关键词: AI Computer-aided drug design Machine learning QSAR in silico techniques

来  源:   DOI:10.1186/s13321-024-00842-z   PDF(Pubmed)

Abstract:
As the world grapples with the relentless challenges posed by diseases like malaria, the advent of sophisticated computational tools has emerged as a beacon of hope in the quest for effective treatments. In this study we delve into the strategies behind computational tools encompassing virtual screening, molecular docking, artificial intelligence (AI), and machine learning (ML). We assess their effectiveness and contribution to the progress of malaria treatment. The convergence of these computational strategies, coupled with the ever-increasing power of computing systems, has ushered in a new era of drug discovery, holding immense promise for the eradication of malaria. SCIENTIFIC CONTRIBUTION: Computational tools remain pivotal in drug design and development. They provide a platform for researchers to explore various treatment options and save both time and money in the drug development pipeline. It is imperative to assess computational techniques and monitor their effectiveness in disease control. In this study we examine renown computational tools that have been employed in the battle against malaria, the benefits and challenges these tools have presented, and the potential they hold in the future eradication of the disease.
摘要:
随着世界努力应对疟疾等疾病带来的无情挑战,先进的计算工具的出现已经成为寻求有效治疗的希望灯塔。在这项研究中,我们深入研究了包含虚拟筛选的计算工具背后的策略,分子对接,人工智能(AI)机器学习(ML)我们评估其有效性和对疟疾治疗进展的贡献。这些计算策略的收敛,再加上计算机系统不断增长的能力,开创了药物发现的新时代,对消灭疟疾有着巨大的希望。科学贡献:计算工具在药物设计和开发中仍然至关重要。它们为研究人员提供了一个探索各种治疗方案的平台,并在药物开发管道中节省时间和金钱。必须评估计算技术并监测其在疾病控制中的有效性。在这项研究中,我们研究了在抗击疟疾的斗争中使用的著名计算工具,这些工具带来的好处和挑战,以及他们未来根除这种疾病的潜力。
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