Speaker
Description
Abstract:
Chirality is a pervasive and functionally critical property of biological macromolecules, yet distributed and emergent forms of chirality remain poorly quantified in complex systems such as membrane proteins. To address this gap, we introduce Chirobiophore, a multiscale, coordinate-invariant framework for capturing biochirality from atomic geometries to global structural asymmetries. The framework encodes chirality as a six-dimensional vector—comprising Local Tetrahedral Asymmetry (LTA), Helical Path Curvature (HPC), Asymmetric Environment Score (AES), Directional Density Profile (DDP), Leaflet Asymmetry Index (LAI), and Orientation Twist Score (OTS). Applied to canonical α-helical proteins, G protein–coupled receptors, and topologically complex membrane proteins, Chirobiophore reveals distinct chirality signatures that cluster by structural class and functional role. We further show that Chirobiophore descriptors can be projected onto tissue-level asymmetry indices, providing a bridge between molecular structure and morphogenetic patterning. This paradigm offers a unified and extensible platform for structural biology, protein engineering, and developmental modeling of chirality.
Reference:
1. Chirality descriptors for structure–activity relationship
modeling of bioactive molecules, R. Natarajan, C. N. Lungu, and S. C. Basak, Journal of Mathematical Chemistry
https://doi.org/10.1007/s10910-023-01531-2
