In Silico Database of In Vitro Tested Antiviral Compounds

Antivirals are drugs used to treat viral diseases by inhibiting the infection or replication of viruses. With the wide variety of viruses, it is crucial to constantly find new antiviral options. One approach is to reposition existing drugs, which is a more cost-effective and faster method than traditional research and development. The problem is that there is a lack of organized and standardized data on these drugs. This work aims to address this issue by creating a database of in vitro-tested antivirals. The information and compounds were collected from published in vitro antiviral studies. The database includes six different file formats (SMILES, MOL, SDF 2D, MOL2, PDB, and PDBQT) and categorizes the compounds based on their antiviral activity.

抗病毒药物系一类用于治疗病毒性疾病，通过抑制病毒感染或复制的药物。鉴于病毒种类的繁多，持续寻找新的抗病毒药物选项显得尤为关键。一种方法是对现有药物进行重新定位，相较于传统的研究与开发，此法更为经济高效且速度更快。然而，关于这些药物的有序化和标准化数据尚显匮乏。本项工作旨在解决此问题，通过构建一个体外测试的抗病毒药物数据库。信息与化合物均来源于已发表的体外抗病毒研究。该数据库包含六种不同的文件格式（SMILES、MOL、SDF 2D、MOL2、PDB 及 PDBQT），并基于其抗病毒活性对化合物进行分类。

搜集汇总

背景与挑战

背景概述

该数据集是一个计算机模拟抗病毒化合物数据库，旨在解决抗病毒药物数据缺乏组织化和标准化的问题，通过收集已发表的体外抗病毒研究中的化合物信息构建而成。数据库包含325种化合物，以六种不同文件格式（SMILES、MOL、SDF 2D、MOL2、PDB、PDBQT）提供，覆盖一维到三维分子结构，并根据抗病毒活性进行分类，便于药物发现和计算化学研究。