Journal of pharmaceutical analysis最新文献

{"title":"Generation of SARS-CoV-2 dual-target candidate inhibitors through 3D equivariant conditional generative neural networks.","authors":"Zhong-Xing Zhou, Hong-Xing Zhang, Qingchuan Zheng","doi":"10.1016/j.jpha.2025.101229","DOIUrl":"10.1016/j.jpha.2025.101229","url":null,"abstract":"<p><p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations are influenced by random and uncontrollable factors, and the risk of the next widespread epidemic remains. Dual-target drugs that synergistically act on two targets exhibit strong therapeutic effects and advantages against mutations. In this study, a novel computational workflow was developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main protease selected as the two target proteins. The drug-like molecules of our self-constructed 3D scaffold database were used as high-throughput molecular docking probes for feature extraction of two target protein pockets. A multi-layer perceptron (MLP) was employed to embed the binding affinities into a latent space as conditional vectors to control conditional distribution. Utilizing a conditional generative neural network, cG-SchNet, with 3D Euclidean group (E3) symmetries, the conditional probability distributions of molecular 3D structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated. The 1D probability, 2D joint probability, and 2D cumulative probability distribution results indicate that the generated sets are significantly enhanced compared to the training set in the high binding affinity area. Among the 201 generated molecules, 42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol, demonstrating structure diversity along with strong dual-target affinities, good absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and ease of synthesis. Dual-target drugs are rare and difficult to find, and our \"high-throughput docking-multi-conditional generation\" workflow offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 6","pages":"101229"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12269411/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661535","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}

{"title":"Perturbation response scanning of drug-target networks: Drug repurposing for multiple sclerosis.","authors":"Yitan Lu, Ziyun Zhou, Qi Li, Bin Yang, Xing Xu, Yu Zhu, Mengjun Xie, Yuwan Qi, Fei Xiao, Wenying Yan, Zhongjie Liang, Qifei Cong, Guang Hu","doi":"10.1016/j.jpha.2025.101295","DOIUrl":"10.1016/j.jpha.2025.101295","url":null,"abstract":"<p><p>Combined with elastic network model (ENM), the perturbation response scanning (PRS) has emerged as a robust technique for pinpointing allosteric interactions within proteins. Here, we proposed the PRS analysis of drug-target networks (DTNs), which could provide a promising avenue in network medicine. We demonstrated the utility of the method by introducing a deep learning and network perturbation-based framework, for drug repurposing of multiple sclerosis (MS). First, the MS comorbidity network was constructed by performing a random walk with restart algorithm based on shared genes between MS and other diseases as seed nodes. Then, based on topological analysis and functional annotation, the neurotransmission module was identified as the \"therapeutic module\" of MS. Further, perturbation scores of drugs on the module were calculated by constructing the DTN and introducing the PRS analysis, giving a list of repurposable drugs for MS. Mechanism of action analysis both at pathway and structural levels screened dihydroergocristine as a candidate drug of MS by targeting a serotonin receptor of serotonin 2B receptor (HTR2B). Finally, we established a cuprizone-induced chronic mouse model to evaluate the alteration of HTR2B in mouse brain regions and observed that HTR2B was significantly reduced in the cuprizone-induced mouse cortex. These findings proved that the network perturbation modeling is a promising avenue for drug repurposing of MS. As a useful systematic method, our approach can also be used to discover the new molecular mechanism and provide effective candidate drugs for other complex diseases.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 6","pages":"101295"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12268079/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661537","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}

