Chalcone Derivatives as Potential Inhibitors of P-Glycoprotein and NorA: An In Silico and In Vitro Study

Acridine-Based Chalcone 1C and ABC Transporters

Chalcones, potential anticancer agents, have shown promise in the suppression of multidrug resistance due to the inhibition of drug efflux driven by certain adenosine triphosphate (ATP)-binding cassette (ABC) transporters. The gene and protein expression of chosen ABC transporters (multidrug resistance protein 1, ABCB1; multidrug resistance-associated protein 1, ABCC1; and breast cancer resistance protein, ABCG2) in human colorectal cancer cells (COLO 205 and COLO 320, which overexpress active ABCB1) was mainly studied in this work under the influence of a novel synthetic acridine-based chalcone, 1C. While gene expression dropped just at 24 h, compound 1C selectively suppressed colorectal cancer cell growth and greatly lowered ABCB1 protein levels in COLO 320 cells at 24, 48, and 72 h. It also reduced ABCC1 protein levels after 48 h. Molecular docking and ATPase tests show that 1C probably acts as an allosteric modulator of ABCB1. It also lowered galectin-1 (GAL1) expression in COLO 205 cells at 24 h. Functional tests on COLO cells revealed ABCB1 and ABCC1/2 to be major contributors to multidrug resistance in both. Overall, 1C transiently lowered GAL1 in COLO 205 while affecting important functional ABC transporters, mostly ABCB1 and to a lesser extent ABCC1 in COLO 320 cells. COLO 320's absence of GAL1 expression points to a possible yet unknown interaction between GAL1 and ABCB1.

Discovery of drug transporter inhibitors tied to long noncoding RNA in resistant cancer cells; a computational model -in silico- study

Chemotherapeutic resistance is a major obstacle to chemotherapeutic failure. Cancer cell resistance involves several mechanisms, including epithelial-to-mesenchymal transition (EMT), signaling pathway bypass, drug efflux activation, and impairment of drug entry. P-glycoproteins (P-gp) are an efflux transporter that pumps chemotherapeutic drugs out of cancer cells, resulting in chemotherapeutic resistance. Several types of long noncoding RNA (lncRNAs) have been identified in resistant cancer cells, including ODRUL, MALAT1, and ANRIL. The high expression level of ODRUL is related to the induction of ATP-binding cassette (ABC) gene expression, resulting in the emergence of doxorubicin resistance in osteosarcoma. lncRNAs are observed to be regulators of drug transporters in cancer cells such as MALAT1 and ANRIL. Targeting P-gp expression using natural products is a new strategy to overcome cancer cell resistance and improve the sensitivity of resistant cells toward chemotherapies. This review validates the inhibitory effects of natural products on P-gp expression and activity using in silico molecular docking. In silico analysis showed that Delphinidin and Asparagoside-f are the most significant natural product inhibitors of p-glycoprotein-1. These inhibitors can reverse multi-drug resistance and induce the sensitivity of resistant cancer cells toward chemotherapy based on in silico molecular docking. It is important to validate that pre-elementary docking can be confirmed using in vitro and in vivo experimental data.

Discovery of novel flavonoid derivatives as potential dual inhibitors against α-glucosidase and α-amylase: virtual screening, synthesis, and biological evaluation

Diabetes mellitus is one of the top ten causes of death worldwide, accounting for 6.7 million deaths in 2021, and is one of the most rapidly growing global health emergencies of this century. Although several classes of therapeutic drugs have been invented and applied in clinical practice, diabetes continues to pose a serious and growing threat to public health and places a tremendous burden on those affected and their families. The strategy of reducing carbohydrate digestibility by inhibiting the activities of α-glucosidase and α-amylase is regarded as a promising preventative treatment for type 2 diabetes. In this study, we investigated the dual inhibitory effect against two polysaccharide hydrolytic enzymes of flavonoid derivatives from an in-house chemical database. By combining molecular docking and structure-activity relationship analysis, twelve compounds with docking energies less than or equal to - 8.0 kcal mol-1 and containing required structural features for dual inhibition of the two enzymes were identified and subjected to chemical synthesis and in vitro evaluation. The obtained results showed that five compounds exhibited dual inhibitory effects on the target enzymes with better IC50 values than the approved positive control acarbose. Molecular dynamics simulations were performed to elucidate the binding of these flavonoids to the enzymes. The predicted pharmacokinetic and toxicological properties suggest that these compounds are viable for further development as type 2 diabetes drugs.

Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery. Unfortunately, there is an evident gap between the number of machine learning applications in science and the effective implementation of these systems. This narrative review highlights some of the outstanding opportunities that machine learning offers when applied in research related to antimicrobial resistance. In the future, machine learning tools may prove to be superbugs' kryptonite. This review aims to provide an overview of available publications to aid researchers that are looking to expand their work with new approaches and to acquaint them with the current application of machine learning techniques in this field.

Potential of Flavonoids as Promising Phytotherapeutic Agents to Combat Multidrug-Resistant Infections

BACKGROUND

Considering the limited number of current effective treatments, Multidrug- Resistant (MDR) illnesses have grown to be a serious concern to public health. It has become necessary to look for new antimicrobial drugs because of the emergence of resistance to numerous kinds of antibiotics. The use of flavonoids is one phytotherapeutic strategy that has been researched as a potential remedy for this issue. Secondary plant compounds called flavonoids have been found to have an antibacterial effect against resistant microorganisms.

OBJECTIVE

This review seeks to give readers a glimpse into contemporary studies on flavonoids' potential to fight MDR infections.

METHODS

A systematic search was conducted on electronic databases (PubMed, Scopus, and Google Scholar) using relevant keywords such as flavonoids, MDR infections, antimicrobial activity, and resistance microbes. Studies that investigated the antimicrobial activity of flavonoids against resistant microbes were included in this review.

RESULTS

Most research found that flavonoids have antibacterial efficacy against resistant microorganisms, and some also showed that they have synergistic benefits with traditional antibiotics. The flavonoids quercetin, kaempferol, apigenin, and luteolin were the most often investigated ones. According to research, flavonoids affect microbial gene expression, inhibit microbial enzymes, and disrupt the integrity of microbial cell membranes. Additionally, a few studies have noted the flavonoids' low toxicity and safety.

CONCLUSION

For the treatment of infections that are resistant to many drugs, flavonoids constitute a promising class of phytotherapeutic agents. To develop flavonoid-based treatment methods for treating MDR illnesses and assess the potential of flavonoids as adjuvants to conventional antimicrobial drugs, more study is required.

The green chemistry of chalcones: Valuable sources of privileged core structures for drug discovery

The sustainable use of resources is essential in all production areas, including pharmaceuticals. However, the aspect of sustainability needs to be taken into consideration not only in the production phase, but during the whole medicinal chemistry drug discovery trajectory. The continuous progress in the fields of green chemistry and the use of artificial intelligence are contributing to the speed and effectiveness of a more sustainable drug discovery pipeline. In this light, here we review the most recent sustainable and green synthetic approaches used for the preparation and derivatization of chalcones, an important class of privileged structures and building blocks used for the preparation of new biologically active compounds with a broad spectrum of potential therapeutic applications. The literature here reported has been retrieved from the SciFinder database using the term "chalcone" as a keyword and filtering the results applying the concept: "green chemistry", and from the Reaxys database using the keywords "chalcone" and "green". For both databases the time-frame was 2017-2022. References were manually selected based on relevance.