Simple off-lattice model to study the folding and aggregation of peptides

Combe, Nicolas; Frenkel, Daan

doi:10.1080/00268970601175483

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…The model uses four important parameters of amino acid residues in the peptide, namely their position, secondary structural state, side-chain direction, and amino acid type, to simulate the different transition states of the peptide. Some off-lattice models (consider hydrogen bonds and amino acid interactions to study folding and aggregation), which are computationally expensive than the lattice models, have also been proposed to simulate the conformational transition of monomeric peptides to non-specific aggregates (Combe and Frenkel, 2007).…”

Section: Theoretical Models To Study Aβ Peptidesmentioning

confidence: 99%

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Saravanan

Zhang

et al. 2020

Front. Bioeng. Biotechnol.

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Understanding the conformational dynamics of proteins and peptides involved in important functions is still a difficult task in computational structural biology. Because such conformational transitions in β-amyloid (Aβ) forming peptides play a crucial role in many neurological disorders, researchers from different scientific fields have been trying to address issues related to the folding of Aβ forming peptides together. Many theoretical models have been proposed in the recent years for studying Aβ peptides using mathematical, physicochemical, and molecular dynamics simulation, and machine learning approaches. In this article, we have comprehensively reviewed the developmental advances in the theoretical models for Aβ peptide folding and interactions, particularly in the context of neurological disorders. Furthermore, we have extensively reviewed the advances in molecular dynamics simulation as a tool used for studying the conversions between polymorphic amyloid forms and applications of using machine learning approaches in predicting Aβ peptides and aggregation-prone regions in proteins. We have also provided details on the theoretical advances in the study of Aβ peptides, which would enhance our understanding of these peptides at the molecular level and eventually lead to the development of targeted therapies for certain acute neurological disorders such as Alzheimer's disease in the future.

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Section: Theoretical Models To Study Aβ Peptidesmentioning

confidence: 99%

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Saravanan

Zhang

et al. 2020

Front. Bioeng. Biotechnol.

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“…Thus, the simple model reproduces a feature of real proteins, which fold into a highly specific structure and show a peak in the heat capacity when unfolding. Folding of a model protein into a specific structure has also been achieved in off-lattice studies (11,12) typically using the same statistical pairpotentials as mentioned above.…”

Section: Introductionmentioning

confidence: 99%

Accounting for Protein-Solvent Contacts Facilitates Design of Nonaggregating Lattice Proteins

Abeln

Frenkel

2011

Biophysical Journal

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The folding specificity of proteins can be simulated using simplified structural models and knowledge-based pair-potentials. However, when the same models are used to simulate systems that contain many proteins, large aggregates tend to form. In other words, these models cannot account for the fact that folded, globular proteins are soluble. Here we show that knowledge-based pair-potentials, which include explicitly calculated energy terms between the solvent and each amino acid, enable the simulation of proteins that are much less aggregation-prone in the folded state. Our analysis clarifies why including a solvent term improves the foldability. The aggregation for potentials without water is due to the unrealistically attractive interactions between polar residues, causing artificial clustering. When a water-based potential is used instead, polar residues prefer to interact with water; this leads to designed protein surfaces rich in polar residues and well-defined hydrophobic cores, as observed in real protein structures. We developed a simple knowledge-based method to calculate interactions between the solvent and amino acids. The method provides a starting point for modeling the folding and aggregation of soluble proteins. Analysis of our simple model suggests that inclusion of these solvent terms may also improve off-lattice potentials for protein simulation, design, and structure prediction.

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General Methodology to Identify the Minimum Alphabet Size for Heteropolymer Design

Cardelli

Nerattini

Tubiana

et al. 2019

Advcd Theory and Sims

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Understanding how to design the structure of heteropolymers through their monomer sequence will have a significant impact on the creation of novel artificial materials. According to mean‐field theories, the minimum number—or alphabet—of distinct monomers necessary to achieve such designability is directly related to the conformational entropy ω of compact polymer structures. Here, a computational strategy to calculate this conformational entropy is introduced and thus predict the minimum alphabet to achieve designability, for a generalized heteropolymer model. The comparison of the predictions with previous results proves the robustness of the approach. It is quantified for the first time how the number of directional interactions is critical for achieving the designability. The methodology that is introduced can be easily generalized to models representing specific polymers. A comparison between conventional polymers monomers are provided, and it is predicted that polyurea, polyamide, and polyurethane residues are optimal candidates to be functionalized for the experimental synthesis of designable heteropolymers. As such, our method can guide the engineering of new types of self‐assembling modular polymers, that will open new possibilities for polymer‐based materials with unmatched versatility and control.

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Simple off-lattice model to study the folding and aggregation of peptides

Cited by 5 publications

References 33 publications

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

On the Conformational Dynamics of β-Amyloid Forming Peptides: A Computational Perspective

Accounting for Protein-Solvent Contacts Facilitates Design of Nonaggregating Lattice Proteins

General Methodology to Identify the Minimum Alphabet Size for Heteropolymer Design

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