Current topics in medicinal chemistry最新文献

{"title":"Innovations in Depression Diagnosis and Treatment: A Review of Biological, Cognitive, and Psychosocial Advances.","authors":"Guizhen Lyu, Dongbing Li","doi":"10.2174/0115680266437457251129112908","DOIUrl":"https://doi.org/10.2174/0115680266437457251129112908","url":null,"abstract":"<p><p>Depression is a leading cause of global disability, affecting over 300 million individuals and imposing substantial personal, clinical, and societal burdens. This comprehensive review synthesizes recent advances in understanding depression across biological, cognitive, and psychosocial domains, emphasizing innovations in diagnosis, pathophysiology, and treatment. We explore emerging distinctions between major depressive disorder (MDD) and bipolar depression (BD), highlighting novel biomarkers and neuroimaging tools to reduce misdiagnosis. Special attention is given to under-researched subtypes, including postpartum, inflammation-related, and adolescent depression, which present unique diagnostic and therapeutic challenges. Pathophysiological insights reveal dysregulated neurotransmitter systems, neuroinflammation, and disrupted neural connectivity as central mechanisms, while genetic-environment interactions underscore the need for personalized approaches. Cognitive dysfunction is examined as both a core symptom and a predictor of treatment resistance, with validated tools enabling targeted remediation strategies. Advances in treatment span from FDA-approved neurosteroid therapies for postpartum depression (e.g., brexanolone) to breakthrough psychedelic-assisted psychotherapy for treatment-resistant cases. The paradigm shift toward precision psychiatry and quasi-treatment-resistant depression frameworks is discussed, alongside socioeconomic and cultural barriers to equitable care. Finally, we address the heightened vulnerability of special populations-adolescents, older adults with comorbid dementia, and women in the peripartum period, and propose interdisciplinary models to close critical gaps in global mental health. This review highlights the need for a holistic and personalized approach to depression care, aiming to reduce healthcare disparities and improve long-term outcomes.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148142992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ranolazine Co-Crystal: Molecular Docking, Coformer Selection, In vitro, In vivo Pharmacokinetic Assesment in Rat Plasma.","authors":"Ketkee Mandawar, Uttam Patle, Kalyani R Thombre, Krishna Radheshyam Gupta, Milind J Umekar","doi":"10.2174/0115680266325425251118032250","DOIUrl":"https://doi.org/10.2174/0115680266325425251118032250","url":null,"abstract":"<p><p>Ranolazine is an antianginal agent, but its low water solubility and bioavailability limit its therapeutic use. In this study, we have attempted to improve the solubility and bioavailability of Ranolazine by forming co-crystals with selected co-formers. In silico screening was first performed to select the potential co-formers forming stable co-crystals with Ranolazine. Based on the predicted interactions and physicochemical properties, co-formers 2-amino caffeine, nicotinamide, and benzamide were selected. Co-crystals were synthesized by solvent drop grinding, antisolvent addition and slow evaporation methods. Characterization of synthesized co-crystals was carried out by UV, FTIR, and DSC techniques to confirm the successful formation and structural properties. In vitro dissolution studies showed that the co-crystals significantly improved the release rate of Ranolazine as compared to the pure drug. A pharmacokinetic study used a validated RP-HPLC method to quantify Ranolazine and its co-crystals in rat plasma after oral administration. The analysis showed enhanced plasma concentrations (Cmax) for Ranolazine co-crystals, which indicated improved bioavailability. The RP-HPLC method was found to be accurate, sensitive, linear and specific following ICH guidelines, with hydrochlorothiazide as the internal standard. This study demonstrated the potential of in silico screening for selecting appropriate co-formers to enhance the physicochemical properties of Ranolazine, and the co-crystals have shown potential for improved therapeutic outcomes. These results indicate that further preclinical and clinical investigations of Ranolazine co-crystals could effectively improve drug performance.