computation of compositional details and physicochemical properties was done for 606 anti-dengue peptides that are present in our dataset. 4.2. Development of backend and frontend The core of ADPDB backend was constructed using an HTTPS server in PhpMyAdmin (version 5.1.1), housing a Relational Database Management System (RDBMS) i.e., MySQL server (version 5.7.36). The frontend development employs HTML5, Bootstrap5, CSS3, JS, jQuery, Chart.js, DataTables, and AJAX. 4.3. User interface of the database The user interface (UI) of the database is very simple, straightforward, responsive, and interactive. Figure 1 shows some of the glimpses of the database UI. 4.3.1. Homepage : The homepage of ADPDB displays a brief introduction about the database. 4.3.2. Search : On this page, a user will be able to find the simple text search and advanced search options. A user can search for any relevant information regarding anti-dengue peptides in the simple text search facility. In the case of the advanced search facility, a user can search in a specific field like ‘peptide name’, ‘length’, ‘source’, and more. A help button is given with both types of search facilities for user assistance. 4.3.3. Result retrieving : All the search results will appear in a table format. The table is searchable and sortable itself. Pagination is also provided in the table for ease of use. Moreover, users can download specific entry/entries by selecting them or current page entries or all entries in a suitable format (including FASTA, TSV, CSV, LIST, JSON, TEXT, and Custom TSV) by clicking on the appropriate option from the download button. Users can view a single entry by clicking on the individual ID (e.g., ADPDB2) and export in FASTA, TEXT, and PDF format further. 4.3.4. Browse : On this page, the entire data of ADPDB is displayed. Users can study all the entries of ADPDB using this page. 4.3.5. Statistics : On this page, the data statistics are categorized by ‘peptide source’, ‘length’, ‘molecular weight’, and ‘net charge’ & displayed as an interactive bar chart. The Y axis of all bar charts is initially set to a scale of 10, as there is a considerable range between the lowest and highest number of records. This deliberate design choice aims to enhance visualizations. To adjust the scale, users can click on either the \"Rescale X Axis\" or \"Rescale Y Axis\" buttons to modify the plot accordingly. Click on \"Rescale to Initial\" to bring the plot to its initial point. Figure 2 shows the data statistics of ADPDB. 4.3.6. Downloads : From this page, a user can download the master dataset of ADPDB in XLSX, CSV, TSV, LIST, TEXT, and FASTA format. 4.3.7. News/updates : All the latest news/updates regarding ADPDB will be displayed on this page. 4.3.8. Developers : Users can find all the developer's information on this page. 4.3.9. Help : On this page, all the details of the search facilities and a full description of the TEXT format of ADPDB are shown. 4.3.10. Contact : The contact details of the principal investigator and core technical developers are displayed here. Users can reach out to them from this page. A web form is also provided on the same page which can be used by the user to raise any query/doubt. In Fig. 3 a diagrammatic representation of the end-to-end development of ADPDB is shown. Results and discussion 5.1 Insights from ADPDB ADPDB is the first comprehensive knowledge base of anti-dengue peptides found widely. This database can be specifically used to target dengue viruses (including DENV-1, DENV-2, DENV-3, DENV-4). The database supports simple text searches to intuitive advanced search facility. Moreover, the database also allows user to manipulate the data as per their need and export it in multiple formats like TSV, TEXT, LIST, FSATA, JSON, etc. in local machines for further analysis or development. Users also can obtain fully customized reports as per their requirements from the database's custom report facility. While viewing an individual entry the database displays the result in the following 6 parts. General description which includes ADPDB ID, peptide name, source, taxonomy, and validation. Peptide sequence & composition which includes length, molecular formula, amino acid (AA) counts, AA frequencies, missing AA, AA which occurs most & less, hydrophobic & hydrophilic AA counts, acidic & basic AA counts, counts and frequencies of modified AA. Physicochemical properties which include molecular weight, aromaticity, aliphatic index, instability index, hydrophobic moment, GRAVY, net charge, secondary structure fraction (SSF), molar extinction coefficient, mass shift, etc. Structural Class of the Peptide. Activity Information includes target organism, family, inhibition concentration information, target component information, target process information, mode of action, toxicity, and hemolytic activity. Database cross-references which include the PubMed ID. At present, this database contains a total of 606 peptide entries. These peptides originate from different sources: Algae (1), Animalia (34), Bacteria (10), Fungi (4), Plantae (16), Synthetic (428), Virus (34). There are 79 peptides for which the source is not available. Out of 606 entries, 32 peptide sequences are unavailable in the database due to their unavailability in the source literature, and 352 sequences are special types of sequences meaning they contain special types of compounds as a part of them. 222 sequences are pure peptide sequences (do not contain any special compound with them) that are present in the database. The length of the peptides varies between 1 to 80 AA, molecular weight lies between 1 to 10000 Da, and net charge lies between − 5 to 20. Scientists, researchers, and pharmaceutical industries can use this database for novel drugs & therapeutics development for dengue. 5.2 Comparison with other existing databases Till now, many databases have been dedicated to AMPs in a generalized and specialized manner, since antimicrobial resistance (AMR) is a major issue. Some of the well-known generalized databases include CAMP R4 (Gawde et al., 2023 ), DRAMP 3.0 (Shi et al., 2022 ), dbAMP 2.0 (Jhong et al., 2022 ), AMPDB v1 (Mondal et al., 2023 ), APD3 (Wang et al., 2016 ), etc. There are also renowned specialized databases of AMPs like Peptaibols Database (Whitmore and Wallace 2004 ), Defensins KnowledgeBase (Seebah et al., 2007 ), LAMP (Zhao et al., 2013 ), InverPep (Gómez et al., 2017 ), MilkAMP (Théolier et al., 2014 ), PhytAMP (Hammami et al., 2009 ), RAPD ( Li et al., 2008 ), SAPdb (Mathur et al., 2021 ), ANTISTAPHYBASE (Zouhir et al., 2017 ), ANTIPSEUDOBASE (Zouhir et al., 2023 ), DRAVP (Liu et al., 2023 ), AVPdb (Qureshi et al., 2014 ), HIPdb (Qureshi et al., 2013 ), ACovPepDB (Zhang et al., 2022 ), etc. The generalized AMP databases contain overall every type of AMP whereas the specialized AMP databases contain the data of some specific types. Peptaibols Database (Whitmore and Wallace 2004 ) and Defensins knowledgebases (Seebah et al., 2007 ) contain the data of peptaibols and defensins whereas LAMP (Zhao et al., 2013 ) deals with linking AMPs. InverPep (Gómez et al., 2017 ), MilkAMP (Théolier et al., 2014 ), and PhytAMP (Hammami et al., 2009 ) contain data of invertebrate AMPs, AMPs from milk sources, and plant AMPs. RAPD ( Li et al., 2008 ) and SAPdb (Mathur et al., 2021 ) deal with the data of recombinant and synthetic AMPs respectively. DRAVP (Liu et al., 2023 ) and AVPdb (Qureshi et al., 2014 ) have information about the antiviral peptides. ANTISTAPHYBASE (Zouhir et al., 2017 ) and ANTIPSEUDOBASE (Zouhir et al., 2023 ) are two specific target bacteria databases that contain data about AMPs and EOs that can be used to target Staphylococcus and Pseudomonas species, whereas HIPdb (Qureshi et al., 2013 ) and ACovPepDB (Zhang et al., 2022 ) are only two target virus databases that holds that information about anti-HIV and anti-Corona virus peptides specifically. All the databases (generalized and specialized) that are dedicated to AMPs, to date, hold very useful information for antimicrobial drugs and therapeutics developments. However, there is no single database which is dedicated to anti-dengue peptides. Moreover, dengue is very prevalent in tropical & sub-tropical countries and the mortality rate for dengue is quite high (Chew et al., 2017 ). The drugs that are available in the market for dengue are less effective and often produce side effects (Obi et al., 2021 ). In this scenario, anti-viral peptides (a type of AMP) can be a better therapeutic alternative. Keeping all this in mind, we developed the ADPDB, the first dedicated database for anti-dengue peptides, to develop a better, safer, and economical treatment strategy for dengue virus. At this moment the drawback of this ADPDB is that this database does not contain any kind of tools like BLAST or MUSCLE or any other related tools. However, it will be improved in its future versions,. Conclusion & Future perspectives Despite an approved dengue vaccine, it doesn't cover all DENV types, posing a challenge in affected regions. Urgently needed are effective drugs for all DENV strains. Promisingly, anti-dengue peptides offer a solution, serving as both drugs and vaccine candidates. While biocompatible and cost-effective, efforts to enhance their effectiveness, using long peptides and nanoparticle delivery, are underway. Recognizing the need, we've developed ADPDB, a dedicated anti-DENV peptide database, to aid future discoveries. As per our knowledge, ADPDB is the first such database to be specialized for anti-DENV peptides. This resource aims to facilitate access to crucial information on peptides against DENV. Currently, the database contains 606 sequences of DENV-active peptides, both natural and synthetic combined. ADPDB allows an easy and fast browsing of peptides and related information on their properties and activity. Using information on these peptide-based drug candidates, the researchers can design new drugs using studies like structure-activity relationships or generate new leads by incorporating the data into ML models. Hopefully, ADPDB will help enhance the understanding of anti-DENV peptides to a better extent and will aid in the development of new molecules for medical use. Declarations 7. Data availability The master dataset of ADPDB is openly accessible in XLSX, CSV, TSV, LIST, FASTA, and TEXT formats at the URL: https://bblserver.org.in/adpdb/adpdb-download. 8. Acknowledgements 9. Rajat Kumar Mondal and Ananya Anurag Anand are thankful to MoE-GoI for their fellowship. We are extremely thankful to IIIT-A for providing the infrastructural facility i.e. Central Computing Facility. 10. Author contributions R.K.M.: Conceptualization, Resources, Investigation and Data Analysis, Validation, Writing; A.A.A.: Resources, Data mining and curation, Data Analysis and Writing; S.K.S.: Conceptualization, Formal Analysis, Supervision, Writing-review & editing. 11. Conflict of interests The authors declare no conflict of interest. 12. Funding There was no funding for this project. References Chew MF, Poh KS, Poh CL (2017) Peptides as therapeutic agents for dengue virus. 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Nucleic Acids Res 32(suppl1):D593–D594 Zhang Q, Chen X, Li B, Lu C, Yang S, Long J, Chen H, Huang J, He B (2022) A database of anti-coronavirus peptides. Scientific Data , 9 (1), p.294 Zhao X, Wu H, Lu H, Li G, Huang Q (2013) LAMP: a database linking antimicrobial peptides. PLoS ONE 8(6):e66557 Zouhir A, Souiai O, Harigua E, Cherif A, Chaalia AB, Sebei K (2023) ANTIPSEUDOBASE: Database of Antimicrobial Peptides and Essential Oils Against Pseudomonas. International Journal of Peptide Research and Therapeutics , 29 (3), p.37 Zouhir A, Taieb M, Lamine MA, Cherif A, Jridi T, Mahjoubi B, Mbarek S, Fliss I, Nefzi A, Sebei K, Hamida B, J (2017) ANTISTAPHYBASE: database of antimicrobial peptides (AMPs) and essential oils (EOs) against methicillin-resistant Staphylococcus aureus (MRSA) and Staphylococcus aureus. Arch Microbiol 199:215–222 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 May, 2024 Read the published version in International Journal of Peptide Research and Therapeutics → Version 1 posted Editorial decision: Revision requested 19 Mar, 2024 Reviews received at journal 08 Mar, 2024 Reviewers agreed at journal 07 Mar, 2024 Reviewers invited by journal 07 Mar, 2024 Editor assigned by journal 01 Mar, 2024 Submission checks completed at journal 01 Mar, 2024 First submitted to journal 29 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-4000627\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":275877192,\"identity\":\"5827d77a-ee1c-4b86-a7e1-60c8623b01e2\",\"order_by\":0,\"name\":\"Rajat Kumar Mondal\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Indian Institute of Information Technology Allahabad (IIIT-A)\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rajat\",\"middleName\":\"Kumar\",\"lastName\":\"Mondal\",\"suffix\":\"\"},{\"id\":275877193,\"identity\":\"74a01c54-97f4-4391-9421-c09d771463ad\",\"order_by\":1,\"name\":\"Ananya Anurag Anand\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Indian Institute of Information Technology Allahabad (IIIT-A)\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ananya\",\"middleName\":\"Anurag\",\"lastName\":\"Anand\",\"suffix\":\"\"},{\"id\":275877194,\"identity\":\"0cf1b37c-5914-4cb0-8216-5dae4762f285\",\"order_by\":2,\"name\":\"Sintu Kumar Samanta\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA70lEQVRIiWNgGAWjYDADNhDxwUCCB8qXIKA+AaSFmYFxBlALD9FaGIBamEHKefArZWCQbz+d+Lnwh509n3T/MWmbAgsZe/YDjB9+MFjk4dJicCZ3s/SMhOTENpnDbNI5IIfxJDBL9jBIFOPUwpC7QRqoKIFNIhmqBehMaaBfEhtwOaz/7ebfPAn19mAtFiAt/A+Yf+PTwnAjdxvQlsOMbSAtDCAtEglseG0xuPF2mzVP2vFEoBZjyx6QlhsP20AMPA7L3Xybx6baXn5G4sMbP/7U2bP3Jx++8aOiDrfDsADGBlCwjIJRMApGwSigAAAA5ltEZW6DCZUAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Indian Institute of Information Technology Allahabad (IIIT-A)\",\"correspondingAuthor\":true,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sintu\",\"middleName\":\"Kumar\",\"lastName\":\"Samanta\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-02-29 17:08:05\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4000627/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4000627/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s10989-024-10610-0\",\"type\":\"published\",\"date\":\"2024-05-07T03:59:10+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":52035964,\"identity\":\"45b8c803-e70c-4616-9a19-ebaa2943e17d\",\"added_by\":\"auto\",\"created_at\":\"2024-03-05 17:05:11\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":164557,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSome screenshots of ADPDB UI.