Protein folding stabilities are a major determinant of oxidation rates for buried methionine residues

The oxidation of protein-bound methionines to form methionine sulfoxides has a broad range of biological ramifications, making it important to delineate factors that influence methionine oxidation rates within a protein. This is especially important for biopharmaceuticals, where oxidation can lead to deactivation and degradation. Previously, neighboring residue effects and solvent accessibility (SA) have been shown to impact the susceptibility of methionine residues to oxidation. In this study, we provide proteome-wide evidence that oxidation rates of buried methionine residues are also strongly influenced by the thermodynamic folding stability of proteins. We surveyed the E. coli proteome using several proteomic methodologies and globally measured oxidation rates of methionines in the presence and absence of tertiary structure, as well as folding stabilities of methionine containing domains. The data indicate that buried methionines have a wide range of protection factors against oxidation which correlate strongly with folding stabilities. Concordantly, we show that in comparison to E. coli, the proteome of the thermophile T. thermophilus is significantly more stable and thus more resistant to methionine oxidation. These results indicate that oxidation rates of buried methionines from the native state of proteins can be used as a metric of folding stability. To demonstrate the utility of this correlation, we used native methionine oxidation rates to survey the folding stabilities of E. coli and T. thermophilus proteomes at various temperatures and suggest a model that relates the temperature dependence of the folding stabilities of these two species to their optimal growth temperatures.

Attention-based convolutional neural networks for protein-protein interaction site prediction

Motivation: Protein-protein interactions are of great importance in the life cycles of living cells. Accurate prediction of the protein-protein interaction site (PPIs) from protein sequence improves our understanding of protein-protein interaction, contributes to the protein-protein docking and is crucial for drug design. However, practical experimental methods are costly and time-consuming so that many sequence-based computational methods have been developed. Most of those methods employ a sliding window approach, which utilize local neighbor information within a window size. However, they don't distinguish and use the effect of each individual neighboring residue at different position. Results: We propose a novel sequence-based deep learning method consisting of convolutional neural networks (CNNs) and attention mechanism to improve the performance of PPIs prediction. Our attention-based CNNs captures the different effect of each neighboring residue within a sliding window, and therefore making a better understanding of the local environment of target residue. We employ experiments on several public benchmark datasets. The experimental results demonstrate that our proposed method significantly outperforms the state-of-the-art techniques. We also analyze the difference using various sliding window lengths and amino acid residue features combination. Availability and implementation: The source code can be obtained from https://github.com/biolushuai/attention-based-CNNs-for-PPIs-prediction Contact: [email protected] or [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

Reporter Assays for Ebola Virus Nucleoprotein Oligomerization, Virion-Like Particle Budding, and Minigenome Activity Reveal the Importance of Nucleoprotein Amino Acid Position 111

For highly pathogenic viruses, reporter assays that can be rapidly performed are critically needed to identify potentially functional mutations for further study under maximal containment (e.g., biosafety level 4 [BSL-4]). The Ebola virus nucleoprotein (NP) plays multiple essential roles during the viral life cycle, yet few tools exist to study the protein under BSL-2 or equivalent containment. Therefore, we adapted reporter assays to measure NP oligomerization and virion-like particle (VLP) production in live cells and further measured transcription and replication using established minigenome assays. As a proof-of-concept, we examined the NP-R111C substitution, which emerged during the 2013–2016 Western African Ebola virus disease epidemic and rose to high frequency. NP-R111C slightly increased NP oligomerization and VLP budding but slightly decreased transcription and replication. By contrast, a synthetic charge-reversal mutant, NP-R111E, greatly increased oligomerization but abrogated transcription and replication. These results are intriguing in light of recent structures of NP oligomers, which reveal that the neighboring residue, K110, forms a salt bridge with E349 on adjacent NP molecules. By developing and utilizing multiple reporter assays, we find that the NP-111 position mediates a complex interplay between NP’s roles in protein structure, virion budding, and transcription and replication.

Reporter assays for Ebola virus nucleoprotein oligomerization, virion-like particle budding, and minigenome activity reveal the importance of nucleoprotein amino acid position 111

For highly pathogenic viruses, reporter assays that can be rapidly performed are critically needed to identify potentially functional mutations for further study under maximal containment (e.g., biosafety level 4 [BSL-4]). The Ebola virus nucleoprotein (NP) plays multiple essential roles during the viral life cycle, yet few tools exist to study the protein under BSL-2 or equivalent containment. Therefore, we adapted reporter assays to measure NP oligomerization and virion-like particle (VLP) production in live cells and further measure transcription and replication using established minigenome assays. As a proof-of-concept, we examined the NP-R111C substitution, which emerged during the 2013–2016 Western African Ebola virus disease epidemic and rose to high frequency. NP-R111C slightly increased NP oligomerization and VLP budding but slightly decreased transcription and replication. By contrast, a synthetic charge-reversal mutant, NP-R111E, greatly increased oligomerization but abrogated transcription and replication. These results are intriguing in light of recent structures of NP oligomers, which reveal that the neighboring residue, K110, forms a salt bridge with E349 on adjacent NP molecules. By developing and utilizing multiple reporter assays, we find that the NP-111 position mediates a complex interplay between NP’s roles in protein structure, virion budding, and transcription and replication.

Hydration effects on Leu's polyproline II population in AcLXPNH2

Hydration effects are revealed by a correlation between neighboring-residue and blocking effects.