Biology subjects

Sathyamoorthy, B.

Publications and source records attributed to Sathyamoorthy, B..

2 recordsLinked to original sources

bioRxiv2022

Why are G-quadruplexes good at preventing protein aggregation?

Maintaining a healthy protein folding environment is essential for cellular function. Recently, we found that nucleic acids, and G-quadruplexes in particular, are potent chaperones for preventing protein aggregation. With the aid of structure-function and NMR analyses of two G-quadruplex forming sequences, PARP-I and LTR-III, we uncovered several contributing factors that affect G-quadruplexes in preventing protein aggregation. Notably, three factors emerged as vital in determining holdase activity of G-quadruplexes: their structural topology, structural dynamics, and oligomerization state. These factors together appear to largely dictate whether a G-quadruplex is able to prevent partially misfolded proteins from aggregating. Understanding the genesis of G-quadruplexes power as chaperones is an important facet to elucidating various protein aggregation diseases. Key Points- How nucleic acids act as protein chaperones is currently unknown. - G-quadruplexes are excellent at preventing protein aggregation, and here we describe basic tenets of this activity. - This activity could help design treatments for multiple neurodegenerative diseases.

biophysics↗

bioRxiv2017

High Performance Virtual Screening by Targeting a High-resolution RNA Dynamic Ensemble

Dynamic ensembles that capture the flexibility of RNA three-dimensional (3D) structures hold great promise in advancing RNA-targeted drug discovery. Here, we experimentally screened the transactivation response element (TAR) RNA from human immunodeficiency virus type-1 (HIV-1) against ~100,000 small molecules. We used this dataset, along with 240 known hit molecules, to evaluate virtual screening (VS) against a high-resolution TAR ensemble determined by combining NMR spectroscopy and molecular dynamics (MD) simulations. Ensemble-based VS (EBVS) scores molecules with an area under the receiver operator characteristic curve (ROC AUC) of 0.87 with ~50% of all hits falling within the top 2% of scored molecules, and also correctly predicts the different TAR inter-helical structures when bound to six molecules. The prediction accuracy decreased significantly with decreasing accuracy of the target ensemble or when docking against a single RNA structure. These results demonstrate that experime ...

biochemistry↗