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4000627/v1/8c5ac21315c4249008acdaa4.jpeg\"},{\"id\":52035965,\"identity\":\"f252e125-1f5d-4fe2-bd68-ce56a76f5c73\",\"added_by\":\"auto\",\"created_at\":\"2024-03-05 17:05:11\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":127149,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSome screenshots of ADPDB data statistics.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4000627/v1/8f97a7d0e2b1a0c9632e6395.png\"},{\"id\":52036815,\"identity\":\"9c73e2e7-778c-43c4-9368-0b142289270e\",\"added_by\":\"auto\",\"created_at\":\"2024-03-05 17:13:11\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":113135,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDiagrammatic representation of end-to-end development process of ADPDB.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4000627/v1/46ddc4dba5369b0832e51594.jpeg\"},{\"id\":56140483,\"identity\":\"0d95fb00-5d15-4f12-a608-e74d263b5916\",\"added_by\":\"auto\",\"created_at\":\"2024-05-09 04:28:37\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":765391,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4000627/v1/dc0c0569-1a87-4bbf-ae51-6a43552defd1.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"ADPDB: A Comprehensive Knowledgebase of Manually Curated Peptides Against Dengue Virus\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eDengue is an important mosquito-borne disease caused by the dengue viruses (DENVs), which is estimated to cause around 25,000 deaths per year (Reginald et al., \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e). \\u003cem\\u003eAedes albopictus\\u003c/em\\u003e and \\u003cem\\u003eAedes aegypti\\u003c/em\\u003e are the commonly known vectors of transmission for DENV (Guardia and Lleonart, \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e). At present, dengue is an endemic disease in more than 100 countries, especially in the sub-tropical and tropical regions (Chew et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). DENV-1-4 are the four serotypes of dengue virus, that are found to be antigenically as well as genetically distinct from each other. Surprisingly, even though they are distinct, they all cause similar sicknesses. People infected with any of these types may experience a range of symptoms, from asymptomatic fever to things like joint pain, rash, and other mild issues.It may also result in life-threatening symptoms like dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS) in severe cases (Shukla et al., \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The most important thing to note regarding these serotypes is that the infection with one induces lifelong immunity against only itself and not the other three serotypes. This is why the disease becomes of utmost concern. A common strategy that has been undertaken to stop DENV infection is primarily by vector control (\\u003cb\\u003eKala et al., 2023\\u003c/b\\u003e). The use of fog and the spreading of genetically modified (GM) mosquitoes are among the commonly known strategies that have failed to prevent the mosquito population from increasing. While active research on the development of vaccines has been ongoing for the past few decades, it has been held back by numerous challenges. The major problems faced during dengue vaccine development include the lack of appropriate animal models and the difference in antigenicity of each serotype which creates a hurdle in developing a single candidate against all four serotypes (\\u003cb\\u003eKala et al., 2023\\u003c/b\\u003e). The first dengue vaccine, CYD-TDV (chimeric yellow fever virus-tetravalent dengue vaccine) was a live-attenuated tetravalent vaccine comprising envelope proteins of DENV (Chew et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). However, its overall efficacy against DENV is low, especially that against DENV-2 remaining at only 39%. The CYD-TDV vaccine has also been shown to cause risks of hospitalization in children who are less than nine years of age. Thus, the World Health Organization (WHO) recommends the usage of this vaccine only in countries with an extremely high burden of dengue.\\u003c/p\\u003e \\u003cp\\u003eAlso, there are no antiviral drugs against DENV available at present (Chew et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). The only therapy is supportive treatment with fluid restoration and close clinical monitoring. Although nucleoside analogs, like balapiravir, had entered preclinical and clinical trials, were terminated due to the lack of potency. Similarly, other anti-DENV drugs, such as chloroquine, celgosivir, and lovastatin, have undergone clinical trials but have failed to meet the expectations. Unlike small molecules, peptides are marked by high selectivity and specificity, along with less off-target toxicity, which makes them insightful candidates for further testing. Due to their excellent pharmacological properties, several peptides are being tested against DENV. Also, the success of the antiviral peptide, Enfuvirtide, which has been recently approved by the Food and Drug Administration (FDA) has further led to gaining more insight on the use of antiviral peptides as an alternative to small molecule-based therapy or other treatment strategies (Lee et al., \\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eIt is crucial to note that any research depends on the existence of certain resources, without which it either slows down or ends up lacking clarity. For the same reason, several specialized databases have been made in the past that contain different AMPs against various target organisms specifically. Some of the most recent examples are ANTISTAPHYBASE (Zouhir et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), ANTIPSEUDOBASE (Zouhir et al., \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), ACovPepDB (Zhang et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), and HIPdb (Qureshi et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e) which contain peptide-based drugs against \\u003cem\\u003eStaphylococcus\\u003c/em\\u003e species, \\u003cem\\u003ePseudomonas species\\u003c/em\\u003e, Coronavirus, and HIV respectively. To date, there is no single database specifically developed for anti-dengue virus peptides. The entire scenario of the spread of dengue worldwide and the limited treatment options, we were provoked to create a database specialized for anti-dengue peptides, named as Anti-Dengue Peptide Database (ADPDB). All the known antimicrobial peptides (AMPs) against DENV and related information has been curated in this crucial database. Hopefully, this database will aid in the further research of anti-dengue peptides.