The discovery of effective AutoTaXin (ATX) inhibitors is crucial for developing therapies targeting various diseases, including cancer, inflammation and fibrosis. Structure-based drug design has emerged as a powerful strategy to identify and optimize ATX inhibitors with enhanced potency and selectivity. This comprehensive review explores recent advancements in structure-based approaches for discovering ATX inhibitors, encompassing computational modeling, structural biology insights and medicinal chemistry strategies. Key findings highlight successful examples of ATX inhibitor development, including structure-activity relationship studies and mechanism-based drug design. The review discusses challenges, opportunities and future directions in leveraging structure-based approaches to accelerate the discovery of next-generation ATX inhibitors for clinical applications.
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