A probabilistic model for crystal growth applied to protein deposition at the microscale

TL;DR

This paper introduces a flexible probabilistic discrete model for 2D protein crystal growth that accurately simulates nucleation and growth processes, validated against real experimental data and analyzing interface regularity effects.

Contribution

The paper presents a novel probabilistic model for protein crystal growth that accounts for space and interface effects, validated with experimental data.

Findings

High agreement between model simulations and real crystallization images

Model effectively captures nucleation and growth dynamics

Interface regularity influences crystal evolution

Abstract

A probabilistic discrete model for 2D protein crystal growth is presented. This model takes into account the available space and can describe growing processes of different nature due to the versatility of its parameters which gives the model great flexibility. The accuracy of the simulation is tested against a real protein (SbpA) crystallization experiment showing high agreement between the proposed model and the actual images of the nucleation process. Finally, it is also discussed how the regularity of the interface (i.e. the curve that separates the crystal from the substrate) affects to the evolution of the simulation.