Evidence map›Paper›PMID 19662104›Full record

ArticleDrug design, development and therapy2008

Structure-Based Design of Anticancer Prodrug PABA/NO.

Xinhua Ji, Ajai Pal, Ravi Kalathur, Xun Hu, Yijun Gu, Joseph E Saavedra, Gregory S Buzard, Aloka Srinivasan, Larry K Keefer, Shivendra V Singh

Open access · goldAbstract read
In one paragraph

Article in Drug design, development and therapy, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

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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

10 authors at 1 institution in 1 country.

Xinhua JiMacromolecular Crystallography Laboratory, National Cancer Institute, National Institutes of Health, Frederick, MD 21702, USA.
Ajai Pal
Ravi Kalathur
Xun Hu
Yijun Gu
Joseph E Saavedra
Gregory S Buzard
Aloka Srinivasan
Larry K Keefer
Shivendra V Singh
National Institutes of Health · US

Funding

Structural of Biomolecular Systems by X Ray DiffractionZ01BC010326 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI JI, XINHUA · 2000 to 2008
$2.6M
Intramural NIH HHS Z01 BC010326NCI NIH HHS N01 CO012400
6 · The paper itself

Abstract

Glutathione S-transferase (GST) is a superfamily of detoxification enzymes, represented by GSTalpha, GSTmu, GSTpi, etc. GSTalpha is the predominant isoform of GST in human liver, playing important roles for our well being. GSTpi is overexpressed in many forms of cancer, thus presenting an opportunity for selective targeting of cancer cells. Our structure-based design of prodrugs intended to release cytotoxic levels of nitric oxide in GSTpi-overexpressing cancer cells yielded PABA/NO, which exhibited anticancer activity both in vitro and in vivo with a potency similar to that of cisplatin (Findlay et al. Mol. Pharmacol. 2004, 65, 1070-1079). Here, we present the details on structural modification, molecular modeling, and enzymatic characterization for the design of PABA/NO. The design was efficient because it was on the basis of the reaction mechanism and the structures of related GST isozymes at both the ground state and the transition state. The ground-state structures outlined the shape and property of the substrate-binding site in different isozymes, and the structural information at the transition-state indicated distinct conformations of the Meisenheimer complex of prodrugs in the active site of different isozymes, providing guidance for the modifications of the molecular structure of the prodrug molecules. Two key alterations of a GSTalpha -selective compound led to the GSTpi-selective PABA/NO.

Identifiers

PMID19662104
PMCPMC2721280
OpenAlexW1992509675

What OpenQuestion holds

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Registered trials

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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.