\\u003c/p\\u003e\"},{\"header\":\"Material \\u0026 Method\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003e4.1. Data curation \\u0026amp; compilation\\u003c/h2\\u003e\\n\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section3\\\"\\u003e\\n\\u003ch2\\u003e4.1.1. Curation of anti-dengue peptides\\u003c/h2\\u003e\\n\\u003cp\\u003ePubMed literature database (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://pubmed.ncbi.nlm.nih.gov/\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e was used as a source database for curating the data. In PubMed, we used the following queries to curate the PubMed IDs of those articles which contain the information about anti-dengue peptides.\\u003c/p\\u003e\\n\\u003cul\\u003e\\n\\u003cli\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eQuery 1: ((((dengue virus) OR breakbone fever)) AND ((peptide) OR peptides)) AND ((inhibit*) OR block*)\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003c/li\\u003e\\n\\u003cli\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eQuery 2: ((((dengue virus) OR dengue)) AND ((peptide) OR peptides)) AND ((inhibit*) OR block*)\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eThe search of both the above queries was done on the 14th of October, 2023. Both queries returned 819 PubMed IDs each (total:1638). Further, all PubMed IDs were listed and the duplicate IDs were removed using Microsoft Excel. After getting rid of redundancy, we got 820 unique PubMed IDs. After this, each article of respective PMID was thoroughly studied one by one and data was curated for the following fields: \\u0026lsquo;anti-dengue peptide name\\u0026rsquo;, \\u0026lsquo;sequence\\u0026rsquo;, \\u0026lsquo;source\\u0026rsquo;, \\u0026lsquo;taxonomy\\u0026rsquo;, \\u0026lsquo;target organism with strain\\u0026rsquo;, \\u0026lsquo;inhibition concentration\\u0026rsquo;, \\u0026lsquo;target component\\u0026rsquo;, \\u0026lsquo;target process\\u0026rsquo;, \\u0026lsquo;mode of action (MoA)\\u0026rsquo;, \\u0026lsquo;toxicity\\u0026rsquo;, \\u0026lsquo;hemolytic activity\\u0026rsquo;, and \\u0026lsquo;validation\\u0026rsquo;. It is important to note that in some peptide sequences, we did not find a linear sequence. These sequences were put as it is in the dataset. Moreover, in some cases \\u0026lsquo;anti-dengue peptide name\\u0026rsquo; was missing and only the \\u0026lsquo;sequence\\u0026rsquo; was available in the article and vice-versa. The missing values fields were filled up with a \\u0026lsquo;not available\\u0026rsquo; string. After curating the data, we got our master anti-dengue peptide dataset with 606 peptides.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section3\\\"\\u003e\\n\\u003ch2\\u003e4.1.2. Compositional details and physicochemical properties computation\\u003c/h2\\u003e\\n\\u003cp\\u003eWe utilized our custom Python package named proteinAnalysis2 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/rajat-kumar-mondal/proteinAnalysis2\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e to calculate the compositional details and physicochemical properties of peptides. This package is developed in pure Python language (version 3.12.1) (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.python.org/\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e, and an upgraded version of the original proteinAnalysis package (version 1) (Mondal et al., \\u003cspan class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). It incorporates functionalities from the proteinAnalysis class of the proteinAnalysis package (version 1) (Mondal et al., \\u003cspan class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), the ProteinAnalysis class of the ProtParam module of the Bio package (version 1.82) (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://biopython.org/\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e, and the Peptide class of the peptides package (version 0.3.1) (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://pypi.org/project/peptides/\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e).\\u003c/span\\u003e The proteinAnalysis2 package (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/rajat-kumar-mondal/proteinAnalysis2\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e is enormously capable of computing various basic details and properties of a peptide which are shown in Table\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e.\\u003c/p\\u003e\\n\\u003cdiv class=\\\"gridtable\\\"\\u003e\\n\\u003cdiv class=\\\"colspec\\\" align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/div\\u003e\\n\\u003cdiv class=\\\"colspec\\\" align=\\\"left\\\"\\u003e\\u0026nbsp;\\u003c/div\\u003e\\n\\u003ctable id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption\\u003e\\n\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\n\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\n\\u003cp\\u003eTable of compositional details and physicochemical properties that can be calculated by proteinAnalysis2 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/rajat-kumar-mondal/proteinAnalysis2\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e).\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/caption\\u003e\\n\\u003cthead\\u003e\\n\\u003ctr\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eCompositional details\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003cth align=\\\"left\\\"\\u003e\\n\\u003cp\\u003ePhysicochemical properties\\u003c/p\\u003e\\n\\u003c/th\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/thead\\u003e\\n\\u003ctbody\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLength\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMolecular weight\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMolecular formula\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAliphatic index\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAmino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eInstability index\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAmino acid frequencies\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eGRAVY\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMissing amino acid\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHydrophilicity\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMost occurring amino acid\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHydrophobic