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• Evaluating AI-Generated Molecules for Drug Discovery: From Generic Metrics to Translational Readiness.
  Artificial intelligence-driven molecular generation has become an increasingly used computational approach for proposing candidate chemical structures in early-stage drug discovery, yet the practical value of the molecules produced is often difficult to judge.…
  europepmc 2026 置信度 0.80
• Artificial Intelligence in skin disease therapeutics: from drug discovery to personalized treatment pathways.
  Artificial intelligence (AI) comprises computational methods capable of performing tasks associated with human cognition, and includes specialized subfields such as machine learning, deep learning, convolutional neural networks for image analysis, and large la…
  europepmc 2026 置信度 0.80
• Bridging the green skills gap: a framework to align the pharmaceutical workforce with sustainable drug discovery.
  Background The pharmaceutical industry's R&D model faces unsustainable costs and environmental impact, yet educational pipelines lag in integrating AI and green chemistry skills essential for modern drug discovery. Methods We conducted cheminformatics analysis…
  europepmc 2026 置信度 0.80
• Diversity Beats Size Scaling for Chemical Language Models.
  Chemical language models, such as transformers trained on SMILES strings, are increasingly used in drug design and have seen rapid growth in both model capacity and training dataset size. The impact of this scaling on practical downstream performance remains u…
  europepmc 2026 置信度 0.80
• Artificial Intelligence in drug discovery and development: current landscape, challenges, and future perspectives.
  Artificial intelligence (AI) is transforming drug discovery and development, fields historically constrained by long timelines, high costs, and substantial attrition. Recent advances, particularly in generative modeling, enable an accelerated and increasingly …
  europepmc 2026 置信度 0.80
• AI in Drug Discovery: Clinical Failures, Regulatory Reality, and the Validation Crisis Behind the Hype.
  The integration of artificial intelligence (AI) into the life sciences has accelerated significantly between 2022 and 2026, accompanied by global investment exceeding USD 100 billion and widespread expectations of a transformative impact in drug discovery. Des…
  europepmc 2026 置信度 0.80
• Agentic and Generative AI for Drug Discovery.
  europepmc 2026 置信度 0.80
• The Potential of AI-Driven High-Content Imaging in Drug Discovery.
  We have authored a compelling and timely review that highlights the transformative potential of high-content imaging for discovering small molecules (SMs). SMs are crucial for advancing drug potency, selectivity, and precision, and their assessment through spe…
  europepmc 2026 置信度 0.80
• A lightweight, integrated generative AI assistant for accelerated early-stage drug discovery on constrained-resource hardware.
  Discovery of novel therapeutic small molecules remains one of the most challenging tasks in pharmaceutical research, as it is described by high attrition rates, well over $2 billion per candidate, and timelines often surpassing a decade. Generative AI has tran…
  europepmc 2026 置信度 0.80
• AI-Driven Design Platforms of Next-Generation Antibody Therapeutics.
  Artificial intelligence (AI) is reshaping drug discovery by bridging the gap between traditional computer-aided drug design (CADD) and next-generation, data-driven methodologies. Unlike conventional CADD, which relies on physical modelling of molecular interac…
  europepmc 2026 置信度 0.80
• Artificial intelligence in drug discovery: from algorithmic foundations to clinical translation.
  Artificial intelligence is quietly reconfiguring the landscape of drug discovery. It sharpens the search for new targets, refines lead compounds, and helps tailor clinical trial designs. Behind these advances sits a family of methods-convolutional, recurrent, …
  europepmc 2026 置信度 0.80
• From Molecules to Manufacturing: Expanding Role of Artificial Intelligence in Pharmaceutical Sciences.
  Artificial Intelligence (AI) addresses many complex problems by rapidly imitating human cognitive abilities. In the pharmaceutical industry, AI is transforming the processes of discovery, formulation, nanomedicine development, and manufacturing. These applicat…
  europepmc 2026 置信度 0.80
• AI-driven discovery of multifunctional peptides: From sequence space to therapeutics.
  Multifunctional peptides (MFPs), defined as single peptide sequences endowed with two or more biological activities, have emerged as a highly promising class of therapeutic candidates for the intervention of complex and multifactorial diseases. Nevertheless, t…
  europepmc 2026 置信度 0.80
• AI-driven discovery and validation of a GIPC1 PDZ domain inhibitor for pancreatic ductal adenocarcinoma.
  Pancreatic ductal adenocarcinoma (PDAC) remains highly aggressive, with a five-year survival rate under 13.3%, due to late diagnosis, rapid progression, and therapeutic resistance, highlighting the need for advanced treatments. GAIP-interacting protein C termi…
  europepmc 2026 置信度 0.80
• Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.