{"title":"Scaffold and SAR studies on c-MET inhibitors using machine learning approaches.","authors":"Jing Zhang, Mingming Zhang, Weiran Huang, Changjie Liang, Wei Xu, Jinghua Zhang, Jun Tu, Innocent Okohi Agida, Jinke Cheng, Dong-Qing Wei, Buyong Ma, Yanjing Wang, Hongsheng Tan","doi":"10.1016/j.jpha.2025.101303","DOIUrl":"10.1016/j.jpha.2025.101303","url":null,"abstract":"<p><p>Numerous c-mesenchymal-epithelial transition (c-MET) inhibitors have been reported as potential anticancer agents. However, most fail to enter clinical trials owing to poor efficacy or drug resistance. To date, the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed. In this study, we constructed the largest c-MET dataset, which included 2,278 molecules with different structures, by inhibiting the half maximal inhibitory concentration (IC₅₀) of kinase activity. No significant differences in drug-like properties were observed between active molecules (1,228) and inactive molecules (1,050), including chemical space coverage, physicochemical properties, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. The higher chemical diversity of the active molecules was downscaled using <i>t</i>-distributed stochastic neighbor embedding (<i>t</i>-SNE) high-dimensional data. Further clustering and chemical space networks (CSNs) analyses revealed commonly used scaffolds for c-MET inhibitors, such as M5, M7, and M8. Activity cliffs and structural alerts were used to reveal \"dead ends\" and \"safe bets\" for c-MET, as well as dominant structural fragments consisting of pyridazinones, triazoles, and pyrazines. Finally, the decision tree model precisely indicated the key structural features required to constitute active c-MET inhibitor molecules, including at least three aromatic heterocycles, five aromatic nitrogen atoms, and eight nitrogen-oxygen atoms. Overall, our analyses revealed potential structure-activity relationship (SAR) patterns for c-MET inhibitors, which can inform the screening of new compounds and guide future optimization efforts.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 6","pages":"101303"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12268054/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661538","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}

{"title":"SITA: Predicting site-specific immunogenicity for therapeutic antibodies.","authors":"Yewei Cun, Hao Ding, Tiantian Mao, Yuan Wang, Caicui Wang, Jiajun Li, Zihao Li, Mengdie Hu, Zhiwei Cao, Tianyi Qiu","doi":"10.1016/j.jpha.2025.101316","DOIUrl":"10.1016/j.jpha.2025.101316","url":null,"abstract":"<p><p>Antibody (Ab) humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic Abs originated from animal models. Computational suggestions have long been desired, but available tools focused on immunogenicity calculation of whole Ab sequences and sequence segments, missing the individual residue sites. This study introduces Site-specific Immunogenicity for Therapeutic Antibody (SITA), a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody, but also individual residues, based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures. A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Ab-Ab structural complexes. On an independent testing dataset derived from 13 Ab-Ab structural complexes, SITA successfully predicted the epitope sites for Ab-Ab structures with a receiver operating characteristic (ROC)-area unver the ROC curve (AUC) of 0.85 and a precision-recall (PR)-AUC of 0.305 at the residue level. Furthermore, the SITA score can significantly distinguish immunogenicity levels of whole human Abs, therapeutic Abs and non-human-derived Abs. More importantly, analysis of an additional 25 therapeutic Abs revealed that over 70% of them were detected with decreased immunogenicity after modification compared to their parent variants. Among these, nearly 66% Abs successfully identified actual modification sites from the top five sites with the highest SITA scores, suggesting the ability of SITA scores for guide the humanization of antibody. Overall, these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 6","pages":"101316"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12268063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144661539","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}

