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Cry11 proteins are toxic to Aedes aegypti, the vector of dengue, chikungunya, and Zika viruses. Cry11Aa and Cry11Bb are protoxins, which when activated present their active-toxin form in two fragments between 30 and 35 kDa respectively. Previous studies conducted with Cry11Aa and Cry11Bb genes using DNA shuffling generated variant 8, which presented a deletion in the first 73 amino acids and one at position 572 and 9 substitutions including L553F and L556W. In this study, variant 8 mutants were constructed using site-directed mutagenesis, resulting in conversion of phenylalanine (F) and tryptophan (W) to leucine (L) at positions 553 and 556, respectively, producing the mutants 8F553L, 8W556L, and 8F553L/8W556L. Additionally, two mutants, A92D and C157R, derived from Cry11Bb were also generated. The proteins were expressed in the non-crystal strain BMB171 of Bacillus thuringiensis and subjected to median-lethal concentration (LC50) tests on first-instar larvae of A. aegypti. LC50 analysis showed that the 8F553L, 8W556L, 8F553L/8W556L, and C157R variants lost their toxic activity (>500 ng·mL-1), whereas the A92D protein presented a loss of toxicity of 11.4 times that of Cry11Bb. Cytotoxicity assays performed using variant 8, 8W556L and the controls Cry11Aa, Cry11Bb, and Cry-negative BMB171 on the colorectal cancer cell line SW480 reported 30-50% of cellular viability except for BMB171. Molecular dynamic simulations performed to identify whether the mutations at positions 553 and 556 were related to the stability and rigidity of the functional tertiary structure (domain III) of the Cry11Aa protein and variant 8 showed the importance of these mutations in specific regions for the toxic activity of Cry11 against A. aegypti. This generates pertinent knowledge for the design of Cry11 proteins and their biotechnological applications in vector-borne disease control and cancer cell lines.

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The aggregation of epitopes that are also able to bind major histocompatibility complex (MHC) alleles raises questions around the potential connection between the formation of epitope aggregates and their affinities to MHC receptors. We first performed a general bioinformatic assessment over a public dataset of MHC class II epitopes, finding that higher experimental binding correlates with higher aggregation-propensity predictors. We then focused on the case of P10, an epitope used as a vaccine candidate against Paracoccidioides brasiliensis that aggregates into amyloid fibrils. We used a computational protocol to design variants of the P10 epitope to study the connection between the binding stabilities towards human MHC class II alleles and their aggregation propensities. The binding of the designed variants was tested experimentally, as well as their aggregation capacity. High-affinity MHC class II binders in vitro were more disposed to aggregate forming amyloid fibrils capable of binding Thioflavin T and congo red, while low affinity MHC class II binders remained soluble or formed rare amorphous aggregates. This study shows a possible connection between the aggregation propensity of an epitope and its affinity for the MHC class II cleft.

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INTRODUCTION: The use of technological resources to support processes in health systems has generated robust, interoperable and dynamic platforms. In the case of institutions working with neglected tropical diseases (NTD), there is a need for NTD-specific customizations. OBJECTIVES: To establish a medical records platform, specialized for NTD, which would facilitate the analysis of treatment evolution in patients, as well as generate more accurate data about various clinical aspects. MATERIALS AND METHODS: Here we developed a customized electronic medical record system based on OpenMRS for multiple NTDs. A set of forms and functionalities was developed under the OpenMRS guidelines, using shared community modules. RESULTS: All the customized information was packaged in a distribution called NTD Health. The platform is web-based and can be upgraded and improved by users without technological barriers. CONCLUSIONS: The EMR system can become a useful tool for other institutions to improve their health practices as well as the quality of life for NTD patients, simplifying the customization of healthcare systems able to interoperate with other platforms.

