Functional training improves peak oxygen consumption and quality of life of individuals with heart failure: a randomized clinical trial.

BACKGROUND: Functional training may be an effective non-pharmacological therapy for heart failure (HF). This study aimed to compare the effects of functional training with strength training on peak VO2 and quality of life in individuals with HF. METHODS: A randomized, parallel-design and examiner-blinded controlled clinical trial with concealed allocation, intention-to-treat and per-protocol analyses. Twenty-seven participants with chronic HF were randomly allocated to functional or strength training group, to perform a 12-week physical training, three times per week, totalizing 36 sessions. Primary outcomes were the difference on peak VO2 and quality of life assessed by cardiopulmonary exercise testing and Minnesota Living with Heart Failure Questionnaire, respectively. Secondary outcomes included functionality assessed by the Duke Activity Status Index and gait speed test, peripheral and inspiratory muscular strength, assessed by hand grip and manovacuometry testing, respectively, endothelial function by brachial artery flow-mediated dilation, and lean body mass by arm muscle circumference. RESULTS: Participants were aged 60 ± 7 years, with left ventricular ejection fraction 29 ± 8.5%. The functional and strength training groups showed the following results, respectively: peak VO2 increased by 1.4 ± 3.2 (16.9 ± 2.9 to 18.6 ± 4.8 mL.kg-1.min-1; p time = 0.011) and 1.5 ± 2.5 mL.kg-1.min-1 (16.8 ± 4.0 to 18.6 ± 5.5 mL.kg-1.min-1; p time = 0.011), and quality of life score decreased by 14 ± 15 (25.8 ± 14.8 to 10.3 ± 7.8 points; p time = 0.001) and 12 ± 28 points (33.8 ± 23.8 to 19.0 ± 15.1 points; p time = 0.001), but no difference was observed between groups (peak VO2: p interaction = 0.921 and quality of life: p interaction = 0.921). The functional and strength training increased the activity status index by 6.5 ± 12 and 5.2 ± 13 points (p time = 0.001), respectively, and gait speed by 0.2 ± 0.3 m/s (p time = 0.002) in both groups. CONCLUSIONS: Functional and strength training are equally effective in improving peak VO2, quality of life, and functionality in individuals with HF. These findings suggest that functional training may be a promising and innovative exercise-based strategy to treat HF. TRIAL REGISTRATION: NCT03321682. Registered date: 26/10/2017.

KORP-PL: a coarse-grained knowledge-based scoring function for protein-ligand interactions.

MOTIVATION: Despite the progress made in studying protein-ligand interactions and the widespread application of docking and affinity prediction tools, improving their precision and efficiency still remains a challenge. Computational approaches based on the scoring of docking conformations with statistical potentials constitute a popular alternative to more accurate but costly physics-based thermodynamic sampling methods. In this context, a minimalist and fast sidechain-free knowledge-based potential with a high docking and screening power can be very useful when screening a big number of putative docking conformations. RESULTS: Here, we present a novel coarse-grained potential defined by a 3D joint probability distribution function that only depends on the pairwise orientation and position between protein backbone and ligand atoms. Despite its extreme simplicity, our approach yields very competitive results with the state-of-the-art scoring functions, especially in docking and screening tasks. For example, we observed a twofold improvement in the median 5% enrichment factor on the DUD-E benchmark compared to Autodock Vina results. Moreover, our results prove that a coarse sidechain-free potential is sufficient for a very successful docking pose prediction. AVAILABILITYAND IMPLEMENTATION: The standalone version of KORP-PL with the corresponding tests and benchmarks are available at https://team.inria.fr/nano-d/korp-pl/ and https://chaconlab.org/modeling/korp-pl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Relation between ABCB1 overexpression and COX2 and ALOX5 genes in human erythroleukemia cell lines.

