Publications by authors named "Ytreberg F"

Killer toxins are proteinaceous antifungal molecules produced by yeasts, with activity against a wide range of human and plant pathogenic fungi. Fungus gardens of attine ants in Brazil were surveyed to determine the presence of killer toxin-producing yeasts and to define their antifungal activities and ecological importance. Our results indicate that up to 46% of yeasts isolated from specific fungal gardens can be killer yeasts, with an overall prevalence of 17% across all strains tested.

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Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain.

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Antibody escape mutations pose a significant challenge to the effectiveness of vaccines and antibody-based therapies. The ability to predict these escape mutations with computer simulations would allow us to detect threats early and develop effective countermeasures, but a lack of large-scale experimental data has hampered the validation of these calculations. In this study, we evaluate the ability of the MD+FoldX molecular modeling method to predict escape mutations by leveraging a large deep mutational scanning dataset, focusing on the SARS-CoV-2 receptor binding domain.

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Background: Computational methods of predicting protein stability changes upon missense mutations are invaluable tools in high-throughput studies involving a large number of protein variants. However, they are limited by a wide variation in accuracy and difficulty of assessing prediction uncertainty. Using a popular computational tool, FoldX, we develop a statistical framework that quantifies the uncertainty of predicted changes in protein stability.

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It has been 49 years since the last discovery of a new virus family in the model yeast Saccharomyces cerevisiae. A large-scale screen to determine the diversity of double-stranded RNA (dsRNA) viruses in S. cerevisiae has identified multiple novel viruses from the family Partitiviridae that have been previously shown to infect plants, fungi, protozoans, and insects.

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SARS-CoV-2 is the pathogen responsible for COVID-19 that has claimed over six million lives as of July 2022. The severity of COVID-19 motivates a need to understand how it could evolve to escape potential treatments and to find ways to strengthen existing treatments. Here, we used the molecular modeling methods MD + FoldX and PyRosetta to study the SARS-CoV-2 spike receptor binding domain (S-RBD) bound to two neutralizing antibodies, B38 and CB6 and generated lists of antibody escape and antibody strengthening mutations.

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The interaction between the HIV-1 capsid and human nucleoporin 153 (NUP153) is vital for delivering the HIV-1 preintegration complex into the nucleus via the nuclear pore complex. The interaction with the capsid requires a phenylalanine/glycine-containing motif in the C-terminus of NUP153 (NUP153C). This study used molecular modeling and biochemical assays to comprehensively determine the amino acids in NUP153 that are important for capsid interaction.

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Monoclonal antibodies are increasingly used for the prevention and/or treatment of viral infections. One caveat of their use is the ability of viruses to evolve resistance to antibody binding and neutralization. Computational strategies to identify viral mutations that may disrupt antibody binding would leverage the wealth of viral genomic sequence data to monitor for potential antibody-resistant mutations.

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When two or more amino acid mutations occur in protein systems, they can interact in a nonadditive fashion termed epistasis. One way to quantify epistasis between mutation pairs in protein systems is by using free energy differences: ϵ = ΔΔG  - (ΔΔG  + ΔΔG ) where ΔΔG refers to the change in the Gibbs free energy, subscripts 1 and 2 refer to single mutations in arbitrary order and 1,2 refers to the double mutant. In this study, we explore possible biophysical mechanisms that drive pairwise epistasis in both protein-protein binding affinity and protein folding stability.

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Serum albumin is the most abundant protein in blood plasma, and it is involved in multiple biological processes. Serum albumin has recently been adapted for improving biomaterial integration with bone tissue, and studies have shown the importance of this protein in bone repair and regeneration. However, the mechanism of action is not yet clear.

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Normal cellular processes give rise to toxic metabolites that cells must mitigate. Formaldehyde is a universal stressor and potent metabolic toxin that is generated in organisms from bacteria to humans. Methylotrophic bacteria such as Methylorubrum extorquens face an acute challenge due to their production of formaldehyde as an obligate central intermediate of single-carbon metabolism.

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Protein-protein binding is fundamental to most biological processes. It is important to be able to use computation to accurately estimate the change in protein-protein binding free energy due to mutations in order to answer biological questions that would be experimentally challenging, laborious, or time-consuming. Although nonrigorous free-energy methods are faster, rigorous alchemical molecular dynamics-based methods are considerably more accurate and are becoming more feasible with the advancement of computer hardware and molecular simulation software.

