scholarly journals Unsupervised Inference of Protein Fitness Landscape from Deep Mutational Scan

2020 ◽  
Vol 38 (1) ◽  
pp. 318-328 ◽  
Author(s):  
Jorge Fernandez-de-Cossio-Diaz ◽  
Guido Uguzzoni ◽  
Andrea Pagnani
Keyword(s):  
Protein Design ◽  
Large Scale ◽  
Fitness Landscape ◽  
Structural Information ◽  
Space Exploration ◽  
Combinatorial Libraries ◽  
Computational Method ◽  
Screening Experiment ◽  
Technological Advances

Abstract The recent technological advances underlying the screening of large combinatorial libraries in high-throughput mutational scans deepen our understanding of adaptive protein evolution and boost its applications in protein design. Nevertheless, the large number of possible genotypes requires suitable computational methods for data analysis, the prediction of mutational effects, and the generation of optimized sequences. We describe a computational method that, trained on sequencing samples from multiple rounds of a screening experiment, provides a model of the genotype–fitness relationship. We tested the method on five large-scale mutational scans, yielding accurate predictions of the mutational effects on fitness. The inferred fitness landscape is robust to experimental and sampling noise and exhibits high generalization power in terms of broader sequence space exploration and higher fitness variant predictions. We investigate the role of epistasis and show that the inferred model provides structural information about the 3D contacts in the molecular fold.

scholarly journals Unsupervised inference of protein fitness landscape from deep mutational scan

2020 ◽  
Author(s):  
Jorge Fernandez-de-Cossio-Diaz ◽  
Guido Uguzzoni ◽  
Andrea Pagnani
Keyword(s):  
Protein Design ◽  
Large Scale ◽  
Fitness Landscape ◽  
Structural Information ◽  
Space Exploration ◽  
Combinatorial Libraries ◽  
Computational Method ◽  
Screening Experiment ◽  
Technological Advances

The recent technological advances underlying the screening of large combinatorial libraries in high-throughput mutational scans, deepen our understanding of adaptive protein evolution and boost its applications in protein design. Nevertheless, the large number of possible genotypes requires suitable computational methods for data analysis, the prediction of mutational effects and the generation of optimized sequences. We describe a computational method that, trained on sequencing samples from multiple rounds of a screening experiment, provides a model of the genotype-fitness relationship. We tested the method on five large-scale mutational scans, yielding accurate predictions of the mutational effects on fitness. The inferred fitness landscape is robust to experimental and sampling noise and exhibits high generalization power in terms of broader sequence space exploration and higher fitness variant predictions. We investigate the role of epistasis and show that the inferred model provides structural information about the 3D contacts in the molecular fold.

scholarly journals A Computational Method to Predict Effects of Residue Mutations on the Catalytic Efficiency of Hydrolases

Catalysts ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 286
Author(s):  
Yun Li ◽  
Kun Song ◽  
Jian Zhang ◽  
Shaoyong Lu
Keyword(s):  
Structural Information ◽  
Characteristic Curve ◽  
Catalytic Efficiency ◽  
Computational Method ◽  
Classification Model ◽  
Blind Test ◽  
Data Set ◽  
Enzyme Modification ◽  
Vitro Assay ◽  
Technological Advances

With scientific and technological advances, growing research has focused on engineering enzymes that acquire enhanced efficiency and activity. Thereinto, computer-based enzyme modification makes up for the time-consuming and labor-intensive experimental methods and plays a significant role. In this study, for the first time, we collected and manually curated a data set for hydrolases mutation, including structural information of enzyme-substrate complexes, mutated sites and Kcat/Km obtained from vitro assay. We further constructed a classification model using the random forest algorithm to predict the effects of residue mutations on catalytic efficiency (increase or decrease) of hydrolases. This method has achieved impressive performance on a blind test set with the area under the receiver operating characteristic curve of 0.86 and the Matthews Correlation Coefficient of 0.659. Our results demonstrate that computational mutagenesis has an instructive effect on enzyme modification, which may expedite the design of engineering hydrolases.

scholarly journals PremPS: Predicting the impact of missense mutations on protein stability

2020 ◽  
Vol 16 (12) ◽  
pp. e1008543
Author(s):  
Yuting Chen ◽  
Haoyu Lu ◽  
Ning Zhang ◽  
Zefeng Zhu ◽  
Shuqin Wang ◽  
...  
Keyword(s):  
Protein Stability ◽  
Protein Design ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Predictive Performance ◽  
Computational Method ◽  
Single Mutation ◽  
Missense Mutations ◽  
Benchmark Datasets ◽  
The Impact