  The integration of multiomics technologies with artificial intelligence (AI) has become a transformative force in modern precision medicine, particularly within drug discovery. Multiomics approaches, including genome-wide association studies, transcriptomic pr…
  europepmc 2026 置信度 0.80
• AI-assisted fragment-based drug discovery of SARS-CoV-2 macrodomain binders validated by NMR and X-ray crystallography.
  Fragment-based drug discovery (FBDD) is an effective approach for exploring chemical space using small, low-affinity fragments as starting points to facilitate development of lead compounds. Strategies to improve fragment potency include fragment merging and l…
  europepmc 2026 置信度 0.80
• Generative AI for controllable protein sequence design: A survey.
  The design of novel protein sequences with targeted functionalities underpins a central theme in protein engineering, impacting diverse fields such as drug discovery and enzymatic engineering. However, navigating this vast combinatorial search space remains a …
  europepmc 2026 置信度 0.80
• A brave new world: the rise of agentic AI in rapid cycle RWE analytics.
  Introduction Real-world evidence (RWE) has become a critical asset across drug discovery and market access, with regulators accepting evidence from real-world data (RWD) to supplement negotiations. With increasing demand for rapid RWE generation across the pro…
  europepmc 2026 置信度 0.80
• Advancing Drug Discovery with AI: Machine and Deep Learning Strategies for Target Identification and Precision Nanomedicine.
  The integration of machine learning (ML) and deep learning (DL) into drug discovery and target identification has catalyzed a paradigm shift in pharmaceutical research, enhancing efficiency and translational potential for nano-enabled therapeutics. ML models h…
  europepmc 2026 置信度 0.80
• Research progress of artificial intelligence in high-throughput drug screening.
  High-throughput screening (HTS) is widely used in modern drug discovery. It enables batch activity testing of compounds and provides important support for the identification of active compounds. However, its screening efficiency and accuracy need to be improve…
  europepmc 2026 置信度 0.80
• Perception of artificial intelligence and machine learning applications in the Nigerian healthcare sector: A cross-sectional study.
  Artificial intelligence (AI) has significant benefits across various facets of healthcare delivery, notably in personalised pharmacotherapy and the development of targeted health interventions for specific demographic groups. This study aimed to comprehensivel…
  europepmc 2026 置信度 0.80
• Next-Generation Artificial Intelligence Strategies for Mechanistic Cancer Target Discovery and Drug Development: A State-of-the-Art Review.
  Artificial intelligence (AI) is increasingly used in cancer research, enabling integrative analysis of complex biomedical data to identify actionable therapeutic vulnerabilities. This review specifically examines how AI advances mechanistic cancer target disco…
  europepmc 2026 置信度 0.80
• Balancing optimism versus potential risks of AI-driven drug discovery.
  1. There is much optimism, to understate the $3.8B investment in 2025 by venture capital [1], regarding the “revolution” in AI-driven drug discovery. A 2025 report from the McKinsey Global Institut...
  europepmc 2026 置信度 0.80
• AI-Powered Traditional Medicine Discovery: A Structured Narrative Review of "AI"-Titled Studies.
  Introduction Artificial intelligence is increasingly applied in Traditional Medicine research, yet whether studies explicitly self-labelled as "AI-based" substantively advance drug-discovery remains unclear. This review characterises how studies with "AI" in t…
  europepmc 2026 置信度 0.80
• AI is Excellent at the Discovery and Identification of Unrecognized Scientific Knowledge but There Is No Evidence That AI Can Create New Scientific Knowledge.
  europepmc 2026 置信度 0.80
• Drug Discovery in the Era of Artificial Intelligence: From Target Identification to Clinical Trials
  Drug discovery remains costly and time-consuming, requiring substantial effort across target identification, lead optimization, and clinical validation. The rapid growth of artificial intelligence (AI) and machine learning (ML), particularly deep learning (DL)…
  europepmc 2026 置信度 0.80
• AI-driven drug reposition for pathogens: a new paradigm in pandemic preparedness.
  Faced with a severe outbreak of diseases caused by newly emerging and recurrent pathogens, the development cycle of traditional drugs is long, making it difficult to meet emergency needs. Drug repositioning has become a key strategy for rapidly providing thera…
  europepmc 2026 置信度 0.80
• Training the next-generation of biomedical scientists through artificial intelligence-driven education and research in pharmacology and pharmaceutical sciences.
  Artificial intelligence (AI)-driven graduate education and research in pharmacology and pharmaceutical sciences (AIPPS) aims to address the rapidly-growing role of AI and machine learning (ML) applications in biomedical sciences. This review provides perspecti…
  europepmc 2026 置信度 0.80
• The Emerging Role of Artificial Intelligence in Drug Discovery and Development: Implications for Cardiovascular Pharmacology.
