Evidence map›Paper›PMID 20305804›Full record

ArticleChimia2009

Engineering Kinases to Phosphorylate Nucleoside Analogs for Antiviral and Cancer Therapy.

Stefan Lutz, Lingfeng Liu, Yichen Liu

Open access · diamondAbstract read
In one paragraph

Article in Chimia, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 41% of its field
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

5 citing papers in PubMed, 15 citations in OpenAlex.

  1. Live-Cell RNA Imaging via Clickable TriPPPro Nucleotide Reporters.Angewandte Chemie (International ed. in English) · 2026
    Article
  2. Article
  3. The journal of physical chemistry. C, Nanomaterials and interfaces · 2025
    Article
  4. Article
  5. Review
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

3 authors at 2 institutions in 2 countries.

Stefan Lutz
Lingfeng Liu
Yichen Liu
Emory University · USZHAW Zurich University of Applied Sciences · CH

Funding

Virology and Molecular Biomarkers CoreP30AI050409 · NIAID · EMORY UNIVERSITY · PI Carlos del Rio · 2002 to 2026
$74.0M
Improving nucleoside phosphorylation with hybrid kinasesR01GM069958 · NIGMS · EMORY UNIVERSITY · PI LUTZ, STEFAN · 2005 to 2009
$1.2M
NIAID NIH HHS P30 AI050409NIGMS NIH HHS R01 GM069958
6 · The paper itself

Abstract

Enzyme engineering by directed evolution presents a powerful strategy for tailoring the function and physicochemical properties of biocatalysts to therapeutic and industrial applications. Our laboratory's research focuses on developing novel molecular tools for protein engineering, as well as on utilizing these methods to customize enzymes and to study fundamental aspects of their structure and function. Specifically, we are interested in nucleoside and nucleotide kinases which are responsible for the intracellular phosphorylation of nucleoside analog (NA) prodrugs to their biologically active triphosphates. The high substrate specificity of the cellular kinases often interferes with prodrug activation and consequently lowers the potency of NAs as antiviral and cancer therapeutics. A working solution to the problem is the co-adminstration of a promiscuous kinase from viruses, bacteria, and other mammals. However, further therapeutic enhancements of NAs depend on the selective and efficient prodrug phosphorylation. In the absence of true NA kinases in nature, we are pursuing laboratory evolution strategies to generate efficient phosphoryl-transfer catalysts. This review summarizes some of our recent work in the field and outlines future challenges.

Identifiers

PMID20305804
PMCPMC2839369
OpenAlexW2016019565

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.