Dataset Information

A Computer-Driven Approach to Discover Natural Product Leads for Methicillin-Resistant Staphylococcus aureus Infection Therapy.

ABSTRACT: The risk of methicillin-resistant Staphylococcus aureus (MRSA) infection is increasing in both the developed and developing countries. New approaches to overcome this problem are in need. A ligand-based strategy to discover new inhibiting agents against MRSA infection was built through exploration of machine learning techniques. This strategy is based in two quantitative structure?activity relationship (QSAR) studies, one using molecular descriptors (approach A) and the other using descriptors (approach B). In the approach A, regression models were developed using a total of 6645 molecules that were extracted from the ChEMBL, PubChem and ZINC databases, and recent literature. The performance of the regression models was successfully evaluated by internal and external validation, the best model achieved R² of 0.68 and RMSE of 0.59 for the test set. In general natural product (NP) drug discovery is a time-consuming process and several strategies for dereplication have been developed to overcome this inherent limitation. In the approach B, we developed a new NP drug discovery methodology that consists in frontloading samples with 1D NMR descriptors to predict compounds with antibacterial activity prior to bioactivity screening for NPs discovery. The NMR QSAR classification models were built using 1D NMR data (¹H and 13C) as descriptors, from crude extracts, fractions and pure compounds obtained from actinobacteria isolated from marine sediments collected off the Madeira Archipelago. The overall predictability accuracies of the best model exceeded 77% for both training and test sets.

SUBMITTER: Dias T

PROVIDER: S-EPMC6356832 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Computer-Driven Approach to Discover Natural Product Leads for Methicillin-Resistant <i>Staphylococcus aureus</i> Infection Therapy.

Dias Tiago T Gaudêncio Susana P SP Pereira Florbela F

Marine drugs 20181228 1

The risk of methicillin-resistant <i>Staphylococcus aureus</i> (MRSA) infection is increasing in both the developed and developing countries. New approaches to overcome this problem are in need. A ligand-based strategy to discover new inhibiting agents against MRSA infection was built through exploration of machine learning techniques. This strategy is based in two quantitative structure⁻activity relationship (QSAR) studies, one using molecular descriptors (approach A) and the other using descri ...[more]

PMID: 30597893

Similar Datasets

Project description:Methicillin resistant Staphylococcus aureus (MRSA) infection is becoming refractory to existing antibiotic therapy owing to the inherent ability of S. aureus to develop rapid resistance and is considered a major threat to public health. We found that a natural isolate of Bacillus pumilus from the Columbia River Estuary produces a strong anti-MRSA compound, amicoumacin A. As amicoumacin A has been reported to exhibit anti-microbial, anti-inflammatory, and anti-ulcer activities, we sought to uncover its mechanism of action. Genome-wide transcriptome analysis of S. aureus COL in response to amicoumacin A showed alteration in the expression of genes involved in several cellular processes including cell envelope turnover, cross-membrane transport, virulence, metabolism, and general stress response. The most highly induced gene was lrgA, encoding an antiholin-like product, which has been shown to be induced in response to a collapse of membrane potential. In order to gain further insight into the mechanism of action of amicoumacin A, a whole genome comparison of wild-type COL and amicoumacin A-resistant mutants isolated by serial passage method was carried out. Single point mutations resulting in codon substitutions were uncovered in several distinct genes: ksgA, RNA dimethyltranferase; fusA, elongation factor G; dnaG, primase, ; lacD, tagatose 1,6-bisphosphate aldolase, ; and SACOL0611, encoding a putative glycosyl transferase gene. Based on these results, a candidate approach was undertaken to recreate the same amino acid substitution individually in FusA and KsgA, each of which resulted in two-fold resistance towards amicoumacin A. The fusA gene is known as the site for fusidic acid- resistant mutations; however the codon substitutions in EF-G that cause amicoumacin A resistance and fusidic acid resistance occur in separate domains and do not bring about cross resistance. Taken together, these results suggest that amicoumacin A might cause perturbation of the cell membrane and lead to energy dissipation. Decreased rates of cellular metabolism including protein synthesis and DNA replication in resistant strains might allow cells to compensate for membrane dysfunction and thus increase cell survivability.

Project description:UnlabelledSkin is the most common site of Staphylococcus aureus infection. While most of these infections are self-limited, recurrent infections are common. Keratinocytes and recruited immune cells participate in skin defense against infection. We postulated that S. aureus is able to adapt to the milieu within human keratinocytes to avoid keratinocyte-mediated clearance. From a collection of S. aureus isolated from chronically infected patients with atopic dermatitis, we noted 22% had an agr mutant-like phenotype. Using several models of human skin infection, we demonstrate that toxin-deficient, agr mutants of methicillin-resistant S. aureus (MRSA) USA300 are able to persist within keratinocytes by stimulating autophagy and evading caspase-1 and inflammasome activation. MRSA infection induced keratinocyte autophagy, as evidenced by galectin-8 and LC3 accumulation. Autophagy promoted the degradation of inflammasome components and facilitated staphylococcal survival. The recovery of more than 58% agr or RNAIII mutants (P < 0.0001) of an inoculum of wild-type (WT) MRSA from within wortmannin-treated keratinocytes compared to control keratinocytes reflected the survival advantage for mutants no longer expressing agr-dependent toxins. Our results illustrate the dynamic interplay between S. aureus and keratinocytes that can result in the selection of mutants that have adapted specifically to evade keratinocyte-mediated clearance mechanisms.ImportanceHuman skin is a major site of staphylococcal infection, and keratinocytes actively participate in eradication of these pathogens. We demonstrate that methicillin-resistant Staphylococcus aureus (MRSA) is ingested by keratinocytes and activates caspase-1-mediated clearance through pyroptosis. Toxin-deficient MRSA mutants are selected within keratinocytes that fail to induce caspase-1 activity and keratinocyte-mediated clearance. These intracellular staphylococci induce autophagy that enhances their intracellular survival by diminishing inflammasome components. These findings suggest that S. aureus mutants, by exploiting autophagy, can persist within human keratinocytes.

Dataset Information

A Computer-Driven Approach to Discover Natural Product Leads for Methicillin-Resistant Staphylococcus aureus Infection Therapy.

Publications

A Computer-Driven Approach to Discover Natural Product Leads for Methicillin-Resistant <i>Staphylococcus aureus</i> Infection Therapy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets