Round up of research articles published in Aug 2023
Autophagy and AlphaFold2
Until recently, understanding how proteins in our cells work together has been like exploring uncharted territory. But now, thanks to AlphaFold2 (AF2), things have changed. AF2 uses artificial intelligence to guess the structure of proteins accurately. This means we can now look at the structures of lots of proteins in our cells.
In this study, the authors looked at how well AF2 can predict the structures of 38 key proteins involved in autophagy and 378 other proteins that interact with them. Before AF2, only half of these proteins’ structures could be studied in detail.
They also used computer simulations to understand how some of these proteins move and behave. For example, they looked at a protein called ATG2A, it was found to be rod shaped and predicted to have a function in lipid transport. They also studied a group of proteins called ATG7-ATG10, which play a crucial role in autophagy. It was discovered that the complex holds together because of the presence of salt bridges.
They have also developed a web resource where scientists can find all the structures and associated functional predictions discovered with AF2. This will help other scientists study autophagy.
-By ChatGPT
AI-based AlphaFold2 significantly expands the structural space of the autophagy pathway
Cdk5 and neurodegeneration in diabetes
Various proteins and enzymes have been identified that help in modifying the connections between neurons called synaptic plasticity, which is important for learning and memory. Cdk5 is one such enzyme. How the increased activity of Cdk5 leads to neuronal death and neurodegeneration is not understood. It is essential to understand because this hyperactivity is seen in diabetes where cognitive impairment and neurodegeneration is also observed.
The authors identified the pathway that leads to hyperactivity of this kinase in a neuronal cell line. Oxidative stress mediated increased activity of Cdk5 led to ER stress and activation of the unfolded protein response. Thus, antioxidants like Glutathione and N-acetyl Cysteine should have the potential to rescue neurons by removing the stimulus that causes hyperactivity of Cdk5. This was shown by the authors in a Type 2 diabetes mouse model, thus highlighting the need for further studies as antioxidants like glutathione and N-acetyl cysteine holds potential for treatment of other diseases which share the Cdk5 mediated neurodegeneration process.
-By the core team
Potential drug for acne
Cutibacterium acnes, a culprit in acne, thrives by breaking down compounds on white blood cells’ surfaces. Antibiotics used for acne have negative side effects.
The authors explored 1030 FDA-approved drugs to find inhibitors for a key virulence factor (sialidase). Naloxone, fenoldopam, labetalol, and thalitone stood out with strong binding energies. Molecular simulations confirmed naloxone’s stability and affinity. These findings suggest FDA drugs, especially naloxone, could serve as potential sialidase inhibitors for acne treatment. – By ChatGPT
Alu repeats and COVID-19
The COVID-19 pandemic has shown that the illness can affect people in many different ways. This suggests that various factors play a role in how the disease develops and how it might turn out for each person. While some research has looked into how the body’s immune system responds to the virus and how it can go wrong in severe cases, most of these studies have focused only on genes.
However, viruses, especially RNA viruses like SARS-CoV-2 (the virus causing COVID-19), are known for using the body’s machinery to replicate themselves. This can have unintended effects on the gene expression patterns of the host. In this study, the authors have looked at how the virus affects the transcriptome, especially the splicing machinery and the various isoforms synthesized from the same genes.
The authors found that in people who didn’t survive COVID-19, there were fewer transcript isoforms, and certain repetitive elements (Alu) near the promoter site of genes and splicing sites seemed to play a role in controlling how genes were expressed. This could help us understand how severe the disease might become for a person and what the outcome might be.
-By ChatGPT
The story of miRNA and resveratrol in lungs
Exposure to air pollutants causes damage to lungs leading to fibrosis, where the levels of extracellular matrix proteins like collagen, and fibronectin go up, thereby affecting the functioning of lungs and causing respiratory disorders. The present study used the identification of miRNA based approach to find potential drugs for reversing the process of fibrosis.
The authors used a mouse model to identify the miRNAs which get differentially expressed after diesel exhaust exposure. They further identified one of the enzymes that was being targeted by miR-213-3p, one of miRNAs that was found to be upregulated.
By using an antioxidant – resveratrol in the mouse model, the levels of extracellular matrix proteins could be brought down, along with the reversal of fibrosis. The same molecular players that were found to be influenced by miR-213-3p were found to be affected. Thus, the therapeutic role of resveratrol needs to be further investigated for respiratory diseases occurring because of fibrosis. -By core team
Predicting effective epilepsy medication
Epilepsy is a disease that presents with a variety of symptoms that vary from individual to individual and that becomes a challenge in choosing a specific anti-epileptic medicine (anti-seizure medication).
There are known genetic variants that influence the effectiveness of anti-seizure medication. The current study utilized a data mining approach, where a literature search was conducted to identify the known variants that are associated with anti-seizure medication response.
They identified nine different variants that can be pursued further for their potential in choosing an effective method of treatment for epilepsy. -By core team
Assessment of clinically actionable pharmacogenetic markers to stratify anti-seizure medications
Potential dengue diagnostics
Prevalence of dengue infections is high in countries like India. The disease response is highly variable, with severe disease leading to high mortality.
To delineate viral load and identify disease severity, the present study used a RNAseq based approach to look at the host response at the level of gene expression.
They identified two sets of genes that get affected because of dengue infection. The specific transcripts can serve as indicators of the viral load to predict severity of the infection. In addition, they also identified that high neutrophils and low lymphocytes are a signature that can help identify the infection early.
Together these findings can help in early disease diagnosis and prediction of the disease severity. -By core team