Introducción. El uso de recursos tecnológicos destinados a apoyar procesos en los sistemas de salud ha generado plataformas sólidas, interoperables y dinámicas. En el caso de las instituciones que trabajan con enfermedades tropicales desatendidas, existe la necesidad de personalizaciones específicas en las herramientas de uso médico. Objetivos. Establecer una plataforma para historias clínicas especializada en enfermedades tropicales desatendidas, con el fin de facilitar el análisis de la evolución del tratamiento de los pacientes, además de generar datos más precisos sobre diversos aspectos clínicos. Materiales y métodos. Se compiló un conjunto de requisitos para implementar formularios, conceptos y funcionalidades que permitan incluir enfermedades tropicales desatendidas. Se utilizó una distribución de OpenMRS (versión 2.3) como referencia para construir la plataforma, siguiendo las pautas recomendadas y módulos compartidos por la comunidad. Resultados. Toda la información personalizada se implementó en una plataforma llamada NTD Health, la cual se encuentra almacenada en la web y los usuarios pueden actualizarla y mejorarla sin barreras tecnológicas. Conclusiones. El sistema de historias clínicas electrónicas puede convertirse en una herramienta útil para que otras instituciones mejoren sus prácticas en salud, así como la calidad de vida de los pacientes con enfermedades tropicales desatendidas, simplificando la personalización de los sistemas de salud capaces de interoperar con otras plataformas.

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In Colombia, different dairy breeds were introduced from Europe and the United States, which underwent different crossing and selection processes that generated specific qualities or differences and which likely have their own genomic structure. To characterize genetic diversity, population structure, and admixture, we used genotypes from 23,182 autosomal single nucleotide polymorphisms (SNPs) of 130 animals representing four dairy cattle breed groups from Nariño. In addition, we merged genotypes from 43,043 autosomal SNPs, from 137 animals from the Decker database (Decker et al., 2014) (DRYAD doi:10.5061/dryad.th092). After the quality control process of pruning the merged dataset, we were left with 7,475 autosomal SNPs shared by both databases of Nariño (127 samples) and Decker (135 samples). Genetic diversity levels were moderate in all breeds (average observed heterozygosity = 0.40). Based on the fixation index values, we conclude that Brahman individuals were more differentiated than the taurine breeds (-0.374 to 0.076 for Brown Swiss). Pairs between taurine breeds showed low genetic differentiation (0.011-0.479). Principal component analysis revealed that in both the Nariño and Decker databases, the taurine formed the most compact cluster compared with other breeds known not to share the same ancestry, and Jersey, Brown Swiss, and Normand individuals exhibited high similarity with Holstein individuals. Hierarchical cluster analysis with Admixture revealed that Brahman, Jersey, Normand, and Holstein from the Decker databases most of which were clustered together with the dairy breeds of the Nariño highland tropics are not able to create different groups, thus having greater similarity with each other. This can be explained by the crosses made by farmers to increase milk production volume, always based on the Holstein breed with semen of bulls from America and Canada. Detrimental impacts due to intensive selection might cause some specific traits from the region to be fixed in the offspring, which can influence their adaptive capacity to the highland tropics.

Na Colômbia foram introduzidas diferentes raças leiteiras trazidas da Europa e dos Estados Unidos, que passaram por diferentes processos de cruzamento e seleção, gerando o desenvolvimento de características ou diferenças específicas nas raças bovinas e provavelmente, exibem sua própria estrutura genômica. Para caracterizar a diversidade genética e estrutura populacional foram utilizados genótipos de 23.182 polimorfismos de nucleotídeo único (SNPs) autossômicos de 130 animais, representando quatro grupos de raças de gado leiteiro de Nariño. Além disso, juntamos genótipos de 43.043 SNPs autossômicos, de 137 animais do banco de dados Decker (Decker et al., 2014) (DRYAD doi:10.5061/dryad.th092). Após o processo de controle de qualidade, o conjunto de dados misto ficou com 7.475 SNPs autossômicos compartilhados em ambos os bancos de dados de Nariño (127 amostras) e Decker (135 amostras). Os níveis de diversidade genética foram moderados em todas as raças (heterozigose média observada = 0,40). Com base nos valores do índice de fixação, concluímos que os indivíduos Brahman (zebuínos) foram mais diferenciados em comparação às raças taurinas (-0,374 a 0,076 para Pardo Suíço). Pares entre as raças taurinas apresentaram baixa diferenciação genética (0,011 ­ 0,479). O resultado dos componentes principais mostra que nos dois bancos de dados, Nariño e Decker, os taurinos formaram o cluster mais compacto em comparação com outras raças conhecidas por não compartilharem a mesma ancestralidade; indivíduos Jersey, Pardo Suíço e Normando denotaram alta similaridade com indivíduos Holandeses. A análise de agrupamento hierárquico com Admixture mostrou que Brahman, Jersey, Normando e Holandês da base de dados Decker, a maioria deles também agrupados com as raças leiteiras do alto trópico de Nariño, não são capazes de criar grupos diferentes, portanto, mostram maior semelhança entre eles. Isso pode ser explicado devido aos cruzamentos feitos pelos pecuaristas para aumentar o volume de produção de leite, sempre tendo como base a raça Holandesa com sêmen de touros da América e Canadá. Impactos prejudiciais, devido à seleção intensiva, podem fazer com que algumas características específicas da região sejam fixadas na prole e isso pode influenciar a sua capacidade adaptativa aos trópicos altos.

