Sulfonamides: Antiviral Strategy for Neglected Tropical Disease Virus

Sulfonamides as anticancer agents: A brief review on sulfonamide derivatives as inhibitors of various proteins overexpressed in cancer

Sulfonamides have gained prominence as versatile agents in cancer therapy, effectively targeting a spectrum of cancer-associated enzymes. This review provides an extensive exploration of their multifaceted roles in cancer biology. Sulfonamides exhibit adaptability by acting as tyrosine kinase inhibitors, disrupting pivotal signaling pathways in cancer progression. Moreover, they disrupt pH regulation mechanisms in cancer cells as carbonic anhydrase inhibitors, inhibiting growth, and survival. Sulfonamides also serve as aromatase inhibitors, interfering with estrogen synthesis in hormone-driven cancers. Inhibition of matrix metalloproteinases presents an opportunity to impede cancer cell invasion and metastasis. Additionally, their emerging role as histone deacetylase inhibitors offers promising prospects in epigenetic-based cancer therapies. These diverse roles underscore sulfonamides as invaluable tools for innovative anti-cancer treatments, warranting further exploration for enhanced clinical applications and patient outcomes.

Diazotization-Enabled Deaminative Late-Stage Functionalization of Primary Sulfonamides

We, for the first time, disclosed a simple and efficient strategy for the late-stage functionalization of primary sulfonamides by diazotization, leading to sulfonyl chlorides, sulfonates, and complex sulfonamides. This protocol obviates the requirement for the prefunctionalization of sulfonamides. Its applicability is exemplified by the late-stage functionalization of sulfonamide-type drugs.

Conjugates of ibuprofen inhibit CHIKV infection and inflammation

Chikungunya virus infection has become a global health concern because of its high rates of morbidity and mortality in patients with preexisting conditions. Inflammation and arthritis are the major symptoms of CHIKV that persist even after clearance of CHIKV. To develop an antiviral that can reduce infection and manage inflammation independent of the CHIKV infection, ibuprofen (IBU) conjugates with sulfonamide and thiosemicarbazide were synthesized. The conjugates, IBU-SULFA, IBU-ISS and IBU-IBT significantly inhibited CHIKV infection in vitro with a selectivity index (CC₅₀/IC₅₀) of > 11.9, > 25.1 and > 21, respectively. The reduction in infection was attributed to the interference of the conjugates in the early stages of CHIKV life cycle. With no acute oral toxicity, these compounds significantly reduced inflammation and arthritis in rats. Unlike IBU, the conjugates were not ulcerogenic. In conclusion, the conjugation imparted anti-CHIKV properties while retaining the anti-inflammatory properties of IBU. These findings can encourage further validation and research to develop an antiviral for CHIKV to manage both infection and arthritis.

Synthesis and Antimicrobial Activity of New Heteroaryl(aryl) Thiazole Derivatives Molecular Docking Studies

Herein, we report the design, synthesis, and evaluation of the antimicrobial activity of new heteroaryl (aryl) thiazole derivatives. The design was based on a molecular hybridization approach. The in vitro evaluation revealed that these compounds demonstrated moderate antibacterial activity. The best activity was achieved for compound 3, with MIC and MBC in the range of 0.23–0.7 and 0.47–0.94 mg/mL, respectively. Three compounds (2, 3, and 4) were tested against three resistant strains, namely methicillin resistant Staphylococcus aureus, P. aeruginosa, and E. coli, which showed higher potential than the reference drug ampicillin. Antifungal activity of the compounds was better with MIC and MFC in the range of 0.06–0.47 and 0.11–0.94 mg/mL, respectively. The best activity was observed for compound 9, with MIC at 0.06–0.23 mg/mL and MFC at 0.11–0.47 mg/mL. According to docking studies, the predicted inhibition of the E. coli MurB enzyme is a putative mechanism of the antibacterial activity of the compounds, while inhibition of 14a-lanosterol demethylase is probably the mechanism of their antifungal activity.

Synthesis and biological evaluation of N-alkyl sulfonamides derived from polycyclic hydrocarbon scaffolds using a nitrogen-centered radical approach

Polycyclic hydrocarbons (PH) provide intriguing potential as lipophilic scaffolds within medicinal chemistry, but are currently limited by the availability of synthetic tools for predictable modification of the PH unit. Herein we report the development of new methods for installation of a sulfonamide unit to PH cores. In the first method, a xanthate ester serves as reagent for aminosulfonation using pre-formed imidoiodinane as N-source. An investigation of the reaction mechanism was performed to implicate a process involving a N-centered radical. An additional method for sulfonamide installation is described that involves the use of commercially available reagents and operationally convenient conditions. Using the new synthetic methods, 22 compounds were prepared and screened for biological activity against 6 mammalian cell lines along with Gram-positive and Gram-negative bacterial strains. Results of the viability assays have identified compounds that exhibit higher potency than other known anticancer agents such as indisulam and ABT-751. Additionally, the physicochemical and drug-likeness properties of the synthesized compounds have been determined experimentally and using in silico predictive tools. The initial exploration into sulfonamide insertion into PH cores has resulted in a number of compounds that warrant further development to produce molecules with therapeutic value.

