Biology subjects

Chen, S. A.

Publications and source records attributed to Chen, S. A..

3 recordsLinked to original sources

bioRxiv2023

SARS-CoV-2 Mpro protease variants of concern display altered viral and host target processing but retain potency towards antivirals

Main protease of SARS-CoV-2 (Mpro) is the most promising drug target against coronaviruses due to its essential role in virus replication. With newly emerging variants there is a concern that mutations in Mpro may alter structural and functional properties of protease and subsequently the potency of existing and potential antivirals. We explored the effect of 31 mutations belonging to 5 variants of concern (VOC) on catalytic parameters and substrate specificity, which revealed changes in substrate binding and rate of cleavage of a viral peptide. Crystal structures of 11 Mpro mutants provided structural insight into their altered functionality. Additionally, we show Mpro mutations influence proteolysis of an immunomodulatory host protein Galectin-8 (Gal-8) and subsequent significant decrease in cytokine secretion, providing evidence for alterations in escape of host-antiviral mechanisms. Accordingly, mutations associated with the highly virulent Delta VOC resulted in significant increase in Gal-8 cleavage. Importantly, IC50s of nirmatrelvir (Pfizer) and our irreversible inhibitor AVI-8053 demonstrated no changes in potency for both drugs for all mutants, suggesting Mpro will remain a high-priority antiviral drug candidate as SARS-CoV-2 evolves.

biochemistry↗

bioRxiv2020

-SATA: A MATLAB based toolbox to estimate Current Density generated by Transcranial Direct Current Stimulation in an Individual Brain

BackgroundTranscranial Direct Current Stimulation (tDCS) is a technique where a weak current is passed through the electrodes placed on the scalp. The distribution of the electric current induced in the brain due to tDCS is provided by simulation toolbox like Realistic-volumetric-Approach-based-Simulator-for-Transcranial-electric-stimulation (ROAST). However, the procedure to estimate the total current density induced at the target and the intermediary region of the cortex is complex. The Systematic-Approach-for-tDCS-Analysis (SATA) was developed to overcome this problem. However, SATA is limited to standardized headspace only. Here we develop individual-SATA (-SATA) to extend it to individual head. MethodT1-weighted images of 15 subjects were taken from two Magnetic Resonance Imaging (MRI) scanners of different strengths. Across the subjects, the montages were simulated in ROAST. -SATA converts the ROAST output to Talairach space. The x, y and z coordinates of the anterior commissure (AC), posterior commissure (PC), and Mid-Sagittal (MS) points are necessary for the conversion. AC and PC are detected using the acpcdetect toolbox. We developed a method to determine the MS in the image and cross-verified its location manually using BrainSight(R). ResultDetermination of points with -SATA is fast and accurate. The -SATA provided estimates of the current-density induced across an individuals cortical lobes and gyri as tested on images from two different scanners. ConclusionResearchers can use -SATA for customizing tDCS-montages. With -SATA it is also easier to compute the inter-individual variation in current-density across the target and intermediary regions of the brain. The software is publicly available.

neuroscience↗

bioRxiv2019

Maximizing Dissimilarity in Resting State detects Heterogeneous Subtypes in Healthy population associated with High Substance-Use and Problems in Antisocial Personality

Patterns in resting-state fMRI (rs-fMRI) are widely used to characterize the trait effects of brain function. In this aspect, multiple rs-fMRI scans from single subjects can provide interesting clues about the rs-fMRI patterns, though scan-to-scan variability pose challenges. Therefore, rs-fMRIs are either concatenated or the functional connectivity is averaged. This leads to loss of information. Here, we use an alternative way to extract the rs-fMRI features that are common across all the scans by applying Common-and-Orthogonal-Basis-Extraction (COBE) technique. To address this, we employed rs-fMRI of 788 subjects from the human connectome project and estimated the common-COBE-component of each subject from the four rs-fMRI runs. Since the common-COBE-component are specific to a subject, the pattern was used to classify the subjects based on the similarity/dissimilarity of the features. The subset of subjects (n=107) with maximal-COBE-Dissimilarity (MCD) was extracted and the remaining subjects (n = 681) formed the COBE-similarity (CS) group. The distribution of weights of the common-COBE-component for the two groups across rs-fMRI networks and subcortical regions was evaluated. We found the weights in the default mode network to be lower in the MCD compared to the CS. We compared the scores of 69 behavioral measures and found 6 behaviors related to the use of marijuana, illicit drugs, alcohol, and tobacco; and including a measure of antisocial personality to differentiate the two groups. Gender differences were also significant. Altogether findings suggested that subtypes exist even in healthy control population and comparison studies (Case vs Control) need to be mindful of it.

neuroscience↗