  Abstract Cardiovascular diseases remain the leading cause of global morbidity and mortality, highlighting the urgent need for more efficient, precise, and cost-effective drug development strategies. Traditional drug discovery pipelines face persistent challeng…
  europepmc 2026 置信度 0.80
• Artificial intelligence (AI) as a catalyst for mechanistic target discovery: Integrating systems pharmacology and multimodal data.
  Artificial intelligence (AI) is evolving from a predictive tool into a foundational computational infrastructure for mechanism-driven pharmacology, fundamentally reshaping drug discovery. This review examines how this transformation addresses persistent challe…
  europepmc 2026 置信度 0.80
• GEM-GPT Enables Personalized Cell Type-Resolved Therapeutic Design for Systems Pharmacology
  Generative artificial intelligence (AI) has emerged as a powerful framework for drug discovery, yet most current approaches follow one-drug-one-gene target-based paradigms that struggle to capture the complexity and heterogeneity of chronic and systemic diseas…
  europepmc 2026 置信度 0.80
• AI & ML Utilisation in the Discovery of Antimicrobial Drug Design, Application, Current Trends, and Future Perspective: An Extensive Review.
  The application of Artificial Intelligence (AI) and other technologies in drug discovery has received substantial attention, as they streamline the process and overcome challenges that traditionally make it time-consuming and resource-intensive. Research in an…
  europepmc 2026 置信度 0.80
• Integrating experimental biology, computational methods, and artificial intelligence in anticancer drug discovery: Bridging the translational gap.
  Cancer remains a leading cause of mortality globally, with the incidence projected to reach 28.4 million new cases annually by 2040. Traditional drug discovery is notoriously inefficient: 10-17 years and up to $2.8 billion per approved drug, with fewer than 10…
  europepmc 2026 置信度 0.80
• Recent Advances in Computer-Aided Drug Design and Drug Discovery.
  The field of Computer-Aided Drug Design (CADD) has undergone remarkable transformations, evolving from a niche discipline into a cornerstone of modern pharmaceutical research [...].
  europepmc 2026 置信度 0.80
• The role of AI-assisted drug repurposing in neurological disorders: a systematic review of validation strategies, challenges and opportunities.
  Neurological disorders refer to a diverse group of conditions that affect the brain, peripheral nerves, and spinal cord and impair socioemotional, cognitive, motor, and sensory functions. Alzheimer's disease (AD), Multiple Sclerosis (MS), Parkinson's disease (…
  europepmc 2026 置信度 0.80
• AI-Driven discovery and experimental validation of covalent FGFR4 inhibitors for hepatocellular carcinoma.
  Background FGFR4 signaling is an essential driver in hepatocellular carcinoma. However, traditional screening is often time-consuming, highlighting a need for efficient strategies to identify covalent chemotypes and accelerate FGFR4 drug discovery. Methods We …
  europepmc 2026 置信度 0.80
• Artificial Intelligence Applications in Antimicrobial Resistance: Comprehensive Review of Predictive Models, Diagnostic Innovations, and Clinical Integration.
  Antimicrobial resistance (AMR) represents a critical global health crisis, driving increased mortality, treatment failure, and economic burden. Artificial intelligence (AI) offers transformative potential to counter this threat by enhancing detection, diagnost…
  europepmc 2026 置信度 0.80
• Lessons From Drug Discovery for Cryoprotective Agent Design: An AI-Oriented Perspective.
  Cryopreservation is the storage of biological materials like cells, tissues, or even organs at cryogenic temperatures. This technology is a key enabler for biobanking, reproductive medicine, and cell therapy, and is positioned as a vital part of the future of …
  europepmc 2026 置信度 0.80
• Conditional superiorities and unaddressed bottlenecks: a critical review of artificial intelligence for waterborne microbial detection.
  Although conventional microbial detection approaches for water samples are widely applied, they still suffer from prolonged assay durations (24-72 h), low sensitivity, and the absence of real-time monitoring capacity. Artificial intelligence (AI) has demonstra…
  europepmc 2026 置信度 0.80
• Transforming mRNA drug design with AI: From UTR and codon optimization to coordinated design.
  Background The design of mRNA drugs involves a complex and high-dimensional optimization of sequence elements to balance stability, translation efficiency, and immunogenicity. Traditional methods, often relying on local rules or limited biological templates, s…
  europepmc 2026 置信度 0.80
• AI-Driven Synthesis in Medicinal Chemistry: Integrating Large Language Models, Robotic Automation, and Sustainability Metrics to Accelerate Drug Discovery.
