Cheminformatic Approaches to Hit-Prioritization and Target Prediction of Potential Anti-MRSA Natural Products
Samson O. Oselusi · University of the Western Cape Electronic Theses and Dissertations Repository (University of the Western Cape) · 2020
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 costeffective 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.This was followed by the prioritization of hits and identification of the liabilities among the AMNPs for possible optimization.Reverse molecular docking was used to predict the possible targets of these natural compounds based on their predicted free binding energy to 34 selected druggable targets in MRSA.The results for the cheminformatics profiling revealed that most of the AMNPs were within the required drug-like space of the investigated properties.The AMNPs (up to 80 %) showed good compliance with the Lipinski, Veber, and Egan predictive rules for oral absorption and permeability.About 30 % of the AMNPs showed prospects to penetrate the blood-brain barrier.Conversely, only 50 to 60 % of the CDs complied with these predictive rules for oral absorption and permeability, and none of the CDs showed the likelihood to pass through the blood-brain barrier.Good oral absorption and permeability are desirable to achieve the desired plasma concentration of the AMNPs, which is a prerequisite to their effectiveness.Regarding the effect on cytochromeP450 (CYP450) enzymes, 16 to 43 % AMNPs were predicted as inhibitors of one or more CYP450 enzymes.CYP450 enzyme inhibitors might be http://etd.uwc.ac.za/ v given less consideration during hit-prioritization and selection because of the potential to interact with other drugs.The analysis of toxicity revealed that 80 and 59 % of the CDs and AMNPs respectively, might have low or no toxicity risks.Hit-prioritization strategy using a novel "desirability scoring function" revealed that the AMNPs with the desired drug-likeness showed the best score.Hit-optimization strategies implemented on AMNPs with poor desirability scores led to the design of two compounds with improved desirability scores and good synthetic accessibility scores.Evaluation of the structural-activity relationship of the AMNPs revealed chemical groups that may be the determinants of the reported bioactivity of the compounds.Regarding druggable target prediction, more than two-thirds of the compounds revealed a sufficient free binding energy (≤ -6 kcal/mol) for all the investigated targets (proteins) involved in fatty acid metabolism.The results also showed that some of the AMNPs might have multiple druggable targets.Prediction of the potential targets of the AMNPs provides a hypothesis for the mechanism of action of the AMNPs.Overall, this study has mined the available bioactivity data and predicted properties of the AMNPs to gain the knowledge for rational AMNPs hit-prioritization and implementation of hit-optimization strategies.This could also be the crucial starting point for the development of drug candidates against MRSA infections from natural compounds.http: