The Experts below are selected from a list of 171 Experts worldwide ranked by ideXlab platform
Sebastia E Ahne - One of the best experts on this subject based on the ideXlab platform.
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duplication accelerates the evolution of structural complexity in Protein Quaternary Structure
bioRxiv, 2020Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:Gene duplication, from single genes to whole genomes, has been observed in organisms across all taxa. Despite its prevalence, the evolutionary benefits of this mechanism are the subject of ongoing debate. Gene duplication can significantly alter the self-assembly of Protein Quaternary Structures, impacting the dosage or interaction proclivity. Here we use a lattice model of self-assembly as a coarse-grained representation of Protein complex assembly, and show that it can be used to examine potential evolutionary advantages of duplication. Duplication provides a unique mechanism for increasing the evolvability of Protein complexes by enabling the transformation of symmetric homomeric interactions into heteromeric ones. This transformation is extensively observed in in silico evolutionary simulations of the lattice model, with duplication events significantly accelerating the rate at which structural complexity increases. These coarse-grained simulation results are corroborated with a large-scale analysis of complexes from the Protein Data Bank.
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evolution of interface binding strengths in simplified model of Protein Quaternary Structure
PLOS Computational Biology, 2019Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:The self-assembly of Proteins into Protein Quaternary Structures is of fundamental importance to many biological processes, and Protein misassembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of Protein self-assembly have been used to simulate the evolution and assembly of Protein Quaternary Structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalized model we are able to reproduce two important results established for real Protein complexes: The first is that Protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new idealized framework to facilitate the study of Protein self-assembly processes and their evolution.
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evolution of interface binding strengths in simplified model of Protein Quaternary Structure
bioRxiv, 2019Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:The self-assembly of Proteins into Protein Quaternary Structures is of fundamental importance to many biological processes, and Protein mis-assembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of Protein self-assembly have been used to simulate the evolution and assembly of Protein Quaternary Structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalised model we are able to reproduce two important results established for real Protein complexes: The first is that Protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new framework for the study of Protein self-assembly processes and their evolution.
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a tractable genotype phenotype map modelling the self assembly of Protein Quaternary Structure
Journal of the Royal Society Interface, 2014Co-Authors: Sam F Greenbury, Iai G Johnsto, Ard A Louis, Sebastia E AhneAbstract:The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here, we introduce a rich, intuitive and biologically realistic genotype–phenotype (GP) map ...
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a tractable genotype phenotype map for the self assembly of Protein Quaternary Structure
arXiv: Populations and Evolution, 2013Co-Authors: Sam F Greenbury, Iai G Johnsto, Ard A Louis, Sebastia E AhneAbstract:The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here we introduce a rich, intuitive, and biologically realistic genotype-phenotype (GP) map, that serves as a model of self-assembling biological Structures, such as Protein complexes, and remains computationally and analytically tractable. Our GP map arises naturally from the self-assembly of polyomino Structures on a 2D lattice and exhibits a number of properties: $\textit{redundancy}$ (genotypes vastly outnumber phenotypes), $\textit{phenotype bias}$ (genotypic redundancy varies greatly between phenotypes), $\textit{genotype component disconnectivity}$ (phenotypes consist of disconnected mutational networks) and $\textit{shape space covering}$ (most phenotypes can be reached in a small number of mutations). We also show that the mutational robustness of phenotypes scales very roughly logarithmically with phenotype redundancy and is positively correlated with phenotypic evolvability. Although our GP map describes the assembly of disconnected objects, it shares many properties with other popular GP maps for connected units, such as models for RNA secondary Structure or the HP lattice model for Protein tertiary Structure. The remarkable fact that these important properties similarly emerge from such different models suggests the possibility that universal features underlie a much wider class of biologically realistic GP maps.
Alexande S Leonard - One of the best experts on this subject based on the ideXlab platform.
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duplication accelerates the evolution of structural complexity in Protein Quaternary Structure
bioRxiv, 2020Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:Gene duplication, from single genes to whole genomes, has been observed in organisms across all taxa. Despite its prevalence, the evolutionary benefits of this mechanism are the subject of ongoing debate. Gene duplication can significantly alter the self-assembly of Protein Quaternary Structures, impacting the dosage or interaction proclivity. Here we use a lattice model of self-assembly as a coarse-grained representation of Protein complex assembly, and show that it can be used to examine potential evolutionary advantages of duplication. Duplication provides a unique mechanism for increasing the evolvability of Protein complexes by enabling the transformation of symmetric homomeric interactions into heteromeric ones. This transformation is extensively observed in in silico evolutionary simulations of the lattice model, with duplication events significantly accelerating the rate at which structural complexity increases. These coarse-grained simulation results are corroborated with a large-scale analysis of complexes from the Protein Data Bank.
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evolution of interface binding strengths in simplified model of Protein Quaternary Structure
PLOS Computational Biology, 2019Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:The self-assembly of Proteins into Protein Quaternary Structures is of fundamental importance to many biological processes, and Protein misassembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of Protein self-assembly have been used to simulate the evolution and assembly of Protein Quaternary Structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalized model we are able to reproduce two important results established for real Protein complexes: The first is that Protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new idealized framework to facilitate the study of Protein self-assembly processes and their evolution.
