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Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds

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Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds molecules Review Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds Samson Olaitan Oselusi 1,* , Alan Christoffels 2 and Samuel Ayodele Egieyeh 1 1 School of Pharmacy, University of the Western Cape, Bellville, Cape Town 7535, South Africa; [email protected] 2 South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town 7535, South Africa; [email protected] * Correspondence: [email protected] Abstract: 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 an- timicrobial 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 Citation: Oselusi, S.O.; Christoffels, A.; Egieyeh, S.A. Cheminformatic few selected open-access tools commonly used for these studies, are briefly outlined. Characterization of Natural Antimicrobial Products for the Keywords: antimicrobial resistance; natural products; cheminformatics; hit prioritization; hit- Development of New Lead optimization; drug-likeness Compounds. Molecules 2021, 26, 3970. https://doi.org/10.3390/ molecules26133970 1. Introduction Academic Editors: Hilal Zaid, The advent of antibiotics in the 20th century has been a significant turning point in Zipora Tietel, Birgit Strodel and medical sciences and humanity [1]. Many antibiotics were discovered and developed for Olujide Olubiyi human use twenty years after the second world war [2]. This golden era (the 1940s to 1970s) is remembered for the rise of antibiotics in transforming human health by saving many lives Received: 10 April 2021 through the treatment of infectious diseases [2,3]. However, the few antibiotics developed Accepted: 2 June 2021 Published: 29 June 2021 after the period were derivatives of the existing ones. The situation was compounded by the sudden emergence of antibiotic-resistant pathogens [1,4]. This condition has resulted in Publisher’s Note: MDPI stays neutral a global burden of bacterial infections to a significant threat level, especially among those with regard to jurisdictional claims in pathogens, which cannot be controlled using the old classes of antimicrobial agents [5,6]. published maps and institutional affil- Therefore, there is a need for the discovery and development of novel antibiotics. iations. Natural products (NPs) have continued to gain relevance in the battlefront against infectious diseases. Newman and Cragg [7] studied the use of NPs as sources of novel drugs approved between 1981 and 2019. The authors concluded that these compounds have prospects for discovering new agents against various infectious diseases. An earlier study conducted by Seyed [8] also reported the potential of NPs as antimicrobial agents Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. acting against a wide range of human diseases. The efficient exploration of libraries of NPs This article is an open access article using modern drug discovery techniques, such as cheminformatic characterization can distributed under the terms and help identify potential antibiotics. conditions of the Creative Commons Several cheminformatic techniques have been developed and employed in drug dis- Attribution (CC BY) license (https:// covery, design, and development to reduce the research cycle and minimize the cost of creativecommons.org/licenses/by/ producing new anti-infective agents [9]. Generally, the cheminformatics approach to ratio- 4.0/). nal drug design involves the estimation of pharmacokinetic and toxic properties of potential Molecules 2021, 26, 3970. https://doi.org/10.3390/molecules26133970 https://www.mdpi.com/journal/molecules Molecules 2021, 26, 3970 2 of 18 drug candidates, with the prospect of minimizing the risk of future attrition [10–12]. Here, we reviewed natural products with antimicrobial activities and described the role of chem- informatics characterization in hit profiling, hit prioritization, and hit optimization for antimicrobial development. 