ReviewACS nano2025
Autonomous Nucleic Acid and Protein Nanocomputing Agents Engineered to Operate in Living Cells.
Review in ACS nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Design and optimization of a kinase-controlled allosteric switch.Nature methods · 2026Article
- Expanding Chemical Space of Nucleic Acid Nanoparticles for Tunable Antiviral-Like Immunomodulatory Responses and Potent Adjuvant Activity.Advanced functional materials · 2026Article
- From Sequence to Response: AI-Guided Prediction of Nucleic Acid Nanoparticles Immune Recognitions.Small (Weinheim an der Bergstrasse, Germany) · 2025Article
- Nucleic Acid Nanoparticles Redefine Traditional Regulatory Terminology: The Blurred Line between Active Pharmaceutical Ingredients and Excipients.ACS nano medicine · 2025Article
- The Evolving Landscape of Protein Allostery: From Computational and Experimental Perspectives.Journal of molecular biology · 2025Review
- Optogenetic enzymes: A deep dive into design and impact.Current opinion in structural biology · 2025Review
- Nucleic acid nanobiosystems for cancer theranostics: an overview of emerging trends and challenges.Nanomedicine (London, England) · 2025Review
- Leveraging Immunological Properties of Nucleic Acid Nanoparticles to Improve Cancer Therapy.RNA nanomed · 2025Article
- The role of bioinformatics algorithms in modern biopharmaceutical design: Progress, challenges, and future perspectives.BioImpacts : BI · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
In recent years, the rapid development and employment of autonomous technology have been observed in many areas of human activity. Autonomous technology can readily adjust its function to environmental conditions and enable an efficient operation without human control. While applying the same concept to designing advanced biomolecular therapies would revolutionize nanomedicine, the design approaches to engineering biological nanocomputing agents for predefined operations within living cells remain a challenge. Autonomous nanocomputing agents made of nucleic acids and proteins are an appealing idea, and two decades of research has shown that the engineered agents act under real physical and biochemical constraints in a logical manner. Throughout all domains of life, nucleic acids and proteins perform a variety of vital functions, where the sequence-defined structures of these biopolymers either operate on their own or efficiently function together. This programmability and synergy inspire massive research efforts that utilize the versatility of nucleic and amino acids to encode functions and properties that otherwise do not exist in nature. This Perspective covers the key concepts used in the design and application of nanocomputing agents and discusses potential limitations and paths forward.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.