moment\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eLess occurring amino acid\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eNet charge\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHydrophobic amino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eIsoelectric point\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eHydrophilic amino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eStructural class\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eBasic amino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMass shift\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAcidic amino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eAromaticity\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eModified amino acid counts\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eSecondary structure fraction\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003ctr\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eModified amino acid frequencies\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003ctd align=\\\"left\\\"\\u003e\\n\\u003cp\\u003eMolar extinction coefficient (cysteine|cysteine)\\u003c/p\\u003e\\n\\u003c/td\\u003e\\n\\u003c/tr\\u003e\\n\\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003c/div\\u003e\\n\\u003cp\\u003eBy invoking the \\u0026lsquo;all_comp_physP\\u0026rsquo; function from proteinAnalysis2 class of the proteinAnalysis2 package (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/rajat-kumar-mondal/proteinAnalysis2\\u003c/span\\u003e\\u003c/span\\u003e\\u003cspan class=\\\"Underline\\\"\\u003e)\\u003c/span\\u003e, users can effortlessly obtain a dictionary containing all the compositional details and physicochemical properties of a given peptide sequence. This function was specifically employed to compute these details for anti-dengue peptides. As we mentioned earlier in some cases of peptide sequence, we did not find the straightforward sequence and in some cases peptide sequence was unavailable, in those cases, we put the following information as a string.\\u003c/p\\u003e\\n\\u003cul\\u003e\\n\\u003cli\\u003e\\n\\u003cp\\u003eIf the peptide sequence is unavailable, we put \\u0026ldquo;The peptide sequence is unavailable. Unable to calculate compositional details and physicochemical properties\\u0026rdquo;.\\u003c/p\\u003e\\n\\u003c/li\\u003e\\n\\u003cli\\u003e\\n\\u003cp\\u003eIf the peptide sequence contains some special characteristics (e.g., benzoyl compound), we put \\u0026ldquo;Some special compound(s) is/are present with the peptide sequence. Unable to calculate compositional details and physicochemical properties\\u0026rdquo;.\\u003c/p\\u003e\\n\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eIn this way, the computation of compositional details and physicochemical properties was done for 606 anti-dengue peptides that are present in our dataset.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003e4.2. Development of backend and frontend\\u003c/h2\\u003e\\n\\u003cp\\u003eThe core of ADPDB backend was constructed using an HTTPS server in PhpMyAdmin (version 5.1.1), housing a Relational Database Management System (RDBMS) i.e., MySQL server (version 5.7.36). The frontend development employs HTML5, Bootstrap5, CSS3, JS, jQuery, Chart.js, DataTables, and AJAX.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\n\\u003ch2\\u003e4.3. User interface of the database\\u003c/h2\\u003e\\n\\u003cp\\u003eThe user interface (UI) of the database is very simple, straightforward, responsive, and interactive. Figure\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e shows some of the glimpses of the database UI.\\u003c/p\\u003e\\n\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section3\\\"\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.1. Homepage\\u003c/strong\\u003e: The homepage of ADPDB displays a brief introduction about the database.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.2. Search\\u003c/strong\\u003e: On this page, a user will be able to find the simple text search and advanced search options. A user can search for any relevant information regarding anti-dengue peptides in the simple text search facility. In the case of the advanced search facility, a user can search in a specific field like \\u0026lsquo;peptide name\\u0026rsquo;, \\u0026lsquo;length\\u0026rsquo;, \\u0026lsquo;source\\u0026rsquo;, and more. A help button is given with both types of search facilities for user assistance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.3. Result retrieving\\u003c/strong\\u003e: All the search results will appear in a table format. The table is searchable and sortable itself. Pagination is also provided in the table for ease of use. Moreover, users can download specific entry/entries by selecting them or current page entries or all entries in a suitable format (including FASTA, TSV, CSV, LIST, JSON, TEXT, and Custom TSV) by clicking on the appropriate option from the download button. Users can view a single entry by clicking on the individual ID (e.g., ADPDB2) and export in FASTA, TEXT, and PDF format further.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.4. Browse\\u003c/strong\\u003e: On this page, the entire data of ADPDB is displayed. Users can study all the entries of ADPDB using this page.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.5. Statistics\\u003c/strong\\u003e: On this page, the data statistics are categorized by \\u0026lsquo;peptide source\\u0026rsquo;, \\u0026lsquo;length\\u0026rsquo;, \\u0026lsquo;molecular weight\\u0026rsquo;, and \\u0026lsquo;net charge\\u0026rsquo; \\u0026amp; displayed as an interactive bar chart. The Y axis of all bar charts is initially set to a scale of 10, as there is a considerable range between the lowest and highest number of records. This deliberate design choice aims to enhance visualizations. To adjust the scale, users can click on either the \\\"Rescale X Axis\\\" or \\\"Rescale Y Axis\\\" buttons to modify the plot accordingly. Click on \\\"Rescale to Initial\\\" to bring the plot to its initial point. Figure\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e shows the data statistics of ADPDB.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.6. Downloads\\u003c/strong\\u003e: From this page, a user can download the master dataset of ADPDB in XLSX, CSV, TSV, LIST, TEXT, and FASTA format.\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec9\\\" class=\\\"Section3\\\"\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003e4.3.7. News/updates\\u003c/strong\\u003e: All the latest news/updates regarding ADPDB will be displayed on this page.\\u003c/h2\\u003e\\n\\u003c/div\\u003e\\n\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section3\\\"\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003e4.3.8. Developers\\u003c/strong\\u003e: Users can find all the developer's information on this page.