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Estimating free energy differences by computer simulation is useful for a wide variety of applications such as virtual screening for drug design and for understanding how amino acid mutations modify protein interactions. However, calculating free energy differences remains challenging and often requires extensive trial and error and very long simulation times in order to achieve converged results. Here, we present an implementation of the adaptive integration method (AIM).

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A growing number of computational tools have been developed to accurately and rapidly predict the impact of amino acid mutations on protein-protein relative binding affinities. Such tools have many applications, for example, designing new drugs and studying evolutionary mechanisms. In the search for accuracy, many of these methods employ expensive yet rigorous molecular dynamics simulations.

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One of the long-standing holy grails of molecular evolution has been the ability to predict an organism's fitness directly from its genotype. With such predictive abilities in hand, researchers would be able to more accurately forecast how organisms will evolve and how proteins with novel functions could be engineered, leading to revolutionary advances in medicine and biotechnology. In this work, we assemble the largest reported set of experimental TEM-1 β-lactamase folding free energies and use this data in conjunction with previously acquired fitness data and computational free energy predictions to determine how much of the fitness of β-lactamase can be directly predicted by thermodynamic folding and binding free energies.

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Models of Titan predict that there is a subsurface ocean of water and ammonia under a layer of ice. Such an ocean would be important in the search for extraterrestrial life since it provides a potentially habitable environment. To evaluate how Earth-based proteins would behave in Titan's subsurface ocean environment, we used molecular dynamics simulations to calculate the properties of proteins with the most common secondary structure types (alpha helix and beta sheet) in both Earth and Titan-like conditions.

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The 2014 outbreak of Ebola virus disease (EVD) in Western Africa is the largest recorded filovirus disease outbreak and led to the death of over 11,000 people. The recent EVD outbreaks (since May 2018) in the Democratic Republic of the Congo has already claimed the lives of over 250 people. Tackling Ebola virus (EBOV) outbreaks remains a challenge.

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Vision is the dominant sensory modality in many organisms for foraging, predator avoidance, and social behaviors including mate selection. Vertebrate visual perception is initiated when light strikes rod and cone photoreceptors within the neural retina of the eye. Sensitivity to individual colors, i.

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Determination of protein-protein binding affinity values is key to understanding various underlying biological phenomena, such as how missense variations change protein-protein binding. Most existing non-rigorous (fast) and rigorous (slow) methods that rely on all-atom representation of the proteins force the user to choose between speed and accuracy. In an attempt to achieve balance between speed and accuracy, we have combined rigorous umbrella sampling molecular dynamics simulation with a coarse-grained protein model.

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Multi-species microbial communities play a critical role in human health, industry, and waste remediation. Recently, the evolution of synthetic consortia in the laboratory has enabled adaptation to be addressed in the context of interacting species. Using an engineered bacterial consortium, we repeatedly evolved cooperative genotypes and examined both the predictability of evolution and the phenotypes that determine community dynamics.

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Since the recent devastating outbreak of Ebola virus disease in western Africa, there has been significant effort to understand the evolution of the deadly virus that caused the outbreak. There has been a considerable investment in sequencing Ebola virus (EBOV) isolates, and the results paint an important picture of how the virus has spread in western Africa. EBOV evolution cannot be understood outside the context of previous outbreaks, however.

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The 2014 Ebola virus (EBOV) outbreak in West Africa is the largest in recorded history and resulted in over 11,000 deaths. It is essential that strategies for treatment and containment be developed to avoid future epidemics of this magnitude. With the development of vaccines and antibody-based therapies using the envelope glycoprotein (GP) of the 1976 Mayinga strain, one important strategy is to anticipate how the evolution of EBOV might compromise these efforts.

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The cis and trans conformations of the Xaa-Pro (Xaa: any amino acid) peptide bond are thermodynamically stable while other peptide bonds strongly prefer trans. The effect of proline cis-trans isomerization on protein binding has not been thoroughly investigated. In this study, computer simulations were used to calculate the absolute binding affinity for a p53 peptide (residues 17-29) to MDM2 for both cis and trans isomers of the p53 proline in position 27.

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A short segment of the disordered p53 transactivation domain (p53TAD) forms an amphipathic helix when bound to the E3 ubiquitin ligase, MDM2. In the unbound p53TAD, this short segment has transient helical secondary structure. Using a method that combines broad sampling of conformational space with re-weighting, it is shown that it is possible to generate multiple, independent structural ensembles that have highly similar secondary structure distributions for both p53TAD and a P27A mutant.

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