WeMol: A Cloud-Based and Zero-Code Platform for AI-Driven Molecular Design and Simulation

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Authors: Haihan Liu, Xiaoli Yan, Hao Fang, Hu Ge, Xuben Hou
Cited by: 6
References: 68

Abstract

Artificial intelligence (AI) has demonstrated remarkable potential in reshaping modern drug discovery, yet its widespread adoption is hindered by fragmented tools, high technical barriers, and the lack of user-friendly interfaces. Here, we present WeMol, an AI-driven one-stop molecular computing platform designed to streamline early-stage drug discovery. WeMol integrates a series of modules, covering molecular similarity search, structure-based and AI-enhanced docking, ADMET prediction, molecular generation, and molecular dynamics simulations. The platform features a zero-code, cloud-based interface that enables researchers without programming expertise to construct and execute comprehensive computational workflows. By integrating advanced AI algorithms with practical applications, WeMol lowers the entry barrier for nonexperts and provides a versatile, accessible, and reproducible solution to accelerate early drug design and discovery.

Fields of Study & Subjects

Machine Learning in Materials Science Computational Drug Discovery Methods Scientific Computing and Data Management

Publication details

Journal / source
Journal of Chemical Information and Modeling
Publisher
American Chemical Society (ACS)
Volume
66
Issue
4
Pages
2369–2381
Publication date
11 February 2026
Language
EN