Evidence map›Paper›PMID 33946965›Full record

SynthesisMolecules (Basel, Switzerland)2021

Predicting Accurate Lead Structures for Screening Molecular Libraries: A Quantum Crystallographic Approach.

Suman Kumar Mandal, Parthapratim Munshi

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

2 authors at 1 institution in 1 country.

Suman Kumar MandalChemical and Biological Crystallography, Department of Chemistry, School of Natural Sciences, Shiv Nadar University, Dadri 201314, Uttar Pradesh, India.ORCID 0000-0002-7753-9974
Parthapratim MunshiChemical and Biological Crystallography, Department of Chemistry, School of Natural Sciences, Shiv Nadar University, Dadri 201314, Uttar Pradesh, India.ORCID 0000-0002-3745-9187
Shiv Nadar University · IN

Funding

SERB, India Govt. EMR/2014/000491
6 · The paper itself

Abstract

Optimization of lead structures is crucial for drug discovery. However, the accuracy of such a prediction using the traditional molecular docking approach remains a major concern. Our study demonstrates that the employment of quantum crystallographic approach-counterpoise corrected kernel energy method (KEM-CP) can improve the accuracy by and large. We select human aldose reductase at 0.66 Å, cyclin dependent kinase 2 at 2.0 Å and estrogen receptor β at 2.7 Å resolutions with active site environment ranging from highly hydrophilic to moderate to highly hydrophobic and several of their known ligands. Overall, the use of KEM-CP alongside the GoldScore resulted superior prediction than the GoldScore alone. Unlike GoldScore, the KEM-CP approach is neither environment-specific nor structural resolution dependent, which highlights its versatility. Further, the ranking of the ligands based on the KEM-CP results correlated well with that of the experimental IC

Indexed as

Models, MolecularQuantitative Structure-Activity RelationshipSmall Molecule LibrariesBinding SitesBiomarkersCrystallographyDrug DiscoveryHumansLigandsMolecular ConformationProtein BindingBiomarkersLigandsSmall Molecule Librarieskernel energy methodlead structuremolecular dockingprotein-ligand interactionquantum crystallographyscoring function

Identifiers

PMID33946965
PMCPMC8124947
OpenAlexW3157548125

What OpenQuestion 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 OpenQuestion graph.