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数据管:一个完全自动化的统一软件平台,用于计算机辅助药物设计

Mohemmed Faraz Khan^1,2, Shubhangi Kandwal¹, Darren Fayne¹

¹Molecular Design Group, School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin 2, Ireland.

|October 30, 2023

概括

通过将多个软件工具集成到统一的工作流中,DataPype简化了计算机辅助药物设计 (CADD). 这个平台自动化了数据处理和虚拟选,提高了识别潜在药物候选者的效率和信心.

科学领域:

计算化学是一种计算化学.
生物信息学是一种生物信息学.
药物发现药物发现

背景情况:

计算机辅助药物设计 (CADD) 通过使生物活性分子的预测,彻底改变了药物发现.
现有的CADD工具往往需要专业知识,并为多学科团队在数据集成和处理方面提出挑战.
越来越多的小分子数据需要简化数据采购和自动化处理用于CADD应用程序.

研究的目的:

开发一个新的软件平台DataPype,将多种CADD软件包集成到一个统一的工作流中.
为了自动化搜索命中化合物的过程,并提高非专业用户的CADD工具的可用性.
提高在药物发现早期阶段虚拟查的效率和可靠性.

主要方法:

开发了DataPype,这是一个软件平台,围绕现有的CADD软件包进行包装.
实施了一种统一的,自动化的工作流程,用于使用专业软件搜索命中化合物.
能够在单个工作流中集成多个虚拟选包.
设计了在计算机服务器上执行的平台,以加速虚拟选.

主要成果:

DataPype提供了一个统一的接口,可以访问多个CADD工具,简化复杂的工作流程.
该平台自动化数据处理和清理,使其与各种CADD软件兼容.
同时运行多个虚拟选包可以增加对预测打击组合的信心.
基于服务器的执行DataPype显著加快虚拟选过程.

结论:

通过提高CADD工具的可用性和效率,DataPype增强了早期药物发现.
综合平台通过简化对专业软件的访问来促进多学科合作.
DataPype提供的自动化工作流程和并行计算能力加快了新药候选药物的识别.

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