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MolOptimizer:基于片段的药物设计的分子优化工具包。

MolOptimizer: A Molecular Optimization Toolkit for Fragment-Based Drug Design.

机构信息

Department of Chemistry, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

Data Science Research Centre, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel.

出版信息

Molecules. 2024 Jan 4;29(1):276. doi: 10.3390/molecules29010276.

Abstract

MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.

摘要

MolOptimizer 是一个用户友好的计算工具包,旨在简化药物发现中的从命中到先导物优化过程。MolOptimizer 使用用户提供的、标记的和小分子数据集提取特征并训练机器学习模型,以准确预测与焦点靶标具有相似骨架的新小分子的结合值。MolOptimizer 托管在 Azure 基于网络的服务器上,是一个重要的资源,可加速具有改善结合特性的新型候选药物的发现和开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b92d/10780997/a7ddf3c1025c/molecules-29-00276-g001.jpg

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