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing CRISPR-Cas Technology for Precision Antimicrobial Targeting.","authors":"Zulfa Nooreen, Neha Verma, Shailendra Singh Narwariya, Manish R Bhise, Ankita Wal, Rakesh Verma, Abida Khan, Sangappa Teli","doi":"10.2174/0115680266395401251105000157","DOIUrl":"https://doi.org/10.2174/0115680266395401251105000157","url":null,"abstract":"<p><strong>Introduction: </strong>Antibiotics have made major contributions to medicine, but misuse has resulted in antimicrobial resistance (AMR), which is caused by organisms such as ESKAPE and poses a danger to world health, which can potentially claim many more lives by 2050. Traditional antibiotics do not eliminate these resistant microbes, necessitating the development of new treatments. CRISPR-Cas systems, which target specific bacterial genes, present a viable strategy for combating AMR. CRISPR-Cas technologies provide a viable option for precision antimicrobial targeting by selectively inactivating resistance genes and virulence factors.</p><p><strong>Method: </strong>The relevant data were obtained by reading several sources, including review papers from various publications from 2015 to 2024, to ensure that the study is inclusive, current, and relevant to new developments and trends in deep learning applications for the CRISPR-Cas system that included keywords like antimicrobial resistance, CRISPR-Cas system, and ESKAPE. Additionally, information was gathered from online sources.</p><p><strong>Result: </strong>This system has demonstrated encouraging promise in targeting antimicrobial-resistant (AMR) bacteria and viruses, especially when combined with other delivery systems as conjugative plasmids, bacteriophages, and nanoparticles. Its capacity to specifically break foreign DNA has been shown in studies to either kill bacteria or suppress the production of harmful genes. CRISPRCas technologies have been effectively used to fight AMR pathogens. Furthermore, it has been demonstrated that CRISPR efficiently targets viral genomes, such as those of SARS-CoV-2 and Hepatitis B, offering great therapeutic promise in the treatment of viral-borne diseases.</p><p><strong>Discussion: </strong>CRISPR-Cas technology inhibits certain resistance and virulence genes, providing a precise, tailored approach to address antibiotic resistance. Compared to conventional antibiotics, it efficiently eradicates infections while preserving good bacteria. Its ability to combat a variety of drug-resistant bacteria and viruses has increased because of recent developments in delivery systems, including conjugative plasmids, bacteriophages, and nanoparticles. This precise method might lessen dependency on traditional medicines and transform infection control.</p><p><strong>Conclusion: </strong>It is a novel yet precise tool for genome editing, that provides an innovative method to combat antimicrobial resistance by efficiently aiding in antibacterial targeting. It selectively eliminates dangerous pathogens while maintaining beneficial microbiota by enabling precise gene editing. By effectively treating resistant infections and promoting individualized care, this precision holds the potential to transform antimicrobial treatments.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomarkers and Potential Therapeutic Agents for Chronic Kidney Disease in the Context of Aging: An Integrated Bioinformatics and Machine Learning Study.","authors":"Xu Li, Hua Jin, Lan Hu, Qin Hu","doi":"10.2174/0115680266468115260513114043","DOIUrl":"https://doi.org/10.2174/0115680266468115260513114043","url":null,"abstract":"<p><strong>Introduction: </strong>Aging is a key factor accelerating the progression of chronic kidney disease (CKD). This study aims to identify core therapeutic targets for aging-related CKD and predict potential therapeutic agents.</p><p><strong>Methods: </strong>CKD expression profile was constructed by combining the GSE37171 and GSE62792 datasets. Differentially expressed genes (DEGs) were identified through differential expression analysis, followed by the intersection of these DEGs with key module genes from weighted gene co-expression network analysis and aging-related genes to pinpoint aging-related DEGs (ARDEGs). Machine learning algorithms were employed to identify hub genes, while ROC curves and nomogram models were used to evaluate the diagnostic performance of these genes. Gene set enrichment analysis (GSEA) was conducted to explore the molecular mechanisms underlying the hub genes. Finally, the DGIdb database was utilized to predict potential agents.