NPJ drug discovery最新文献_第3页

Considerations for the dynamic role of bile acids during oral drug discovery and development. 考虑胆汁酸在口服药物发现和开发中的动态作用。

NPJ drug discovery Pub Date : 2026-09-02 DOI: 10.1038/s44386-026-00065-2

Zahraa Al-Tamimi, Michael J Hageman

引用次数: 0

A curated benchmark for cofolding models on kinase conformational states. 对激酶构象状态的共折叠模型的策划基准。

NPJ drug discovery Pub Date : 2026-09-02 DOI: 10.1038/s44386-026-00068-z

Kunyang Sun, Teresa Head-Gordon

{"title":"A curated benchmark for cofolding models on kinase conformational states.","authors":"Kunyang Sun, Teresa Head-Gordon","doi":"10.1038/s44386-026-00068-z","DOIUrl":"10.1038/s44386-026-00068-z","url":null,"abstract":"Protein kinases are critical drug targets, requiring therapeutics that can modulate their active and inactive conformational states. While cofolding models can generate global folds directly from kinase sequences and ligand SMILES strings, these models have not yet been tested on their ability to recover ligand-induced-fit conformational states of the kinase proteins. Here, we introduce KinConfBench, a curated benchmark of 2225 high-quality human kinase chains to evaluate the ability of four state-of-the-art cofolding models-Boltz-2, Chai-1, Protenix, and RoseTTAFold-All-Atom-to recover both canonical and rare conformational states. We show that geometric success metrics of a ligand pose in the active site do not correlate strongly with the correct kinase conformational state, motivating a new set of dynamical benchmarks for assessing cofolding models. While all four cofolding models achieve ~60-80% prediction accuracy for kinase conformational classification, they exhibit severe mode collapse when performing multiple inferences, show negligible structural diversity in sampling induced-fit motions, and display a prevalent \"apo-drift\" in which most cofolding models predominantly predict the kinase to be in its ligand-free state. Our results highlight that capturing ligand-induced protein conformational diversity, not just geometric fit, is critical for next-generation structure-based drug discovery.","PeriodicalId":520448,"journal":{"name":"NPJ drug discovery","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13538545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148883303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Publisher Correction: FeatureDock for protein-ligand docking guided by physicochemical feature-based local environment learning using transformer. 使用transformer进行基于物理化学特征的局部环境学习指导的蛋白质配体对接的FeatureDock。

NPJ drug discovery Pub Date : 2026-08-22 DOI: 10.1038/s44386-026-00071-4

Mingyi Xue, Bojun Liu, Siqin Cao, Xuhui Huang

引用次数: 0

Triple potentiator combinations increase the functional correction of several CFTR gating mutants. 三重增强剂组合增加了几种CFTR控制突变体的功能校正。

NPJ drug discovery Pub Date : 2026-08-14 DOI: 10.1038/s44386-026-00061-6

Guido Veit, Christian Vaccarin, Márton A Simon, Haijin Xu, Houriyeh Hajizadeh, Tina He, Adriana Chilin, Elias Matouk, László Csanády, Giovanni Marzaro, Gergely L Lukacs

{"title":"Triple potentiator combinations increase the functional correction of several CFTR gating mutants.","authors":"Guido Veit, Christian Vaccarin, Márton A Simon, Haijin Xu, Houriyeh Hajizadeh, Tina He, Adriana Chilin, Elias Matouk, László Csanády, Giovanni Marzaro, Gergely L Lukacs","doi":"10.1038/s44386-026-00061-6","DOIUrl":"https://doi.org/10.1038/s44386-026-00061-6","url":null,"abstract":"The Trikafta drug combination, comprising the corrector tezacaftor (VX-661), the potentiator ivacaftor (VX-770) and the dual corrector/potentiator elexacaftor (VX-445), has been FDA-approved for treatment of cystic fibrosis caused by ~300 cystic fibrosis transmembrane conductance regulator (CFTR) mutations. Nevertheless, several CFTR variants exhibit limited response to Trikafta. To address this therapeutic gap, we investigated whether the potentiator activity of VX-445 can complement the VX-770 and preclinical \"co-potentiators\" activity in partially responsive CFTR mutants. Functional clustering of clinical and preclinical potentiator profiles suggests that VX-445 represents a distinct potentiator class, an inference supported by its additivity with both VX-770/VX-770-like potentiators and co-potentiators across five CFTR mutants in bronchial epithelia. This concept was further validated in gene-edited 16HBE and primary human nasal epithelia, expressing G551D-, N1303K-, and W1282X-CFTR, the 3rd, 4th, and 6th most common CF-mutations, respectively, and was confirmed at the single-channel level. Moreover, we present the development of a novel series of co-potentiator compounds that are derived from our previously described 4172 corrector scaffold, which exhibit low micromolar potency. Our findings suggest that triple potentiation can significantly enhance functional restoration of poorly responsive gating mutants, thereby uncovering novel avenues for therapeutic development.","PeriodicalId":520448,"journal":{"name":"NPJ drug discovery","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13476245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148763301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