{"title":"Huangqin decoction inhibits colorectal inflammatory cancer transformation by improving gut microbiome-mediated metabolic dysfunction.","authors":"Lu Lu, Yuan Li, Hang Su, Sisi Ren, Yujing Liu, Gaoxuan Shao, Weiwei Liu, Guang Ji, Hanchen Xu","doi":"10.1016/j.jpha.2024.101138","DOIUrl":"10.1016/j.jpha.2024.101138","url":null,"abstract":"<p><p>Colorectal inflammatory cancer transformation poses a major risk to patients with colitis. Patients with chronic intestinal inflammation have an approximately 2-3 folds increased risk of developing colorectal cancer (CRC). Unfortunately, there is currently no effective intervention available. Huangqin decoction (HQD), a well-known traditional Chinese medicine (TCM) formula, is frequently clinically prescribed for treating patients with colitis, and its active ingredients have effective antitumour efficacy. Nonetheless, the mechanism of HQD-mediated prevention of colorectal inflammatory cancer transformation remains unclear. A strategy integrating metagenomic, lipidomic, and messenger RNA (mRNA) sequencing analysis was used to investigate the regulatory effects of HQD on the gut microbiome, metabolism and potential mechanisms involved in colorectal inflammatory cancer transformation. Our study revealed that HQD suppressed colorectal inflammatory cancer transformation, which was associated with enhanced intestinal barrier function, decreased the inflammatory response, and regulation of the gut microbiome. Notably, cohousing experiments revealed that the transfer of the gut microbiome from HQD-treated mice largely inhibited the pathological transformation of colitis. Moreover, gut microbiome transfer from HQD-treated mice primarily resulted in the altered regulation of fatty acid metabolism, especially the remodeling of arachidonic acid metabolism, which was associated with the amelioration of pathological transformation. Arachidonic acid metabolism and the key metabolic enzyme arachidonic acid 12-lipoxygenase (ALOX12) were affected by HQD treatment, and no obvious protective effect of HQD was observed in <i>Alox</i> <i>12</i> ^-/- mice, which revealed that ALOX12 was a critical mediator of HQD protection against colorectal inflammatory cancer transformation. In summary, multiple omics analyses were applied to produce valuable data and theoretical support for the application of HQD as a promising intervention for the transformation of inflammatory CRC.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101138"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12153368/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277279","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}

{"title":"A promising strategy of brain targeted delivery for the treatment of Parkinson's disease: Cyclodextrin supramolecular inclusion complex based thermosensitive gel.","authors":"Yan-Qiu Wang, Li-Ming Wang, Li-Feng Han, Yi-Bing Chen, Yuan-Lu Cui","doi":"10.1016/j.jpha.2024.101102","DOIUrl":"10.1016/j.jpha.2024.101102","url":null,"abstract":"<p><p>Image 1.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101102"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251687","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}

{"title":"Characterization of preclinical radio ADME properties of ARV-471 for predicting human PK using PBPK modeling.","authors":"Yifei He, Chenggu Zhu, Peng Lei, Chen Yang, Yifan Zhang, Yuandong Zheng, Xingxing Diao","doi":"10.1016/j.jpha.2024.101175","DOIUrl":"10.1016/j.jpha.2024.101175","url":null,"abstract":"<p><p>Proteolysis-targeting chimeras (PROTACs) represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can, potentially revolutionizing drug discovery and treatment strategies. However, the links between <i>in vitro</i> and <i>in vivo</i> data are poorly understood, hindering a comprehensive understanding of the absorption, distribution, metabolism, and excretion (ADME) of PROTACs. In this work, ¹⁴C-labeled vepdegestrant (ARV-471), which is currently in phase III clinical trials for breast cancer, was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics (PK) by establishing a physiologically based pharmacokinetics (PBPK) model. For <i>in vitro</i>-<i>in vivo</i> extrapolation (IVIVE), hepatocyte clearance correlated more closely with <i>in vivo</i> rat PK data than liver microsomal clearance did. PBPK models, which were initially developed and validated in rats, accurately simulate ARV-471's PK across fed and fasted states, with parameters within 1.75-fold of the observed values. Human models, informed by <i>in vitro</i> ADME data, closely mirrored postoral dose plasma profiles at 30 mg. Furthermore, no human-specific metabolites were identified <i>in vitro</i> and the metabolic profile of rats could overlap that of humans. This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between <i>in vitro</i> and <i>in vivo</i> characteristics.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101175"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12151198/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268260","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}