</p><p><strong>Results: </strong>Three hub genes-AGER, PDGFRB, and SOD2-were selected through machine learning. GSEA revealed its involvement in the CKD process. ROC analysis demonstrated the potential diagnostic value, while the nomogram model exhibited strong predictive performance. Seven potential therapeutic agents were predicted through drug-target interaction analysis.</p><p><strong>Discussions: </strong>AGER, PDGFRB, and SOD2 were identified as potential key targets linking aging to CKD, specifically through their roles in CKD-related fibrosis and oxidative stress. The predicted drugs targeting these mechanisms show promise for therapeutic intervention. However, experimental validation is required to confirm the therapeutic potential of these findings.</p><p><strong>Conclusion: </strong>This study identifies key targets for CKD in the context of aging and predicts agents with potential therapeutic value, providing insights for treatment development.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148142983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Biological Effects of Biochanin A on Glioblastoma T98G Cells and Evaluation of Endoplasmic Reticulum Stress Genes.","authors":"Ezel Demir, Elif Merve Avcu, Beril Erdem, Emel Saglar Ozer","doi":"10.2174/0115680266454835260327210120","DOIUrl":"https://doi.org/10.2174/0115680266454835260327210120","url":null,"abstract":"<p><strong>Introduction: </strong>Glioblastoma multiforme is one of the common central nervous system tumors characterized by a low survival rate and a high risk of recurrence. This study aimed to investigate the cell viability and ER stress in the T98G glioma cell line after the application of Biochanin A, an isoflavone.</p><p><strong>Methods: </strong>A non-toxic dose was determined for T98G cells after Biochanin A application. Then, using a non-toxic concentration of Biochanin A, a flow cytometry experiment was performed for apoptotic cell ratios, quantitative Real-time PCR was performed to verify the expression levels of GRP78, ATF4, EIF2S1, and XBP1 genes that are associated with ER stress, a wound healing assay was performed to show cellular migration, and intracellular Ca2+ levels were determined.</p><p><strong>Results: </strong>The ratio of early and late apoptosis was low for the control group compared to Biochanin A-treated cells. Although it was not statistically significant, a trend towards increased apoptosis was observed after Biochanin A application. Biochanin A-treated T98G cells showed reduced migration compared to control cells. Among the studied genes, ATF4 was statistically upregulated (p=0.0002) while no changes in intracellular Ca2+ level were observed.</p><p><strong>Discussion: </strong>In this study, the effects of Biochanin A application on glioblastoma cells were evaluated from the perspective of cell viability and ER stress. We concluded that Biochanin A application upregulates the ATF4 gene expression, which has important roles during tumor progression and affects the migration of T98G glioblastoma cells.</p><p><strong>Conclusion: </strong>The results of the study will contribute to the development of new treatment strategies supported by isoflavones such as Biochanin A.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pomegranate Peel Extract-loaded Chitosan Nanoparticles Exhibit Anticancer and Hepatorenal Activities Against Solid Ehrlich Carcinoma.","authors":"Walaa Adel, Ahmed Abdel Aziz Baiomy, Ayman Saber Mohamed, Hebatallah Hassan","doi":"10.2174/0115680266454698260330174944","DOIUrl":"https://doi.org/10.2174/0115680266454698260330174944","url":null,"abstract":"<p><strong>Introduction: </strong>Conventional cancer treatments have several limitations, including toxicity and reduced selectivity, which have prompted the exploration of novel therapeutic strategies. Pomegranate peel extract (PPE) demonstrates significant anticancer, antioxidative, and antiinflammatory properties. This study was conducted with the purpose of improving the anticancer specificity of PPE using chitosan nanoparticles as drug delivery against subcutaneous Ehrlich Carcinoma (SEC) in a mouse model.