Evidence map›Paper›PMID 35365662›Full record

ArticleScientific data2022

AB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials.

Silvia Gervasoni, Giuliano Malloci, Andrea Bosin, Attilio V Vargiu, Helen I Zgurskaya, Paolo Ruggerone

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

6 authors.

Silvia GervasoniUniversity of Cagliari, Department of Physics, I-09042, Monserrato (Cagliari), Italy.ORCID 0000-0002-5731-3396
Giuliano MallociUniversity of Cagliari, Department of Physics, I-09042, Monserrato (Cagliari), Italy. giuliano.malloci@dsf.unica.it.ORCID 0000-0002-5985-257X
Andrea BosinUniversity of Cagliari, Department of Physics, I-09042, Monserrato (Cagliari), Italy.ORCID 0000-0001-6300-5712
Attilio V VargiuUniversity of Cagliari, Department of Physics, I-09042, Monserrato (Cagliari), Italy.ORCID 0000-0003-4013-8867
Helen I ZgurskayaUniversity of Oklahoma, Department of Chemistry and Biochemistry, Norman, OK, 73072, United States.
Paolo RuggeroneUniversity of Cagliari, Department of Physics, I-09042, Monserrato (Cagliari), Italy.ORCID 0000-0003-0825-0824

Funding

Optimization of efflux avoidance and inhibition for antibiotic developmentR01AI136799 · NIAID · UNIVERSITY OF OKLAHOMA · PI GNANAKARAN, SANDRASEGARAM, RUGGERONE, PAOLO · 2018 to 2022
$5.7M
NIAID NIH HHS R01 AI136799U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) R01AI136799
6 · The paper itself

Abstract

Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.

Indexed as

Anti-Infective AgentsMolecular Dynamics SimulationAnti-Infective Agents

Identifiers

PMID35365662
PMCPMC8976083

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.