Computational methods that predict protein stability changes induced by missense mutations have made a lot of progress over the past decades. Most of the available methods however have very limited accuracy in predicting stabilizing mutations because existing experimental sets are dominated by mutations reducing protein stability. Moreover, few approaches could consistently perform well across different test cases. To address these issues, we developed a new computational method PremPS to more accurately evaluate the effects of missense mutations on protein stability. The PremPS method is composed of only ten evolutionary- and structure-based features and parameterized on a balanced dataset with an equal number of stabilizing and destabilizing mutations. A comprehensive comparison of the predictive performance of PremPS with other available methods on nine benchmark datasets confirms that our approach consistently outperforms other methods and shows considerable improvement in estimating the impacts of stabilizing mutations. A protein could have multiple structures available, and if another structure of the same protein is used, the predicted change in stability for structure-based methods might be different. Thus, we further estimated the impact of using different structures on prediction accuracy, and demonstrate that our method performs well across different types of structures except for low-resolution structures and models built based on templates with low sequence identity. PremPS can be used for finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. PremPS is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/, which allows to do large-scale mutational scanning and takes about four minutes to perform calculations for a single mutation per protein with ~ 300 residues and requires ~ 0.4 seconds for each additional mutation.

scholarly journals PremPS: Predicting the Effects of Single Mutations on Protein Stability

2020 ◽  
Author(s):  
Yuting Chen ◽  
Haoyu Lu ◽  
Ning Zhang ◽  
Zefeng Zhu ◽  
Shuqin Wang ◽  
...  
Keyword(s):  
Protein Stability ◽  
Protein Design ◽  
Large Scale ◽  
Molecular Mechanisms ◽  
Considerable Improvement ◽  
Computational Method ◽  
List Type ◽  
Missense Mutations ◽  
Neutral Mutations ◽  
Distinct Features

ABSTRACTProtein stability is related to its functional activities, and effect on stability or misfolding could be one of the major disease-causing mechanisms of missense mutations. Here we developed a novel machine learning computational method PremPS, which predicts the effects of single mutations on protein stability by calculating the changes in unfolding Gibbs free energy. PremPS uses only ten evolutionary- and structure-based features and is parameterized on five thousand mutations. Our approach outperforms previous methods and shows a considerable improvement in estimating the effects of mutations increasing protein stability. In addition, PremPS presents an outstanding performance in predicting the pathogenicity of missense mutations using an experimental dataset composed of two thousand non-neutral and neutral mutations. PremPS can be applied to many tasks, including finding functionally important variants, revealing the molecular mechanisms of functional influences and protein design. It is freely available at https://lilab.jysw.suda.edu.cn/research/PremPS/.Key PointsConsiderable improvement in estimating the effects of mutations increasing protein stability;Comprehensive comparison with other 25 computational methods on different test sets;An outstanding performance in predicting the pathogenicity of missense mutations;PremPS employs only ten distinct features belonging to six categories, and the most important feature describes evolutionary conservation of the site;The webserver allows to do large-scale mutational scanning and takes about ten minutes to perform calculations for one thousand mutations from a normal size protein.

The Role of Sense of Direction and Other Factors During Navigation in a Large-Scale, Unconstrained Environment

2013 ◽  
Author(s):  
Elisabeth J. Ploran ◽  
Ericka Rovira ◽  
James C. Thompson ◽  
Raja Parasuraman
Keyword(s):  
Large Scale ◽  
Sense Of Direction

Value-driven issues throughout the development of sociological theory

2020 ◽  
pp. 147-160
Author(s):  
Gulbarshyn Chepurko ◽  
Valerii Pylypenko
Keyword(s):  
Social Interactions ◽  
Social System ◽  
Sociological Theory ◽  
Social Scientists ◽  
Social Sphere ◽  
Technological Advances ◽  
The Social ◽  
The Individual ◽  
Different Levels

The paper examines and compares how the major sociological theories treat axiological issues. Value-driven topics are analysed in view of their relevance to society in times of crisis, when both societal life and the very structure of society undergo dramatic change. Nowadays, social scientists around the world are also witnessing such a change due to the emergence of alternative schools of sociological thought (non-classical, interpretive, postmodern, etc.) and, subsequently, the necessity to revise the paradigms that have been existed in sociology so far. Since the above-mentioned approaches are often used to address value-related issues, building a solid theoretical framework for these studies takes on considerable significance. Furthermore, the paradigm revision has been prompted by technological advances changing all areas of people’s lives, especially social interactions. The global human community, integral in nature, is being formed, and production of human values now matters more than production of things; hence the “expansion” of value-focused perspectives in contemporary sociology. The authors give special attention to collectivities which are higher-order units of the social system. These units are described as well-organised action systems where each individual performs his/her specific role. Just as the role of an individual is distinct from that of the collectivity (because the individual and the collectivity are different as units), so too a distinction is drawn between the value and the norm — because they represent different levels of social relationships. Values are the main connecting element between the society’s cultural system and the social sphere while norms, for the most part, belong to the social system. Values serve primarily to maintain the pattern according to which the society is functioning at a given time; norms are essential to social integration. Apart from being the means of regulating social processes and relationships, norms embody the “principles” that can be applied beyond a particular social system. The authors underline that it is important for Ukrainian sociology to keep abreast of the latest developments in the field of axiology and make good use of those ideas because this is a prerequisite for its successful integration into the global sociological community.