On the generalization and usability of cofolding models for GPCR drug discovery. 关于GPCR药物发现的共折叠模型的泛化和可用性。

NPJ drug discovery Pub Date : 2026-08-14 DOI: 10.1038/s44386-026-00066-1

Lichirui Zhang, Richard A Friesner, Edward B Miller, João P Glm Rodrigues

引用次数: 0

New paradigm of q-CAR drug development targeting disease-specific protein conformations. 针对疾病特异性蛋白质构象的q-CAR药物开发的新范例。

NPJ drug discovery Pub Date : 2026-08-14 DOI: 10.1038/s44386-026-00057-2

Libin Ye

引用次数: 0

Induced proximity-based therapeutics for advanced prostate cancer. 诱导邻近治疗晚期前列腺癌。

NPJ drug discovery Pub Date : 2026-08-14 DOI: 10.1038/s44386-026-00062-5

John Ching, Cindy H Chau, William D Figg

引用次数: 0

Structure-based TCR-pMHC binding prediction and generalization to unseen peptides. 基于结构的TCR-pMHC结合预测及对未知肽的推广。

NPJ drug discovery Pub Date : 2026-08-14 DOI: 10.1038/s44386-026-00064-3

A N M Nafiz Abeer, Raj S Roy, Xiaoning Qian, Byung-Jun Yoon

{"title":"Structure-based TCR-pMHC binding prediction and generalization to unseen peptides.","authors":"A N M Nafiz Abeer, Raj S Roy, Xiaoning Qian, Byung-Jun Yoon","doi":"10.1038/s44386-026-00064-3","DOIUrl":"https://doi.org/10.1038/s44386-026-00064-3","url":null,"abstract":"The interaction between T-cell receptors (TCRs) with the peptide-bound major histocompatibility complex (MHC) intricately impacts the functional specificity of T-cell-mediated adaptive immune response. Consequently, implication in immunotherapy has contributed to the ever-growing computational methods for TCR recognition, which have recently attracted structure-based approaches due to advancements in protein structure modeling. Despite access to structural information of the predicted binding interface, graph neural network (GNN)-based TCR-pMHC binding specificity classifiers tend to show poor accuracy for samples with unseen peptides. In this work, we comprehensively assess the potential factors that critically impact the generalization performance of classifiers trained with computationally predicted structures. Specifically, our experiments focus on analyzing the sensitivity of such predictors to the interaction features in the TCR-pMHC interface and the structural uncertainty. Building on the analysis, we demonstrate how the design of classifier architecture with auxiliary training objectives can improve the generalization performance to novel peptides not yet seen during model training. Overall, our work highlights the challenges of unseen peptide generalization from different perspectives of the GNN-based classifier paradigm, showcasing the strengths and weaknesses of the current state-of-the-art approaches in the generalization landscape.","PeriodicalId":520448,"journal":{"name":"NPJ drug discovery","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13476271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148762670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ubiquitin family as novel protein partners for molecular glues. 泛素家族作为分子胶的新蛋白伙伴。

NPJ drug discovery Pub Date : 2026-08-04 DOI: 10.1038/s44386-026-00059-0

Laura Silvian

引用次数: 0

Diversity Beats Size Scaling for Chemical Language Models. 化学语言模型的多样性胜过大小缩放。

NPJ drug discovery Pub Date : 2026-08-04 DOI: 10.1038/s44386-026-00056-3

Borja Medina, Alessandro Tibo, Jiazhen He, Jon Paul Janet, Nicklas Österbacka

引用次数: 0