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Introduction: The use of technological resources to support processes in health systems has generated robust, interoperable, and dynamic platforms. In the case of institutions working with neglected tropical diseases, there is a need for specific customizations of these diseases. Objectives: To establish a medical record platform specialized in neglected tropical diseases which could facilitate the analysis of treatment evolution in patients, as well as generate more accurate data about various clinical aspects. Materials and methods: A set of requirements to develop state of the art forms, concepts, and functionalities to include neglected tropical diseases were compiled. An OpenMRS distribution (version 2.3) was used as reference to build the platform, following the recommended guidelines and shared-community modules. Results: All the customized information was developed in a platform called NTD Health, which is web-based and can be upgraded and improved by users without technological barriers. Conclusions: The electronic medical record system can become a useful tool for other institutions to improve their health practices as well as the quality of life for neglected tropical disease patients, simplifying the customization of healthcare systems able to interoperate with other platforms.

Introducción. El uso de recursos tecnológicos destinados a apoyar procesos en los sistemas de salud ha generado plataformas sólidas, interoperables y dinámicas. En el caso de las instituciones que trabajan con enfermedades tropicales desatendidas, existe la necesidad de personalizaciones específicas en las herramientas de uso médico. Objetivos. Establecer una plataforma para historias clínicas especializada en enfermedades tropicales desatendidas, con el fin de facilitar el análisis de la evolución del tratamiento de los pacientes, además de generar datos más precisos sobre diversos aspectos clínicos. Materiales y métodos. Se compiló un conjunto de requisitos para implementar formularios, conceptos y funcionalidades que permitan incluir enfermedades tropicales desatendidas. Se utilizó una distribución de OpenMRS (versión 2.3) como referencia para construir la plataforma, siguiendo las pautas recomendadas y módulos compartidos por la comunidad. Resultados. Toda la información personalizada se implementó en una plataforma llamada NTD Health, la cual se encuentra almacenada en la web y los usuarios pueden actualizarla y mejorarla sin barreras tecnológicas. Conclusiones. El sistema de historias clínicas electrónicas puede convertirse en una herramienta útil para que otras instituciones mejoren sus prácticas en salud, así como la calidad de vida de los pacientes con enfermedades tropicales desatendidas, simplificando la personalización de los sistemas de salud capaces de interoperar con otras plataformas.

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Peptides are commonly used as therapeutic agents. However, they suffer from easy degradation and instability. Replacing natural by non-natural amino acids can avoid these problems, and potentially improve the affinity towards the target protein. Here, we present a computational pipeline to optimize peptides based on adding non-natural amino acids while improving their binding affinity. The workflow is an iterative computational evolution algorithm, inspired by the PARCE protocol, that performs single-point mutations on the peptide sequence using modules from the Rosetta framework. The modifications can be guided based on the structural properties or previous knowledge of the biological system. At each mutation step, the affinity to the protein is estimated by sampling the complex conformations and applying a consensus metric using various open protein-ligand scoring functions. The mutations are accepted based on the score differences, allowing for an iterative optimization of the initial peptide. The sampling/scoring scheme was benchmarked with a set of protein-peptide complexes where experimental affinity values have been reported. In addition, a basic application using a known protein-peptide complex is also provided. The structure- and dynamic-based approach allows users to optimize bound peptides, with the option to personalize the code for further applications. The protocol, called mPARCE, is available at: https://github.com/rochoa85/mPARCE/ .