This study aimed to characterize the relationship between the COX2 and ALOX5 genes, as well as their link with the multidrug resistance (MDR) phenotype in sensitive (K562) and MDR (K562-Lucena and FEPS) erythroleukemia cells. For this, the inhibitors of 5-LOX (zileuton) and COX-2 (acetylsalicylic acid-ASA) and cells with the silenced ABCB1 gene were used. The treatment with ASA caused an increase in the gene expression of COX2 and ABCB1 in both MDR cell lines, and a decrease in the expression of ALOX5 in the FEPS cells. Silencing the ABCB1 gene induced a decrease in COX2 expression and an increase in the ALOX5 gene. Treatment with zileuton did not alter the expression of COX2 and ABCB1. Cytometry data showed that there was an increase in ABCB1 protein expression after exposure to ASA. In addition, the increased activity of ABCB1 in the K562-Lucena cell line indicates that ASA may be a substrate for this efflux pump, corroborating the molecular docking that showed that ASA can bind to ABCB1. Regardless of the genetic alteration in COX2 and ABCB1, the direct relationship between these genes and the inverse relationship with ALOX5 remained in the MDR cell lines. We assume that ABCB1 can play a regulatory role in COX2 and ALOX5 during the transformation of the parental cell line K562, explaining the increased gene expression of COX2 and decreased ALOX5 in the MDR cell lines.

Mefloquine synergism with anti-tuberculosis drugs and correlation to membrane effects: Biologic, spectroscopic and molecular dynamics simulations studies.

Studies displaying the combination of mefloquine (MFL) with anti-tuberculosis (TB) substances are limited in the literature. In this work, the effect of MFL-association with two first-line anti-TB drugs and six fluoroquinolones was evaluated against Mycobacterium tuberculosis drug resistant strains. MFL showed synergistic interaction with isoniazid, pyrazinamide, and several fluoroquinolones, reaching fractional inhibitory concentration indexes (FICIs) ranging from 0.03 to 0.5. In order to better understand the observed results, two approaches have been explored: (i) spectroscopic responses attributed to the effect of MFL on physicochemical properties related to a liposomal membrane model composed by soybean asolectin; (ii) molecular dynamics (MD) simulation data regarding MFL interaction with a membrane model based on PIM2, a lipid constituent of the mycobacterial cell wall. FTIR and NMR data showed that MFL affects expressively the region between the phosphate and the first methylene groups of soybean asolectin membranes, disordering these regions. MD simulations results detected high MFL density in the glycolipid interface and showed that the drug increases the membrane lateral diffusion, enhancing its permeability. The obtained results suggest that synergistic activities related to MFL are attributed to its effect of lipid disorder and membrane permeability enhancement.

In Vitro Effects of 2-{4-[Methylthio(methylsulfonyl)]phenyl}-3-substitutedthiazolidin-4-ones on the Acetylcholinesterase Activity in Rat Brain and Lymphocytes: Isoform Selectivity, Kinetic Analysis, and Molecular Docking.

This work evaluated the in vitro effect of thiazolidin-4-ones on the activity of AChE (total and isoforms) isolated from the cerebral cortex, hippocampus, and lymphocytes. Kinetic parameters were evaluated and molecular docking was performed. Our results showed that thiazolidinones derived from 4-(methylthio)benzaldehyde (1) and from 4-(methylsulfonyl)benzaldehyde (2) were capable of inhibiting the AChE activity in vitro. Three compounds, two with a propylpiperidine (1b and 2b) moiety and one with a 3-(diethylamino)propyl (1c) moiety showed IC50 values of 13.81 µM, and 3.13 µM (1b), 55.36 µM and 44.33 µM (1c) for cerebral cortex and hippocampus, respectively, and 3.11 µM for both (2b). Enzyme kinetics revealed that the type of AChE inhibition was mixed. Compound 1b inhibited the G1 and G4 AChE isoforms, while compounds 1c and 2b selectively inhibited the G4 isoform. Molecular docking showed a possible three-dimensional fit into the enzyme. Our findings showed that these thiazolidin-4-ones, especially those containing the propylpiperidine core, have a potential cholinesterase inhibitory activity and can be considered good candidates for future Alzheimer's therapy.

Cardiopulmonary exercise capacity and quality of life of patients with heart failure undergoing a functional training program: study protocol for a randomized clinical trial.

