Cheminformatic Profiling and Hit Prioritization of Natural Products with Activities against Methicillin-Resistant Staphylococcus aureus (MRSA)

Abstract

Several natural products (NPs) have displayed varying in vitro activities against methicillin-resistant Staphylococcus aureus (MRSA). However, few of these compounds have not been developed into potential antimicrobial drug candidates. This may be due to the high cost and tedious and time-consuming process of conducting the necessary preclinical tests on these compounds. In this study, cheminformatic profiling was performed on 111 anti-MRSA NPs (AMNPs), using a few orally administered conventional drugs for MRSA (CDs) as reference, to identify compounds with prospects to become drug candidates. This was followed by prioritizing these hits and identifying the liabilities among the AMNPs for possible optimization. Cheminformatic profiling revealed that most of the AMNPs were within the required drug-like region of the investigated properties. For example, more than 76% of the AMNPs showed compliance with the Lipinski, Veber, and Egan predictive rules for oral absorption and permeability. About 34% of the AMNPs showed the prospect to penetrate the blood–brain barrier (BBB), an advantage over the CDs, which are generally non-permeant of BBB. The analysis of toxicity revealed that 59% of the AMNPs might have negligible or no toxicity risks. Structure–activity relationship (SAR) analysis revealed chemical groups that may be determinants of the reported bioactivity of the compounds. A hit prioritization strategy using a novel “desirability scoring function” was able to identify AMNPs with the desired drug-likeness. Hit optimization strategies implemented on AMNPs with poor desirability scores led to the design of two compounds with improved desirability scores.

In Vitro Evaluation of the Anti-Diabetic Potential of Aqueous Acetone Helichrysum petiolare Extract (AAHPE) with Molecular Docking Relevance in Diabetes Mellitus

“…Lipinski’s rule of five, referred to as Pfizer’s rule, is one of the techniques used to evaluate the drug-likeness of a chemical compound as it delineates the relationship between pharmacokinetics and physicochemical parameters. It determines the potential of the biological activities or pharmacological properties of a chemical compound and its effectiveness as an oral drug in humans [ 39 , 40 ]. We adhered to compounds with no violations or a minimum of a single violation, as violations of two or more indicate that drug candidates may not be orally active [ 40 , 41 ].…”

“…It determines the potential of the biological activities or pharmacological properties of a chemical compound and its effectiveness as an oral drug in humans [ 39 , 40 ]. We adhered to compounds with no violations or a minimum of a single violation, as violations of two or more indicate that drug candidates may not be orally active [ 40 , 41 ]. Hence, compounds with predicted poor oral absorption but high potency, as revealed in the Supplementary Materials , could be improved upon using an optimized absorption enhancement approach in future research.…”

“…Essentially, CYP and P-glycoprotein (P-gp) offer protection to tissues and organisms by processing molecules or drugs synergistically. The inhibition of CYP connotes a significant cause of pharmacokinetics-related drug–drug interactions, with increased toxicity and unwanted side effects predominating because of the reduced clearance and bioaccumulation effect of the drug or metabolite [ 40 , 42 ]. In drug discovery and development, potential drug candidates with unfavourable absorption, distribution, metabolism, and elimination (ADME) parameters are disqualified from clinical trials [ 31 ].…”

“…In the field of drug discovery and development, both experimental and computational strategies are valid and complimentary. The use of information from chemical and biological entities, such as ligands or targets, in the identification and optimization of new drugs, the elimination of compounds with undesirable characteristics (poor activity and/or poor absorption, distribution, metabolism, excretion, and toxicity (ADMET)), and ensuring that the process of drug discovery and development is streamlined are benefits of computational techniques [ 31 , 40 , 48 ]. Overall, enriched compounds with drug-likeness, lead-likeness, active qualities, and elimination of molecules with inactive, reactive, toxic, or poor ADMET/PK properties are highly desired in drug discovery and development [ 32 , 40 , 48 ].…”

Computational Target-Based Screening of Anti-MRSA Natural Products Reveals Potential Multitarget Mechanisms of Action through Peptidoglycan Synthesis Proteins

“…The identification of compounds that can target different stages of the biosynthesis of peptidoglycan cell wall may result in the 22 To update the data set, a further literature search, using the same keywords and search strategies described in the study was used to identify other recent studies that reported natural products with activities against MRSA. 22 In all, a sum of 262 anti-MRSA natural products (AMNPs) sourced from plants, marine organisms and microorganisms was used in this study. The Simplified Molecular Input Line Entry System (SMILES) structures of the AMNPs and their respective bioactivity data were retrieved and stored as text files (Table S1).…”