</p><p><strong>Methods: </strong>Mice were inoculated subcutaneously in the dorsal flank with Ehrlich ascites carcinoma (EAC) cells, at a concentration of 2.5 × 10⁶ cells per mouse on the 0th day. The experiment involved five groups: control, SEC, SEC+ PPE (200 mg/kg, orally), SEC+ chitosan NPs (60 mg/kg, orally), and SEC+ PPE nanoparticles (PPENPs) (60 mg/kg, orally). Each group received the corresponding treatment for 3 weeks.</p><p><strong>Results: </strong>Oral administration of PPENPs exerted a significant antitumor effect via reducing tumor size and arginase activity within the tumor microenvironment while enhancing oxidative stress and inducing collagen accumulation in tumor tissue. Moreover, the PPENPs-treated group showed a significant increase in caspase-3 expression and a decrease in TNF-α levels, indicating activated apoptosis and reduced inflammation. On the other hand, PPENPs preserved hepatorenal function markers near normal levels and attenuated oxidative stress in liver and kidney tissues.</p><p><strong>Discussion: </strong>PPENPs effectively suppressed tumor proliferation by inducing ROS-mediated apoptotic cell death, increasing apoptotic markers, and modulating inflammatory responses. Additionally, PPENPs reduced systemic oxidative stress and protected vital organs from tumor-induced damage, demonstrating a systemic protective profile alongside their anticancer effects.</p><p><strong>Conclusion: </strong>Thus, PPENPs exhibit dual roles as promising anticancer and hepatorenal protective agents against subcutaneous Ehrlich carcinoma.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Target Perturbation of Genetically Proxied Antidiabetic Drug Targets and Pneumonia Risk: A Mendelian Randomization Analysis.","authors":"Siyi Lin, Hongxia Xu, Jingyan Xia, Feng Xu","doi":"10.2174/0115680266449667260407052340","DOIUrl":"https://doi.org/10.2174/0115680266449667260407052340","url":null,"abstract":"<p><strong>Introduction: </strong>Type 2 Diabetes Mellitus (T2DM) and various antidiabetic medications have been linked to the incidence and mortality of pneumonia, yet the causality remains unclear. This Mendelian Randomization (MR) study aimed to evaluate the potential causal relationships between them.</p><p><strong>Methods: </strong>We conducted two-sample MR analyses utilizing genetic instruments associated with T2DM and 6 antidiabetic drug targets (PPARG, GIPR, GLP1R, INSR, ABCC8, and KCNJ11), focusing on 9 pneumonia subtypes. Pneumonia patients for discovery and validation cohorts were sourced from FinnGen, GWAS Catalog, and other large consortia. Meta-analysis was performed to integrate the results of two cohorts. Additionally, Summary-data-based Mendelian Randomization (SMR) was performed as an exploratory analysis to explore potential gene-expression-mediated signals. Statistical power was calculated using mRnd to assess the robustness of MR estimates.</p><p><strong>Results: </strong>MR analyses identified strong connections between ABCC8/KCNJ11 and cytomegaloviral pneumonitis (OR = 5.000 × 10-4, 95% CI: 6.046 × 10-6-0.043, P = 0.0008) and between GIPR and pneumonia (OR = 1.088, 95% CI: 1.022-1.159, P = 0.008). Nominal associations of PPARG, ABCC8/KCNJ11, GLP1R, and INSR with pneumonia, bacterial pneumonia, and pneumococcal pneumonia were detected, which should be interpreted cautiously given limited power. Exploratory SMR analysis linked ABCC8 (OR = 0.977, 95% CI: 0.955-0.999, P = 0.042) and GIPR (OR = 0.662, 95% CI: 0.469-0.935, P = 0.020) to pneumonia risk. No statistically significant bias due to pleiotropy or genetic confounding was found by sensitivity analyses.</p><p><strong>Discussion: </strong>The study systematically explored the causality between T2DM, 6 antidiabetic drug targets, and pneumonia risks.</p><p><strong>Conclusion: </strong>Certain genetically proxied antidiabetic drug targets are associated with pneumonia risk, providing hypothesis-generating insights for future mechanistic research and clinical evaluation. However, caution is warranted in interpreting rare pneumonia subtypes with limited case numbers. Future studies with larger sample sizes and diverse populations are needed for validation.