People believe political opponents accept blatant moral wrongs, fueling partisan divides.

Efforts to bridge political divides often focus on navigating complex and divisive issues, but eight studies reveal that we should also focus on a more basic misperception: that political opponents are willing to accept basic moral wrongs. In the United States, Democrats, and Republicans overestimate the number of political outgroup members who approve of blatant immorality (e.g.

AllergenAI: a deep learning model predicting allergenicity based on protein sequence.

Innovations in protein engineering can help redesign allergenic proteins to reduce adverse reactions in sensitive individuals. To accomplish this aim, a better knowledge of the molecular properties of allergenic proteins and the molecular features that make a protein allergenic is needed. We present a novel AI-based tool, AllergenAI, to quantify the allergenic potential of a given protein.

Displaying alphavirus physicochemical consensus antigens on immunogenic liposomes enhances antibody elicitation in mice.

Cobalt-porphyrin phospholipid displays recombinant protein antigens on liposome surfaces via antigen polyhistidine-tag (His-tag), and when combined with monophosphorylated lipid A and QS-21 yields the "CPQ" vaccine adjuvant system. In this proof of principle study, CPQ was used to generate vaccine prototypes that elicited antibodies for two different alphaviruses (AV). Mice were immunized with computationally designed, His-tagged, physicochemical property consensus (PCP) protein antigens representing the variable B-domain of the envelope protein 2 (E2) from the serotype specific Venezuelan Equine Encephalitis Virus (VEEV) or a broad-spectrum AV-antigen termed EVC The CPQ adjuvant enhanced the antigenicity of both proteins without eliciting detectable anti-His-tag antibodies.

The updated Structural Database of Allergenic Proteins (SDAP 2.0) provides 3D models for allergens and incorporated bioinformatics tools.

Background: Allergenic proteins can cause IgE-mediated adverse reactions in sensitized individuals. Although the sequences of many allergenic proteins have been identified, bioinformatics data analysis with advanced computational methods and modeling is needed to identify the basis for IgE binding and cross-reactivity.

Objective: We aim to present the features and use of the updated Structural Database of Allergenic Proteins 2.

Identifying Similar Allergens and Potentially Cross-Reacting Areas Using Structural Database of Allergenic Proteins (SDAP) Tools and D-Graph.

The Structural Database of Allergenic Proteins (SDAP) provides rapid search tools to identify similarities among allergens, their IgE epitopes, and to determine the potential allergenicity of any novel protein. Many labs have identified IgE-binding proteins and their antibody binding or T cell epitopes using dotspots or microarrays. This chapter describes how to determine the relationship of these proteins and peptides to known allergens using the tools implemented in SDAP.