Applications of Computational Methods to Simulations of Proteins Dynamics

Nowak, Wiesław

doi:10.1007/978-3-319-27282-5_31

Cited by 3 publications

(2 citation statements)

References 353 publications

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“…However, also in these cases, it is hard to tell if the protein-folding kinetics resembles the experiments. More details can be found in recent reviews [21], [22].…”

Section: The Franzese-stanley Coarse-grained Water Modelmentioning

confidence: 99%

Water Contribution to the Protein Folding and Its Relevance in Protein Design and Protein Aggregation

Franzese

Rojas

Bianco

et al. 2021

Springer Proceedings in Physics

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Water plays a fundamental role in protein stability. However, the effect of the properties of water on the behaviour of proteins is only partially understood. Several theories have been proposed to give insight into the mechanisms of cold and pressure denaturation, or the limits of temperature and pressure above which no protein has a stable, functional state, or how unfolding and aggregation are related. Here we review our results based on a theoretical approach that can rationalise the water contribution to protein solutions' free energy. We show, using Monte Carlo simulations, how we can rationalise experimental data with our recent results. We discuss how our findings can help develop new strategies for the design of novel synthetic biopolymers or possible approaches for mitigating neurodegenerative pathologies.

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“…However, also in these cases, it is hard to tell if the protein-folding kinetics resembles the experiments. More details can be found in recent reviews [21], [22].…”

Section: The Franzese-stanley Coarse-grained Water Modelmentioning

confidence: 99%

Water Contribution to the Protein Folding and Its Relevance in Protein Design and Protein Aggregation

Franzese

Rojas

Bianco

et al. 2021

Springer Proceedings in Physics

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“…Molecular dynamics (MD) simulation is a well-established method [17] used to generate trajectories of atomic complexes, such as proteins and/or nucleic acids, in their conformational spaces. In the MD approach numerical algorithms are used to solve sets of classical, differential equations of motion.…”

Section: Introductionmentioning

confidence: 99%

Petri nets formalism facilitates analysis of complex biomolecular structural data

2016

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Molecular dynamics (MD) simulation is a popular method of protein and nucleic acids research. Current MD output trajectories are huge files and therefore they are hard to analyze. Petri nets (PNs) is a mathematical modeling language that allows for concise, graphical representation of complex data. We have developed a few algorithms for PNs generation from such large MD trajectories. One of them, called the One Place One Conformation (OPOC) algorithm, is presented in a greater detail. In the OPOC algorithm one biomolecular conformation corresponds to one PN place and a transition occurring in PN graph is related to a change between biomolecules conformations. As case studies three simulations are analyzed: an enforced steered MD (SMD) dissociation of a transthyretin protein tetramer into dimers, the SMD dissociation of an antibody-antigen complex and a classical MD simulation of transthyretin. We show that PNs reproduce events hidden in MD trajectories and enable observations of the conformational space features hard-to-see by the other clustering methods. Thus, a fundamental process of biomolecular data classification may be optimized using the PN approach.

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Polypeptide and Protein Modeling for Drug Design

O’Mara

Deplazes²

2015

Encyclopedia of Computational Neuroscience

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Computational modeling, structure-aided drug design, computational structural biology DefinitionModeling of polypeptides and proteins, often referred to as biomolecular or molecular modeling, encompasses the use of theoretical models and computational methods to model the structure and dynamics of molecules of biological interest such as peptides, proteins and small organic molecules (ligands).The aims of protein and peptide modeling for drug design include: (i) modeling the threedimensional structure of proteins of current or potential drug targets; (ii) identifying and characterizing the structural dynamics associated with the function of a particular protein or peptide; and (iii) predicting the structure and molecular interactions of protein-ligand complexes. This knowledge underpins structure-based and rational drug design. It can aid in the design and optimization of drug molecules by shedding light on their mode of action, specificity and selectivity.

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Applications of Computational Methods to Simulations of Proteins Dynamics

Cited by 3 publications

References 353 publications

Water Contribution to the Protein Folding and Its Relevance in Protein Design and Protein Aggregation

Water Contribution to the Protein Folding and Its Relevance in Protein Design and Protein Aggregation

Petri nets formalism facilitates analysis of complex biomolecular structural data

Polypeptide and Protein Modeling for Drug Design

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