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148143026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mendelian Randomization Analysis of the Relationship between Neurotransmitter-related Genes and Cancer: Insights from Multi-omics Data.","authors":"Quan Yuan, Yuli Xi, Hao Yu, Rongjie Ye, Neng Wang, Ge Yu, Ming Niu","doi":"10.2174/0115680266436608260406113212","DOIUrl":"https://doi.org/10.2174/0115680266436608260406113212","url":null,"abstract":"<p><strong>Introduction: </strong>Epidemiological studies indicate a potential link between mental disorders and cancer; however, the role of neurotransmitter-related genes (NRGs) in carcinogenesis remains unclear. In this study, we employed Mendelian randomization utilizing multi-omics data to investigate the causal effects and mechanisms of NRGs in cancer.</p><p><strong>Methods: </strong>We assessed the causal relationships between ten mental disorders and fourteen cancer types. NRGs were sourced from GeneCards, and transcriptome data for breast cancer (BC) were obtained from the Gene Expression Omnibus (GEO). Summary-data-based Mendelian Randomization (SMR) integrated genome-wide association study (GWAS) data with expression quantitative trait loci (eQTLs), DNA methylation QTLs (mQTLs), intestinal eQTLs, and fecal microbiota QTLs (mbQTLs). Colocalization analyses were conducted to explore the relationships between host genes and gut microbiota, with sensitivity assessments performed using two additional Mendelian randomization methods.</p><p><strong>Results: </strong>Mendelian randomization confirmed a causal association between mental disorders and BC. A meta-analysis of five BC datasets identified 821 differentially expressed genes (DEGs) among 829 non-redundant genes. SMR highlighted KRTCAP2 as a potential causal gene in blood, and cg24674445 as a significant methylation site. The expression of KRTCAP2 was found to be inversely correlated with BC, while methylation at cg24674445 downregulated KRTCAP2, suggesting that cg24674445 may promote BC progression.</p><p><strong>Discussion: </strong>This study advances beyond established epidemiological correlations by providing genetically validated evidence for a causal link between mental disorders and breast cancer. Its primary significance lies in delineating a plausible biological pathway-epigenetic regulation of neurotransmitter-related genes-that may mechanistically elucidate this connection. By integrating multi-omics data, we transition from mere association to a testable model of disease etiology, where genetic predispositions to mental illness and cancer converge upon shared regulatory mechanisms within the genome.</p><p><strong>Conclusion: </strong>Multi-omics Mendelian randomization demonstrates that DNA methylation modulates the association between neurotransmitter-related genes and breast cancer.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147981025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>In Silico</i> ADMET Profiling: Evolution from Traditional Models to Deep Learning Techniques.","authors":"Akhalesh Kumar, Mukul Yadav, Pushkar Kumar Ray, Rakhi Mishra, Amit Upadhyay, Shivendra Mani Tripathi, Sudhanshu Mishra","doi":"10.2174/0115680266439252260329214559","DOIUrl":"https://doi.org/10.2174/0115680266439252260329214559","url":null,"abstract":"<p><p>A key element in the early stages of drug discovery and development is the accurate prediction of Absorption, Distribution, Metabolism, Excretion, and Toxicity properties. Traditional experimental methods for ADMET profiling are costly, time-consuming, and often limited in scalability, leading to high rates of clinical trial failures due to poor toxicological or pharmacokinetic profiles. Machine learning (ML) has emerged as a powerful tool for modeling complex nonlinear relationships between molecular structure and ADMET behavior, due to the increasing availability of chemical and biological data. Looking ahead, integrating explainable AI, transfer learning, and active learning methods offers the potential to address data scarcity and improve model interpretability and regulatory acceptance. As the field progresses, machine learning-based ADMET prediction is expected to become increasingly reliable, helping to streamline drug development pipelines and facilitate the creation