  Artificial intelligence (AI) is transforming synthetic chemistry from task-specific predictors into integrated platforms that unify retrosynthesis, reaction optimization, and closed-loop robotic automation. This review highlights how AI-assisted planning and r…
  europepmc 2026 置信度 0.80
• Discovery of TYR inhibitors from de novo molecular generation to dual-track lead optimization: "Competition" between AI and chemists.
  This study introduces a unified framework combining artificial intelligence (AI)-directed de novo molecular generation with dual-track lead optimization-comprising expert-guided strategies and AI-driven pathways-to discover tyrosinase (TYR) inhibitors for hype…
  europepmc 2026 置信度 0.80
• Rapid and energy-efficient ultra-large library screening for drug discovery on a SpiNNaker2 neuromorphic chip.
  The virtual screening of make-on-demand small molecule libraries can prioritize drug candidates for rapid experimental validation to accelerate pre-clinical drug discovery. As ultra-large libraries grow to billions of compounds, exhaustive screening incurs pro…
  europepmc 2026 置信度 0.80
• Artificial intelligence-driven drug discovery: a new era in therapeutic innovation.
  Artificial intelligence (AI) is a computer system that performs tasks that require learning, problem-solving and decision-making skills. It mimics humans' cognitive functions, which include pattern recognition. Vast amounts of data serve as "experience" for AI…
  europepmc 2026 置信度 0.80
• [Artificial intelligence-based mining of antimicrobial peptides in the microbiome].
  Antimicrobial peptides (AMPs) are small-molecule polypeptides with broad-spectrum antimicrobial activity that are induced by the innate immune system of organisms and constitute a crucial component of the innate immune defense. With the misuse of antibiotics a…
  pubmed Guo X, Mo N, Fu T, Lai Y 等 2026 置信度 0.82
• Cyclic Peptides as Modulators of Protein-Protein Interactions: A Survival Guide from Discovery Platforms to AI-Driven Design.
  Protein-protein interactions (PPIs) represent a vast and largely underexplored landscape of therapeutic targets, yet their structural features-including large, flat, and dynamic interfaces-have historically limited their druggability. In this context, cyclic p…
  europepmc 2026 置信度 0.80
• AI-Driven Discovery of a Hydrophobic-Tag Degrader Targeting NSD3 for Lung Squamous Carcinoma Therapy.
  Nuclear receptor-binding SET domain protein 3 (NSD3) is a histone H3K36 methyltransferase implicated in lung squamous cell carcinoma, yet chemical targeting is challenging due to the shallow PWWP reader pocket. Here, we report XSY12, a hydrophobic-tag degrader…
  europepmc 2026 置信度 0.80
• F.A.D.E. (Fully Agentic Drug Engine): A Conversational AI Platform for Drug Discovery
  Drug discovery remains one of the costliest and most time-intensive endeavors in the pharmaceutical pipeline, with average development costs exceeding $2.3 billion per drug, timelines spanning more than a decade, and attrition rates above 90% in clinical trial…
  europepmc 2026 置信度 0.80
• From DNA to drug discovery AI models for cardiovascular precision medicine.
  Cardiovascular diseases remain the world's leading cause of death-yet the molecular mechanisms linking genetic variation to clinical outcomes are still poorly mapped. Recent advances in artificial intelligence (AI), especially foundation models trained on geno…
  europepmc 2026 置信度 0.80
• Improving hit discovery by integrating activity cliff sensitivity into active learning.
  Motivation Active learning has emerged as an effective strategy for accelerating molecular discovery under limited labeling budgets. However, existing methods primarily focus on global information, often overlooking activity cliff-sharp changes in bioactivity …
  europepmc 2026 置信度 0.80
• Using generative AI to transform peptide hits into small molecule leads.
  There is a wealth of structural data on peptides that bind potential drug targets, serving as rich inspiration for designing small molecule inhibitors which can recapitulate key binding interactions while improving pharmacokinetic properties. With the rapid ad…
  europepmc 2026 置信度 0.80
• Computational strategies for allosteric drug discovery: from cryptic pocket detection to rational design.
  Allostery offers a powerful route to regulate protein function and expands drug discovery beyond the orthosteric paradigm. By acting at sites distinct from the active site, allosteric modulators can achieve greater selectivity, reduce off-target effects, and o…
  europepmc 2026 置信度 0.80
• Data-quality-guided AI strategies for natural product drug discovery.
