Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Some useful ideas for multistate protein design: Effect of amino acid substitutions on the multistate proteins stability and the rate of protein structure formation.

ABSTRACT: The design of new protein variants is usually confined to slightly "fixing" an already existing protein, adapting it to certain conditions or to a new substrate. This is relatively easy to do if the fragment of the protein to be affected, such as the active site of the protein, is known. But what if you need to "fix" the stability of a protein or the rate of its native or intermediate state formation? Having studied a large number of protein mutant forms, we have established the effect of various amino acid substitutions on the energy landscape of the protein. As a result, we have revealed a number of patterns to help researchers identify amino acid residues that determine the folding rate and the stability of globular proteins states and design a mutant form of a protein with desired properties.

SUBMITTER: Majorina MA

PROVIDER: S-EPMC9462454 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Some useful ideas for multistate protein design: Effect of amino acid substitutions on the multistate proteins stability and the rate of protein structure formation.

Majorina M A MA Melnik T N TN Glukhov A S AS Melnik B S BS

Frontiers in molecular biosciences 20220826

The design of new protein variants is usually confined to slightly "fixing" an already existing protein, adapting it to certain conditions or to a new substrate. This is relatively easy to do if the fragment of the protein to be affected, such as the active site of the protein, is known. But what if you need to "fix" the stability of a protein or the rate of its native or intermediate state formation? Having studied a large number of protein mutant forms, we have established the effect of variou ...[more]

PMID: 36090043

Similar Datasets

Sequence feature-based prediction of protein stability changes upon amino acid substitutions.

Project description:BACKGROUND: Protein destabilization is a common mechanism by which amino acid substitutions cause human diseases. Although several machine learning methods have been reported for predicting protein stability changes upon amino acid substitutions, the previous studies did not utilize relevant sequence features representing biological knowledge for classifier construction. RESULTS: In this study, a new machine learning method has been developed for sequence feature-based prediction of protein stability changes upon amino acid substitutions. Support vector machines were trained with data from experimental studies on the free energy change of protein stability upon mutations. To construct accurate classifiers, twenty sequence features were examined for input vector encoding. It was shown that classifier performance varied significantly by using different sequence features. The most accurate classifier in this study was constructed using a combination of six sequence features. This classifier achieved an overall accuracy of 84.59% with 70.29% sensitivity and 90.98% specificity. CONCLUSIONS: Relevant sequence features can be used to accurately predict protein stability changes upon amino acid substitutions. Predictive results at this level of accuracy may provide useful information to distinguish between deleterious and tolerant alterations in disease candidate genes. To make the classifier accessible to the genetics research community, we have developed a new web server, called MuStab (http://bioinfo.ggc.org/mustab/).

| S-EPMC2975416 | biostudies-literature

Structural assessment of the effects of amino acid substitutions on protein stability and protein protein interaction.

Project description:A structure-based approach is described for predicting the effects of amino acid substitutions on protein function. Structures were predicted using a homology modelling method. Folding and binding energy differences between wild-type and mutant structures were computed to quantitatively assess the effects of amino acid substitutions on protein stability and protein protein interaction, respectively. We demonstrated that pathogenic mutations at the interaction interface could affect binding energy and destabilise protein complex, whereas mutations at the non-interface might reduce folding energy and destabilise monomer structure. The results suggest that the structure-based analysis can provide useful information for understanding the molecular mechanisms of diseases.

| S-EPMC3319068 | biostudies-literature

Multistate approaches in computational protein design.

