Health Science Center, Federal University of Paraíba, 50670-910, João Pessoa, PB, Brazil.
Teaching and Research Management-University Hospital, Federal University of Paraíba, João Pessoa, PB, Brazil.
Curr Top Med Chem. 2023;23(5):349-370. doi: 10.2174/1568026623666230126112628.
Neurological disorders are composed of several diseases that affect the central and peripheral nervous system; among these are neurodegenerative diseases, which lead to neuronal death. Many of these diseases have treatment for the disease and symptoms, leading patients to use several drugs that cause side effects.
The search for new treatments has led to the investigation of multi-target drugs.
This review aimed to investigate in the literature the multi-target effect in neurological disorders through an in silico approach. Studies were reviewed on the diseases such as epilepsy, Alzheimer's disease, Amyotrophic Lateral Sclerosis (ALS), Huntington's disease, cerebral ischemia, and Parkinson's disease.
As a result, the study emphasize the relevance of research by computational techniques such as quantitative structure-activity relationship (QSAR) prediction models, pharmacokinetic prediction models, molecular docking, and molecular dynamics, besides presenting possible drug candidates with multi-target activity.
It was possible to identify several targets with pharmacological activities. Some of these targets had diseases in common such as carbonic anhydrase, acetylcholinesterase, NMDA, and MAO being relevant for possible multi-target approaches.
神经系统疾病由多种影响中枢和外周神经系统的疾病组成;其中包括神经退行性疾病,可导致神经元死亡。许多此类疾病都有针对疾病和症状的治疗方法,导致患者使用多种会引起副作用的药物。
对新疗法的探索促使人们研究多靶点药物。
本综述旨在通过计算机方法研究神经退行性疾病中的多靶点作用。对癫痫、阿尔茨海默病、肌萎缩性侧索硬化症(ALS)、亨廷顿病、脑缺血和帕金森病等疾病进行了研究。
研究强调了研究的重要性,例如定量构效关系(QSAR)预测模型、药代动力学预测模型、分子对接和分子动力学等计算技术,并提出了具有多靶点活性的可能候选药物。
已经可以确定几种具有药理活性的靶点。其中一些靶点具有共同的疾病,如碳酸酐酶、乙酰胆碱酯酶、NMDA 和 MAO,这对于可能的多靶点方法非常重要。