Anti-COVID-19 activity of some benzofused 1,2,3-triazolesulfonamide hybrids using in silico and in vitro analyses

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a pandemic fatal infection with no known treatment. The severity of the disease and the fast viral mutations forced the scientific community to search for potential solution. Here in the present manuscript, some benzofused1,2,3triazolesulfonamide hybrids were synthesized and evaluated for their anti- SARS-CoV-2 activity using in silico prediction then the most potent compounds were assessed using in-Vitro analysis. The in-Silico study was assessed against RNA dependent RNA polymerase, Spike protein S1, Main protease (3CLpro) and 2'-O-methyltransferase (nsp16). It was found that 4b and 4c showed high binding scores against RNA dependent RNA polymerase reached -8.40 and -8.75 ​kcal/mol, respectively compared to the approved antiviral (remdesivir -6.77 ​kcal/mol). Upon testing the binding score with SARS-CoV-2 Spike protein it was revealed that 4c exhibited the highest score (-7.22 ​kcal/mol) compared to the reference antibacterial drug Ceftazidime (-6.36 ​kcal/mol). Surprisingly, the two compounds 4b and 4c showed the highest binding scores against SARS-CoV-2 3CLpro (-8.75, -8.48 ​kcal/mol, respectively) and nsp16 (- 8.84 and - 8.89 ​kcal/mol, respectively) displaying many types of interaction with all the enzymes binding sites. The derivatives 4b and 4c were examined in vitro for their potential anti-SARS-CoV-2 and it was revealed that 4c was the most promising compound with IC50 reached 758.8108 ​mM and complete (100%) inhibition of the binding of SARS-CoV-2 virus to human ACE2 can be accomplished by using 0.01 ​mg.

Machine learning enabled identification of potential SARS-CoV-2 3CLpro inhibitors based on fixed molecular fingerprints and Graph-CNN neural representations

Aim

Rapidly developing AI and machine learning (ML) technologies can expedite therapeutic development and in the time of current pandemic their merits are particularly in focus. The purpose of this study was to explore various ML approaches for molecular property prediction and illustrate their utility for identifying potential SARS-CoV-2 3CLpro inhibitors.

Materials and methods

We perform a series of drug discovery screenings based on supervised ML models operating in different ways on molecular representations, encompassing shallow learning methods based on fixed molecular fingerprints, Graph Convolutional Neural Network (Graph-CNN) with its self-learned molecular representations, as well as ML methods based on combining fixed and Graph-CNN learned representations.

Results

Results of our ML models are compared both with respect to the aggregated predictive performance in terms of ROC-AUC based on the scaffold splits, as well as on the granular level of individual predictions, corresponding to the top ranked repurposing candidates. This comparison reveals both certain characteristic homogeneity regarding chemical and pharmacological classification, with a prevalence of sulfonamides and anticancer drugs, as well as identifies novel groups of potential drug candidates against COVID-19.

Conclusions

A series of ML approaches for molecular property prediction enables drug discovery screenings, illustrating the utility for COVID-19. We show that the obtained results correspond well with the already published research on COVID-19 treatment, as well as provide novel insights on potential antiviral characteristics inferred from in vitro data.

AI drug discovery screening for COVID-19 reveals zafirlukast as a repurposing candidate

AIMS

Over the past few years, AI has been considered as potential important area for improving drug development and in the current urgent need to fight the global COVID-19 pandemic new technologies are even more in focus with the hope to speed up this process. The purpose of our study was to identify the best repurposing candidates among FDA-approved drugs, based on their predicted antiviral activity against SARS-CoV-2.

MATERIALS AND METHODS

This article describes a drug discovery screening based on a supervised machine learning model, trained on in vitro data encoded in chemical fingerprints, representing particular molecular substructures. Predictive performance of our model has been evaluated using so-called scaffold splits offering a state-of-the-art setup for assessing model's ability to generalize to new chemical spaces, critical for drug repurposing applications.

KEY FINDINGS

Our study identified zafirlukast as the best repurposing candidate for COVID-19.

SIGNIFICANCE

Zafirlukast could be potent against COVID-19 both due to its predicted antiviral properties and its ability to attenuate the so called cytokine storm. Thus, these two critical mechanisms of action may be combined in one drug as a novel and promising pharmacotherapy in the current pandemic.