Magnetic Properties of xCeO2•(50 − x) PbO•50B2O3 Glasses and Glass Ceramics

2017 ◽  
Vol 13 (1) ◽  
pp. 4486-4494 ◽  
Author(s):  
G.El Damrawi ◽  
F. Gharghar
Keyword(s):  
Magnetic Properties ◽  
Large Scale ◽  
Glass Ceramics ◽  
Magnetic Behavior ◽  
Crystal Formation ◽  
Dual Roles ◽  
Effective Agent ◽  
Ordered Structures ◽  
Essential Change

Cerium oxide in borate glasses of composition xCeO2·(50 − x)PbO·50B2O3 plays an important role in changing both microstructure and magnetic behaviors of the system. The structural role of CeO2 as an effective agent for cluster and crystal formation in borate network is clearly evidenced by XRD technique. Both structure and size of well-formed cerium separated clusters have an effective influence on the structural properties. The cluster aggregations are documented to be found in different range ordered structures, intermediate and long range orders are the most structures in which cerium phases are involved. The nano-sized crystallized cerium species in lead borate phase are evidenced to have magnetic behavior.  The criteria of building new specific borate phase enriched with cerium as ferrimagnetism has been found to keep the magnetization in large scale even at extremely high temperature. Treating the glass thermally or exposing it to an effective dose of ionized radiation is evidenced to have an essential change in magnetic properties. Thermal heat treatment for some of investigated materials is observed to play dual roles in the glass matrix. It can not only enhance alignment processes of the magnetic moment but also increases the capacity of the crystallite species in the magnetic phases. On the other hand, reverse processes are remarked under the effect of irradiation. The magnetization was found to be lowered, since several types of the trap centers which are regarded as defective states can be produced by effect of ionized radiation. 

The Impact of Quantitative Easing on Emerging Markets – Literature Review

e-Finanse ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 67-76
Author(s):  
Piotr Bartkiewicz
Keyword(s):  
Emerging Markets ◽  
Large Scale ◽  
Empirical Literature ◽  
Quantitative Easing ◽  
Methodological Choices ◽  
The Subject ◽  
Methodological Approaches ◽  
The Impact ◽  
Sufficient Precision

AbstractThe article presents the results of the review of the empirical literature regarding the impact of quantitative easing (QE) on emerging markets (EMs). The subject is of interest to policymakers and researchers due to the increasingly larger role of EMs in the world economy and the large-scale capital flows occurring after 2009. The review is conducted in a systematic manner and takes into consideration different methodological choices, samples and measurement issues. The paper puts the summarized results in the context of transmission channels identified in the literature. There are few distinct methodological approaches present in the literature. While there is a consensus regarding the direction of the impact of QE on EMs, its size and durability have not yet been assessed with sufficient precision. In addition, there are clear gaps in the empirical findings, not least related to relative underrepresentation of the CEE region (in particular, Poland).

Age Advantages of Emotional Experience during the COVID-19 Pandemic are Robust, but Diminished Compared to Pre-pandemic Conditions

2020 ◽  
Author(s):  
Rui Sun ◽  
Disa Sauter
Keyword(s):  
Older Adults ◽  
Large Scale ◽  
Negative Emotion ◽  
Emotional Experience ◽  
Negative Emotions ◽  
Older Individuals ◽  
Selection Strategies ◽  
Scale Test ◽  
Prolonged Stress

Getting old is generally seen as unappealing, yet aging confers considerable advantages in several psychological domains (North & Fiske, 2015). In particular, older adults are better off emotionally than younger adults, with aging associated with the so-called “age advantages,” that is, more positive and less negative emotional experiences (Carstensen et al., 2011). Although the age advantages are well established, it is less clear whether they occur under conditions of prolonged stress. In a recent study, Carstensen et al (2020) demonstrated that the age advantages persist during the COVID-19 pandemic, suggesting that older adults are able to utilise cognitive and behavioural strategies to ameliorate even sustained stress. Here, we build on Carstensen and colleagues’ work with two studies. In Study 1, we provide a large-scale test of the robustness of Carstensen and colleagues’ finding that older individuals experience more positive and less negative emotions during the COVID-19 pandemic. We measured positive and negative emotions along with age information in 23,629 participants in 63 countries in April-May 2020. In Study 2, we provide a comparison of the age advantages using representative samples collected before and during the COVID-19 pandemic. We demonstrate that older people experience less negative emotion than younger people during the prolonged stress of the COVID-19 pandemic. However, the advantage of older adults was diminished during the pandemic, pointing to a likely role of older adults use of situation selection strategies (Charles, 2010).

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