{"title":"A gene set enrichment analysis for cancer hallmarks.","authors":"Otília Menyhart, William Jayasekara Kothalawala, Balázs Győrffy","doi":"10.1016/j.jpha.2024.101065","DOIUrl":"10.1016/j.jpha.2024.101065","url":null,"abstract":"<p><p>The \"hallmarks of cancer\" concept provides a valuable framework for understanding fundamental organizing principles common to various cancers. However, without a consensus gene set for cancer hallmarks, data comparison and integration result in diverse biological interpretations across studies. Therefore, we aimed to form a consensus cancer hallmark gene set by merging data from available mapping resources and establishing a framework for mining these gene sets. By consolidating data from seven projects, 6763 genes associated with 10 cancer hallmarks were identified. A cancer hallmarks enrichment analysis was performed for prognostic genes associated with overall survival across 12 types of solid tumors. \"Tissue invasion and metastasis\" was most prominent in cancers of the stomach (<i>P =</i> 2.2 × 10^-11), pancreas (<i>P =</i> 4.2 × 10^-9), bladder (<i>P =</i> 3.3 × 10^-8), and ovaries (<i>P =</i> 0.0007), aligning with their heightened potential to spread. \"Sustained angiogenesis\" was most prominent in squamous cell carcinomas of the lung (<i>P =</i> 2.5 × 10^-7), while \"genome instability\" showed strong enrichment in lung adenocarcinomas (LUADs) (<i>P =</i> 1.5 × 10^-8) and cancers of the liver (<i>P =</i> 5.5 × 10^-10), pancreas (<i>P =</i> 2.1 × 10^-5), and kidney (<i>P</i> = 0.018). Pancreatic cancers displayed the highest enrichment of hallmarks, emphasizing the disease's complexity, while in melanomas and cancers of the liver, prostate, and kidney, a single hallmark was enriched among the prognostic markers of survival. Additionally, an online tool (www.cancerhallmarks.com) that allows the identification of cancer-associated hallmarks from new gene sets was established. In summary, our aim of establishing a consensus list of cancer hallmark genes was achieved. Furthermore, the analysis of survival-associated genes revealed a unique pattern of hallmark enrichment with potential pharmacological implications in different tumor types.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101065"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12151186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268256","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}

{"title":"An improved reporter gene assay for evaluating the biological activity of recombinant human growth hormone.","authors":"Xiaoming Zhang, Heyang Li, Ying Huang, Ping Lv, Lvyin Wang, Kezheng Xu, Yi Li, Xinyue Hu, Yue Sun, Cheng-Gang Liang, Jing Li","doi":"10.1016/j.jpha.2024.101073","DOIUrl":"10.1016/j.jpha.2024.101073","url":null,"abstract":"<p><p>Image 1.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101073"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150084/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268259","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}

{"title":"Exploring cellular plasticity and resistance mechanisms in lung cancer: Innovations and emerging therapies.","authors":"Caiyu Jiang, Shenglong Xie, Kegang Jia, Gang Feng, Xudong Ren, Youyu Wang","doi":"10.1016/j.jpha.2024.101179","DOIUrl":"10.1016/j.jpha.2024.101179","url":null,"abstract":"<p><p>Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and remains the leading cause of cancer-related mortality worldwide. Firstly, this review explores the limitations of conventional therapies, chemotherapy, radiotherapy, and surgery, focusing on the development of drug resistance and significant toxicity that often hinder their efficacy. Thereafter, advancements in targeted therapies, such as immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), are discussed, highlighting their impact on improving outcomes for patients with specific genetic mutations, including c-ros oncogene 1 receptor tyrosine kinase (ROS1), anaplastic lymphoma kinase (ALK), and epidermal growth factor receptor (EGFR). Additionally, the emergence of novel immunotherapies and phytochemicals is examined, emphasizing their potential to overcome therapeutic resistance, particularly in advanced-stage diseases. The review also delves into the role of next-generation sequencing (NGS) in enabling personalized treatment approaches and explores the clinical potential of innovative agents, such as bispecific T-cell engagers (BiTEs) and antibody-drug conjugates (ADCs). Finally, we address the socioeconomic barriers that limit the accessibility of these therapies in low-resource settings and propose future research directions aimed at improving the long-term efficacy and accessibility of these treatments.</p>","PeriodicalId":94338,"journal":{"name":"Journal of pharmaceutical analysis","volume":"15 5","pages":"101179"},"PeriodicalIF":0.0,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12151197/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144268261","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}