Project description:Computational protein design (CPD) is a useful tool for protein engineers. It has been successfully applied towards the creation of proteins with increased thermostability, improved binding affinity, novel enzymatic activity, and altered ligand specificity. Traditionally, CPD calculations search and rank sequences using a single fixed protein backbone template in an approach referred to as single-state design (SSD). While SSD has enjoyed considerable success, certain design objectives require the explicit consideration of multiple conformational and/or chemical states. Cases where a "multistate" approach may be advantageous over the SSD approach include designing conformational changes into proteins, using native ensembles to mimic backbone flexibility, and designing ligand or oligomeric association specificities. These design objectives can be efficiently tackled using multistate design (MSD), an emerging methodology in CPD that considers any number of protein conformational or chemical states as inputs instead of a single protein backbone template, as in SSD. In this review article, recent examples of the successful design of a desired property into proteins using MSD are described. These studies employing MSD are divided into two categories--those that utilized multiple conformational states, and those that utilized multiple chemical states. In addition, the scoring of competing states during negative design is discussed as a current challenge for MSD.

| S-EPMC3631354 | biostudies-literature

Computational design of thermostabilizing D-amino acid substitutions.

Project description:Judicious incorporation of D-amino acids in engineered proteins confers many advantages such as preventing degradation by endogenous proteases and promoting novel structures and functions not accessible to homochiral polypeptides. Glycine to D-alanine substitutions at the carboxy termini can stabilize α-helices by reducing conformational entropy. Beyond alanine, we propose additional side chain effects on the degree of stabilization conferred by D-amino acid substitutions. A detailed, molecular understanding of backbone and side chain interactions is important for developing rational, broadly applicable strategies in using D-amino acids to increase protein thermostability. Insight from structural bioinformatics combined with computational protein design can successfully guide the selection of stabilizing D-amino acid mutations. Substituting a key glycine in the Trp-cage miniprotein with D-Gln dramatically stabilizes the fold without altering the protein backbone. Stabilities of individual substitutions can be understood in terms of the balance of intramolecular forces both at the α-helix C-terminus and throughout the protein.

| S-EPMC3443866 | biostudies-literature

A generic program for multistate protein design.

Project description:Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.

| S-EPMC3130737 | biostudies-literature

Amino acid substitutions in CPC-LIKE MYB reveal residues important for protein stability in Arabidopsis roots.

Project description:TRYPTICHON (TRY) and ENHANCER OF TRY AND CPC2 (ETC2) encode R3-type MYB transcription factors that are involved in epidermal cell differentiation in Arabidopsis thaliana. TRY and ETC2 belong to the CPC-like MYB gene family, which includes seven homolog genes. Previously, we showed that among the CPC family members, TRY and ETC2 are characterized by rapid proteolysis compared with that of other members, and we demonstrated that this proteolysis is mediated by the proteasome-dependent pathway. In this study, we compared the functions of the wild-type TRY and ETC2 proteins and their amino acid-substituted versions. Our results showed that the substitution of amino acids in the C-terminal of TRY and ETC2 conferred them the ability to induce root hair formation. Furthermore, we confirmed that these mutations enhanced the stability of the TRY and ETC2 proteins. These results revealed that the amino acids, which are important for the functions of TRY and ETC2, mediate morphological pattern formation and can be useful in understanding the pathway determining the fate of root hair cells.

| S-EPMC6181395 | biostudies-literature

Sequence entropy of folding and the absolute rate of amino acid substitutions.

Project description:Adequate representations of protein evolution should consider how the acceptance of mutations depends on the sequence context in which they arise. However, epistatic interactions among sites in a protein result in hererogeneities in the substitution rate, both temporal and spatial, that are beyond the capabilities of current models. Here we use parallels between amino acid substitutions and chemical reaction kinetics to develop an improved theory of protein evolution. We constructed a mechanistic framework for modelling amino acid substitution rates that uses the formalisms of statistical mechanics, with principles of population genetics underlying the analysis. Theoretical analyses and computer simulations of proteins under purifying selection for thermodynamic stability show that substitution rates and the stabilization of resident amino acids (the 'evolutionary Stokes shift') can be predicted from biophysics and the effect of sequence entropy alone. Furthermore, we demonstrate that substitutions predominantly occur when epistatic interactions result in near neutrality; substitution rates are determined by how often epistasis results in such nearly neutral conditions. This theory provides a general framework for modelling protein sequence change under purifying selection, potentially explains patterns of convergence and mutation rates in real proteins that are incompatible with previous models, and provides a better null model for the detection of adaptive changes.

| S-EPMC5701738 | biostudies-literature

iCFN: an efficient exact algorithm for multistate protein design.