2. Natural Products in Antimicrobial Drug Discovery Compounds sourced from natural products (NPs) have proven to be promising in the discovery and development of novel antimicrobial drugs [13,14]. These compounds are obtained from living organisms, such as bacteria, fungi, plants, and marine microorgan- isms [15,16]. Studies have reported that four-fifths of the population in most developing nations live on trado-medical practices as the primary source of treatment in essential healthcare services [17,18]. The approval of some NP-based therapies against a range of diseases, such as Alzheimer, cancer, diabetes, and other infections was extensively dis- cussed in another study [19]. Furthermore, three out of the five newly developed drugs by the United States Food and Drug Administration (FDA), representing novel classes of antibiotics between 1981 and 2010, were also sourced from NPs [20]. Therefore, there has been increasing interest in exploring and pursuing NPs as promising lead compounds in combating multidrug-resistant bacteria [18,21]. The antimicrobial potential of crude extracts and pure NPs has been studied by observ- ing the growth response of pathogens to samples. Table1 shows selected NPs with their reported bioactivity against some antimicrobial-resistant bacteria. The selection criteria of promising antimicrobial compounds are based on minimum inhibitory concentration (MIC) values of not more than 100 µg/mL and 25 µM for crude extract, and pure compounds, respectively [22–24]. Molecules 2021, 26, x FOR PEER REVIEW 3 of 19 Molecules 2021, 26, x FOR PEER REVIEW 3 of 19 Molecules 2021, 26, x FOR PEER REVIEW 3 of 19 Table 1. Selected natural products with their reported antimicrobial activity. Table 1. Selected natural products with their reported antimicrobial activity. Average Reported Natural Source of No of the MoleculesSN2021 , 26, 3970 Table 1.Structure Selected natural products with their reported antimicrobialPathogen activity. MICAverage Reference 3 of 18 Compound Compounds ReportedTested Strains Natural Source of (μAverageg/mL) No of the SN Structure Pathogen MIC Reference Compound Compounds ReportedValue Tested Strains Natural Table 1. Selected natural productsSource withof their reported antimicrobial(μg/mL) activity. No of the SN Structure Pathogen MIC Reference Compound Compounds Value Tested Strains Natural Source of (μg/mL) Average Reported No of the SN Structure Methicillin-Pathogen Reference Compound FruitsCompounds such as Value MIC (µg/mL) Value Tested Strains resistant 1 Resveratrol grapes, peanuts, Methicillin- 1.25 3 [25,26] Fruits such as Staphylococcus and cranberries resistant 1 Resveratrol grapes, peanuts, aureusMethicillin- (MRSA) 1.25 3 [25,26] FruitsFruits such such as grapes,as StaphylococcusMethicillin-resistant and cranberries resistant 11 ResveratrolResveratrol grapes,peanuts, peanuts, aureusStaphylococcus (MRSA) aureus1.25 3 1.25[25,26] 3 [25,26] Staphylococcus andand cranberries cranberries (MRSA) aureus (MRSA) Majorly found in 2 Pterostilbene fruits such as MRSA 0.078 2 [26,27] MajorlyMajorlyblueberries foundfound inin 22 PterostilbenePterostilbene fruitsfruits such such as MRSAMRSA 0.078 2 0.078[26,27] 2 [26,27] Majorly found in asblueberries blueberries 2 Pterostilbene fruits such as MRSA 0.078 2 [26,27] blueberries Molecules 2021, 26, x FOR PEER REVIEW7-amino-4-7-amino-4- Endophytic 4 of 19 33 Endophytic XylariaShigella flexneriShigellaflexneri 6.3 1 6.3[28] 1 [28] methylcoumarinmethylcoumarin Xylaria 7-amino-4- Endophytic 3 Shigella flexneri 6.3 1 [28] methylcoumarin Xylaria 7-amino-4- Endophytic 3 Shigella flexneri 6.3 1 [28] methylcoumarin Xylaria PlantsPlants 44 Quercetin MRSA MRSA31.2–125 29 31.2–125[29] 29 [29] (Guss(Guss extracts) extracts) Marine 5 Anthracimycin Bacillus anthracis 0.031 1 [30] actinobacteria Protocatechuic Plants and 6 Escherichia coli 1 1 [31] acid mushroom Plants (Juncaceae 7 Juncuenin D MRSA 12.5 1 [32] family) Molecules 2021, 26, x FOR PEER REVIEW 4 of 19 Molecules 2021, 26, x FOR PEER REVIEW 4 of 19 Molecules 2021, 26, x FOR PEER REVIEW 4 of 19 Plants 4 Quercetin MRSA 31.2–125 29 [29] Molecules 2021, 26, 3970 4 of 18 (GussPlants extracts) 4 Quercetin MRSA 31.2–125 29 [29] (GussPlants extracts) 4 Quercetin MRSA 31.2–125 29 [29] (Guss extracts) Table 1. Cont. Natural Source of Average Reported No of the SN Structure Pathogen Reference Compound CompoundsMarine MIC (µg/mL) Value Tested Strains 5 Anthracimycin Bacillus anthracis 0.031 1 [30] actinobacteriaMarine 5 Anthracimycin Bacillus anthracis 0.031 1 [30] actinobacteria MarineMarine 55 Anthracimycin Anthracimycin Bacillus anthracisBacillus anthracis0.031 1 0.031[30] 1 [30] actinobacteriaactinobacteria Protocatechuic Plants and 6 Escherichia coli 1 1
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