组蛋白脱乙酰酶 6 (HDAC6) 是治疗癌症、神经退行性疾病（特别是阿尔茨海默病）和多发性硬化症等人类疾病的有前景的药物靶点。选择性无毒 HDAC6 抑制剂的开发受到了相当多的关注。为此，我们成功形成了一组 3854 种化合物，并提出了 HDAC6 抑制剂的充分回归 QSAR 模型。这些模型是使用 PubChem、Klekota-Roth、2D 原子对指纹、RDkit 描述符以及梯度增强、支持向量机、神经网络和 k 最近邻方法开发的。这些模型已集成到开发的 HT_PREDICT 应用程序中，该应用程序可在 https://htpredict.streamlit.app/ 上免费获取。体外研究已经证实了集成到 HT_PREDICT Web 应用程序中的所提出的 QSAR 模型的预测能力。此外，使用 HT_PREDICT Web 应用程序进行的虚拟筛选使我们能够提出两种有前途的抑制剂以供进一步研究。

Histone deacetylase 6 (HDAC6) is a promising drug target for the treatment of human diseases such as cancer, neurodegenerative diseases (in particular, Alzheimer's disease), and multiple sclerosis. Considerable attention is paid to the development of selective non-toxic HDAC6 inhibitors. To this end, we successfully form a set of 3854 compounds and proposed adequate regression QSAR models for HDAC6 inhibitors. The models have been developed using the PubChem, Klekota-Roth, 2D atom pair fingerprints, and RDkit descriptors and the gradient boosting, support vector machines, neural network, and k-nearest neighbours methods. The models are integrated into the developed HT_PREDICT application, which is freely available at https://htpredict.streamlit.app/. In vitro studies have confirmed the predictive ability of the proposed QSAR models integrated into the HT_PREDICT web application. In addition, the virtual screening performed with the HT_PREDICT web application allowed us to propose two promising inhibitors for further investigations.