Project description:MotivationMultistate protein design addresses real-world challenges, such as multi-specificity design and backbone flexibility, by considering both positive and negative protein states with an ensemble of substates for each. It also presents an enormous challenge to exact algorithms that guarantee the optimal solutions and enable a direct test of mechanistic hypotheses behind models. However, efficient exact algorithms are lacking for multistate protein design.ResultsWe have developed an efficient exact algorithm called interconnected cost function networks (iCFN) for multistate protein design. Its generic formulation allows for a wide array of applications such as stability, affinity and specificity designs while addressing concerns such as global flexibility of protein backbones. iCFN treats each substate design as a weighted constraint satisfaction problem (WCSP) modeled through a CFN; and it solves the coupled WCSPs using novel bounds and a depth-first branch-and-bound search over a tree structure of sequences, substates, and conformations. When iCFN is applied to specificity design of a T-cell receptor, a problem of unprecedented size to exact methods, it drastically reduces search space and running time to make the problem tractable. Moreover, iCFN generates experimentally-agreeing receptor designs with improved accuracy compared with state-of-the-art methods, highlights the importance of modeling backbone flexibility in protein design, and reveals molecular mechanisms underlying binding specificity.Availability and implementationhttps://shen-lab.github.io/software/iCFN.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC6129278 | biostudies-literature

Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge.

Project description:Frataxin (FXN) is a highly conserved protein found in prokaryotes and eukaryotes that is required for efficient regulation of cellular iron homeostasis. Experimental evidence associates amino acid substitutions of the FXN to Friedreich Ataxia, a neurodegenerative disorder. Recently, new thermodynamic experiments have been performed to study the impact of somatic variations identified in cancer tissues on protein stability. The Critical Assessment of Genome Interpretation (CAGI) data provider at the University of Rome measured the unfolding free energy of a set of variants (FXN challenge data set) with far-UV circular dichroism and intrinsic fluorescence spectra. These values have been used to calculate the change in unfolding free energy between the variant and wild-type proteins at zero concentration of denaturant (ΔΔGH2O) . The FXN challenge data set, composed of eight amino acid substitutions, was used to evaluate the performance of the current computational methods for predicting the ΔΔGH2O value associated with the variants and to classify them as destabilizing and not destabilizing. For the fifth edition of CAGI, six independent research groups from Asia, Australia, Europe, and North America submitted 12 sets of predictions from different approaches. In this paper, we report the results of our assessment and discuss the limitations of the tested algorithms.

| S-EPMC6744327 | biostudies-literature

PON-Fold: Prediction of Substitutions Affecting Protein Folding Rate.

Project description:Most proteins fold into characteristic three-dimensional structures. The rate of folding and unfolding varies widely and can be affected by variations in proteins. We developed a novel machine-learning-based method for the prediction of the folding rate effects of amino acid substitutions in two-state folding proteins. We collected a data set of experimentally defined folding rates for variants and used them to train a gradient boosting algorithm starting with 1161 features. Two predictors were designed. The three-class classifier had, in blind tests, specificity and sensitivity ranging from 0.324 to 0.419 and from 0.256 to 0.451, respectively. The other tool was a regression predictor that showed a Pearson correlation coefficient of 0.525. The error measures, mean absolute error and mean squared error, were 0.581 and 0.603, respectively. One of the previously presented tools could be used for comparison with the blind test data set, our method called PON-Fold showed superior performance on all used measures. The applicability of the tool was tested by predicting all possible substitutions in a protein domain. Predictions for different conformations of proteins, open and closed forms of a protein kinase, and apo and holo forms of an enzyme indicated that the choice of the structure had a large impact on the outcome. PON-Fold is freely available.

| S-EPMC10455311 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data