PubMed Health⌕ Search

PubMed · 11909114

Surface-induced conformational changes in lattice model proteins by Monte Carlo simulation.

Abstract

We present Monte Carlo simulations of thermal, structural, and dynamic properties of a 27-segment lattice model protein adsorbed to a solid surface. The protein consists of a sequence of A and B segments whose order and topological contact energy values are chosen so that a unique (3x3x3 cubic) folded state occurs in the absence of an adsorbing surface [E. I. Shakhnovich and M. Gutin, Proc. Natl. Acad. Sci. USA 90, 7195 (1993)]. The surface consists of a plane of sites that interact either (i) equally with all contacting protein segments (an equal affinity surface) or (ii) more strongly with type A contacting segments (an A affinity surface). For both surfaces, we find the conformational change of an initially folded protein to begin with a continuous transition to a structure where all segments contact the surface. This is followed by a partial refolding to a low energy state; this step is continuous and results in full surface contact for the equal affinity surface and is activated and results in significant loss of surface contact for the A affinity surface. We also observe a lesser (greater) degree of average surface contact in the equal (A) affinity surface with an increase in temperature.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Victoria Castells, Shaoxiong Yang, Paul R Van Tassel. 2002-03-05. Surface-induced conformational changes in lattice model proteins by Monte Carlo simulation.. https://doi.org/10.1103/physreve.65.031912

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

RadiSeq: a single- and bulk-cell whole-genome DNA sequencing simulator for radiation-damaged cell models.

Objective.To build and validate a simulation framework to perform single-cell and bulk-cell whole genome sequencing simulation of radiation-exposed Monte Carlo (MC) cell models to assist radiation genomics studies.Approach.Sequencing the genomes of radiation-damaged cells can provide useful insight into radiation action for radiobiology research. However, carrying out post-irradiation sequencing experiments can often be challenging, expensive, and time-consuming. Although computational simulations have the potential to provide solutions to these experimental challenges, and aid in designing optimal experiments, the absence of tools currently limits such application. MC toolkits exist to simulate radiation exposures of cell models but there are no tools to simulate single- and bulk-cell sequencing of cell models containing radiation-damaged DNA. Therefore, we aimed to develop a MC simulation framework to address this gap by designing a tool capable of simulating sequencing processes for radiation-damaged cells. Main results.We developed RadiSeq-a multi-threaded whole-genome DNA sequencing simulator written in C++. RadiSeq can be used to simulate Illumina sequencing of radiation-damaged cell models produced by MC simulations. RadiSeq has been validated through comparative analysis, where simulated data were matched against experimentally obtained data, demonstrating reasonable agreement between the two. Additionally, it comes with numerous features designed to closely resemble actual whole-genome sequencing. RadiSeq is also highly customizable with a single input parameter file.Significance.RadiSeq enables the research community to perform complex simulations of radiation-exposed DNA sequencing, supporting the optimization, planning, and validation of costly and time-intensive radiation biology experiments. This framework provides a powerful tool for advancing radiation genomics research.

Monte Carlo Method↗

Thermal versus mechanical unfolding of ubiquitin.

The authors studied the temperature-induced unfolding of ubiquitin by all-atom Monte Carlo simulations. The unfolding behavior is compared with that seen in previous simulations of the mechanical unfolding of this protein, based on the same model. In mechanical unfolding, secondary-structure elements were found to break in a quite well-defined order. In thermal unfolding, the authors saw somewhat larger event-to-event fluctuations, but the unfolding pathway was still far from random. Two long-lived secondary-structure elements could be identified in the simulations. These two elements have been found experimentally to be the thermally most stable ones. Interestingly, one of these long-lived elements, the first beta-hairpin, was found to break early in the mechanical unfolding simulations. Their combined simulation results thus enable the authors to predict in detail important differences between the thermal and mechanical unfolding behaviors of ubiquitin.

Monte Carlo Method↗