Selective inhibition of poly(ADP-ribose) polymerase 1 (PARP1) may reduce the hematologic toxicity associated with dual PARP1/PARP2 inhibition. We performed molecular dynamics simulations for five selective inhibitors in complexes with PARP1 and PARP2, using three independent 50 ns runs per complex after docking and equilibration, followed by protein–ligand interaction fingerprint and statistical analyses. All complexes remained dynamically stable, with ligand root-mean-square deviation values generally within 0.3 nm. Comparative analysis identified three αF-helix residue pairs with nominally reduced interaction frequencies in PARP2: Asn767/Ala336, Leu769/Gly338, and Asp770/Asp339 (p < 0.05). After Benjamini–Hochberg correction for multiple comparisons, Leu769/Gly338 remained significant (q < 0.05), indicating that this pair represents the most statistically robust interaction difference within this region. Using palacaparib as the most selective inhibitor, these differences were associated with weakened or lost hydrophobic, van der Waals, and cation–π interactions in PARP2. Selective binding of modern PARP1 inhibitors appears to be associated with αF-helix-dependent interaction patterns, providing a mechanistic basis for the rational design of next-generation selective inhibitors with improved selectivity and potentially reduced toxicity.

Breast cancer (BC) remains one of the most prevalent malignancies worldwide, with approximately 70% of cases being estrogen receptor-positive (ER+). Endocrine therapy targeting the estrogen receptor has revolutionized BC treatment, evolving from surgical oophorectomy to selective estrogen receptor modulators (SERMs) and aromatase inhibitors (AIs). Selective estrogen receptor degraders (SERDs) represent the latest advancement in hormonal therapy, offering complete receptor blockade and degradation. This review comprehensively examines the mechanisms of SERD action, their role in overcoming resistance to conventional endocrine therapy, and clinical applications of approved agents including fulvestrant, elacestrant, imlunestrant, and vepdegestrant, the first FDA-approved PROTAC estrogen receptor degrader. We discuss emerging oral SERDs such as giredestrant and camizestrant, novel PROTAC-based approaches, and combination strategies with CDK4/6 inhibitors, PI3K inhibitors, and other targeted agents. Special attention is given to ESR1 mutations as biomarkers for patient selection and therapy optimization. The review highlights key clinical trials including EMERALD, EMBER-3, SERENA-6, and lidERA that have shaped current treatment guidelines and points toward future directions in SERD development.

Endocrine therapy continues to be a fundamental treatment for estrogen receptor-positive (ER+) breast cancer; however, its long-term effectiveness is often hindered by the development of acquired resistance. This resistance poses a significant challenge in clinical management, limiting the durability of treatment responses. Recently, new clinical data have emerged showing promise with combination therapies that integrate endocrine agents and pathway inhibitors, offering renewed hope for patients. Nevertheless, resistance to these combination therapies still occurs, emphasizing the urgent need for further investigation into the underlying mechanisms. Preclinical models, including cell lines and animal studies, play a crucial role in advancing this research. Various in vitro models have been developed to mimic resistance to different endocrine therapies, such as long-term estrogen deprivation models that simulate aromatase inhibitor treatment, as well as models resistant to tamoxifen and selective estrogen receptor degraders like fulvestrant. This review systematically examines these preclinical models used to study the multifactorial mechanisms that drive antiestrogen resistance, highlighting their relevance and utility in improving therapeutic strategies. Understanding resistance pathways through these models is essential to developing more effective interventions for overcoming endocrine therapy resistance in ER+ breast cancer.

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