Centro de Investigaciones Farmacognósticas de la Flora Panameña (CIFLORPAN), Facultad de Farmacia, Universidad de Panamá, Ciudad de Panamá, Apartado, 0824-00178, Panamá.
Sistema Nacional de Investigación (SNI), Secretaria Nacional de Ciencia, Tecnología e Innovación (SENACYT), Ciudad del Saber, Clayton, Panamá.
Comb Chem High Throughput Screen. 2024;27(4):502-515. doi: 10.2174/1386207326666230705150110.
Chemical libraries and compound data sets are among the main inputs to start the drug discovery process at universities, research institutes, and the pharmaceutical industry. The approach used in the design of compound libraries, the chemical information they possess, and the representation of structures, play a fundamental role in the development of studies: chemoinformatics, food informatics, pharmacokinetics, computational toxicology, bioinformatics, and molecular modeling to generate computational hits that will continue the optimization process of drug candidates. The prospects for growth in drug discovery and development processes in chemical, biotechnological, and pharmaceutical companies began a few years ago by integrating computational tools with artificial intelligence methodologies. It is anticipated that it will increase the number of drugs approved by regulatory agencies shortly.
化学文库和化合物数据集是大学、研究机构和制药行业启动药物发现过程的主要输入之一。化合物文库设计中使用的方法、它们所具有的化学信息以及结构的表示形式,在研究的发展中起着至关重要的作用:化学生信学、食品信息学、药代动力学、计算毒理学、生物信息学和分子建模,以生成计算命中,从而继续药物候选物的优化过程。几年前,通过将计算工具与人工智能方法相结合,化学、生物技术和制药公司的药物发现和开发过程的前景开始增长。预计这将很快增加监管机构批准的药物数量。