Correlated mutations via regularized multinomial regression

Background In addition to sequence conservation, protein multiple sequence alignments contain evolutionary signal in the form of correlated variation among amino acid positions. This signal indicates positions in the sequence that influence each other, and can be applied for the prediction of intra- or intermolecular contacts. Although various approaches exist for the detection of such correlated mutations, in general these methods utilize only pairwise correlations. Hence, they tend to conflate direct and indirect dependencies. Results We propose RMRCM, a method for Regularized Multinomial Regression in order to obtain Correlated Mutations from protein multiple sequence alignments. Importantly, our method is not restricted to pairwise (column-column) comparisons only, but takes into account the network nature of relationships between protein residues in order to predict residue-residue contacts. The use of regularization ensures that the number of predicted links between columns in the multiple sequence alignment remains limited, preventing overprediction. Using simulated datasets we analyzed the performance of our approach in predicting residue-residue contacts, and studied how it is influenced by various types of noise. For various biological datasets, validation with protein structure data indicates a good performance of the proposed algorithm for the prediction of residue-residue contacts, in comparison to previous results. RMRCM can also be applied to predict interactions (in addition to only predicting interaction sites or contact sites), as demonstrated by predicting PDZ-peptide interactions. Conclusions A novel method is presented, which uses regularized multinomial regression in order to obtain correlated mutations from protein multiple sequence alignments

Field Evaluation of Traditionally Used Plant-Based Insect Repellents and Fumigants Against the Malaria Vector Anopheles darlingi in Riberalta, Bolivian Amazon

Inexpensive insect repellents may be needed to supplement the use of impregnated bed-nets in the Amazon region, where the primary malaria vector, Anopheles darlingi (Root), is exophilic and feeds in the early evening. Three plants that are traditionally used to repel mosquitoes in Riberalta, Bolivian Amazon, were identified by focus group, and then they were tested against An. darlingi as well as Mansonia indubitans (Dyar & Shannon)/Mansonia titillans (Walker). Cymbopogon citratus (Staph), Guatemalan lemongrass, essential oil at 25% was used as a skin repellent, and it provided 74% protection for 2.5 h against predominantly An. darlingi and 95% protection for 2.5 h against Mansonia spp. Attalea princeps (name not verified) husks, burned on charcoal in the traditional way provided 35 and 51% protection against An. darlingi and Mansonia spp., respectively. Kerosene lamps, often used to light rural homes, were used as a heat source to volatilize 100% Mentha arvensis (Malinv ex. Bailey) essential oil, and they reduced biting by 41% inside traditional homes against Mansonia spp., although they were ineffective outdoors against An. darlingi. All three plant-based repellents provided significant protection compared with controls. Plant-based repellents, although less effective than synthetic alternatives, were shown by focus groups to be more culturally acceptable in this setting, in particular para-menthane-3, 8, idol derived from lemon eucalyptus, Corymbia citriodora (Hook). Plant-based repellents have the potential to be produced locally and therefore sold more cheaply than synthetic commercial repellents. Importantly, their low cost may encourage user compliance among indigenous and marginalized populations