SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability,Journal of Chemical Information and Modeling

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SmartCADD: AI-QM Empowered Drug Discovery Platform with Explainability
Journal of Chemical Information and Modeling ( IF 5.6 ) Pub Date : 2024-08-23 , DOI: 10.1021/acs.jcim.4c00720
Ayesh Madushanka ₁ , Eli Laird ₂ , Corey Clark ₂ , Elfi Kraka ₁

Affiliation

Artificial intelligence (AI) has emerged as a pivotal force in enhancing productivity across various sectors, with its impact being profoundly felt within the pharmaceutical and biotechnology domains. Despite AI’s rapid adoption, its integration into scientific research faces resistance due to myriad challenges: the opaqueness of AI models, the intricate nature of their implementation, and the issue of data scarcity. In response to these impediments, we introduce SmartCADD, an innovative, open-source virtual screening platform that combines deep learning, computer-aided drug design (CADD), and quantum mechanics methodologies within a user-friendly Python framework. SmartCADD is engineered to streamline the construction of comprehensive virtual screening workflows that incorporate a variety of formerly independent techniques─spanning ADMET property predictions, de novo 2D and 3D pharmacophore modeling, molecular docking, to the integration of explainable AI mechanisms. This manuscript highlights the foundational principles, key functionalities, and the unique integrative approach of SmartCADD. Furthermore, we demonstrate its efficacy through a case study focused on the identification of promising lead compounds for HIV inhibition. By democratizing access to advanced AI and quantum mechanics tools, SmartCADD stands as a catalyst for progress in pharmaceutical research and development, heralding a new era of innovation and efficiency.

中文翻译：

SmartCADD：AI-QM 赋能的具有可解释性的药物发现平台

人工智能 (AI) 已成为提高各个行业生产力的关键力量，其影响在制药和生物技术领域得到了深刻的体现。尽管人工智能得到了迅速采用，但其与科学研究的融合仍面临着诸多挑战：人工智能模型的不透明性、其实施的复杂性以及数据稀缺问题。为了应对这些障碍，我们推出了 SmartCADD，这是一个创新的开源虚拟筛选平台，它将深度学习、计算机辅助药物设计 (CADD) 和量子力学方法结合在用户友好的 Python 框架中。 SmartCADD 旨在简化综合虚拟筛选工作流程的构建，该工作流程融合了各种以前独立的技术 — 涵盖 ADMET 特性预测、从头 2D 和 3D 药效团建模、分子对接，以及可解释的 AI 机制的集成。本手稿重点介绍了 SmartCADD 的基本原理、关键功能和独特的集成方法。此外，我们通过一个案例研究证明了其功效，该案例研究重点是鉴定有前途的抑制艾滋病毒的先导化合物。通过实现先进人工智能和量子力学工具的民主化，SmartCADD 成为药物研发进步的催化剂，预示着创新和效率的新时代。

更新日期：2024-08-28

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