Evidence map›Paper›PMID 33707429›Full record

ReviewNPJ systems biology and applications2021

Nanoscale programming of cellular and physiological phenotypes: inorganic meets organic programming.

Nikolay V Dokholyan

Abstract readReview
In one paragraph

Review in NPJ systems biology and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Optogenetic enzymes: A deep dive into design and impact.Current opinion in structural biology · 2025
    Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Allosteric regulation of kinase activity in living cells.bioRxiv : the preprint server for biology · 2023
    Article
  9. Article
  10. Allosteric inactivation of an engineered optogenetic GTPase.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Nikolay V DokholyanDepartments of Pharmacology, Penn State College of Medicine, Hershey, PA, 17033-0850, USA. dokh@psu.edu.ORCID 0000-0002-8225-4025

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
Nanoscale programming of cellular and physiological phenotypes: EquipmentR35GM134864 · NIGMS · UNIVERSITY OF VIRGINIA · PI Nikolay Dokholyan · 2020 to 2026
$5.2M
NCATS NIH HHS UL1 TR002014NIGMS NIH HHS R35 GM134864
6 · The paper itself

Abstract

The advent of protein design in recent years has brought us within reach of developing a "nanoscale programing language," in which molecules serve as operands with their conformational states functioning as logic gates. Combining these operands into a set of operations will result in a functional program, which is executed using nanoscale computing agents (NCAs). These agents would respond to any given input and return the desired output signal. The ability to utilize natural evolutionary processes would allow code to "evolve" in the course of computation, thus enabling radically new algorithmic developments. NCAs will revolutionize the studies of biological systems, enable a deeper understanding of human biology and disease, and facilitate the development of in situ precision therapeutics. Since NCAs can be extended to novel reactions and processes not seen in biological systems, the growth of this field will spark the growth of biotechnological applications with wide-ranging impacts, including fields not typically considered relevant to biology. Unlike traditional approaches in synthetic biology that are based on the rewiring of signaling pathways in cells, NCAs are autonomous vehicles based on single-chain proteins. In this perspective, I will introduce and discuss this new field of biological computing, as well as challenges and the future of the NCA. Addressing these challenges will provide a significant leap in technology for programming living cells.

Indexed as

Autonomous VehiclesProteinsBiotechnologyHumansPhenotypeSignal TransductionProteins

Identifiers

PMID33707429
PMCPMC7952909

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.