  The component specification problem-the mismatch between bioactivity observed in chemically unresolved extracts and the constituent-level chemical definition required for reliable artificial intelligence (AI) inference-remains a key bottleneck in computational…
  europepmc 2026 置信度 0.80
• Generative AI–Driven Design and Experimental Validation of EGFPAN_EMBS, a Novel EGFR Inhibitor in Pancreatic Cancer
  Abstract Pancreatic cancer remains a highly lethal malignancy with limited targeted therapeutic options, necessitating innovative drug discovery strategies. The epidermal growth factor receptor (EGFR) is a key driver of tumor progression and a validated therap…
  europepmc 2026 置信度 0.80
• Using Computational Intelligence to Connect Data and Drug Design in Medicinal Chemistry: A Review.
  The landscape of drug discovery is being rapidly transformed by the integration of computational intelligence (CI) techniques with big data resources in medicinal chemistry. Traditional drug development methods are often time-consuming, costly, and prone to hi…
  europepmc 2026 置信度 0.80
• Structural characteristics and evolutionary trajectories of knowledge recombination in the field of AI-driven drug discovery.
  The rapid evolution of artificial intelligence (AI) and its profound integration with the pharmaceutical industry essentially constitute a process of knowledge recombination. Yet, empirical evidence systematically characterizing the structural and evolutionary…
  europepmc 2026 置信度 0.80
• A review on artificial intelligence in pharmaceutical sciences: opportunities and challenges.
  Significance The review aims to systematically explore the transformative impact of artificial intelligence (AI) on pharmaceutical sciences. It addresses key research questions regarding how AI accelerates drug development, enhances clinical trial design, opti…
  europepmc 2026 置信度 0.80
• Sovereign AI supercomputers: a global landscape review of unprecedented biomedical research infrastructure.
  Artificial intelligence (AI) has rapidly become the focal point of global governmental attention and investment. Nations are launching AI for science strategies on a scale comparable to historic endeavors such as Apollo and the Manhattan Project. These coordin…
  europepmc 2026 置信度 0.80
• Decoding Herbal Medicine: Machine Learning-Driven Insights into Structural Identification and Pharmacological Research.
  Herbal medicine is indispensable and crucial to many healthcare systems. Its therapeutic value arises from diverse plant-derived compounds with potential pharmacological activities. This review summarizes recent advances in applying artificial intelligence (AI…
  europepmc 2026 置信度 0.80
• Artificial Intelligence-driven Drug Discovery: Transforming Pharmaceutical Innovation Through Computational Approaches.
  The process of identifying and optimizing new drugs has long been recognized as expensive and complex. Many promising compounds have failed during the late stages of development, resulting in lost time and investment. Despite major advances in pharmaceutical s…
  europepmc 2026 置信度 0.80
• The technological blind spot: Why pharma is missing the human element.
  Despite major investments in technology and artificial intelligence (AI), the pharmaceutical industry faces persistent underperformance, with clinical trial dropout rates of 30-70% and sales variability of up to 300%. Behavioral factors are systematically unde…
  europepmc 2026 置信度 0.80
• Artificial intelligence in antimicrobial drug discovery: predictive and generative strategies.
  Introduction The slow pipeline of antimicrobial drug development stands in stark contrast to the continued expansion of microbial infections, which pose a persistent and major threat to global public health. Traditional discovery strategies, including natural …
  europepmc 2026 置信度 0.80
• Recent advances in venom pharmacology reshaping venom-to-drug discovery.
  Animal venoms represent rich sources of pharmacologically active molecules, yet their translation into clinical therapeutics has historically progressed slowly. Recent advances in AI-driven venomics, cryo-electron microscopy, and computational peptide engineer…
  europepmc 2026 置信度 0.80
• Clinical registry metadata as a hidden bottleneck in AI-driven drug discovery: a computational audit of translational phase data in glioma research.
  Clinical translation in glioma and glioblastoma remains inefficient despite advances in computational drug discovery. An underrecognized contributor to this gap is structural degradation of clinical registry metadata. We analyzed the complete set of 2.357 glio…
  europepmc 2026 置信度 0.80
• Efficient and valid large molecule generation via self-supervised generative models.
  The realm of molecular design, particularly for large molecules, presents unique challenges and opportunities in drug discovery and materials science. Large molecule design is inherently more complex and less explored compared to designing small molecules, add…
  europepmc 2026 置信度 0.80
• Artificial Intelligence Across the Drug Development Lifecycle.
  Artificial intelligence (AI) is becoming a central driver of change across the drug development lifecycle. However, its integration is evolving so rapidly that it remains essential to understand how these technologies are currently positioned within the field.…
  europepmc 2026 置信度 0.80
• AI-guided identification of natural CTSL inhibitors with therapeutic potential for renal injury.