BACKGROUND: Exercise intolerance is a common finding in heart failure that generates a vicious cycle in which the individual starts to limit his activities even more due to progressive fatigue. Regular physical exercise can increase the cardiopulmonary exercise capacity of these individuals. A new approach to physical exercise, known as functional training, could improve the oxygen consumption and quality of life of patients with heart failure; however, there is no information about the effect of this modality of exercise in this patient population. This randomized trial will compare the effects of 36 sessions of functional training versus strength training in heart failure patients. METHODS: This randomized parallel-design examiner-blinded clinical trial includes individuals of both sexes aged ≥40 years receiving regular follow-up at a single academic hospital. Subjects will be randomly allocated to an intervention group (for 12-week functional training) or an active comparator group (for 12-week strength training). The primary outcomes will be the difference from baseline to the 3-month time point in peak oxygen consumption on cardiopulmonary exercise testing and quality of life assessed by the Minnesota Living with Heart Failure Questionnaire. Secondary outcome measures will include functionality assessed by the Duke Activity Status Index and gait speed test; peripheral and inspiratory muscular strength, assessed by hand grip and manovacuometry testing, respectively; endothelial function by brachial artery flow-mediated dilation; lean body mass by arm muscle circumference; and participant adherence to the exercise programs classified as a percentage of the prescribed exercise dose. DISCUSSION: The functional training program aims to improve the functional capacity of the individual using exercises that relate to his specific physical activity transferring gains effectively to one's daily life. In this context, we believe that that functional training can increase the cardiopulmonary exercise capacity and quality of life of patients with heart failure. The trial has been recruiting patients since October 2017. TRIAL REGISTRATION: NCT03321682. Registered on October 26, 2017.

Use of Text Messaging (SMS) for the Management of Side Effects in Cancer Patients Undergoing Chemotherapy Treatment: a Randomized Controlled Trial.

Cancer patients are often not sufficiently oriented to manage side effects at home. Sending text messages with self-care guidelines aimed managing side effects is the main objective of this randomized controlled trial. Patients who started outpatient chemotherapy treatment between March and December 2017 at a hospital in southern Brazil were invited to participate in this study and were allocated to the intervention or control group (ratio 1: 1). Each patient in the intervention group received a daily SMS (short message service) with some guidance on management or prevention of side effects. All text messages were sent to the intervention group patients in an automated and tailored way by our app called cHEmotHErApp. Side effects experienced by patients were verified using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core-30 (EORTC QLQ-C30). Results showed intervention group patients experienced fewer side effects compared to the control group in cycle 1 (p < 0.05), in general. In addition, intervention group experienced less nausea in relation to the control group, in the cycle 1 and cycle 2 (p < 0.05). This study indicate text messaging may be a tool for supporting side effect management in patients receiving chemotherapy. This study was enrolled in ClinicalTrials.gov with the identification number NCT03087422. This research was performed in accordance with the Declaration of Helsinki.

Computational MitoTarget Scanning Based on Topological Vacancies of Single-Walled Carbon Nanotubes with the Human Mitochondrial Voltage-Dependent Anion Channel (hVDAC1).

We present an in silico approach for modeling the noncovalent interactions between the human mitochondrial voltage-dependent anion channel (hVDAC1) and a family of single-walled carbon nanotubes (SWCNTs) with a defined pattern of topological vacancies ( v = 1-16), obtained by removing atoms from the SWCNT surface. The general results showed more stable docking interaction complexes (SWCNT-hVDAC1), with more negative Gibbs free energy of binding affinity values, and a strong dependence on the vacancy number ( R2 = 0.93) and vacancy formation energy ( R2 = 0.96). In addition, for most of the SWCNT vacancies that were analyzed, the interatomic distances for the interactions of the SWCNT-hVDAC1 complex with the functional catalytic residues (i.e., Pro7, Gln199, Gln182, Phe181, Val20, Asp19, Lys15, Gly14, Asp12, Ala11, and Arg18) that form the hVDAC1 active site (i.e., the voltage-sensing N-terminal α-helix segment) were very similar to or shorter than the interatomic distances of these residues for ATP-hVDAC1 interactions. In particular, the hVDAC1 residues that can be phosphorylated like Tyr10, Tyr198, and Se16 were significantly perturbed by the interactions with SWCNT with at least nine vacancies. In addition, the SWCNT vacancy family members can affect the flexibility properties of the hVDAC1 N-terminal α-helix segment inducing different patterns of local perturbations in inter-residue communication. Finally, vacancy quantitative structure-binding relationships (V-QSBRs) were unveiled for setting up a robust model that can predict the strength of docking interactions between SWCNTs with a specific topological vacancy and hVDAC1. The developed V-QSBR model classified properly all of the SWCNTs with a different number of SWCNT vacancies with exceptional sensitivity and specificity (both equal to 100%), indicating a strong potential to unequivocally predict the influence of SWCNT vacancies on the mitochondrial channel interactions.

