Effects Of Single Point Mutations Research Articles

ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction.

The solute carrier transporter family 6 (SLC6) is of key interest for their critical role in the transport of small amino acids or amino acid-like molecules. Their dysfunction is strongly associated with human diseases such as including schizophrenia, depression, and Parkinson's disease. Linking single point mutations to disease may support insights into the structure-function relationship of these transporters. This work aimed to develop a computational model for predicting the potential pathogenic effect of single point mutations in the SLC6 family. Missense mutation data was retrieved from UniProt, LitVar, and ClinVar, covering multiple protein-coding transcripts. As encoding approach, amino acid descriptors were used to calculate the average sequence properties for both original and mutated sequences. In addition to the full-sequence calculation, the sequences were cut into twelve domains. The domains are defined according to the transmembrane domains of the SLC6 transporters to analyse the regions' contributions to the pathogenicity prediction. Subsequently, several classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) with the hyperparameters optimized through grid search were built. For estimation of model performance, repeated stratified k-fold cross-validation was used. The accuracy values of the generated models are in the range of 0.72 to 0.80. Analysis of feature importance indicates that mutations in distinct regions of SLC6 transporters are associated with an increased risk for pathogenicity. When applying the model on an independent validation set, the performance in accuracy dropped to averagely 0.6 with high precision but low sensitivity scores.

Additional PfCRT mutations driven by selective pressure for improved fitness can result in the loss of piperaquine resistance and altered Plasmodium falciparum physiology.

Our study leverages gene editing techniques in Plasmodium falciparum asexual blood stage parasites to profile novel mutations in mutant PfCRT, an important mediator of piperaquine resistance, which developed in Southeast Asian field isolates or in parasites cultured for long periods of time. We provide evidence that increased parasite fitness of these lines is the primary driver for the emergence of these PfCRT variants. These mutations differentially impact parasite susceptibility to piperaquine and chloroquine, highlighting the multifaceted effects of single point mutations in this transporter. Molecular features of drug resistance and parasite physiology were examined in depth using proteoliposome-based drug uptake studies and peptidomics, respectively. Energy minimization calculations, showing how these novel mutations might impact the PfCRT structure, suggested a small but significant effect on drug interactions. This study reveals the subtle interplay between antimalarial resistance, parasite fitness, PfCRT structure, and intracellular peptide availability in PfCRT-mediated parasite responses to changing drug selective pressures.

Effects of single-point mutations on translocation of non-interacting heteropolymer protein chains

We analyse the role of single-point mutations on the translocation of heteropolymer protein chains with helical folding. We propose a statistical mechanics model that computes the equilibrium partition function of a given protein by incorporating experimental helix propensities of amino acids. From that we evaluate the free energy barrier for translocation and the average translocation time for single-point protein mutants and compared with wild-type proteins used as reference. In our calculations, single-point mutations that increase energy of the folded state in increase the energy barrier for translocation up to , , in consequence, the translocation time undergoes variations between and with the largest variations associated to substitutions of amino acids glycine and proline by alanine. In fact, substitutions of amino acids with the lowest helix propensities by amino acids with the largest helix propensities induced the largest mutational effects. These results indicate that effects of single-point mutations become evident when mutations increase energy of the folded state at least in . Our model predicts translocation time delays for proline to alanine single-point mutations which agree with deficiencies of protein translocation observed recently in experiments.

Hybrid enhanced sampling approaches to gain structural insights into leucine-rich repeat kinase 2 (LRRK2) Parkinson's disease mutation.

Parkinson's disease (PD) is a neurodegenerative disease affecting millions worldwide. A commonly mutated gene in PD is leucine-rich repeat kinase 2 (LRRK2), which contains multiple domains, including but not limited to kinase, ATPase, and GTPase. LRRK2 has been found to increase kinase activity and colocalize with microtubules. LRRK2 protein dynamics are affected by its conformation, regulating microtubule interactions and potentially enhancing intracellular trafficking. Despite recent advances in the structural insights of LRRK2, detailed studies on the effects of single-point mutations on the dynamics and conformations of LRRK2 are limited. Consequently, an all-atomistic molecular dynamics simulation is required to understand the allosteric and dynamical effects of single-point disease mutations in LRRK2, but it would be computationally expensive. We thereby employ enhanced molecular dynamics simulations to study single-point mutations in LRRK2, particularly the G2019S, R1441C, R1441G, R1441H, and Y1699C mutations. Our two-phase approach incorporates implementing Gaussian-accelerated molecular dynamics (GaMD) for enhanced sampling, followed by the weighted ensemble (WE) method. GaMD is an enhanced MD approach where a boost potential is added to the total potential energy of the system to accelerate the conformational search, while the WE method readjusts the weight of the simulation trajectories by frequent resampling to obtain the kinetic properties of interest accurately. Investigating the dynamics of such single-point mutations in LRRK2 could explain why specific mutations result in increased kinase activation and dynamicity of LRRK2.