\\u003c/h2\\u003e\\n\\u003cstrong\\u003e4.3.9. Help\\u003c/strong\\u003e: On this page, all the details of the search facilities and a full description of the TEXT format of ADPDB are shown.\\u003cbr /\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e4.3.10. Contact\\u003c/strong\\u003e: The contact details of the principal investigator and core technical developers are displayed here. Users can reach out to them from this page. A web form is also provided on the same page which can be used by the user to raise any query/doubt.\\u003c/p\\u003e\\n\\u003cp\\u003eIn Fig.\\u0026nbsp;\\u003cspan class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003ea diagrammatic representation of the end-to-end development of ADPDB is shown.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003c/div\\u003e\\n\\u003c/div\\u003e\"},{\"header\":\"Results and discussion\",\"content\":\"\\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.1 Insights from ADPDB\\u003c/h2\\u003e \\u003cp\\u003eADPDB is the first comprehensive knowledge base of anti-dengue peptides found widely. This database can be specifically used to target dengue viruses (including DENV-1, DENV-2, DENV-3, DENV-4). The database supports simple text searches to intuitive advanced search facility. Moreover, the database also allows user to manipulate the data as per their need and export it in multiple formats like TSV, TEXT, LIST, FSATA, JSON, etc. in local machines for further analysis or development. Users also can obtain fully customized reports as per their requirements from the database's custom report facility. While viewing an individual entry the database displays the result in the following 6 parts.\\u003c/p\\u003e \\u003cp\\u003e \\u003col\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eGeneral description which includes ADPDB ID, peptide name, source, taxonomy, and validation.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003ePeptide sequence \\u0026amp; composition which includes length, molecular formula, amino acid (AA) counts, AA frequencies, missing AA, AA which occurs most \\u0026amp; less, hydrophobic \\u0026amp; hydrophilic AA counts, acidic \\u0026amp; basic AA counts, counts and frequencies of modified AA.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003ePhysicochemical properties which include molecular weight, aromaticity, aliphatic index, instability index, hydrophobic moment, GRAVY, net charge, secondary structure fraction (SSF), molar extinction coefficient, mass shift, etc.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eStructural Class of the Peptide.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eActivity Information includes target organism, family, inhibition concentration information, target component information, target process information, mode of action, toxicity, and hemolytic activity.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003cspan\\u003e \\u003cli\\u003e \\u003cp\\u003eDatabase cross-references which include the PubMed ID.\\u003c/p\\u003e \\u003c/li\\u003e \\u003c/span\\u003e \\u003c/ol\\u003e \\u003c/p\\u003e \\u003cp\\u003eAt present, this database contains a total of 606 peptide entries. These peptides originate from different sources: Algae (1), Animalia (34), Bacteria (10), Fungi (4), Plantae (16), Synthetic (428), Virus (34). There are 79 peptides for which the source is not available. Out of 606 entries, 32 peptide sequences are unavailable in the database due to their unavailability in the source literature, and 352 sequences are special types of sequences meaning they contain special types of compounds as a part of them. 222 sequences are pure peptide sequences (do not contain any special compound with them) that are present in the database. The length of the peptides varies between 1 to 80 AA, molecular weight lies between 1 to 10000 Da, and net charge lies between \\u0026minus;\\u0026thinsp;5 to 20. Scientists, researchers, and pharmaceutical industries can use this database for novel drugs \\u0026amp; therapeutics development for dengue.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e5.2 Comparison with other existing databases\\u003c/h2\\u003e \\u003cp\\u003eTill now, many databases have been dedicated to AMPs in a generalized and specialized manner, since antimicrobial resistance (AMR) is a major issue. Some of the well-known generalized databases include CAMP R4 (Gawde et al., \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), DRAMP 3.0 (Shi et al., \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), dbAMP 2.0 (Jhong et al., \\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), AMPDB v1 (Mondal et al., \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), APD3 (Wang et al., \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e), etc. There are also renowned specialized databases of AMPs like Peptaibols Database (Whitmore and Wallace \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e), Defensins KnowledgeBase (Seebah et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e), LAMP (Zhao et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), InverPep (G\\u0026oacute;mez et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), MilkAMP (Th\\u0026eacute;olier et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e), PhytAMP (Hammami et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e), RAPD (\\u003cb\\u003eLi et al., 2008\\u003c/b\\u003e), SAPdb (Mathur et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e), ANTISTAPHYBASE (Zouhir et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), ANTIPSEUDOBASE (Zouhir et al., \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), DRAVP (Liu et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e), AVPdb (Qureshi et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e), HIPdb (Qureshi et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e), ACovPepDB (Zhang et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e), etc.\\u003c/p\\u003e \\u003cp\\u003eThe generalized AMP databases contain overall every type of AMP whereas the specialized AMP databases contain the data of some specific types. Peptaibols Database (Whitmore and Wallace \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e) and Defensins knowledgebases (Seebah et al., \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e) contain the data of peptaibols and defensins whereas LAMP (Zhao et al., \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e) deals with linking AMPs. InverPep (G\\u0026oacute;mez et al., \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e), MilkAMP (Th\\u0026eacute;olier et al., \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e), and PhytAMP (Hammami et al., \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e) contain data of invertebrate AMPs, AMPs from milk sources, and plant AMPs. RAPD (\\u003cb\\u003eLi et al., 2008\\u003c/b\\u003e) and SAPdb (Mathur et al., \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e) deal with the data of recombinant and synthetic AMPs respectively. DRAVP (Liu et al., \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e) and AVPdb (Qureshi et al., \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e) have information about the antiviral peptides. ANTISTAPHYBASE (Zouhir et al., \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e) and ANTIPSEUDOBASE (Zouhir et al., \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e) are two specific target bacteria databases that contain data about AMPs and EOs that can be used to target Staphylococcus and Pseudomonas species, whereas HIPdb (Qureshi et al., \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2013\\u003c/span\\u003e) and ACovPepDB (Zhang et al., \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e) are only two target virus databases that holds that information about anti-HIV and anti-Corona virus peptides specifically.