Silencing the OCT4-PG1 pseudogene reduces OCT-4 protein levels and changes characteristics of the multidrug resistance phenotype in chronic myeloid leukemia.

Cancer stem cells show epigenetic plasticity and intrinsic resistance to anti-cancer therapy, rendering capable of initiating cancer relapse and progression. Transcription factor OCT-4 regulates various pathways in stem cells, but its expression can be regulated by pseudogenes. This work evaluated how OCT4-PG1 pseudogene can affect OCT-4 expression and mechanisms related to the multidrug resistance (MDR) phenotype in FEPS cells. Considering that OCT-4 protein is a transcription factor that regulates expression of ABC transporters, level of gene expression, activity of ABC proteins and cell sensitivity to chemotherapy were evaluated after OCT4-PG1 silencing. Besides we set up a STRING network. Results showed that after OCT4-PG1 silencing, cells expressed OCT-4 gene and protein to a lesser extent than mock cells. The gene and protein expression of ABCB1, as well as its activity were reduced. On the other hand, ALOX5 and ABCC1 genes was increased even as the activity of this transporter. Moreover, the silencing cells become sensitive to two chemotherapics tested. The network structure demonstrated that OCT4-PG1 protein interacts directly with OCT-4, SOX2, and NANOG and indirectly with ABC transporters. We conclude that OCT4-PG1 pseudogene plays a key role in the regulation OCT-4 transcription factor, which alters MDR phenotype in the FEPS cell line.

A Computational Method to Propose Mutations in Enzymes Based on Structural Signature Variation (SSV).

With the use of genetic engineering, modified and sometimes more efficient enzymes can be created for different purposes, including industrial applications. However, building modified enzymes depends on several in vitro experiments, which may result in the process being expensive and time-consuming. Therefore, computational approaches could reduce costs and accelerate the discovery of new technological products. In this study, we present a method, called structural signature variation (SSV), to propose mutations for improving enzymes' activity. SSV uses the structural signature variation between target enzymes and template enzymes (obtained from the literature) to determine if randomly suggested mutations may provide some benefit for an enzyme, such as improvement of catalytic activity, half-life, and thermostability, or resistance to inhibition. To evaluate SSV, we carried out a case study that suggested mutations in ß-glucosidases: Essential enzymes used in biofuel production that suffer inhibition by their product. We collected 27 mutations described in the literature, and manually classified them as beneficial or not. SSV was able to classify the mutations with values of 0.89 and 0.92 for precision and specificity, respectively. Then, we used SSV to propose mutations for Bgl1B, a low-performance ß-glucosidase. We detected 15 mutations that could be beneficial. Three of these mutations (H228C, H228T, and H228V) have been related in the literature to the mechanism of glucose tolerance and stimulation in GH1 ß-glucosidase. Hence, SSV was capable of detecting promising mutations, already validated by in vitro experiments, that improved the inhibition resistance of a ß-glucosidase and, consequently, its catalytic activity. SSV might be useful for the engineering of enzymes used in biofuel production or other industrial applications.

Text Messaging (SMS) Helping Cancer Care in Patients Undergoing Chemotherapy Treatment: a Pilot Study.

Cancer treatment is an extremely stressful life experience that is accompanied by a range of psychological, social, physical, and practical difficulties. Cancer patients need to receive information that helps them to better understand the disease, assists them in decision-making, and helps them deal with treatment. Patients are interested in receiving such information. The degree of satisfaction with the information received has been associated with positive health outcomes, specifically regarding quality of life, severity of side effects, and psychological well-being. This study investigates a method of guiding cancer patients, in relation to outpatient chemotherapy treatment, using SMS (short message service) text messaging. A smartphone application called cHEmotHErApp was developed, and its primary function is to send out SMS text messages with guidance for self-care and emotional support for oncology patients undergoing chemotherapy. Thus, the main objective of this study is to evaluate the acceptance and perception of patients of the receipt of these SMS messages, as well as to evaluate the possible benefits reported by the participants. Adult patients diagnosed with cancer, who started the first outpatient chemotherapy treatment scheme between August and November 2016 at the School Hospital (HE) of the Federal University of Pelotas (UFPel), were invited to participate in this pilot study. In total, 14 cancer patients were adherent to this study. Each of these patients received a daily text message on their cell phone with some guidance on encouraging self-care and emotional support. Patients reported that, because of the SMS text messages they received, they felt more confident in their treatment, felt more supported and encouraged, and that the text messages facilitated self-care. In addition, patients reported that the SMS text messages they received helped them to take better care of themselves and to continue further treatment.

