Aptamers are emerging as important molecular recognition ligands in oncology, playing significant roles in cancer diagnostics, targeted therapies, drug delivery systems, and molecular imaging, and the development of next-generation aptamer-based diagnostics and therapeutics.
Abstract
Aptamers are emerging as important molecular recognition ligands in oncology, playing significant roles in cancer diagnostics, targeted therapies, drug delivery systems, and molecular imaging. Numerous aptamers have advanced to clinical trials, indicating their potential for real-world applications; however, existing databases fail to capture that. To bridge this critical gap, we developed AptCancerDB (https://webs.iiitd.edu.in/raghava/aptcancerdb/), a comprehensive, manually curated database of experimentally verified anticancer aptamers. The current release contains 1,941 entries collected from studies published between 2000 and 2025, covering 29 cancer types, approximately 200 cancer cell lines, and direct links to 22 clinical trials. Each entry is annotated with sequence information, target details, cancer type, cell line, SELEX methodology, affinity determination data, chemical modifications, and biological activities. The dataset is dominated by 82.7% ssDNA, reflecting its superior stability and ease of synthesis, while only 16.6% is ssRNA and appears primarily in studies targeting complex intracellular or protein-protein interactions. To facilitate structural analysis, predicted secondary structures, dot-bracket notations, specific structural elements, and minimum free energy values were also included. AptCancerDB integrates a MySQL backend with an ArcadeDB/OpenCypher-based Knowledge Graph, enabling exploration of relationships among aptamers, targets, cancer types, cell lines, and functional applications. The platform provides advanced search and browsing facilities, BLASTn-based similarity searching, and GC Calculator. Built on a modern, responsive frontend (React/TypeScript/Tailwind CSS), the platform includes a REST API for data retrieval. By integrating fragmented experimental data into a unified cancer-focused resource, AptCancerDB serves as a valuable resource for comparative analysis, aptamer discovery, and the development of next-generation aptamer-based diagnostics and therapeutics. Highlights Curated knowledge base of experimentally validated anticancer aptamers. AptCancerDB contain therapeutic, tumor-homing and cell-penetrating aptamers. Summarizes clinical progress and translational trends in anticancer aptamer research. Supports rational aptamer design using molecular, functional, and clinical annotations Disease-focused resource for cancer diagnosis, therapy, and drug delivery Teaser AptCancerDB maintains experimentally validated anticancer aptamers relevant to diagnosis, drug delivery, and therapy.
In an era of increasing drug resistance, exploring alternative molecules is crucial for the efficient management and treatment of viral diseases. Nucleic acid aptamers have emerged as highly promising candidates due to their exceptional target specificity, low immunogenicity, and versatile mechanisms for viral blocking. This manuscript describes AptViralDB, a manually curated database providing comprehensive information on experimentally validated antiviral aptamers. It contains 1,768 entries of antiviral aptamers against 40 viral species and 104 molecular targets, compiled from literature and existing databases. Each entry provides detailed annotations, including sequence, aptamer type, target, chemical modifications, binding affinity, antiviral activity, stability, and cytotoxicity. We also provide predicted secondary structures and their corresponding minimum free energy (MFE) values. Additionally, a knowledge graph created using ArcadeDB/openCypher enables users to seamlessly explore connections among aptamers, viruses, molecular targets, and biological activities. Finally, the platform offers advanced search and browsing tools, BLAST-based sequence similarity searches, GC-content analysis, downloadable datasets, and REST API access to support computational applications. (https://webs.iiitd.edu.in/raghava/aptviraldb/).
N. Bajiya, Shivansh Singh, P. S. Gahlot et al.· bioRxiv· 0 citations
Aptamers are widely used in biosensing and targeted therapeutics, yet reported data remain fragmented across unstructured text, tables, and figures. Existing databases are limited in coverage and diversity, which constrains computational modeling. Here, we present AptaNexus (https://www.aptanexus.com/), a multitier aptamer database containing over 12,000 sequences targeting 1900 molecular entities, curated from literature published between 2005 and 2025. Its extraction pipeline, Dual-LLM Extraction with Reverse Grounding (Dual-LLMs+RG), achieves an F1 score of 0.970 at a fraction of the cost of the state-of-the-art model. Records are stratified into four quality tiers, supporting both experimental selection and machine learning applications. Beyond conventional keyword search, AptaNexus incorporates the Model Context Protocol (MCP) and an embedded conversational agent, Chat Aptamer, enabling natural-language queries that return structured, source-linked, and application-oriented recommendations. For example, users can request detection of a target in blood to receive a ranked list of aptamers with validated sensor platforms or query drug delivery targets to obtain functionally annotated candidates. By combining large-scale, evidence-grounded data with agent-accessible interfaces, AptaNexus makes aptamer information readily accessible across disciplines and, for the first time, provides native AI-agent interoperability.