\\u003c/p\\u003e \\u003cp\\u003eAll the databases (generalized and specialized) that are dedicated to AMPs, to date, hold very useful information for antimicrobial drugs and therapeutics developments. However, there is no single database which is dedicated to anti-dengue peptides. Moreover, dengue is very prevalent in tropical \\u0026amp; sub-tropical countries and the mortality rate for dengue is quite high (Chew et al., \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). The drugs that are available in the market for dengue are less effective and often produce side effects (Obi et al., \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). In this scenario, anti-viral peptides (a type of AMP) can be a better therapeutic alternative. Keeping all this in mind, we developed the ADPDB, the first dedicated database for anti-dengue peptides, to develop a better, safer, and economical treatment strategy for dengue virus. At this moment the drawback of this ADPDB is that this database does not contain any kind of tools like BLAST or MUSCLE or any other related tools. However, it will be improved in its future versions,.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Conclusion \\u0026 Future perspectives\",\"content\":\"\\u003cp\\u003eDespite an approved dengue vaccine, it doesn't cover all DENV types, posing a challenge in affected regions. Urgently needed are effective drugs for all DENV strains. Promisingly, anti-dengue peptides offer a solution, serving as both drugs and vaccine candidates. While biocompatible and cost-effective, efforts to enhance their effectiveness, using long peptides and nanoparticle delivery, are underway. Recognizing the need, we've developed ADPDB, a dedicated anti-DENV peptide database, to aid future discoveries.\\u003c/p\\u003e \\u003cp\\u003eAs per our knowledge, ADPDB is the first such database to be specialized for anti-DENV peptides. This resource aims to facilitate access to crucial information on peptides against DENV. Currently, the database contains 606 sequences of DENV-active peptides, both natural and synthetic combined. ADPDB allows an easy and fast browsing of peptides and related information on their properties and activity. Using information on these peptide-based drug candidates, the researchers can design new drugs using studies like structure-activity relationships or generate new leads by incorporating the data into ML models. Hopefully, ADPDB will help enhance the understanding of anti-DENV peptides to a better extent and will aid in the development of new molecules for medical use.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003e7. Data availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe master dataset of ADPDB is openly accessible in XLSX, CSV, TSV, LIST, FASTA, and TEXT formats at the URL: https://bblserver.org.in/adpdb/adpdb-download.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e8. Acknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e9. Rajat Kumar Mondal and Ananya Anurag Anand are thankful to MoE-GoI for their fellowship. We are extremely thankful to IIIT-A for providing the infrastructural facility i.e. Central Computing Facility.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e10. Author contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eR.K.M.: Conceptualization, Resources, Investigation and Data Analysis, Validation, Writing; A.A.A.: Resources, Data mining and curation, Data Analysis and Writing; S.K.S.: Conceptualization, Formal Analysis, Supervision, Writing-review \\u0026amp; editing.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e11. Conflict of interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare no conflict of interest.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e12. Funding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThere was no funding for this project.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eChew MF, Poh KS, Poh CL (2017) Peptides as therapeutic agents for dengue virus. \\u003cem\\u003eInternational journal of medical sciences\\u003c/em\\u003e, \\u003cem\\u003e14\\u003c/em\\u003e(13), p.1342\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDe La Guardia C, Lleonart R (2014) Progress in the identification of dengue virus entry/fusion inhibitors. \\u003cem\\u003eBioMed research international\\u003c/em\\u003e, \\u003cem\\u003e2014\\u003c/em\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGawde U, Chakraborty S, Waghu FH, Barai RS, Khanderkar A, Indraguru R, Shirsat T, Idicula-Thomas S (2023) CAMPR4: a database of natural and synthetic antimicrobial peptides. Nucleic Acids Res 51(D1):D377\\u0026ndash;D383\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eG\\u0026oacute;mez EA, Giraldo P, Orduz S (2017) InverPep: a database of invertebrate antimicrobial peptides. J global Antimicrob Resist 8:13\\u0026ndash;17\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHammami R, Ben Hamida J, Vergoten G, Fliss I (2009) PhytAMP: a database dedicated to antimicrobial plant peptides. Nucleic Acids Res 37(suppl1):D963\\u0026ndash;D968\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJhong JH, Yao L, Pang Y, Li Z, Chung CR, Wang R, Li S, Li W, Luo M, Ma R, Huang Y (2022) dbAMP 2.0: updated resource for antimicrobial peptides with an enhanced scanning method for genomic and proteomic data. Nucleic Acids Res 50(D1):D460\\u0026ndash;D470\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLee MF, Anasir MI, Poh CL (2023) Development of novel antiviral peptides against dengue serotypes 1\\u0026ndash;4. \\u003cem\\u003eVirology\\u003c/em\\u003e, \\u003cem\\u003e580\\u003c/em\\u003e, pp.10\\u0026ndash;27\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Chen Z (2008) RAPD: a database of recombinantly-produced antimicrobial peptides. FEMS Microbiol Lett 289(2):126\\u0026ndash;129\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLiu Y, Zhu Y, Sun X, Ma T, Lao X, Zheng H (2023) DRAVP: A Comprehensive Database of Antiviral Peptides and Proteins. \\u003cem\\u003eViruses\\u003c/em\\u003e, \\u003cem\\u003e15\\u003c/em\\u003e(4), p.820\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMathur D, Kaur H, Dhall A, Sharma N, Raghava GP (2021) SAPdb: A database of short peptides and the corresponding nanostructures formed by self-assembly. \\u003cem\\u003eComputers in Biology and Medicine\\u003c/em\\u003e, \\u003cem\\u003e133\\u003c/em\\u003e, p.104391\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMondal RK, Sen D, Arya A, Samanta SK (2023) Developing anti-microbial peptide database version 1 to provide comprehensive and exhaustive resource of manually curated AMPs. \\u003cem\\u003eScientific Reports\\u003c/em\\u003e, \\u003cem\\u003e13\\u003c/em\\u003e(1), p.17843\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eObi JO, Guti\\u0026eacute;rrez-Barbosa H, Chua JV, Deredge DJ (2021) Current trends and limitations in dengue antiviral research. \\u003cem\\u003eTropical Medicine and Infectious Disease\\u003c/em\\u003e, \\u003cem\\u003e6\\u003c/em\\u003e(4), p.180\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePalanichamy Kala M, John S, A.L. and, Rathore AP (2023) Dengue: Update on Clinically Relevant Therapeutic Strategies and Vaccines. \\u003cem\\u003eCurrent Treatment Options in Infectious Diseases\\u003c/em\\u003e, pp.1\\u0026ndash;26\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQureshi A, Thakur N, Kumar M (2013) HIPdb: a database of experimentally validated HIV inhibiting peptides. PLoS ONE 8(1):e54908\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eQureshi A, Thakur N, Tandon H, Kumar M (2014) AVPdb: a database of experimentally validated antiviral peptides targeting medically important viruses. Nucleic Acids Res 42(D1):D1147\\u0026ndash;D1153\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eReginald K, Chan Y, Plebanski M, Poh CL (2018) Development of peptide vaccines in dengue. Curr Pharm Design 24(11):1157\\u0026ndash;1173\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSeebah S, Suresh A, Zhuo S, Choong YH, Chua H, Chuon D, Beuerman R, Verma C (2007) Defensins knowledgebase: a manually curated database and information source focused on the defensins family of antimicrobial peptides. 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Arch Microbiol 199:215\\u0026ndash;222\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"international-journal-of-peptide-research-and-therapeutics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ijpr\",\"sideBox\":\"Learn more about [International Journal of Peptide Research and Therapeutics](http://link.springer.com/journal/10989)\",\"snPcode\":\"10989\",\"submissionUrl\":\"https://submission.nature.com/new-submission/10989/3\",\"title\":\"International Journal of Peptide Research and Therapeutics\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"Anti-dengue peptides, Anti-Dengue Peptide Database (ADPDB), Anti-microbial peptides (AMPs), Biological Data Curation \\u0026 Analysis, Biological Database Development.\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4000627/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4000627/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eRecently, there have been estimates of 390\\u0026nbsp;million dengue infections annually worldwide. Thus, Dengue viruses (DENV) continue to result in a severe burden on the human health all over the world. There are four different serotypes of DENV depending on antigenicity. Each can result in a life-threatening condition. For such a severe disease, present-day options of treatment are certainly limited and most patients rely on supportive care. Although there has been a dengue vaccine approved with modest efficacy, there is an urgent need for drugs that can reduce the complications that occur as a result of dengue. Some recent advances have been made in the development of drugs for combating dengue. These include some new vaccine candidates, invention of peptide-based drugs (antimicrobial peptides or AMPs), and repurposing of a few existing ones. Out of these, peptide-based drugs are recently under the limelight for their enhanced efficacy against the DENV and are being tested for their efficacy in preventing dengue in different parts of the world. In this context, we have developed a database that highlights the efforts made in the direction of peptide-based drugs against DENV. The database mentions the important features of all the anti-DENV peptides recorded up to date. These include source, target, mode of action, sequence, length, IC50, toxicity, etc. Our database also presents a holistic view of the overall situation of the peptide-based discovery for dengue. The database is accessible via any web browser at https://bblserver.org.in/adpdb/.\\u003c/p\\u003e\",\"manuscriptTitle\":\"ADPDB: A Comprehensive Knowledgebase of Manually Curated Peptides Against Dengue Virus\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-03-05 17:05:06\",\"doi\":\"10.21203/rs.3.rs-4000627/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-03-19T14:11:08+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-03-08T20:12:22+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"c4b170b1-d63a-4213-95f7-fe8b01de72e6\",\"date\":\"2024-03-07T16:52:50+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-03-07T16:50:51+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-03-01T19:37:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-03-01T19:37:56+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"International Journal of Peptide Research and Therapeutics\",\"date\":\"2024-02-29T16:48:36+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"international-journal-of-peptide-research-and-therapeutics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"ijpr\",\"sideBox\":\"Learn more about [International Journal of Peptide Research and Therapeutics](http://link.springer.com/journal/10989)\",\"snPcode\":\"10989\",\"submissionUrl\":\"https://submission.nature.com/new-submission/10989/3\",\"title\":\"International Journal of Peptide Research and Therapeutics\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"f5c18dce-de52-4d44-a89b-4a3a0f5d7b61\",\"owner\":[],\"postedDate\":\"March 5th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-05-09T03:59:10+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-4000627\",\"link\":\"https://doi.org/10.1007/s10989-024-10610-0\",\"journal\":{\"identity\":\"international-journal-of-peptide-research-and-therapeutics\",\"isVorOnly\":false,\"title\":\"International Journal of Peptide Research and Therapeutics\"},\"publishedOn\":\"2024-05-07 03:59:10\",\"publishedOnDateReadable\":\"May 7th, 2024\"},\"versionCreatedAt\":\"2024-03-05 17:05:06\",\"video\":\"\",\"vorDoi\":\"10.1007/s10989-024-10610-0\",\"vorDoiUrl\":\"https://doi.org/10.1007/s10989-024-10610-0\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4000627\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4000627\",\"identity\":\"rs-4000627\",\"version\":[\"v1\"]},\"buildId\":\"cBFmMYwuxLRRLfASyISRj\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}