Evidence map›Paper›PMID 36323739›Full record

ArticleScientific reports2022

Design of amino acid- and carbohydrate-based anticancer drugs to inhibit polymerase η.

Sepideh Kalhor, Alireza Fattahi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 33% 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

7 citing papers in PubMed, 10 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

2 authors at 1 institution in 1 country.

Sepideh KalhorDepartment of Chemistry, Sharif University of Technology, Tehran, Iran.
Alireza FattahiDepartment of Chemistry, Sharif University of Technology, Tehran, Iran. fattahi@sharif.edu.
Sharif University of Technology · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA polymerase η (polη) is of significant value for designing new families of anticancer drugs. This protein takes a role in many stages of the cell cycle, including DNA replication, translesion DNA synthesis, and the repairing process of DNA. According to many studies, a high level of expression of polη in most cases has been associated with low rates of patients' survival, regardless of considering the stage of tumor cells. Thus, the design of new drugs with fewer side effects to inhibit polη in cancerous cells has attracted attention in recent years. This project aims to design and explore the alternative inhibitors for polη, which are based on carbohydrates and amino acids. In terms of physicochemical properties, they are similar to the traditional anticancer drugs such as Cytarabine (cytosine arabinose). These alternative inhibitors are supposed to disrupt the DNA replication process in cancerous cells and prevent the tumor cells from mitosis. These newly designed structures, which are based on natural products, are expected to be non-toxic and to have the same chemotherapeutic impact as the traditional agents. The combinatorial use of quantum mechanics studies and molecular dynamic simulation has enabled us to precisely predict the inhibition mechanism of the newly designed structure, which is based on carbohydrates and amino acids, and compare it with that of the traditional chemotherapeutic drugs such as Cytarabine. Our results suggest that the inhibitors containing the natural building blocks of amino acid and carbohydrate could be considered alternative drugs for Cytarabine to block polη.

Indexed as

Amino AcidsAntineoplastic AgentsCarbohydratesCytarabineDNADNA DamageDNA ReplicationHumansAmino AcidsAntineoplastic AgentsCarbohydratesCytarabineDNA

Identifiers

PMID36323739
PMCPMC9630280
OpenAlexW4307989619

What OpenQuestion holds

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LicenceCC BY
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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.