  Cathepsin L (CTSL) is a prominent therapeutic target for kidney injury, yet clinically available CTSL inhibitors remain limited. Here, we developed an artificial intelligence (AI)-assisted discovery strategy to identify novel CTSL inhibitors from a natural pro…
  europepmc 2026 置信度 0.80
• Editorial: Dynamics and functional exploration of pharmacologically active proteins.
  Pharmacologically active proteins are proteins in the body that interact with drugs, therapeutic compounds, or biologically active molecules to produce a physiological effect [ 1 ]. They play an important role in modern biomedical research and drug discovery, …
  europepmc 2026 置信度 0.80
• How Advanced Artificial Intelligence Technologies Shape Drug-Drug and Drug-Target Interaction Modeling.
  Drug molecular interactions, including drug-drug interactions (DDIs) and drug-target interactions (DTIs), are critical for drug discovery and clinical safety, increasingly propelled by artificial intelligence (AI) technologies. Although previously treated as s…
  europepmc 2026 置信度 0.80
• Artificial Intelligence in Healthcare Administration and Clinical Informatics: A Critical Review and Governance Roadmap.
  Artificial intelligence (AI) is increasingly influencing healthcare administration and clinical informatics by supporting disease diagnosis, clinical decision-making, treatment personalization, drug discovery, remote monitoring, public health surveillance, and…
  europepmc 2026 置信度 0.80
• Harnessing Machine Learning for Accelerated Drug Discovery: Opportunities and Unmet Challenges.
  The process of drug discovery is one of the most expensive, time-consuming, and high-risk endeavors in modern science. Translating initial scientific insights into safe and effective therapies, supported by genomics, structural biology, and computational chemi…
  europepmc 2026 置信度 0.80
• AI-assisted design of next-generation antibiotics against multidrug-resistant Staphylococcus aureus.
  Multidrug-resistant (MDR) Staphylococcus aureus remains a leading cause of life-threatening infections worldwide and is designated a high-priority pathogen by the WHO. The accumulation of resistance mechanisms, such as β-lactam insensitivity, reduced vancomyci…
  europepmc 2026 置信度 0.80
• The Rise of Generalist Foundation Models and Quantum Computing in Oncology.
  In the field of oncology, Artificial intelligence (AI) and deep learning (DL) are an essential component of decision-support. However, traditional narrow-AI models have significant limitations in clinics with respect to narrow, task-specificity (TS), high data…
  pubmed Kakar M 2026 Jan-Dec 置信度 0.82
• Fructose-1,6-bisphosphatase as a therapeutic target for type 2 diabetes: from molecular mechanisms to clinical translation.
  Type 2 diabetes mellitus (T2DM) affects over 415 million individuals globally, with excessive hepatic glucose production representing a primary contributor to hyperglycaemia. Fructose-1,6-bisphosphatase (FBP1), a rate-limiting gluconeogenic enzyme, has emerged…
  pubmed Joshi P, Mazumder A, Pentela B, Debnath A 2026 Aug 6 置信度 0.82
• Mössbauer spectroscopy in drug discovery: revealing Fe- and Fe-S cluster dependent targets.
  Iron- and iron-sulfur cluster (Fe-S)-containing proteins are essential for diverse biological processes, including electron transfer, genome maintenance, metabolism, cellular signaling, and host-pathogen interactions. Despite their broad biological importance …
  pubmed Chen J, Quist T, Fang R, Nguyen HT 等 2026 Aug 5 置信度 0.82
• Large animal models of right heart failure due to pulmonary hypertension: a bridge to translational success.
  Right heart failure drives morbidity and mortality in pulmonary arterial hypertension (PAH). At present, there are no chronic pharmaceutical interventions that directly augment right heart function in humans despite many promising results in rodent studies. Th…
  pubmed Prins SE, Blake MJ, Helke KL, Di Salvo T 等 2026 Jul 置信度 0.82
• AI-driven Identification of Zika Virus Inhibitors.
  Research engaged with AI has dramatically increased due to a huge improvement of technologies in terms of cost and time-effectiveness as well as decreasing use of animals. High throughput screening (HTS) is a frequently used method in drug discovery. Here, we …
  pubmed Otsuka Y, Shumate J, Rye TF, Goldberg I 等 2026 Aug 5 置信度 0.82
• Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.
  Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads…
  pubmed Rahmaniar W, Sunarwidhi AL, Hernawan A 2026 Aug 3 置信度 0.82
• Design, Synthesis, and Herbicidal Activity of Indole-Containing Fusarium Acid Derivatives Targeting Transketolase.
