Characterization of the cofactor-binding site in the SPOUT-fold methyltransferases by computational docking of S-adenosylmethionine to three crystal structures

BACKGROUND: There are several evolutionarily unrelated and structurally dissimilar superfamilies of S-adenosylmethionine (AdoMet)-dependent methyltransferases (MTases). A new superfamily (SPOUT) has been recently characterized on a sequence level and three structures of its members (1gz0, 1ipa, and 1k3r) have been solved. However, none of these structures include the cofactor or the substrate. Due to the strong evolutionary divergence and the paucity of experimental information, no confident predictions of protein-ligand and protein-substrate interactions could be made, which hampered the study of sequence-structure-function relationships in the SPOUT superfamily. RESULTS: We used the computational docking program AutoDock to identify the AdoMet-binding site on the surface of three MTase structures. We analyzed the sequence divergence in two distinct lineages of the SPOUT superfamily in the context of surface features and preferred cofactor binding mode to propose specific function for the conserved residues. CONCLUSION: Our docking analysis has confidently predicted the common AdoMet-binding site in three remotely related proteins structures. In the vicinity of the cofactor-binding site, subfamily-conserved grooves were identified on the protein surface, suggesting location of the target-binding/catalytic site. Functionally important residues were inferred and a general reaction mechanism, involving conformational change of a glycine-rich loop, was proposed

Intentions to be Vaccinated Against COVID-19:The Role of Prosociality and Conspiracy Beliefs across 20 Countries

Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to encourage vaccine uptake.</p

Using Machine Learning to Identify Important Predictors of COVID-19 Infection Prevention Behaviors During the Early Phase of the Pandemic

Before vaccines for COVID-19 became available, a set of infection prevention behaviors constituted the primary means to mitigate the virus spread. Our study aimed to identify important predictors of this set of behaviors. Whereas social and health psychological theories suggest a limited set of predictors, machine learning analyses can identify correlates from a larger pool of candidate predictors. We used random forests to rank 115 candidate correlates of infection prevention behavior in 56,072 participants across 28 countries, administered in March-May 2020. The machine- learning model predicted 52% of the variance in infection prevention behavior in a separate test sample—exceeding the performance of psychological models of health behavior. Results indicated the two most important predictors related to individual- level injunctive norms. Illustrating how data-driven methods can complement theory, some of the most important predictors were not derived from theories of health behavior—and some theoretically-derived predictors were relatively unimportant

COLORADO3D, a web server for the visual analysis of protein structures

COLORADO3D is a World Wide Web server for the visual presentation of three-dimensional (3D) protein structures. COLORADO3D indicates the presence of potential errors (detected by ANOLEA, PROSAII, PROVE or VERIFY3D), identifies buried residues and depicts sequence conservations. As input, the server takes a file of Protein Data Bank (PDB) coordinates and, optionally, a multiple sequence alignment. As output, the server returns a PDB-formatted file, replacing the B-factor column with values of the chosen parameter (structure quality, residue burial or conservation). Thus, the coordinates of the analyzed protein ‘colored’ by COLORADO3D can be conveniently displayed with structure viewers such as RASMOL in order to visualize the 3D clusters of regions with common features, which may not necessarily be adjacent to each other at the amino acid sequence level. In particular, COLORADO3D may serve as a tool to judge a structure's quality at various stages of the modeling and refinement (during both experimental structure determination and homology modeling). The GeneSilico group used COLORADO3D in the fifth Critical Assessment of Techniques for Protein Structure Prediction (CASP5) to successfully identify well-folded parts of preliminary homology models and to guide the refinement of misthreaded protein sequences. COLORADO3D is freely available for academic use at http://asia.genesilico.pl/colorado3d/

Intentions to be Vaccinated Against COVID-19:The Role of Prosociality and Conspiracy Beliefs across 20 Countries

Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to encourage vaccine uptake.</p

Intentions to be Vaccinated Against COVID-19: The Role of Prosociality and Conspiracy Beliefs across 20 Countries

Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to encourage vaccine uptake

Lives versus Livelihoods? Perceived economic risk has a stronger association with support for COVID-19 preventive measures than perceived health risk

This paper examines whether compliance with COVID-19 mitigation measures is motivated by wanting to save lives or save the economy (or both), and which implications this carries to fight the pandemic. National representative samples were collected from 24 countries (N = 25,435). The main predictors were (1) perceived risk to contract coronavirus, (2) perceived risk to suffer economic losses due to coronavirus, and (3) their interaction effect. Individual and country-level variables were added as covariates in multilevel regression models. We examined compliance with various preventive health behaviors and support for strict containment policies. Results show that perceived economic risk consistently predicted mitigation behavior and policy support—and its effects were positive. Perceived health risk had mixed effects. Only two significant interactions between health and economic risk were identified—both positive