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The lack of therapeutic alternatives for the treatment of Chagas disease, a neglected disease, drives the discovery of new drugs with trypanocidal activity. Consequently, we conducted in vitro studies using UBMC-4, a potential Trypanosoma cruzi AKT-like pleckstrin homology (PH) domain inhibitory compound found using bioinformatics tools. The half effective concentration (EC50) on intracellular amastigotes was determined at 1.85 ± 1 µM showing low cytotoxicity (LC50) > 40 µM on human cell lines tested. In order to study the lethal effect caused by the compound on epimastigotes, morphological changes were assessed by scanning and transmission electron microscopy. Progressive alterations such as flagellum inactivation, cell size reduction, nuclear structure alteration, condensation of chromatin towards the nuclear periphery, vacuole formation, and mitochondrial swelling with kinetoplast integrity loss were evidenced. In addition, apoptosis-like markers in T. cruzi were assessed by flow cytometry, demonstrating that the effect of UBMC-4 on T. cruzi AKT-like kinase reduced the tolerance to nutritional stress-triggered, apoptosis-like events, including DNA fragmentation, mitochondrial damage, and loss of plasma membrane integrity. After this, UBMC-4 was formulated for oral administration and pharmacokinetics were analyzed in a mouse model. Finally, upon oral administration of 200 mg/kg in mice, we found that a UBMC-4 plasma concentration remaining in circulation beyond 24 h after administration is well described by the two-compartment model. We conclude that UBMC-4 has an effective trypanocidal activity in vitro at low concentrations and this effect is evident in T. cruzi cell structures. In mice, UBMC-4 was well absorbed and reached plasma concentrations higher than the EC50, showing features that would aid in developing a new drug to treat Chagas disease.

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Epitopes that bind simultaneously to all human alleles of Major Histocompatibility Complex class II (MHC II) are considered one of the key factors for the development of improved vaccines and cancer immunotherapies. To engineer MHC II multiple-allele binders, we developed a protocol called PanMHC-PARCE, based on the unsupervised optimization of the epitope sequence by single-point mutations, parallel explicit-solvent molecular dynamics simulations and scoring of the MHC II-epitope complexes. The key idea is accepting mutations that not only improve the affinity but also reduce the affinity gap between the alleles. We applied this methodology to enhance a Plasmodium vivax epitope for multiple-allele binding. In vitro rate-binding assays showed that four engineered peptides were able to bind with improved affinity toward multiple human MHC II alleles. Moreover, we demonstrated that mice immunized with the peptides exhibited interferon-gamma cellular immune response. Overall, the method enables the engineering of peptides with improved binding properties that can be used for the generation of new immunotherapies.

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Computational peptide design is useful for therapeutics, diagnostics, and vaccine development. To select the most promising peptide candidates, the key is describing accurately the peptide-target interactions at the molecular level. We here review a computational peptide design protocol whose key feature is the use of all-atom explicit solvent molecular dynamics for describing the different peptide-target complexes explored during the optimization. We describe the milestones behind the development of this protocol, which is now implemented in an open-source code called PARCE. We provide a basic tutorial to run the code for an antibody fragment design example. Finally, we describe three additional applications of the method to design peptides for different targets, illustrating the broad scope of the proposed approach.

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The intracellular parasite Leishmania braziliensis is the causal agent of cutaneous and mucocutaneous leishmaniasis, a group of endemic diseases in tropical regions, including Latin America. New therapeutic targets are required to inhibit the pathogen without affecting the host. The enzyme nicotinamide/nicotinate mononucleotide adenylyltransferase (NMNAT; EC: 2.7.7.1/18) is a potential target, since it catalyzes the final step in the biosynthesis of nicotinamide adenine dinucleotide (NAD+), which is an essential metabolite in multiple cellular processes. In this work, we produced and evaluated the catalytic activity of the recombinant protein 6HisΔ241-249LbNMNAT to study the functional relevance of the exclusive insertion present in the enzyme of L. braziliensis (LbNMNAT), but absent in the primary structure of human NMNATs. Our results indicate that the 241-249 insertion constitutes a structural element that connects the protein structure Rossmann topology with the carboxyl-terminal domain of the enzyme. The removal of this region drastically decreases the solubility, and enzymatic activity of the recombinant, causing its inactivation. Molecular dynamics simulations were carried out with the wild-type and truncated enzymes to verify additional changes in their stability, which indicated a better stability in the wild-type protein. These findings constitute an initial step to identify a new inhibition mechanism for the development of focused pharmacological strategies on exclusive insertions from the LbNMNAT protein.

