Deep-learning based repurposing of FDA-approved drugs against Candida albicans dihydrofolate reductase and molecular dynamics study

A beginner's approach to deep learning applied to VS and MD techniques

It has become impossible to imagine the fields of biochemistry and medicinal chemistry without computational chemistry and molecular modelling techniques. In many steps of the drug development process in silico methods have become indispensable. Virtual screening (VS) can tremendously expedite the early discovery phase, whilst the use of molecular dynamics (MD) simulations forms a powerful additional tool to in vitro methods throughout the entire drug discovery process. In the field of biochemistry, MD has also become a compelling method for studying biophysical systems (e.g., protein folding) complementary to experimental techniques. However, both VS and MD come with their own limitations and methodological difficulties, from hardware limitations to restrictions in algorithmic capabilities. One solution to overcoming these difficulties lies in the field of machine learning (ML), and more specifically deep learning (DL). There are many ways in which DL can be applied to these molecular modelling techniques to achieve more accurate results in a more efficient manner or expedite the data analysis of the acquired results. Despite steadily increasing interest in DL amidst computational chemists, knowledge is still limited and scattered over different resources. This review is aimed at computational chemists with knowledge of molecular modelling, who wish to possibly integrate DL approaches in their research and already have a basic understanding of the fundamentals of DL. This review focusses on a survey of recent applications of DL in molecular modelling techniques. The different sections are logically subdivided, based on where DL is integrated in the research: (1) for the improvement of VS workflows, (2) for the improvement of certain workflows in MD simulations, (3) for aiding in the calculations of interatomic forces, or (4) for data analysis of MD trajectories. It will become clear that DL has the capacity to completely transform the way molecular modelling is carried out.

Repurposing and optimization of drugs for discovery of novel antifungals

Although fungal diseases are a major and growing public health concern, there are only four major classes of drug to treat primary fungal pathogens. The pipeline of new antifungals in clinical development is relatively thin compared with other disease classes. One approach to rapidly identify and provide novel treatment options is to repurpose existing drugs as antifungals. However, such proposed drug-repurposing candidates often suffer suboptimal efficacy and pharmacokinetics (PK) for fungal diseases. Herein, we briefly review the current antifungal drug pipeline and recent approaches to optimize existing drugs into novel molecules with unique modes of action relative to existing antifungal drug classes.

Antifungal activity of 2-Chloro-N-phenylacetamide, docking and molecular dynamics studies against clinical isolates of Candida tropicalis and Candida parapsilosis

AIMS

This study evaluated the antifungal, antibiofilm, and molecular docking of 2-Chloro-N-phenylacetamide against clinical isolates of Candida tropicalis and Candida parapsilosis.

METHODS AND RESULTS

MIC of the test drugs was determined by microdilution. A1Cl obtained MIC values ranging from 16 and 256 μg/mL. Fluconazole MIC ranging from 16 and 512 μg/mL. MIC of A1Cl showed fungicide activity, emphasizing the solid antifungal potential of this drug. An association study was performed with A1Cl and fluconazole (checkerboard), revealing indifference by decreasing. Thus, we conducted this study using A1Cl isolated. In the micromorphological assay, the test drugs reduced the production of virulence structures compared to the control (concentration-dependent effect). A1Cl inhibited in vitro biofilm formation at all concentrations tested (1/4MIC to 8xMIC) (p<0.05) and reduced mature biofilm biomass (p<0.05) against C. tropicalis and C. parapsilosis. In the ex vivo biofilm susceptibility testing (human nails fragments), A1Cl inhibited biofilm formation and reduced mature biofilm biomass (p<0.05) more than 50% at MIC. Fluconazole had a similar effect at 4xMIC. In silico studies suggest that the mechanism of antifungal activity of A1Cl involves the inhibition of the enzyme dihydrofolate reductase rather than geranylgeranyltransferase-I.

CONCLUSIONS

The results suggest that A1Cl is a promising antifungal agent. Furthermore, this activity is related to attenuation of expression of virulence factors and antibiofilm effects against C. tropicalis and C. parapsilosis.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our study provides the first evidence that A1Cl, a novel synthetic drug, has fungicidal effects against C. tropicalis and C. parapsilosis. Furthermore, in vitro and ex vivo biofilms assays have demonstrated the potential antibiofilm of A1Cl. The mechanism of action involves inhibiting the enzyme dihydrofolate reductase, which was supported by in silico analyses. Therefore, this potential can be explored as a therapeutic alternative for onychomycosis and, at the same time, contribute to decreasing the resistance of clinical isolates of C. tropicalis and C. parapsilosis.

Functionalized Dendrimer Platforms as a New Forefront Arsenal Targeting SARS-CoV-2: An Opportunity

The novel human coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has caused a pandemic. There are currently several marketed vaccines and many in clinical trials targeting SARS-CoV-2. Another strategy is to repurpose approved drugs to decrease the burden of the COVID-19 (official name for the coronavirus disease) pandemic. as the FDA (U.S. Food and Drug Administration) approved antiviral drugs and anti-inflammatory drugs to arrest the cytokine storm, inducing the production of pro-inflammatory cytokines. Another view to solve these unprecedented challenges is to analyze the diverse nanotechnological approaches which are able to improve the COVID-19 pandemic. In this original minireview, as promising candidates we analyze the opportunity to develop biocompatible dendrimers as drugs themselves or as nanocarriers against COVID-19 disease. From the standpoint of COVID-19, we suggest developing dendrimers as shields against COVID-19 infection based on their capacity to be incorporated in several environments outside the patients and as important means to stop transmission of SARS-CoV-2.