Next-generation IEDB tools: a platform for epitope prediction and analysis.

The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface.

A comprehensive analysis of the IEDB MHC class-I automated benchmark.

In 2014, the Immune Epitope Database automated benchmark was created to compare the performance of the MHC class I binding predictors. However, this is not a straightforward process due to the different and non-standardized outputs of the methods. Additionally, some methods are more restrictive regarding the HLA alleles and epitope sizes for which they predict binding affinities, while others are more comprehensive. To address how these problems impacted the ranking of the predictors, we developed an approach to assess the reliability of different metrics. We found that using percentile-ranked results improved the stability of the ranks and allowed the predictors to be reliably ranked despite not being evaluated on the same data. We also found that given the rate new data are incorporated into the benchmark, a new method must wait for at least 4 years to be ranked against the pre-existing methods. The best-performing tools with statistically indistinguishable scores in this benchmark were NetMHCcons, NetMHCpan4.0, ANN3.4, NetMHCpan3.0 and NetMHCpan2.8. The results of this study will be used to improve the evaluation and display of benchmark performance. We highly encourage anyone working on MHC binding predictions to participate in this benchmark to get an unbiased evaluation of their predictors.

Engineering of single-domain antibodies for next-generation snakebite antivenoms.

Given the magnitude of the global snakebite crisis, strategies to ensure the quality of antivenom, as well as the availability and sustainability of its supply are under development by several research groups. Recombinant DNA technology has allowed the engineering of monoclonal antibodies and recombinant fragments as alternatives to conventional antivenoms. Besides having higher therapeutic efficacy, with broad neutralization capacity against local and systemic toxicity, novel antivenoms need to be safe and cost-effective. Due to the biological and physical chemical properties of camelid single-domain antibodies, with high volume of distribution to distal tissue, their modular format, and their versatility, their biotechnological application has grown considerably in recent decades. This article presents the most up-to-date developments concerning camelid single-domain-based antibodies against major toxins from snake venoms, the main venomous animals responsible for reported envenoming cases and related human deaths. A brief discussion on the composition, challenges, and perspectives of antivenoms is presented, as well as the road ahead for next-generation antivenoms based on single-domain antibodies.

Circumventing the side effects of L-asparaginase.

L-asparaginase is an enzyme that catalyzes the degradation of asparagine and successfully used in the treatment of acute lymphoblastic leukemia. L-asparaginase toxicity is either related to hypersensitivity to the foreign protein or to a secondary L-glutaminase activity that causes inhibition of protein synthesis. PEGylated versions have been incorporated into the treatment protocols to reduce immunogenicity and an alternative L-asparaginase derived from Dickeya chrysanthemi is used in patients with anaphylactic reactions to the E. coli L-asparaginase. Alternative approaches commonly explore new sources of the enzyme as well as the use of protein engineering techniques to create less immunogenic, more stable variants with lower L-glutaminase activity. This article reviews the main strategies used to overcome L-asparaginase shortcomings and introduces recent tools that can be used to create therapeutic enzymes with improved features.

Supersecondary Structures and Fragment Libraries.

The use of smotifs and fragment libraries has proven useful to both simplify and increase the quality of protein models. Here, we present Profrager, a tool that automatically generates putative structural fragments to reproduce local motifs of proteins given a target sequence. Profrager is highly customizable, allowing the user to select the number of fragments per library, the ranking method is able to generate fragments of all sizes, and it was recently modified to include the possibility of output exclusively smotifs.

Critical Features of Fragment Libraries for Protein Structure Prediction.

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Ocorrência de sirfídeos afidófagos (Diptera, Syrphidae) em Lavras, MG / Occurrence of aphidophagous syrphids (Diptera, Syrphidae) in Lavras, MG

A ocorrência de sirfídeos afidófagos nas culturas de citros, couve, pepino, trigo e batata foi registrada. As amostragens foram realizadas, quinzenalmente, de agosto a dezembro de 2002. Constatou-se as espécies:Ocyptamus gastrostactus (Wiedemann, 1830), Allograpta exotica (Wiedemann, 1830), Pseudodorus clavatus (Fabricius, 1794) e Ocyptamus anthiphates (Walker, 1849). P. clavatus ocorreu em todas as culturas amostradas, com a maior densidade populacional (72 por cento), seguido de O. gastrostactus (16 por cento), A. exotica (11 por cento) e O. anthiphates (1 por cento). A ocorrência dos sirfídeos esteve correlacionada com os fatores climáticos e a presenca dos afídeos.