Evidence map›Paper›PMID 31719913›Full record

ArticleCellular and molecular bioengineering2019

Hierarchical-Clustering, Scaffold-Mining Exercises and Dynamics Simulations for Effectual Inhibitors Against Lipid-A Biosynthesis of

Chiranjeevi Pasala, Sudheer Kumar Katari, Ravina Madhulitha Nalamolu, Aparna R Bitla, Umamaheswari Amineni

Abstract read
In one paragraph

Article in Cellular and molecular bioengineering, 2019. 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
–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

2 citing papers in PubMed.

  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

5 authors.

Chiranjeevi PasalaBioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507 AP India.
Sudheer Kumar KatariBioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507 AP India.
Ravina Madhulitha NalamoluBioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507 AP India.
Aparna R BitlaDepartment of Biochemistry, SVIMS University, Tirupati, 517507 AP India.
Umamaheswari AmineniBioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, 517507 AP India.ORCID 0000-0001-5612-6241

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTreatment failures of standard regimens and new strains egression are due to the augmented drug resistance conundrum. These confounding factors now became the drug designers spotlight to implement therapeutics against

methodsWe explored the relationships between existing inhibitors and novel leads at the scaffold level in an appropriate conformational plasticity for lead-optimization campaign. Hierarchical-clustering and shape-based screening against an in-house library of > 21 million compounds resulted in panel of 11,000 compounds. Rigid-receptor docking through virtual screening cascade, quantum-polarized-ligand, induced-fit dockings, post-docking processes and system stability assessments were performed.

resultsAfter docking experiments, an enrichment performance unveiled seven ranked actives better binding efficiencies with Zinc-binding potency than substrate and in-actives (decoy-set) with ROC (1.0) and area under accumulation curve (0.90) metrics. Physics-based membrane permeability accompanied ADME/T predictions and long-range dynamic simulations of 250 ns chemical time have depicted good passive diffusion with no toxicity of leads and sustained consistency of lead1-LpxC in the physiological milieu respectively.

conclusionsIn the study, as these static outcomes obtained from this approach competed with the substrate and existing ligands in binding affinity estimations as well as positively correlated from different aspects of predictions, which could facilitate promiscuous new chemical entities against

Indexed as

Decoy-setEnergy minimizationEnrichment-factorInduced-fit dockingLpxCQuantum-mechanicsRadious of gyrationVirtual-screening

Identifiers

PMID31719913
PMCPMC6816686

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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.