Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the leading causes of bacterial infections in both healthcare and community settings. MRSA can acquire resistance to any current antibiotic, which has major implications for its current and future treatment options. As such, it is globally a major focus for infection control efforts. The mechanical rigidity provided by peptidoglycans in the bacteria cell walls makes it a promising target for broad-spectrum antibacterial drug discovery. The development of drugs that can target different stages of the synthesis of peptidoglycan in MRSA may compromise the integrity of its cell wall and consequently result in the rapid decline of diseases associated with this drug-resistant bacteria. The present study is aimed at screening natural products with known in vitro activities against MRSA to identify their potential to inhibit the proteins involved in the biosynthesis of the peptidoglycan cell wall. A total of 262 compounds were obtained when a literature survey was conducted on anti-MRSA natural products (AMNPs). Virtual screening of the AMNPs was performed against various proteins (targets) that are involved in the biosynthesis of the peptidoglycan (PPC) cell wall using Schrödinger software (release 2020-3) to determine their binding affinities. Nine AMNPs were identified as potential multitarget inhibitors against peptidoglycan biosynthesis proteins. Among these compounds, DB211 showed the strongest binding affinity and interactions with six protein targets, representing three stages of peptidoglycan biosynthesis, and thus was selected as the most promising compound. The MD simulation results for DB211 and its proteins indicated that the protein-ligand complexes were relatively stable over the simulation period of 100 ns. In conclusion, DB211 showed the potential to inhibit six proteins involved in the biosynthesis of the peptidoglycan cell wall in MRSA, thus reducing the chance of MRSA developing resistance to this compound. Therefore, DB211 provided a starting point for the design of new compounds that can inhibit multiple targets in the biosynthesis of the peptidoglycan layer in MRSA.

The growing antimicrobial resistance (AMR) of pathogenic organisms to currently prescribed 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.

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.

Background/Objectives: Cancer and bacterial cases are increasing. Hence, new drugs to treat these diseases are paramount. Ferrocene-based hybrid compounds were synthesizedas potential cancer and bacteria therapeutics. Methods: The synthesized compounds were characterized via FTIR, NMR, and LC-MS and evaluated against different cancer cells and bacterial strains. Moreover, computational studies of these compounds were conducted using several silico tools. Results: Among the synthesized compounds, hybrid 10 was the most promising compound, displaying promising anticancer activity with IC₅₀ values between 42.42 and 45.37 and 50.64 and 73.37 µg/mL against HeLa and CHO cancer cells, respectively, with a selective index greater than one on HeLa cancer cells. Compounds 22–26 displayed promising antibacterial activity with a MIC value of 7.8125 µg/mL against most bacterial strains in vitro. The in silico results revealed that this compound has strong binding affinities for 4qtb, 3eqm, and 2w3l cervical cancer proteins, exhibiting binding energies of −7.3, −8.7, and 7.4 kcal/mol, respectively. Furthermore, hybrid 10 showed promising pharmacokinetics and drug-like properties, including high GI absorption, moderate water solubility, favoring the oral administration route, nontoxicity, and is a P-gp substrate. Conclusions: The findings obtained in this study illustrate that hybrid compounds are potential therapeutics that need to be explored. The compounds also contained functionalities relevant for incorporating into nanocarriers to improve their biological activities further. Therefore, further studies are recommended for the most effective compounds to reinforce these findings.

The evolution of antibiotic‐resistant carbapenemase has negatively impacted the management of critical healthcare‐associated infections.K. pneumoniaecarbapenemase‐2‐ (KPC‐2‐) expressing bacteria have developed resistance to conventional therapeutic options, including those used as a last resort for life‐threatening diseases. In this study,Ehretiaspecies phytoconstituents were screened for their potential to inhibit KPC‐2 protein usingin silicoapproaches. Molecular docking was used to identify strong KPC‐2 protein binding phytoconstituents retrieved from the literature. The best‐docked conformation of the ligands was selected based on their glide energy and binding interactions. To determine their binding free energies, these hit compounds were subjected to molecular mechanics with generalized born and surface area (MM‐GBSA) in the PRIME module. Pharmacological assessments of the ligands were performed to evaluate their drug‐likeness. Molecular dynamic (MD) simulations were used to analyze the conformational stability of the selected druglike compounds within the active site of the KPC‐2 protein. Overall, a total of 69 phytoconstituents were compiled from the literature. Fourteen of these compounds exhibited a stronger binding affinity for the protein target than the reference drugs. Four of these top hit compounds, DB09, DB12, DB28, and DB66, revealed the highest efficacy in terms of drug‐likeness properties. The MD simulation established that among the druglike compounds, DB66 attained stable conformations after 150 ns simulation in the active site of the protein. We concluded that DB66 fromEhretiaspecies could play a significant role in therapeutic efforts against KPC‐2‐expressing bacteria.