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Leishmaniasis is a neglected tropical disease considered a public health problem that requires innovative strategies for its chemotherapeutic control. In the present investigation, a molecular docking approach was carried out using the protein cysteine synthase (CS) of Leishmania braziliensis (CSLb) and Leishmania major (CSLm) parasites to identify new compounds as potential candidates for the development of selective leishmaniasis therapy. CS protein sequence similarity, active site, structural modeling, molecular docking, and ADMET properties of compounds were analyzed using bioinformatics tools. Molecular docking analyses identified 1000 ligands with highly promising binding affinity scores for both CS proteins. A total of 182 compounds for CSLb and 173 for CSLm were selected for more detailed characterization based on the binding energy and frequency values and ADMET properties. Based on Principal Component Analysis (PCA) and K-means clusterization for both CS proteins, we classified compounds into 5 clusters for CSLb and 7 for CSLm, thus providing an excellent starting point for verification of enzyme inhibition in in vitro studies. We found the ZINC16524774 compound predicted to have a high affinity and stability for both CSLb and CSLm proteins, which was also evaluated through molecular dynamics simulations. Compounds within each of the five clusters also displayed pharmacological and structural properties that make them attractive drug candidates for the development of selective cutaneous leishmaniasis chemotherapy.

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Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases' participation in protein-protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

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The prediction of peptide binders to Major Histocompatibility Complex (MHC) class II receptors is of great interest to study autoimmune diseases and for vaccine development. Most approaches predict the affinities using sequence-based models trained on experimental data and multiple alignments from known peptide substrates. However, detecting activity differences caused by single-point mutations is a challenging task. In this work, we used interactions calculated from simulations to build scoring matrices for quickly estimating binding differences by single-point mutations. We modelled a set of 837 peptides bound to an MHC class II allele, and optimized the sampling of the conformations using the Rosetta backrub method by comparing the results to molecular dynamics simulations. From the dynamic trajectories of each complex, we averaged and compared structural observables for each amino acid at each position of the 9°mer peptide core region. With this information, we generated the scoring-matrices to predict the sign of the binding differences. We then compared the performance of the best scoring-matrix to different computational methodologies that range in computational costs. Overall, the prediction of the activity differences caused by single mutated peptides was lower than 60% for all the methods. However, the developed scoring-matrix in combination with existing methods reports an increase in the performance, up to 86% with a scoring method that uses molecular dynamics.

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Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.

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BACKGROUND: Proteases are key drivers in many biological processes, in part due to their specificity towards their substrates. However, depending on the family and molecular function, they can also display substrate promiscuity which can also be essential. Databases compiling specificity matrices derived from experimental assays have provided valuable insights into protease substrate recognition. Despite this, there are still gaps in our knowledge of the structural determinants. Here, we compile a set of protease crystal structures with bound peptide-like ligands to create a protocol for modelling substrates bound to protease structures, and for studying observables associated to the binding recognition. RESULTS: As an application, we modelled a subset of protease-peptide complexes for which experimental cleavage data are available to compare with informational entropies obtained from protease-specificity matrices. The modelled complexes were subjected to conformational sampling using the Backrub method in Rosetta, and multiple observables from the simulations were calculated and compared per peptide position. We found that some of the calculated structural observables, such as the relative accessible surface area and the interaction energy, can help characterize a protease's substrate recognition, giving insights for the potential prediction of novel substrates by combining additional approaches. CONCLUSION: Overall, our approach provides a repository of protease structures with annotated data, and an open source computational protocol to reproduce the modelling and dynamic analysis of the protease-peptide complexes.

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BACKGROUND: In a previous work we showed the feasibility of an interferon gamma release assay (IGRA) for detecting latent infection by Histoplasma capsulatum. While in that proof-of-concept study we used crude fungal extracts as antigens, the newest IGRAs developed for other infections are based on molecularly defined antigens, mostly on mixtures of immunogenic peptides. AIMS: To identify proteins in H. capsulatum that might serve as molecularly defined antigens for an IGRA test. METHODS: We surveyed the literature looking for known H. capsulatum-immunogenic proteins and assayed two of them as antigens in an IGRA test, in a study that involved 80 volunteers. Furthermore, we used several bioinformatics tools to identify specific H. capsulatum proteins and to analyze possible strategies for the design of H. capsulatum-specific immunogenic peptides. RESULTS: Seven H. capsulatum-immunogenic proteins were retrieved from the literature. IGRA tests using either the heat shock protein 60 or the M antigen showed high sensitivities but low specificities, most likely due to the high sequence similarity with the corresponding orthologs in other pathogenic microorganisms. We identified around 2000 H. capsulatum-specific proteins, most of which remain unannotated. Class II T-cell epitope predictions for a small number of these proteins showed a great variability among different alleles, prompting for a "brute force" approach for peptide design. CONCLUSIONS: The H. capsulatum genome encodes a large number of distinctive proteins, which represent a valuable source of potential specific antigens for an IGRA test. Among them, the Cfp4 protein stands out as a very attractive candidate.

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Leishmaniasis is a neglected tropical disease caused by Leishmania parasites and is associated to more than 1.3 million cases annually. Some of the pharmacological options for treating the disease are pentavalent antimonials, pentamidine, miltefosine, and amphotericin B. However, all are associated with a wide range of adverse effects and contraindications, as well as resistance from the parasite. In the present study, we looked for pharmacological alternatives to treat leishmaniasis, with a focus on drug repurposing. This was done by detecting potential homologs between proteins targeted by approved drugs and proteins of the parasite. The proteins were analyzed using an interaction network, and the drugs were subjected to in vitro evaluations and pharmacokinetics simulations to compare probable plasma concentrations with the effective concentrations detected experimentally. This strategy yielded a list of 33 drugs with potential anti-Leishmania activity, and more than 80 possible protein targets in the parasite. From the drugs tested, two reported high in vitro activity (perphenazine EC50 = 1.2 µg/mL and rifabutin EC50 = 8.5 µg/mL). These results allowed us to propose these drugs as candidates for further in vivo studies and evaluations of the effectiveness on their topical forms.

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Predicting the binding affinity of peptides able to interact with major histocompatibility complex (MHC) molecules is a priority for researchers working in the identification of novel vaccines candidates. Most available approaches are based on the analysis of the sequence of peptides of known experimental affinity. However, for MHC class II receptors, these approaches are not very accurate, due to the intrinsic flexibility of the complex. To overcome these limitations, we propose to estimate the binding affinity of peptides bound to an MHC class II by averaging the score of the configurations from finite-temperature molecular dynamics simulations. The score is estimated for 18 different scoring functions, and we explored the optimal manner for combining them. To test the predictions, we considered eight peptides of known binding affinity. We found that six scoring functions correlate with the experimental ranking of the peptides significantly better than the others. We then assessed a set of techniques for combining the scoring functions by linear regression and logistic regression. We obtained a maximum accuracy of 82% for the predicted sign of the binding affinity using a logistic regression with optimized weights. These results are potentially useful to improve the reliability of in silico protocols to design high-affinity binding peptides for MHC class II receptors.

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Discovery of novel or repurposed chemical treatments for leishmaniasis is a priority given the limited number of therapeutic alternatives available. One way to accelerate the finding is by implementing virtual screening methodologies using structural information, with subsequent experimental validations. Here we tested a library of 48 phenylfuranchalcones as anti-Leishmania agents that can be associated to the potential inhibition of a protein target within the parasite. For that purpose, a list of 43 protein structures from different Leishmania species was prepared to dock the virtual compound library. The protein with the best predicted scores was used as reference to select a subset of previously synthesized compounds for in vitro validation of their cytotoxicity and anti-Leishmania activity. We found a set of active compounds (EC50 < 25 µM) that were compared with the computational results using Spearman correlations. The analysis allowed us to propose the inhibition of a phosphodiesterase enzyme as the potential mechanism of action.

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Quinones are secondary metabolites of higher plants associated with many biological activities, including antiviral effects and cytotoxicity. In this study, the anti-herpetic and anti-dengue evaluation of 27 terpenyl-1,4-naphthoquinone (NQ), 1,4-anthraquinone (AQ) and heterocycle-fused quinone (HetQ) derivatives was done in vitro against Human Herpesvirus (HHV) type 1 and 2, and Dengue virus serotype 2 (DENV-2). The cytotoxicity on HeLa and Jurkat tumor cell lines was also tested. Using plaque forming unit assays, cell viability assays and molecular docking, we found that NQ 4 was the best antiviral compound, while AQ 11 was the most active and selective molecule on the tested tumor cells. NQ 4 showed a fair antiviral activity against Herpesviruses (EC50: <0.4 µg/mL, <1.28 µM) and DENV-2 (1.6 µg/mL, 5.1 µM) on pre-infective stages. Additionally, NQ 4 disrupted the viral attachment of HHV-1 to Vero cells (EC50: 0.12 µg/mL, 0.38 µM) with a very high selectivity index (SI = 1728). The in silico analysis predicted that this quinone could bind to the prefusion form of the E glycoprotein of DENV-2. These findings demonstrate that NQ 4 is a potent and highly selective antiviral compound, while suggesting its ability to prevent Herpes and Dengue infections. Additionally, AQ 11 can be considered of interest as a leader for the design of new anticancer agents.

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