Predicting and interpreting large-scale mutagenesis data using analyses of protein stability and conservation

AbstractDespite the intense efforts of the last decades to understand the thermal stability of proteins, the mechanisms responsible for its modulation still remain debated. In this investigation, we tackle this issue by showing how a multi-scale perspective can yield new insights. With the help of temperature-dependent statistical potentials, we analyzed some amino acid interactions at the molecular level, which are suggested to be relevant for the enhancement of thermal resistance. We then investigated the thermal stability at the protein level by quantifying its modification upon amino acid substitutions. Finally, a large scale analysis of protein stability - at the structurome level - contributed to the clarification of the relation between stability and natural evolution, thereby showing that the mutational profile of thermostable and mesostable proteins differ. Some final considerations on how the multi-scale approach could help unraveling the protein stability mechanisms are briefly discussed.

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Using AlphaFold to predict the impact of single mutations on protein stability and function

10.1101/2021.09.19.460937 ◽

2021 ◽

Author(s):

Marina A Pak ◽

Karina A Markhieva ◽

Mariia S Novikova ◽

Dmitry S Petrov ◽

Ilya S Vorobyev ◽

...

Keyword(s):

Protein Folding ◽

Protein Stability ◽

Structure Prediction ◽

Large Scale ◽

3D Structure ◽

Three Dimensional ◽

Single Mutation ◽

Before And After ◽

And Function ◽

The Impact

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability (ΔΔG) and function. To study the question we extracted metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known ΔΔG values. Additionally, we correlated the AlphaFold predictions on the impact of a single mutation on structure with a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold cannot be immediately applied to other problems or applications in protein folding.

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PremPS: Predicting the impact of missense mutations on protein stability

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008543 ◽

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.

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Improved insights into protein thermal stability: from the molecular to the structurome scale

Philosophical Transactions of The Royal Society A Mathematical Physical and Engineering Sciences ◽

10.1098/rsta.2016.0141 ◽

2016 ◽

Vol 374 (2080) ◽

pp. 20160141 ◽

Cited By ~ 8

Author(s):

Fabrizio Pucci ◽

Marianne Rooman

Keyword(s):

Thermal Stability ◽

Amino Acid ◽

Protein Stability ◽

Large Scale ◽

Molecular Level ◽

Multiscale Approach ◽

Temperature Dependent ◽

Natural Evolution ◽

Large Scale Analysis ◽

Thermal Stability Of

Despite the intense efforts of the last decades to understand the thermal stability of proteins, the mechanisms responsible for its modulation still remain debated. In this investigation, we tackle this issue by showing how a multiscale perspective can yield new insights. With the help of temperature-dependent statistical potentials, we analysed some amino acid interactions at the molecular level, which are suggested to be relevant for the enhancement of thermal resistance. We then investigated the thermal stability at the protein level by quantifying its modification upon amino acid substitutions. Finally, a large scale analysis of protein stability—at the structurome level—contributed to the clarification of the relation between stability and natural evolution, thereby showing that the mutational profile of proteins differs according to their thermal properties. Some considerations on how the multiscale approach could help in unravelling the protein stability mechanisms are briefly discussed. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’.

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Predicting the Effect of Amino Acid Single-Point Mutations on Protein Stability—Large-Scale Validation of MD-Based Relative Free Energy Calculations

Journal of Molecular Biology ◽

10.1016/j.jmb.2016.12.007 ◽

2017 ◽

Vol 429 (7) ◽

pp. 948-963 ◽

Cited By ~ 42

Author(s):

Thomas Steinbrecher ◽

Chongkai Zhu ◽

Lingle Wang ◽

Robert Abel ◽

Christopher Negron ◽

...

Keyword(s):

Free Energy ◽

Amino Acid ◽

Protein Stability ◽

Large Scale ◽

Scale Validation ◽

Single Point ◽

Point Mutations ◽

Free Energy Calculations ◽

Relative Free Energy ◽

Single Point Mutations

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Evolutionary variation in MADS-box dimerization affects floral development and protein stability

10.1101/2020.03.09.984260 ◽

2020 ◽

Author(s):

Maria Jazmin Abraham Juarez ◽

Amanda Schrager-Lavelle ◽

Jarrett Man ◽

Clinton Whipple ◽

Pubudu Handakumbura ◽

...

Keyword(s):

Protein Stability ◽

Gene Networks ◽

Large Scale ◽

Floral Development ◽

Experimental System ◽

Mads Box ◽

Molecular Change ◽

Evolutionary Variation ◽

Floral Diversification ◽

Floral Form

AbstractShifting interactions between MADS-box transcription factors may have been critical in the emergence of the flower, and in floral diversification. However, how evolutionary variation in MADS-box interactions affects the development and evolution of floral form remains unknown. Interactions between B-class MADS-box proteins are variable across the grass family. Here, we test the functional consequences of this evolutionary variability using maize as an experimental system. We found that differential B-class dimerization was associated with subtle, quantitative differences in stamen shape. In contrast, differential dimerization resulted in large-scale changes to protein complex composition and downstream gene expression. Differential dimerization also affected B-class complex abundance, independent of RNA levels. Thus, differential dimerization may affect protein stability. This reveals an important consequence for evolutionary variability in MADS-box interactions, adding complexity to the evolution of developmental gene networks. Our results show that floral development is robust to molecular change, even coding change in a master regulator of development. This robustness may contribute to the evolvability of floral form.

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PremPS: Predicting the Effects of Single Mutations on Protein Stability

10.1101/2020.04.07.029074 ◽

2020 ◽

Cited By ~ 1

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.

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Large scale analysis of protein stability in OMIM disease related human protein variants

BMC Genomics ◽

10.1186/s12864-016-2726-y ◽

2016 ◽

Vol 17 (S2) ◽

Cited By ~ 15

Author(s):

Pier Luigi Martelli ◽

Piero Fariselli ◽

Castrense Savojardo ◽

Giulia Babbi ◽

Francesco Aggazio ◽

...

Keyword(s):

Protein Stability ◽

Large Scale ◽

Human Protein ◽

Scale Analysis ◽

Large Scale Analysis ◽

Protein Variants

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Some comments about observations and image processing of comet 29P/Schwassmann-Wachmann 1

International Astronomical Union Colloquium ◽

10.1017/s0252921100031493 ◽

1999 ◽

Vol 173 ◽

pp. 243-248

Author(s):

D. Kubáček ◽

A. Galád ◽

A. Pravda

Keyword(s):

Image Processing ◽

Large Scale ◽

Harvard College ◽

Oak Ridge ◽

Large Scale Structures ◽

Short Period Comet ◽

Short Period ◽

Scale Structures ◽

Harvard College Observatory ◽

Period Comet

AbstractUnusual short-period comet 29P/Schwassmann-Wachmann 1 inspired many observers to explain its unpredictable outbursts. In this paper large scale structures and features from the inner part of the coma in time periods around outbursts are studied. CCD images were taken at Whipple Observatory, Mt. Hopkins, in 1989 and at Astronomical Observatory, Modra, from 1995 to 1998. Photographic plates of the comet were taken at Harvard College Observatory, Oak Ridge, from 1974 to 1982. The latter were digitized at first to apply the same techniques of image processing for optimizing the visibility of features in the coma during outbursts. Outbursts and coma structures show various shapes.

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