Hierarchical Virtual Screening of Potential New Antibiotics from Polyoxygenated Dibenzofurans against Staphylococcus aureus Strains

Author:

Oliveira Lana P. S.12,Lima Lúcio R.234,Silva Luciane B.24,Cruz Jorddy N.2ORCID,Ramos Ryan S.12ORCID,Lima Luciana S.5,Cardoso Francy M. N.125,Silva Aderaldo V.12,Rodrigues Dália P.6,Rodrigues Gabriela S.7,Proietti-Junior Aldo A.15ORCID,dos Santos Gabriela B.7ORCID,Campos Joaquín M.8ORCID,Santos Cleydson B. R.123ORCID

Affiliation:

1. Graduate Program in Biotechnology and Biodiversity-Network BIONORTE, Federal University of Amapá, Macapá 68903-419, Brazil

2. Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, Brazil

3. Graduate Program in Network in Pharmaceutical Innovation, Federal University of Amapá, Macapá 68902-280, Brazil

4. Graduate Program in Medicinal Chemistry and Molecular Modeling, Health Science Institute, Federal Univesity of Pará, Belém 66075-110, Brazil

5. Special Laboratory of Applied Microbiology, Department of Biological and Health Sciences, Federal University of Amapá, Macapá 68902-280, Brazil

6. Laboratory of Bacterial Enteric Pathogens, Oswaldo Cruz Foundation, FIOCRUZ, Rio de Janeiro 21045-900, Brazil

7. Graduate Program in Health Sciences, Institute of Collective Health, Federal University of Western Pará, Santarém 68270-000, Brazil

8. Department of Pharmaceutical and Organic Chemistry, Faculty of Pharmacy, Institute of Biosanitary Research ibs. GRANADA, University of Granada, 18071 Granada, Spain

Abstract

Staphylococcus aureus is a microorganism with high morbidity and mortality due to antibiotic-resistant strains, making the search for new therapeutic options urgent. In this context, computational drug design can facilitate the drug discovery process, optimizing time and resources. In this work, computational methods involving ligand- and structure-based virtual screening were employed to identify potential antibacterial agents against the S. aureus MRSA and VRSA strains. To achieve this goal, tetrahydroxybenzofuran, a promising antibacterial agent according to in vitro tests described in the literature, was adopted as the pivotal molecule and derivative molecules were considered to generate a pharmacophore model, which was used to perform virtual screening on the Pharmit platform. Through this result, twenty-four molecules were selected from the MolPort® database. Using the Tanimoto Index on the BindingDB web server, it was possible to select eighteen molecules with greater structural similarity in relation to commercial antibiotics (methicillin and oxacillin). Predictions of toxicological and pharmacokinetic properties (ADME/Tox) using the eighteen most similar molecules, showed that only three exhibited desired properties (LB255, LB320 and LB415). In the molecular docking study, the promising molecules LB255, LB320 and LB415 showed significant values in both molecular targets. LB320 presented better binding affinity to MRSA (−8.18 kcal/mol) and VRSA (−8.01 kcal/mol) targets. Through PASS web server, the three molecules, specially LB320, showed potential for antibacterial activity. Synthetic accessibility (SA) analysis performed on AMBIT and SwissADME web servers showed that LB255 and LB415 can be considered difficult to synthesize and LB320 is considered easy. In conclusion, the results suggest that these ligands, particularly LB320, may bind strongly to the studied targets and may have appropriate ADME/Tox properties in experimental studies.

Publisher

MDPI AG

Subject

Drug Discovery,Pharmaceutical Science,Molecular Medicine

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