Department of Pharmaceutical Chemistry, School of Pharmaceutical Sciences, Lovely Professional University, Jalandhar- Delhi G.T. Road, Phagwara (Punjab), India.
Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research- Raebareli, New Transit Campus, Bijnor-Sisendi Road, Sarojini Nagar, Near CRPF Base Camp, Lucknow (Uttar Pradesh 226301), India.
Curr Drug Targets. 2021;22(10):1158-1182. doi: 10.2174/1389450121666201119141525.
In this fast-growing era, high throughput data is now being easily accessed by getting transformed into datasets which store the information. Such information is valuable to optimize the hypothesis and drug design via computer-aided drug design (CADD). Nowadays, we can explore the role of CADD in various disciplines like Nanotechnology, Biochemistry, Medical Sciences, Molecular Biology, etc. Methods: We searched the valuable literature using a pertinent database with given keywords like computer-aided drug design, anti-diabetic, drug design, etc. We retrieved all valuable articles which are recent and discussing the role of computation in the designing of anti-diabetic agents.
To facilitate the drug discovery process, the computational approach has set landmarks in the whole pipeline for drug discovery from target identification and mechanism of action to the identification of leads and drug candidates. Along with this, there is a determined endeavor to describe the significance of in-silico studies in predicting the absorption, distribution, metabolism, excretion, and toxicity profile. Thus, globally, CADD is accepted with a variety of tools for studying QSAR, virtual screening, protein structure prediction, quantum chemistry, material design, physical and biological property prediction.
Computer-assisted tools are used as the drug discovery tool in the area of different diseases, and here we reviewed the collaborative aspects of information technologies and chemoinformatic tools in the discovery of anti-diabetic agents, keeping in view the growing importance for treating diabetes.
在这个快速发展的时代,通过转化为存储信息的数据集,现在可以轻松访问高通量数据。这些信息对于通过计算机辅助药物设计(CADD)优化假设和药物设计非常有价值。如今,我们可以在纳米技术、生物化学、医学科学、分子生物学等各个学科中探索 CADD 的作用。
我们使用相关数据库搜索有价值的文献,并使用计算机辅助药物设计、抗糖尿病、药物设计等关键词。我们检索了所有有价值的文章,这些文章都是最近的,讨论了计算在设计抗糖尿病药物中的作用。
为了促进药物发现过程,计算方法在药物发现的整个过程中都具有里程碑意义,从靶标识别和作用机制到先导化合物和药物候选物的识别。此外,人们还在努力描述基于计算机的研究在预测吸收、分布、代谢、排泄和毒性特征方面的重要性。因此,全球范围内,CADD 已被广泛接受,并使用各种工具来研究定量构效关系、虚拟筛选、蛋白质结构预测、量子化学、材料设计、物理和生物性质预测。
计算机辅助工具被用作不同疾病领域的药物发现工具,在这里,我们回顾了信息技术和化学生物信息学工具在抗糖尿病药物发现中的协同方面,考虑到治疗糖尿病的重要性日益增加。