将单个基因与特定疾病和特定药物联系起来的传统理论导致传统药物发现的成功率不断下降。这需要对当代药物设计或药物再利用进行重大转变，这需要将多个基因与不同的生理或病理途径和药物联系起来。最近，药物再利用，即在临床试验中为现有药物或候选药物发现新的/未标记的适应症的艺术，由于其成功率而受到关注。该策略的限速阶段在于目标识别，这通常是通过以疾病为中心和/或以药物为中心的方法驱动的。以疾病为中心的方法基于对关键生物分子的探索，例如目标疾病病理级联背后的基因或蛋白质。研究这些病理相互作用有助于识别可用于新型治疗干预的潜在药物靶点。以药物为中心的方法涉及各种策略，例如探索药物不良反应的机制，可以挖掘潜在的靶点，因为这些不良反应可能被认为是其他疾病条件下理想的治疗措施。目前，人工智能是一种新兴的强大工具，可用于转换上述复杂的生物网络，以提供可解释的数据，以提取精确的分子目标。多种方法的整合、大数据分析和临床验证对于成功的目标挖掘至关重要。本章重点介绍了指导靶点识别的当代策略和药物再利用的多样化框架。这些策略通过近期针对神经退行性疾病、癌症、感染、免疫学和心血管疾病的药物再利用研究策划的案例研究进行了说明。版权所有 © 2024。由 Elsevier Inc. 出版。

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.Copyright © 2024. Published by Elsevier Inc.