MYH7 mutations induce changes in single cell mechanobiology.

Hypertrophic Cardiomyopathy (HCM) is characterized by thickening of the left ventricular wall and hypercontractility and has been linked to mutations in the sarcomere motor protein β-myosin (MYH7). Using single cell mechanobiology studies, we examined how the effects of single point mutations propagate to change the contractile dynamics and cellular morphology (sarcomere spacing, spread area, myofibril alignment) of human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs). We micropattern islands of adhesive protein to constraining the spreading and alignment of hiPSC-CM on hydrogel substrates containing fluorescent microbeads as fiducial markers for traction force microscopy (TFM). We deployed substrate stiffnesses ranging from physiological (10 kPa) to heavily diseased/fibrotic (100 kPa) to test the role of increased “afterload” in functional phenotypes. We use image and video analysis to assess the contractile dynamics of the hiPSC-CM in terms of force, power, and velocities of relaxation and contraction. For example, we assessed multiple MYH7 mutations edited into the WTC line along with isogenic controls. Some lines carried an endogenously labeled alpha-actinin GFP reporter of sarcomere structure to enable visualization of sarcomere structure and dynamics. We assessed the magnitude and dynamics of contractile force output from TFM video analysis and observed increased the contractile force when compared to the control hiPSC-CMs. We also measured significantly different dynamics in the relaxation or contraction velocities compared to control hiPSC-CMs. Interestingly, not all HCM mutant lines presented a significant increase in cell spread area, a proxy for hypertrophy, and this correlated with culture conditions, such as the size of the protein pattern constraining the cells or stiffness of the substrate. Taken together, these results suggest a role for MYH7 mutations driving remodeling of structure and function at a cell-intrinsic level via changes in mechanosignaling.

The introduction of mutations in the wild type coxsackievirus B3 (CVB3) IRES RNA leads to different levels of in vitro reduced replicative and translation efficiencies.

Coxsackievirus B3 (CVB3) is a principal causative agent of viral myocarditis, meningitis and pancreatitis. There is no vaccine available for clinical use. It has been demonstrated that the primary molecular determinant of virulence phenotype is located in the 5’ UTR of the viral genome. Translation initiation of CVB3 RNA is directed by the IRES element situated in the 5’UTR. In the present study, we analyse the effects of single point mutations introduced in different positions in the domain V of the IRES RNA of CVB3 wild type. We characterize in vitro virus replicative capacitiy and translation efficiency and we test in vivo virulence of different CVB3 mutants produced by the introduction of different mutations in the domain V of IRES by site-directed mutagenesis to abolish its structure. Our results demonstrate that all RNA mutants display different levels of decreased replication and translation initiation efficiency in vitro. The translation defect was correlated with significant reduced viral titer of mutant particles in comparison with the wild type. When inoculated in mice, mutant viruses were checked for inflammation and necrosis.In vitro and in vivo Findings strongly suggest that the most attenuated mutant strain could be considered a candidate for live-attenuated CVB3 vaccine.

Design of Pb(II)-Specific E. coli-Based Biosensors by Engineering Regulatory Proteins and Host Cells.

Bacterial cell-based biosensors have been widely developed for detecting environmental toxic materials. The znt-operon in Escherichia coli is a Zn(II)-responsive genetic system and is employed in Zn(II), Cd(II), and Hg(II)-sensing biosensors. In this study, point mutations were introduced in the regulatory protein ZntR to modulate its target selectivity, and metal ion-exporting genes, such as copA and zntA, in host cells were deleted to increase cellular metal ion levels and enhance specificity. Thus, the overall responses of the E. coli cell-based biosensors toward metal(loid) ions were increased, and their selectivity, which was originally for Cd(II) and Hg(II), was shifted to Pb(II). The gene encoding ZntA, known as the Zn(II)-translocating P-type ATPase, showed an impact on the ability of E. coli to export Pb(II), whereas copA deletion showed no significant impact. Noteworthily, the newly generated biosensors employing ZntR Cys115Ile showed the capacity to detect under 5 nM Pb(II) in solution, without response to other tested metal ions within 0–100 nM. To understand the marked effect of single point mutations on ZntR, computational modeling was employed. Although it did not provide clear answers, changes in the sequences of the metal-binding loops of ZntR modulated its transcriptional strength and target selectivity. In summary, the approaches proposed in this study can be valuable to generate new target-sensing biosensors with superior selectivity and specificity, which can in turn broaden the applicability of cell-based biosensors to monitor Pb(II) in environmental systems.