  Transketolase (TKL; EC 2.2.1.1) has been validated as a potential new herbicide target. To develop a new and highly effective herbicides-targeted TKL, a series of indole-containing fusarium acid (FA) derivatives 9a-9s were designed and synthesized. Among them,…
  pubmed Li C, Liu Y, Ma X, Du Z 等 2026 Aug 5 置信度 0.82
• Recent Advances in Conjugation Chemistry Expanding the Applications of the DNA Tetrahedron.
  The tetrahedral DNA nanostructure (TDN) has emerged as a premier, highly programmable framework for targeted drug delivery and diagnostics. This review provides a definitive, chemistry-first design guide for TDN engineering, systematically structured across th…
  pubmed Rutherford TJ, Wilds CJ 2026 Aug 置信度 0.82
• Peptide Therapeutics for Solid Tumors: Functional Classes, AI-Enhanced Discovery and Clinical Advances.
  Solid tumors, the most prevalent form of malignancy, pose therapeutic challenges distinct from hematologic malignancies due to their complex biology, including high tumor heterogeneity, a dense extracellular matrix (ECM), an immunosuppressive tumor microenviro…
  pubmed Liang J, Tang X, Li H, Fang Y 等 2026 Sep 置信度 0.82
• Artificial Intelligence in Infectious Disease Research.
  Infectious diseases remain a major global health challenge, and while AI is rapidly advancing diagnostic techniques such as Computed Tomography (CT), Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), and ultrasound, its full potential in th…
  pubmed Bharathi K, Yadav J, Shastri S, Deo V 等 2026 Aug 4 置信度 0.82
• Diversity Beats Size Scaling for Chemical Language Models.
  Chemical language models, such as transformers trained on SMILES strings, are increasingly used in drug design and have seen rapid growth in both model capacity and training dataset size. The impact of this scaling on practical downstream performance remains u…
  pubmed Medina B, Tibo A, He J, Janet JP 等 2026 Aug 4 置信度 0.82
• [Creation of Patient Summaries from Electronic Medical Records and Integration of Medical Knowledge via Large Language Models-Next-Generation Medical DX and Drug Discovery Support Opened Up by Natural Language Processing].
  In Japan, the adoption rate of electronic medical records (EMR) in general hospitals has surpassed 50%, leading to the rapid digitization of medical information. However, core components such as clinical notes and nursing records remain accumulated as unstruct…
  pubmed Tamiya G 2026 Jun 置信度 0.82
• Can agentic AI dent Eroom's Law? Large reasoning models across the drug discovery and development pipeline.
  Productivity in pharmaceutical R&D continues to fall despite deeper biological insight and steady gains in clinical development operations - a phenomenon termed Eroom's Law. Agentic AI workflows powered by reasoning-trained large language models (LLMs), in…
  pubmed Khan S, Samuelsson JG, Cai X, Natarajan K 等 2026 Aug 4 置信度 0.82
• Leave No Data Behind: Exploring a new paradigm in oncology with foundation models and large language models.
  Foundation models (FMs) and large language models (LLMs) are transforming cancer AI by integrating heterogeneous data sources, including medical imaging, electronic health records, and molecular profiles. By learning from large-scale, unstructured, and label-f…
  pubmed Corso F, Zec A, Favali M, Ligero M 等 2026 Aug 4 置信度 0.82
• Discovery of hydrazone derivatives as novel STAT3 antagonists against pancreatic and colorectal cancers.
  Signal transducer and activator of transcription 3 (STAT3) has been an anti-cancer protein target for three decades due to its over-activation in various cancers; however, direct STAT3 inhibitors have not reached the market. In this study, a series of novel hy…
  pubmed Yang HY, Chiu MH, Shih PC 2026 Jul 28 置信度 0.82
• 2-methoxyestradiol is effective in 2D and 3D models of NCI-H2170 lung squamous cell carcinoma cells.
  Lung squamous cell carcinoma (LUSC) is a difficult cancer to treat, with few targeted therapies to improve its poor prognosis. The goal of this study was to use a drug repurposing strategy to evaluate and compare drug sensitivities using 2D adherent and 3D sph…
  pubmed Mellor P, Kendall S, Anderson DH 2026 置信度 0.82
• Protein neddylation as a therapeutic target: challenges and opportunities.
  Protein neddylation is an evolutionarily conserved posttranslational modification that conjugates NEDD8 to its substrate, catalyzed by an E1-activating enzyme, E2-conjugating enzyme, and E3 ligase. Neddylation is essential for cellular homeostasis, and its dys…
  pubmed Zhang S, Lan H, Sun Y 2026 Aug 3 置信度 0.82
• Wise as a Serpent and Gentle as a Dove: Pharmacological Targeting of NRF2/KEAP1 Pathway from Treasure Trove of Mother Nature.
