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SerotoninAI: Serotonergic System Focused, Artificial Intelligence-Based Application for Drug Discovery

Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

2024Journal of Chemical Information and Modeling14 citationsDOIOpen Access PDF

Abstract

SerotoninAI is an innovative web application for scientific purposes focused on the serotonergic system. By leveraging SerotoninAI, researchers can assess the affinity (pKi value) of a molecule to all main serotonin receptors and serotonin transporters based on molecule structure introduced as SMILES. Additionally, the application provides essential insights into critical attributes of potential drugs such as blood-brain barrier penetration and human intestinal absorption. The complexity of the serotonergic system demands advanced tools for accurate predictions, which is a fundamental requirement in drug development. SerotoninAI addresses this need by providing an intuitive user interface that generates predictions of pKi values for the main serotonergic targets. The application is freely available on the Internet at https://serotoninai.streamlit.app/, implemented in Streamlit with all major web browsers supported. Currently, to the best of our knowledge, there is no tool that allows users to access affinity predictions for serotonergic targets without registration or financial obligations. SerotoninAI significantly increases the scope of drug development activities worldwide. The source code of the application is available at https://github.com/nczub/SerotoninAI_streamlit.

Topics & Concepts

SerotonergicDrug discoveryComputer scienceDrugData scienceArtificial intelligenceMedicinePharmacologyBioinformaticsBiologySerotoninInternal medicineReceptorComputational Drug Discovery Methods
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