Evaluation of the angiogenic properties of Brugia malayi asparaginyl-tRNA synthetase and its mutants: A study on the molecular target for antifilarial drug development

Brugia malayi asparaginyl-tRNA synthetase (BmAsnRS) has been identified as an immunodominant antigen and a physiocrine that mimics Interleukin-8 (IL-8) to induce chemotaxis and angiogenesis in endothelial cells. Computational analyses have shown that the N-terminal region of BmAsnRS has a novel fold, a lysine rich β-hairpin α-helix, (FLIRTKKDGKQIWE) which is similar to that present in IL-8 chemokine, CXCR1. This novel fold is involved in tRNA binding and is integral for the manifestation of the disease, lymphatic filariasis (LF). Drug discovery programmes carried out so far for LF have not been successful because of the target (BmAsnRS) resistance due to the disease-associated mutation. Mutations in AARS targets have been shown to correlate with several diseases. However, no disease-associated mutational studies have been carried out for LF. BmAsnRS has been an established target for LF. It was proposed, therefore, to study the effect of single point mutations in BmAsnRS so as to elucidate the molecular target. An understanding of the molecular consequences of mutations will provide insight into how resistance develops in addition to the identification of the likely resistance-conferring mutations. Three mutants were, therefore, generated by site-directed mutagenesis using CUPSAT server and their angiogenic properties evaluated. Cytometric analysis of the mutants on endothelial cell cycle was also carried out. CUPSAT prediction of protein stability upon point mutations reveal that two mutants generated are likely resistance-conferring mutations. All the three mutants show significant reduction in their angiogenic properties and reduction in the DNA content in the cells of S and G2/M phases thus showing altered function of the gene encoding the drug target. The resistance- conferring mutants, however, show angiogenic properties nearer to the wild type protein, BmAsnRS. Future work on designing newer drugs may take into consideration these drug resistance-conferring mutations.

SAAFEC-SEQ: A Sequence-Based Method for Predicting the Effect of Single Point Mutations on Protein Thermodynamic Stability

Modeling the effect of mutations on protein thermodynamics stability is useful for protein engineering and understanding molecular mechanisms of disease-causing variants. Here, we report a new development of the SAAFEC method, the SAAFEC-SEQ, which is a gradient boosting decision tree machine learning method to predict the change of the folding free energy caused by amino acid substitutions. The method does not require the 3D structure of the corresponding protein, but only its sequence and, thus, can be applied on genome-scale investigations where structural information is very sparse. SAAFEC-SEQ uses physicochemical properties, sequence features, and evolutionary information features to make the predictions. It is shown to consistently outperform all existing state-of-the-art sequence-based methods in both the Pearson correlation coefficient and root-mean-squared-error parameters as benchmarked on several independent datasets. The SAAFEC-SEQ has been implemented into a web server and is available as stand-alone code that can be downloaded and embedded into other researchers’ code.

Computation of FRAP recovery times for linker histone – chromatin binding on the basis of Brownian dynamics simulations

BackgroundFluorescence recovery after photobleaching (FRAP) studies can provide kinetic information about proteins in cells. Single point mutations can significantly affect the binding kinetics of proteins and result in variations in the recovery half time (t50) measured in FRAP experiments. FRAP measurements of linker histone (LH) proteins in the cell nucleus have previously been reported by Brown et al. (2006) and Lele et al. (2006).MethodsWe performed Brownian dynamics (BD) simulations of the diffusional association of the wild-type and 38 single or double point mutants of the globular domain of mouse linker histone H1.0 (gH1.0) to a nucleosome. From these simulations, we calculated the bimolecular association rate constant (kon), the Gibbs binding free energy (ΔG) and the dissociation rate constant (koff) related to formation of a diffusional encounter complex between the nucleosome and the gH1.0.ResultsWe used these parameters, after application of a correction factor to account for the effects of the crowded environment of the nucleus, to compute FRAP recovery times and curves that are in good agreement with previously published, experimentally measured FRAP recovery time courses.ConclusionsOur computational analysis suggests that BD simulations can be used to predict the relative effects of single point mutations on FRAP recovery times related to protein binding.General SignificanceBD simulations assist in providing a detailed molecular level interpretation of FRAP data.

