<scp>PlasmoDocking</scp> : A User‐Friendly Open‐Source Web Tool for Virtual Screening Targeting <scp> <i>Plasmodium falciparum</i> </scp> 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.