New algorithm to determine a minimal representation of the molecular surface
Greta Grassmann, Mattia Miotto, Lorenzo Di Rienzo, Giorgio Gosti,, Giancarlo Ruocco, Edoardo Milanetti

TL;DR
This paper introduces a new computational algorithm that efficiently reduces the number of surface points needed to represent a molecule's shape, preserving critical information for studying molecular interactions.
Contribution
The paper presents a novel theoretical and computational method for selecting surface points that retain shape information while minimizing data, improving over random sampling.
Findings
Higher accuracy in reproducing molecular surface information
Efficient reduction of sampling points
Enhanced shape characterization using Zernike polynomials
Abstract
Most proteins perform their biological function by interacting with one or more molecular partners. In this respect, characterizing the features of the molecular surface, especially in the portions where the interaction takes place, turned out to be a crucial step in the investigation of the mechanisms of recognition and binding between molecules. Predictive methods often rely on extensive samplings of molecular patches with the aim to identify hot spots on the surface. In this framework, analysis of large proteins and/or many molecular dynamics frames is often unfeasible due to the high computational cost. Thus, finding optimal ways to reduce the number of points to be sampled maintaining the biological information carried by the molecular surface is pivotal. Here, we present a new theoretical and computational algorithm with the aim of determining a subset of surface points,…
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Taxonomy
TopicsComputational Drug Discovery Methods · Protein Structure and Dynamics · Molecular spectroscopy and chirality