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evolution of interface binding strengths in simplified model of Protein Quaternary Structure
bioRxiv, 2019Co-Authors: Alexande S Leonard, Sebastia E AhneAbstract:The self-assembly of Proteins into Protein Quaternary Structures is of fundamental importance to many biological processes, and Protein mis-assembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of Protein self-assembly have been used to simulate the evolution and assembly of Protein Quaternary Structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalised model we are able to reproduce two important results established for real Protein complexes: The first is that Protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new framework for the study of Protein self-assembly processes and their evolution.
Feng Yang - One of the best experts on this subject based on the ideXlab platform.
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using chou s pseudo amino acid composition to predict Protein Quaternary Structure a sequence segmented pseaac approach
Amino Acids, 2008Co-Authors: Shaowu Zhang, Wei Chen, Feng YangAbstract:In the Protein universe, many Proteins are composed of two or more polypeptide chains, generally referred to as subunits, which associate through noncovalent interactions and, occasionally, disulfide bonds to form Protein Quaternary Structures. It has long been known that the functions of Proteins are closely related to their Quaternary Structures; some examples include enzymes, hemoglobin, DNA polymerase, and ion channels. However, it is extremely labor-expensive and even impossible to quickly determine the Structures of hundreds of thousands of Protein sequences solely from experiments. Since the number of Protein sequences entering databanks is increasing rapidly, it is highly desirable to develop computational methods for classifying the Quaternary Structures of Proteins from their primary sequences. Since the concept of Chou’s pseudo amino acid composition (PseAAC) was introduced, a variety of approaches, such as residue conservation scores, von Neumann entropy, multiscale energy, autocorrelation function, moment descriptors, and cellular automata, have been utilized to formulate the PseAAC for predicting different attributes of Proteins. Here, in a different approach, a sequence-segmented PseAAC is introduced to represent Protein samples. Meanwhile, multiclass SVM classifier modules were adopted to classify Protein Quaternary Structures. As a demonstration, the dataset constructed by Chou and Cai [(2003) Proteins 53:282–289] was adopted as a benchmark dataset. The overall jackknife success rates thus obtained were 88.2–89.1%, indicating that the new approach is quite promising for predicting Protein Quaternary Structure.
Torsten Schwede - One of the best experts on this subject based on the ideXlab platform.
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modeling Protein Quaternary Structure of homo and hetero oligomers beyond binary interactions by homology
Scientific Reports, 2017Co-Authors: Martino Bertoni, Florian Kiefer, Marco Biasini, Lorenza Bordoli, Torsten SchwedeAbstract:Cellular processes often depend on interactions between Proteins and the formation of macromolecular complexes. The impairment of such interactions can lead to deregulation of pathways resulting in disease states, and it is hence crucial to gain insights into the nature of macromolecular assemblies. Detailed structural knowledge about complexes and Protein-Protein interactions is growing, but experimentally determined three-dimensional multimeric assemblies are outnumbered by complexes supported by non-structural experimental evidence. Here, we aim to fill this gap by modeling multimeric Structures by homology, only using amino acid sequences to infer the stoichiometry and the overall Structure of the assembly. We ask which properties of Proteins within a family can assist in the prediction of correct Quaternary Structure. Specifically, we introduce a description of Protein-Protein interface conservation as a function of evolutionary distance to reduce the noise in deep multiple sequence alignments. We also define a distance measure to structurally compare homologous multimeric Protein complexes. This allows us to hierarchically cluster Protein Structures and quantify the diversity of alternative biological assemblies known today. We find that a combination of conservation scores, structural clustering, and classical interface descriptors, can improve the selection of homologous Protein templates leading to reliable models of Protein complexes.
Sam F Greenbury - One of the best experts on this subject based on the ideXlab platform.
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a tractable genotype phenotype map modelling the self assembly of Protein Quaternary Structure
Journal of the Royal Society Interface, 2014Co-Authors: Sam F Greenbury, Iai G Johnsto, Ard A Louis, Sebastia E AhneAbstract:The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here, we introduce a rich, intuitive and biologically realistic genotype–phenotype (GP) map ...
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a tractable genotype phenotype map for the self assembly of Protein Quaternary Structure
arXiv: Populations and Evolution, 2013Co-Authors: Sam F Greenbury, Iai G Johnsto, Ard A Louis, Sebastia E AhneAbstract:The mapping between biological genotypes and phenotypes is central to the study of biological evolution. Here we introduce a rich, intuitive, and biologically realistic genotype-phenotype (GP) map, that serves as a model of self-assembling biological Structures, such as Protein complexes, and remains computationally and analytically tractable. Our GP map arises naturally from the self-assembly of polyomino Structures on a 2D lattice and exhibits a number of properties: $\textit{redundancy}$ (genotypes vastly outnumber phenotypes), $\textit{phenotype bias}$ (genotypic redundancy varies greatly between phenotypes), $\textit{genotype component disconnectivity}$ (phenotypes consist of disconnected mutational networks) and $\textit{shape space covering}$ (most phenotypes can be reached in a small number of mutations). We also show that the mutational robustness of phenotypes scales very roughly logarithmically with phenotype redundancy and is positively correlated with phenotypic evolvability. Although our GP map describes the assembly of disconnected objects, it shares many properties with other popular GP maps for connected units, such as models for RNA secondary Structure or the HP lattice model for Protein tertiary Structure. The remarkable fact that these important properties similarly emerge from such different models suggests the possibility that universal features underlie a much wider class of biologically realistic GP maps.
