scholarly journals The Adaptive Potential of the Middle Domain of Yeast Hsp90

Author(s):  
Pamela A Cote-Hammarlof ◽  
Inês Fragata ◽  
Julia Flynn ◽  
David Mavor ◽  
Konstantin B Zeldovich ◽  
...  

Abstract The distribution of fitness effects (DFEs) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the distribution of fitness effects of the same ≈2,300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase–chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client-binding interfaces, or residues that are involved in ATPase–chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.

2019 ◽  
Author(s):  
Pamela A. Cote-Hammarlof ◽  
Inês Fragata ◽  
Julia Flynn ◽  
David Mavor ◽  
Konstantin B. Zeldovich ◽  
...  

AbstractThe distribution of fitness effects (DFE) of new mutations across different environments quantifies the potential for adaptation in a given environment and its cost in others. So far, results regarding the cost of adaptation across environments have been mixed, and most studies have sampled random mutations across different genes. Here, we quantify systematically how costs of adaptation vary along a large stretch of protein sequence by studying the DFEs of the same ≈2300 amino-acid changing mutations obtained from deep mutational scanning of 119 amino acids in the middle domain of the heat-shock protein Hsp90 in five environments. This region is known to be important for client binding, stabilization of the Hsp90 dimer, stabilization of the N-terminal-Middle and Middle-C-terminal interdomains, and regulation of ATPase-chaperone activity. Interestingly, we find that fitness correlates well across diverse stressful environments, with the exception of one environment, diamide. Consistent with this result, we find little cost of adaptation; on average only one in seven beneficial mutations is deleterious in another environment. We identify a hotspot of beneficial mutations in a region of the protein that is located within an allosteric center. The identified protein regions that are enriched in beneficial, deleterious, and costly mutations coincide with residues that are involved in the stabilization of Hsp90 interdomains and stabilization of client binding interfaces, or residues that are involved in ATPase chaperone activity of Hsp90. Thus, our study yields information regarding the role and adaptive potential of a protein sequence that complements and extends known structural information.


2016 ◽  
Author(s):  
Lei Dai ◽  
Yushen Du ◽  
Hangfei Qi ◽  
Christian D. Huber ◽  
Nicholas C. Wu ◽  
...  

AbstractRNA viruses are notorious for their ability to evolve rapidly under selection in novel environments. It is known that the high mutation rate of RNA viruses can generate huge genetic diversity to facilitate viral adaptation. However, less attention has been paid to the underlying fitness landscape that represents the selection forces on viral genomes. Here we systematically quantified the distribution of fitness effects (DFE) of about 1,600 single amino acid substitutions in the drug-targeted region of NS5A protein of Hepatitis C Virus (HCV). We found that the majority of non-synonymous substitutions incur large fitness costs, suggesting that NS5A protein is highly optimized in natural conditions. We characterized the adaptive potential of HCV by subjecting the mutant viruses to selection by the antiviral drug Daclatasvir. Both the selection coefficient and the number of beneficial mutations are found to increase with the level of environmental stress, which is modulated by the concentration of Daclatasvir. The changes in the spectrum of beneficial mutations in NS5A protein can be explained by a pharmacodynamics model describing viral fitness as a function of drug concentration. We test theoretical predictions regarding the distribution of beneficial fitness effects of mutations. We also interpret the data in the context of Fisher’s Geometric Model and find an increased distance to optimum as a function of environmental stress. Finally, we show that replication fitness of viruses is correlated with the pattern of sequence conservation in nature and viral evolution is constrained by the need to maintain protein stability.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Seonwoo Min ◽  
Seunghyun Park ◽  
Siwon Kim ◽  
Hyun-Soo Choi ◽  
Byunghan Lee ◽  
...  

2016 ◽  
Author(s):  
Paula Tataru ◽  
Maéva Mollion ◽  
Sylvain Glemin ◽  
Thomas Bataillon

ABSTRACTThe distribution of fitness effects (DFE) encompasses deleterious, neutral and beneficial mutations. It conditions the evolutionary trajectory of populations, as well as the rate of adaptive molecular evolution (α). Inference of DFE and α from patterns of polymorphism (SFS) and divergence data has been a longstanding goal of evolutionary genetics. A widespread assumption shared by numerous methods developed so far to infer DFE and α from such data is that beneficial mutations contribute only negligibly to the polymorphism data. Hence, a DFE comprising only deleterious mutations tends to be estimated from SFS data, and α is only predicted by contrasting the SFS with divergence data from an outgroup. Here, we develop a hierarchical probabilistic framework that extends on previous methods and also can infer DFE and α from polymorphism data alone. We use extensive simulations to examine the performance of our method. We show that both a full DFE, comprising both deleterious and beneficial mutations, and α can be inferred without resorting to divergence data. We demonstrate that inference of DFE from polymorphism data alone can in fact provide more reliable estimates, as it does not rely on strong assumptions about a shared DFE between the outgroup and ingroup species used to obtain the SFS and divergence data. We also show that not accounting for the contribution of beneficial mutations to polymorphism data leads to substantially biased estimates of the DFE and α. We illustrate these points using our newly developed framework, while also comparing to one of the most widely used inference methods available.


