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Dongsheng Cao

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Review Aug 2026

Selective PARP1 inhibitors (2021-2025): patent landscape, structural evolution, and future therapeutic opportunities.

INTRODUCTION Poly(ADP-ribose) polymerase 1 (PARP1) is a key mediator of DNA damage repair and an attractive therapeutic target for homologous recombination-deficient malignancies. The development of selective PARP1 inhibitors has been driven by the need to reduce the hematological toxicities associated with nonselective PARP inhibition. AREA COVERED This review summarizes patents and recent advances in selective PARP1 inhibitors reported from 2021 to the present. Particular emphasis is placed on the structural evolution of AZD5305-derived compounds and emerging quinazolinone- and isoquinolinone-based chemotypes. Key design strategies, including adenine-pocket optimization, linker remodeling, conformational restriction, and scaffold diversification, are discussed together with their impact on PARP1 selectivity and biological activity. EXPERT OPINION Selective PARP1 inhibition has become a major focus of innovation in the PARP field. Current patents indicate that adenine-pocket engagement, linker optimization, conformational control, and scaffold innovation are central to achieving high PARP1 selectivity and represent important directions for future intellectual property development. Despite significant progress, the disclosed chemical space remains relatively limited, highlighting opportunities for further scaffold diversification and differentiated patent strategies. These advances are expected to facilitate the development of next-generation PARP1-targeted therapeutics with improved safety profiles and broader clinical potential.

Jilong Duan, Yanjing Duan, Dongling Gu et al. · 0 citations
Review Open access 2026

Physics-informed deep learning: A new paradigm for macromolecular recognition and rational protein design

By delineating how physics-based priors synergize with data-driven representation learning, this review provides a comprehensive roadmap for generating physically plausible and thermodynamically stable therapeutics, ultimately accelerating the transition of computationally designed molecules from in silico blueprints to viable clinical candidates.

Hao-Bo Xie, Hao Wang, Xiao-Jun Yao et al. · 0 citations

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