of safer, more effective therapies. The purpose of this study is to examine and assess the state-of-the-art machine learning methods for ADMET prediction. Machine learning algorithms, such as support vector machines, gradient boosting algorithms, random forests, graph neural networks, and other software used to forecast all properties, will be examined. To create trustworthy predictive models, we stress the significance of molecular representations, dataset quality, and model evaluation techniques. Recent developments in multi-task learning and data-driven feature building, which improve prediction accuracy across several ADMET endpoints, are given particular emphasis. The web-based tools that we offer in this chapter, together with the hyperlinks that go with them, make it easier to perform In-silico ADMET research on a variety of drug candidates.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic and Computational Insights into SERPINA1 rs17580 as a Susceptibility Biomarker for COPD Progression.","authors":"Muhammad Faizan Qadir, Adil Jamal, Farhan Ikhtiar, Imran Zafar, Syed M Safeer Mehdi Bokhari","doi":"10.2174/0115680266425323260319033402","DOIUrl":"https://doi.org/10.2174/0115680266425323260319033402","url":null,"abstract":"<p><strong>Introduction: </strong>Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disorder influenced by both environmental and genetic factors. Variations in the SERPINA1 gene, particularly rs17580 (Glu288Val), may alter α₁-antitrypsin function and increase susceptibility to COPD. This study aimed to investigate the association of the SERPINA1 rs17580 variant with COPD progression using genetic and computational analyses.</p><p><strong>Methodology: </strong>A total of 300 participants, including 250 clinically diagnosed COPD patients and 50 healthy controls, were recruited for this study. Genomic DNA was extracted from peripheral blood samples, and the SERPINA1 rs17580 (Glu288Val) polymorphism was genotyped using Tetra ARMS-PCR and confirmed by Sanger sequencing. In-silico analyses included protein stability prediction, miRNA binding site assessment, and protein-protein interaction analysis using STRING. Additionally, CRISPR/Cas9 gRNAs targeting SERPINA1 were computationally designed and evaluated for potency and off-target effects to facilitate potential functional validation.</p><p><strong>Results: </strong>In a cohort of 300 participants (250 COPD, 50 controls), COPD patients exhibited reduced lung function (FEV₁/FVC), lower serum A1AT (1.18 vs 1.41 g/L), higher smoking exposure, comorbidities, exacerbations, and reduced physical activity. The SERPINA1 rs17580 (Glu288Val) variant, low-frequency and deleterious (SIFT 0.01, PolyPhen-2 0.998), was confirmed by sequencing. Structural analysis showed increased flexibility, destabilization (ΔΔG -1.24 to -1.78 kcal/mol), and altered dynamics, while functional assessment indicated Glu288 is highly conserved and pathogenic (87% probability). Population analysis revealed MM 60%, SS 10.7%, and ZZ 2%, with allele frequencies differing globally. The mutation affected protein-protein interactions and pathways related to protease-antiprotease balance, inflammation, emphysema, and liver disease. It also altered miRNA binding and mRNA stability (ΔG +6.8 kcal/mol), potentially modulating SERPINA1 expression. A top-ranked CRISPR gRNA showed 100% specificity and minimal offtargets, supporting the feasibility of functional studies.</p><p><strong>Discussion: </strong>The findings highlight the SERPINA1 rs17580 (Glu288Val) variant as a key genetic determinant influencing COPD susceptibility through structural destabilization and dysregulation of α₁-antitrypsin function. This genetic insight advances the understanding of COPD pathogenesis and underscores the potential for personalized interventions, including early genetic screening and targeted therapeutic strategies, to reduce disease progression and improve patient outcomes.</p><p><strong>Conclusion: </strong>These findings highlight rs17580 as a potential genetic biomarker for COPD susceptibility and provide insights for targeted therapeutic strategies.</p>","PeriodicalId":11076,"journal":{"name":"Current topics in medicinal chemistry","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147980962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}