Fernando Loza Guariero, Eduardo Pantoja de Macedo, Elise Bittencourt de Laia, Joseph Albert Medeiros Evaristo, Geisa Paulino Caprini Evaristo, Fernando Berton Zanchi
{"title":"PlasmoDocking:一个用户友好的开源网络工具,用于针对恶性疟原虫酶的虚拟筛选","authors":"Fernando Loza Guariero, Eduardo Pantoja de Macedo, Elise Bittencourt de Laia, Joseph Albert Medeiros Evaristo, Geisa Paulino Caprini Evaristo, Fernando Berton Zanchi","doi":"10.1002/jcc.70225","DOIUrl":null,"url":null,"abstract":"<p>Virtual screening through molecular docking represents a fundamental computational methodology extensively employed in the identification of therapeutic compounds for malaria and other parasitic diseases. Although numerous software platforms are available, including AutodockGPU, the command-line interface requirements present significant barriers to non-specialized users, while multi-target screening protocols introduce additional complexity in receptor preparation procedures. To address these limitations, we developed Plasmodocking, a comprehensive web-based platform designed to automate molecular docking simulations against predefined <i>Plasmodium falciparum</i> targets (https://plasmodocking-unir.ecotechamazonia.com.br/). The platform enables users to submit up to 10 molecular structures (.sdf format) for automated AutodockGPU screening against 38 pre-configured parasite targets, facilitating systematic comparison of binding energies with co-crystallized ligands. Developed using Python and Next.js, Plasmodocking accelerates malaria drug discovery by enabling simultaneous multi-target docking simulations within a single experimental framework. The open-source codebase is available at: https://github.com/LABIOQUIM/PlasmoDocking-Client.</p>","PeriodicalId":188,"journal":{"name":"Journal of Computational Chemistry","volume":"46 23","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70225","citationCount":"0","resultStr":"{\"title\":\"PlasmoDocking: A User-Friendly Open-Source Web Tool for Virtual Screening Targeting Plasmodium falciparum Enzymes\",\"authors\":\"Fernando Loza Guariero, Eduardo Pantoja de Macedo, Elise Bittencourt de Laia, Joseph Albert Medeiros Evaristo, Geisa Paulino Caprini Evaristo, Fernando Berton Zanchi\",\"doi\":\"10.1002/jcc.70225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Virtual screening through molecular docking represents a fundamental computational methodology extensively employed in the identification of therapeutic compounds for malaria and other parasitic diseases. Although numerous software platforms are available, including AutodockGPU, the command-line interface requirements present significant barriers to non-specialized users, while multi-target screening protocols introduce additional complexity in receptor preparation procedures. To address these limitations, we developed Plasmodocking, a comprehensive web-based platform designed to automate molecular docking simulations against predefined <i>Plasmodium falciparum</i> targets (https://plasmodocking-unir.ecotechamazonia.com.br/). The platform enables users to submit up to 10 molecular structures (.sdf format) for automated AutodockGPU screening against 38 pre-configured parasite targets, facilitating systematic comparison of binding energies with co-crystallized ligands. Developed using Python and Next.js, Plasmodocking accelerates malaria drug discovery by enabling simultaneous multi-target docking simulations within a single experimental framework. The open-source codebase is available at: https://github.com/LABIOQUIM/PlasmoDocking-Client.</p>\",\"PeriodicalId\":188,\"journal\":{\"name\":\"Journal of Computational Chemistry\",\"volume\":\"46 23\",\"pages\":\"\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2025-09-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcc.70225\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computational Chemistry\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jcc.70225\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Chemistry","FirstCategoryId":"92","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jcc.70225","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
PlasmoDocking: A User-Friendly Open-Source Web Tool for Virtual Screening Targeting Plasmodium falciparum Enzymes
Virtual screening through molecular docking represents a fundamental computational methodology extensively employed in the identification of therapeutic compounds for malaria and other parasitic diseases. Although numerous software platforms are available, including AutodockGPU, the command-line interface requirements present significant barriers to non-specialized users, while multi-target screening protocols introduce additional complexity in receptor preparation procedures. To address these limitations, we developed Plasmodocking, a comprehensive web-based platform designed to automate molecular docking simulations against predefined Plasmodium falciparum targets (https://plasmodocking-unir.ecotechamazonia.com.br/). The platform enables users to submit up to 10 molecular structures (.sdf format) for automated AutodockGPU screening against 38 pre-configured parasite targets, facilitating systematic comparison of binding energies with co-crystallized ligands. Developed using Python and Next.js, Plasmodocking accelerates malaria drug discovery by enabling simultaneous multi-target docking simulations within a single experimental framework. The open-source codebase is available at: https://github.com/LABIOQUIM/PlasmoDocking-Client.
期刊介绍:
This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.