  Discovery of NRF2 in 1994 was once assumed simplistic and classical but the following years witnessed phenomenal breakthroughs that led to a rapid increase in the components of complex molecular web. Emerging evidence has enabled us to develop a better underst…
  pubmed Farooqi AA, Zhussupov S, Turgambayeva A, Datkhayev U 等 2026 置信度 0.82
• The Potential of AI-Driven High-Content Imaging in Drug Discovery.
  We have authored a compelling and timely review that highlights the transformative potential of high-content imaging for discovering small molecules (SMs). SMs are crucial for advancing drug potency, selectivity, and precision, and their assessment through spe…
  pubmed Ali R, Tamboli Y 2026 Jul 28 置信度 0.82
• Prediction of female reproductive tract infections risk among college-going young adult women in Delhi using explainable artificial intelligence.
  Reproductive tract infections (RTIs) and sexually transmitted infections (STIs) pose a substantial economic burden and public health concern in developing countries such as India, where inadequate early detection and prevention strategies often lead to increas…
  pubmed Ghosh J, Kant R, Bhardwaj P, Muralidhar S 等 2026 置信度 0.82
• GEM-GPT Enables Personalized Cell Type-Resolved Therapeutic Design for Systems Pharmacology.
  Generative artificial intelligence (AI) has emerged as a powerful framework for drug discovery, yet most current approaches follow one-drug-one-gene target-based paradigms that struggle to capture the complexity and heterogeneity of chronic and systemic diseas…
  pubmed Zhang S, Ohlan R, Mottaqi M, Xie L 2026 Jul 22 置信度 0.82
• AI-Assisted Hyperspectral Interferometry and Single-Cell Dispersion Imaging.
  Interferometry techniques are essential for extracting phase information from optical systems enabling precise measurements of dispersion and highly sensitive detection of perturbations. While phase sensing offers enhanced sensitivity compared to conventional …
  pubmed Behrouzi K, Siddique TA, Teng M, Redjem W 等 2026 Jul 20 置信度 0.82
• Design, Synthesis, and In Vitro Evaluation of a PSMA-Targeted Doxorubicin Conjugate.
  Clinical treatment of prostate cancer, particularly metastatic castration-resistant prostate cancer (mCRPC), mainly depends on targeting prostate-specific membrane antigen (PSMA), also known as glutamate carboxypeptidase II (GCPII). Toward this, small molecule…
  pubmed Kumar S, Tyagi M, Pal R, Patro BS 等 2026 Aug 14 置信度 0.82
• AI-driven discovery and validation of a GIPC1 PDZ domain inhibitor for pancreatic ductal adenocarcinoma.
  Pancreatic ductal adenocarcinoma (PDAC) remains highly aggressive, with a five-year survival rate under 13.3%, due to late diagnosis, rapid progression, and therapeutic resistance, highlighting the need for advanced treatments. GAIP-interacting protein C termi…
  pubmed Rachamala HK, Rao Nakka NM, Angom RS, Varanasi SM 等 2026 Jul 31 置信度 0.82
• Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges.
  Medicinal plants represent a vast and evolutionarily refined reservoir of structurally diverse bioactive compounds that have historically contributed to major therapeutic breakthroughs. However, despite their pharmacological richness, systematic translation of…
  pubmed Gangwal A, Ansari A, Siddique MUM, Sawale J 等 2026 Aug 置信度 0.82
• A comprehensive review on bacterial endophytic secondary metabolites: a road map from crude extract to lead molecule production.
  Endophytes are microorganisms that are concealed within the intracellular spaces of the plants in diverse ecological niches across varied habitats, are a prolific source of bioactive metabolites capable of inhibiting human pathogens responsible for mild to sev…
  pubmed Biju R, Osborne WJ 2026 置信度 0.82
• Development of a Novel Immunohistochemistry Assay to Characterize EDB+FN Protein Expression in Solid Tumors.
  Tumor stroma, the cellular and non-cellular support system surrounding cancer cells, is a promising source of novel therapeutic targets. Extradomain-B of fibronectin (EDB+FN), a tumor-specific antigen expressed in the extracellular matrix (ECM) of tumor stroma…
  pubmed Lewandowski SL, Shen C, Diao L, Quigley AM 等 2026 Jul 30 置信度 0.82
• Conditional molecular dynamics refinement for protein-ligand affinity prediction.
  Protein-ligand affinity prediction is fundamental to structure-based virtual screening and lead discovery. However, most existing methods rely on a single static conformation of the complex and exhibit high sensitivity to pose uncertainty and conformational no…
  pubmed Li H, Niu D, Wang X, Wei Z 等 2026 Jul 27 置信度 0.82