Browsing by Author "Oselusi, Samson Olaitan"

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    Cheminformatic Approaches to Hit-Prioritization and Target Prediction of Potential Anti-MRSA Natural Products
    (University of the Western Cape, 2020) Oselusi, Samson Olaitan; Egieyeh, Samuel
    The growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates. Cheminformatic approaches in drug discovery enable chemical data mining, in conjunction with unsupervised and supervised learning from available bioactivity data that may unlock the full potential of NPs in antimicrobial drug discovery. Therefore, taking advantage of the available NPs with their known in vitro activity against MRSA, this study conducted cheminformatic and data mining analysis towards hit profiling, hit-prioritization, hit-optimization, and target prediction of anti-MRSA NPs. Cheminformatic profiling was conducted on the 111 anti-MRSA NPs (AMNPs) retrieved from literature. About 20 current drugs for MRSA (CDs) were used as a reference to identify AMNPs with promising prospects to become drug candidates.
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    Cheminformatic approaches to hit-prioritization and target prediction of potential anti-mrsa natural products
    (University of Western Cape, 2020) Oselusi, Samson Olaitan; Egieyeh, Samuel; Christoffels, Alan
    The growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates.
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    Cheminformatic Characterization of Natural Antimicrob al Products for the Development of New Lead Compounds
    (MDPI, 2021) Egieyeh, Samuel Ayodele; Oselusi, Samson Olaitan; Christoffels, Alan
    The growing antimicrobial resistance (AMR) of pathogenic organisms to currently pre- scribed drugs has resulted in the failure to treat various infections caused by these superbugs. Therefore, to keep pace with the increasing drug resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have been shown to display promising in vitro activities against multidrug-resistant pathogens. Still, only a few of these compounds have been studied as prospective drug candidates. This may be due to the expensive and time-consuming process of conducting important studies on these compounds. The present review focuses on applying cheminformatics strategies to characterize, prioritize, and optimize NPs to develop new lead compounds against antimicrobial resistance pathogens. Moreover, case studies where these strategies have been used to identify potential drug candidates, including a few selected open-access tools commonly used for these studies, are briefly outlined.
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    Phytonanotherapeutic applications of plant extract-synthesized silver nanoparticles in wound healing—a prospective overview
    (Springer, 2024) Oselusi, Samson Olaitan; Sibuyi, Nicole Remaliah Samantha; Madiehe, Abram Madimabe
    Chronic wounds continue to pose severe threats to public health and the global economy. This is because the healing process is hindered by several factors, such as bacterial infections, comorbid conditions, age, and lifestyle. Medical wound therapy is currently based on long-term antibiotic use, and its activity has been limited by various factors, including treatment efficacy, toxicity, and increased risk of opportunistic infections. The advent of novel techniques such as nanotechnology can provide sustainable platforms for developing reliable, cost-effective, and innovative wound healing interventions. In this context, plant extract-synthesized silver nanoparticles (AgNPs) have become attractive to the clinical community because of their wide range of biological properties, such as antibacterial, anti-inflammatory, and wound healing effects. These AgNPs could be used in the development of better dressings for wounds.
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    Zinc(ii) complex of (z)-4-((4-nitrophenyl)amino)pent-3-en-2-one, a potential antimicrobial agent: Synthesis, characterization, antimicrobial screening, dft calculation and docking study
    (Chemical Society of Ethiopia, 2023) Waziri, Ibrahim; Wahab, Olaide O.; Oselusi, Samson Olaitan
    Herein, the synthesis and characterizations of (Z)-4-((4-nitrophenyl)amino)pent-3-en-2-one (HL) ligand and its Zn(II) complex are reported. The compounds were characterized using elemental and thermogravimetric (TGA) analysis, electrochemical studies, FTIR, UV-Vis, 1H and 13C{H}NMR, HRMS, and PXRD techniques. Antimicrobial activity was screened on some Gram-positive and Gram-negative bacteria. DFT predictions were achieved using B3LYP, ωB97XD and M06-2X functional with 6-31+G(d, p) and LANL2DZ basis sets for nonmetallic and metallic atoms, respectively.