Fangyuan Zheng, Lingjing Yang, Jilie Kong et al.· Analytical Chemistry· 0 citations
Non-small-cell lung cancer (NSCLC) is one of the most frequent cancer types and is responsible for the majority of cancer-related deaths worldwide. For this reason, initial diagnosis, prognosis, and targeted therapy of NSCLC represent very attractive areas of study. Aptamers are single-stranded nucleic acids (RNA or DNA) generated through Systematic Evolution of Ligands by Exponential Enrichment (SELEX); they are able to bind to a molecular target with high affinity and specificity. Thanks to their intrinsic nucleic acid properties, they can be easily modified and optimized to enhance target binding and their half-life; moreover, they exhibit no immunogenicity and toxicity. Due to this, many aptamers have just been selected against NSCLC biomarkers and provide specific imaging agents to improve the diagnosis of this type of cancer. However, despite the promising results in preclinical studies, the application of aptamers in NSCLC diagnosis is still in its early stages, mainly due to the limited literature in the research world, the dominance of antibodies in the pharmaceutical market and the challenge of target identification. Consequently, this appears to be a temporary issue, and aptamers could see increasing application in the future; thus, we performed a review aimed at summarizing current knowledge on the new promising DNA and RNA aptamer-based molecules for NSCLC diagnosis. All studies from 2000 were included and investigated. Our findings showed that several DNA and RNA aptamers are promising diagnostic tools for NSCLC management.
Lisa Agnello, Ilaria Leone, Alessandra Affinito et al.· International Journal of Mol...· 0 citations
This study developed a comprehensive strategy integrating computational predictions with in vitro experimental validations that reverses CDDP resistance in PROC by downregulating JUN, which dismantles intracellular pro-survival networks.
Chen Wang, Junfeng Guo, Taiyang Ye et al.· Frontiers in Pharmacology· 0 citations
ICBcDrug is a freely accessible and valuable resource for advancing ICB combination therapy that integrates 2311 reported or predicted compounds across 18 cancer types and accurately predicted both the efficacy and potential mechanisms of the known ICB enhancer entinostat.
Yu Lin, Wen Sun, Yun Xia et al.· Chinese Medical Journal· 0 citations
Anthracycline chemotherapeutics such as doxorubicin and daunorubicin remain indispensable in cancer treatment but possess narrow therapeutic windows, motivating the development of reliable molecular recognition elements for therapeutic drug monitoring, biosensing, and toxicity mitigation. Although an anthracycline aptamer has previously been obtained using immobilized daunorubicin, it lacks a well-defined secondary structure and exhibits poor affinity after truncation. Here, we employed capture-SELEX, which uses free target molecules in solution without immobilization, to isolate DNA aptamers that specifically recognize doxorubicin. The selection yielded three distinct sequence families with well-defined secondary structures and low-nanomolar affinities. Using intrinsic fluorescence quenching, isothermal titration calorimetry, and NMR spectroscopy, we rigorously distinguished specific aptamer recognition from nonspecific intercalation and demonstrated rapid, Mg2+-independent binding. The strongest aptamer, DOX-9, bound doxorubicin with a dissociation constant of 6 nM and also recognized daunorubicin with nanomolar affinity. Compared with the previously reported aptamer, the new sequences exhibit higher affinity, clearer structural features, and greater amenability to truncation. Importantly, they significantly inhibited doxorubicin uptake by HeLa cells, demonstrating potential as functional antidotes in addition to sensing elements. Together, these results establish a new generation of anthracycline aptamers and highlight capture-SELEX as an effective strategy for selecting aptamers against DNA-interacting small molecules.
Meheta Datta, Celine Fidella, Lashaun N. Coote et al.· ACS Chemical Biology· 0 citations
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