Improving the Accuracy of Protein Thermostability Predictions for Single Point Mutations

Accurately predicting the protein thermostability changes upon single point mutations in silico is a challenge that has implications for understanding diseases as well as industrial applications of protein engineering. Free energy perturbation (FEP) has been applied to predict the effect of single point mutations on protein stability for over 40 years and emerged as a potentially reliable prediction method with reasonable throughput. However, applications of FEP in protein stability calculations in industrial settings have been hindered by a number of limitations, including the inability to model mutations to and from prolines in which the bonded topology of the backbone is modified and the complexity in modeling charge-changing mutations. In this study, we have extended the FEP+ protocol to enable the accurate modeling of the effects on protein stability from proline mutations and from charge-changing mutations. We also evaluated the influence of the unfolded model in the stability calculations using increasingly longer peptides with native sequence and conformations. With the abovementioned improvements, the accuracy of FEP predictions of protein stability over a data set of 87 mutations on five different proteins has drastically improved compared with previous studies, with a mean unsigned error of 0.86 kcal/mol and root mean square error of 1.11 kcal/mol, comparable with the accuracy of previously published state-of-the-art small-molecule relative binding affinity calculations, which have been shown to be capable of driving discovery projects.

The importance of the quaternary structure to represent conformational ensembles of the major Mycobacterium tuberculosis drug target

Flexibility is a feature intimately related to protein function, since conformational changes can be used to describe environmental changes, chemical modifications, protein-protein and protein-ligand interactions. In this study, we have investigated the influence of the quaternary structure of 2-trans-enoyl-ACP (CoA) reductase or InhA, from Mycobacterium tuberculosis, to its flexibility. We carried out classical molecular dynamics simulations using monomeric and tetrameric forms to elucidate the enzyme’s flexibility. Overall, we observed statistically significant differences between conformational ensembles of tertiary and quaternary structures. In addition, the enzyme’s binding site is the most affected region, reinforcing the importance of the quaternary structure to evaluate the binding affinity of small molecules, as well as the effect of single point mutations to InhA protein dynamics.

Effect of Single-Point Mutations on Nitric Oxide Rebinding and the Thermodynamic Stability of Myoglobin

Effect of Single-Point Mutations on Nitric Oxide Rebinding and the Thermodynamic Stability of Myoglobin

Effect of Single-Point Mutations on Nitric Oxide Rebinding and the Thermodynamic Stability of Myoglobin.

The effect of single amino acid mutations on the rebinding dynamics of nitrogen monoxide (NO) to myoglobin is investigated using reactive molecular dynamics simulations. In particular, mutations of residues surrounding the heme-active site (Leu29, His64, Val68) were considered. Consistent with experiments, all mutations studied here have a significant effect on the kinetics of the NO-rebinding process, which consists of a rapid (several 10 ps) and a slow (100s of ps) time scale. For all modifications considered, the time scales and rebinding fractions agree to within a few percents with results from experiments by adjusting one single, physically meaningful, conformationally averaged quantity: the asymptotic energy separation between the NO-bound (2A) and photodissociated (4A) states. It is furthermore shown that the thermodynamic stability of wild-type versus mutant Mb for the ligand-free and ligand-bound variants of the protein can be described by the same computational model. Therefore, ligand kinetics and thermodynamics are related in a direct fashion akin to Φ-value analysis, which establishes a relationship between protein folding rates and thermal stability of proteins.

Variable Dynamics of IgG4 Monoclonal Antibody Controlled by Single Point Mutations

An immunoglobulin G (IgG) antibody consists of two heavy and two light chains that bind together to form a Y-shaped structure. Although IgG antibodies are naturally bivalent, weak interaction within the CH3-CH3 domain interface together with a Fab-arm exchange allows the IgG4 antibody to become an effective monovalent half molecule. Recent experiments determined a number of single point mutations in the CH3-CH3 interfacial region that significantly increase the monovalent form [1,2]. In this investigation, we explored the effect of single point mutations in the interface of the CH3-CH3 domain on the structure and dynamics of the full IgG4 molecule using coarse-grained molecular dynamics (MD) simulation employing a Martini force field.

SAAFEC: Predicting the Effect of Single Point Mutations on Protein Folding Free Energy Using a Knowledge-Modified MM/PBSA Approach.

Folding free energy is an important biophysical characteristic of proteins that reflects the overall stability of the 3D structure of macromolecules. Changes in the amino acid sequence, naturally occurring or made in vitro, may affect the stability of the corresponding protein and thus could be associated with disease. Several approaches that predict the changes of the folding free energy caused by mutations have been proposed, but there is no method that is clearly superior to the others. The optimal goal is not only to accurately predict the folding free energy changes, but also to characterize the structural changes induced by mutations and the physical nature of the predicted folding free energy changes. Here we report a new method to predict the Single Amino Acid Folding free Energy Changes (SAAFEC) based on a knowledge-modified Molecular Mechanics Poisson-Boltzmann (MM/PBSA) approach. The method is comprised of two main components: a MM/PBSA component and a set of knowledge based terms delivered from a statistical study of the biophysical characteristics of proteins. The predictor utilizes a multiple linear regression model with weighted coefficients of various terms optimized against a set of experimental data. The aforementioned approach yields a correlation coefficient of 0.65 when benchmarked against 983 cases from 42 proteins in the ProTherm database. Availability: the webserver can be accessed via http://compbio.clemson.edu/SAAFEC/.

Large scale analysis of the mutational landscape in β-glucuronidase: A major player of mucopolysaccharidosis type VII

The lysosomal storage disorders are a group of 50 unique inherited diseases characterized by unseemly lipid storage in lysosomes. These malfunctions arise due to genetic mutations that result in deficiency or reduced activities of the lysosomal enzymes, which are responsible for catabolism of biological macromolecules. Sly syndrome or mucopolysaccharidosis type VII is a lysosomal storage disorder associated with the deficiency of β-glucuronidase (EC 3.2.1.31) that catalyzes the hydrolysis of β-d-glucuronic acid residues from the non-reducing terminal of glycosaminoglycan. The effects of the disease causing mutations on the framework of the sequences and structure of β-glucuronidase (GUSBp) were analyzed utilizing a variety of bioinformatic tools. These analyses showed that 211 mutations may result in alteration of the biological activity of GUSBp, including previously experimentally validated mutations. Finally, we refined 90 disease causing mutations, which presumably cause a significant impact on the structure, function, and stability of GUSBp. Stability analyses showed that mutations p.Phe208Pro, p.Phe539Gly, p.Leu622Gly, p.Ile499Gly and p.Ile586Gly caused the highest impact on GUSBp stability and function because of destabilization of the protein structure. Furthermore, structures of wild type and mutant GUSBp were subjected to molecular dynamics simulation to examine the relative structural behaviors in the explicit conditions of water. In a broader view, the use of in silico approaches provided a useful understanding of the effect of single point mutations on the structure-function relationship of GUSBp.

Effect of single point mutations in a form of systemic amyloidosis.

Amyloid deposits of light-chain proteins are associated with the most common form of systemic amyloidosis. We have studied the effects of single point mutations on amyloid formation of these proteins using explicit solvent model molecular dynamics simulations. For this purpose, we compare the stability of the wild-type immunoglobulin light-chain protein REI in its native and amyloid forms with that of four mutants: R61N, G68D, D82I, and A84T. We argue that the experimentally observed differences in the propensity for amyloid formation result from two effects. First, the mutant dimers have a lower stability than the wild-type dimer due to increase exposure of certain hydrophobic residues. The second effect is a shift in equilibrium between monomers with amyloid-like structure and such with native structures. Hence, when developing drugs against light-chain associated systemic amyloidosis, one should look for components that either stabilize the dimer by binding to the dimer interface or reduce for the monomers the probability of the amyloid form.

ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability.

ENCoM is a coarse-grained normal mode analysis method recently introduced that unlike previous such methods is unique in that it accounts for the nature of amino acids. The inclusion of this layer of information was shown to improve conformational space sampling and apply for the first time a coarse-grained normal mode analysis method to predict the effect of single point mutations on protein dynamics and thermostability resulting from vibrational entropy changes. Here we present a web server that allows non-technical users to have access to ENCoM calculations to predict the effect of mutations on thermostability and dynamics as well as to generate geometrically realistic conformational ensembles. The server is accessible at: http://bcb.med.usherbrooke.ca/encom.

Systems-level response to point mutations in a core metabolic enzyme modulates genotype-phenotype relationship.

Linking the molecular effects of mutations to fitness is central to understanding evolutionary dynamics. Here, we establish a quantitative relation between the global effect of mutations on the E. coli proteome and bacterial fitness. We created E. coli strains with specific destabilizing mutations in the chromosomal folA gene encoding dihydrofolate reductase (DHFR) and quantified the ensuing changes in the abundances of 2,000+ E. coli proteins in mutant strains using tandem mass tags with subsequent LC-MS/MS. mRNA abundances in the same E. coli strains were also quantified. The proteomic effects of mutations in DHFR are quantitatively linked to phenotype: the SDs of the distributions of logarithms of relative (to WT) protein abundances anticorrelate with bacterial growth rates. Proteomes hierarchically cluster first by media conditions, and within each condition, by the severity of the perturbation to DHFR function. These results highlight the importance of a systems-level layer in the genotype-phenotype relationship.