2020 ◽  
Vol 6 (6) ◽  
pp. 42-51
Author(s):  
V. S. Plotnikov ◽  
O. V. Plotnikova

The article is devoted to the problem of accounting reflection of rental relations, which has been the subject of discussion by professional accountants for more than 100 years. At present, more standards are devoted to this problem in world practice than to other accounting objects. Nevertheless, a number of issues remain unresolved. The methodological framework of the study is based on a comparative description of the provisions of IFRS 16 “Leases” and FSBU 25/2018 “Accounting for Leases” and includes a new institutional theory, Conceptual framework for the presentation of financial statements. The research methodology provides for the reclassification of balance sheet items, which allows for significant structural information regarding the reflection of rental objects. The analysis revealed the following differences in standards: the Russian FSBU 25/2018 unreasonably introduces accounting for leasing transactions into the financial lease accounting system; insufficiently convincingly and without proper evidence the issues of identification of financial lease accounting objects are covered. The prospective direction of accounting for financial leases is the possibility of reflecting the property transferred by the lessee as an element of the cost of financial capital, at the same time, the tenant’s long-term obligations should be recognized as existing obligations. The practical significance of the study is determined by the possibility of reducing the level of debt in the balance of the parties to the lease transaction.


Author(s):  
Guangming Xing

Classification/clustering of XML documents based on their structural information is important for many tasks related with document management. In this chapter, we present a suite of algorithms to compute the cost for approximate matching between XML documents and schemas. A framework for classifying/clustering XML documents by structure is then presented based on the computation of distances between XML documents and schemas. The backbone of the framework is the feature representation using a vector of the distances. Experimental studies were conducted on various XML data sets, suggesting the efficiency and effectiveness of our approach as a solution for structural classification/clustering of XML documents.


2019 ◽  
Vol 35 (22) ◽  
pp. 4854-4856 ◽  
Author(s):  
James D Stephenson ◽  
Roman A Laskowski ◽  
Andrew Nightingale ◽  
Matthew E Hurles ◽  
Janet M Thornton

Abstract Motivation Understanding the protein structural context and patterning on proteins of genomic variants can help to separate benign from pathogenic variants and reveal molecular consequences. However, mapping genomic coordinates to protein structures is non-trivial, complicated by alternative splicing and transcript evidence. Results Here we present VarMap, a web tool for mapping a list of chromosome coordinates to canonical UniProt sequences and associated protein 3D structures, including validation checks, and annotating them with structural information. Availability and implementation https://www.ebi.ac.uk/thornton-srv/databases/VarMap. Supplementary information Supplementary data are available at Bioinformatics online.


Pteridines ◽  
2007 ◽  
Vol 18 (1) ◽  
pp. 79-94
Author(s):  
Marco Wiltgen ◽  
Gernot P. Tilz

Abstract Functional specificity of a protein is linked to its structure. A growing section of bioinformatics deals with the prediction and visualization of protein 3D structures. In homology modelling, a protein sequence with an unknown structure is aligned with sequences of known protein structures. By exploiting structural information from the known configurations, the new structure can be predicted. In this introductory paper, we will present the principles of homology modelling and demonstrate the method used, by determining the structure of the enzyme glutamic decarboxylase (GAD 65). This protein is an autoantigen involved in several human autoimmune diseases. We will illustrate the different steps in structure prediction of GAD 65 by use of two experimentally determined structures of pig kidney DOPA decarboxylase (one structure in complex with the inhibitor carbidopa) as templates. The resulting model of GAD 65 provides detailed information about the active site of the protein and selected epitopes. By analysis of the interactions between the DOPA decarboxylase with the inhibitor carbidopa, the residues of the GAD 65 active site can be identified via the sequence alignment between DOPA and GAD 65. The locations of known epitopes in the molecule are visualized in special representations giving insights into mechanisms of antigenicity. Hydrophobicity analysis gives first hints for the adherence ability of GAD 65 to the cell membrane. Homology modelling is at present one of the most efficient techniques to provide accurate structural models of proteins. It is expected that in few years, for every new determined protein sequence, at least one member with a known structure of the same protein family will be available, which will steadily increase the importance and applicability of homology modelling.


2018 ◽  
Author(s):  
Thomas Lenormand ◽  
Noémie Harmand ◽  
Romain Gallet

AbstractThis preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (https://doi.org/10.24072/pci.evolbiol.100052). The cost of resistance, or the fitness effect of resistance mutation in absence of the drug, is a very widepsread concept in evolutionary genetics and beyond. It has represented an important addition to the simplistic view that resistance mutations should solely be considered as beneficial mutations. Yet, this concept also entails a series of serious difficulties in its definition, interpretation and current usage. In many cases, it may be simpler, clearer, and more insightful to study, measure and analyze the fitness effects of mutations across environments and to better distinguish those effects from ‘pleiotropic effects’ of those mutations.


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