Inference of regulatory networks with a convergence improved MCMC sampler.

BACKGROUND: One of the goals of the Systems Biology community is to have a detailed map of all biological interactions in an organism. One small yet important step in this direction is the creation of biological networks from post-genomic data. Bayesian networks are a very promising model for the inference of regulatory networks in Systems Biology. Usually, Bayesian networks are sampled with a Markov Chain Monte Carlo (MCMC) sampler in the structure space. Unfortunately, conventional MCMC sampling schemes are often slow in mixing and convergence. To improve MCMC convergence, an alternative method is proposed and tested with different sets of data. Moreover, the proposed method is compared with the traditional MCMC sampling scheme. RESULTS: In the proposed method, a simpler and faster method for the inference of regulatory networks, Graphical Gaussian Models (GGMs), is integrated into the Bayesian network inference, trough a Hierarchical Bayesian model. In this manner, information about the structure obtained from the data with GGMs is taken into account in the MCMC scheme, thus improving mixing and convergence. The proposed method is tested with three types of data, two from simulated models and one from real data. The results are compared with the results of the traditional MCMC sampling scheme in terms of network recovery accuracy and convergence. The results show that when compared with a traditional MCMC scheme, the proposed method presents improved convergence leading to better network reconstruction with less MCMC iterations. CONCLUSIONS: The proposed method is a viable alternative to improve mixing and convergence of traditional MCMC schemes. It allows the use of Bayesian networks with an MCMC sampler with less iterations. The proposed method has always converged earlier than the traditional MCMC scheme. We observe an improvement in accuracy of the recovered networks for the Gaussian simulated data, but this improvement is absent for both real data and data simulated from ODE.

Benzohydroxamate and nitrobenzohydroxamate affect membrane order: Correlations between spectroscopic and molecular dynamics to approach tuberculosis.

This work correlates the effects of benzohydroxamate (BH) and nitrobenzohydroxamate (NBH) anions in two membrane models which may be used for anti-tuberculosis (anti-TB) spectroscopic studies and/or computational studies. Firstly, the BH and NBH influence in the physico-chemical properties of soy asolectin (ASO)-based large multilamellar vesicles (MLVs) were evaluated by spectroscopic and calorimetric studies. In parallel, the BH and NBH interaction with a Mycobacterium tuberculosis (Mtb) inner membrane model, composed of phosphatidyl-myo-inositol-dimannoside (PIM2), was investigated by molecular dynamics (MD) simulations. Spectroscopic data showed a localization of BH close to the lipid phosphate group, while NBH was found close to the choline region. The BH ordered the ASO choline, phosphate and carbonyl regions and disrupted the acyl methylenes, reducing the membrane packing of the lipid hydrophobic region. On the other hand, NBH showed an ordering effect in all the lipid groups (polar, interface and hydrophobic ones). By MD studies, it was found that NBH enhanced the stability of the PIM2 membrane more than BH, while also being positioned closer to its mannosyl oxygens. As in ASO MLVs, BH was localized close to the PIM2 phosphate group and disrupted its acyl chains. However, higher values of lateral diffusion were observed for NBH than BH. Despite this, BH and NBH increased the membrane thickness by 35 %, which suggests a global ordering effect of both drugs. Findings of this work reinforce the accordance and complementarity between MLVs based on ASO and the PIM2 MD model results to study the drug effects in Mtb membrane properties.

Context-based preprocessing of molecular docking data.

BACKGROUND: Data preprocessing is a major step in data mining. In data preprocessing, several known techniques can be applied, or new ones developed, to improve data quality such that the mining results become more accurate and intelligible. Bioinformatics is one area with a high demand for generation of comprehensive models from large datasets. In this article, we propose a context-based data preprocessing approach to mine data from molecular docking simulation results. The test cases used a fully-flexible receptor (FFR) model of Mycobacterium tuberculosis InhA enzyme (FFR_InhA) and four different ligands. RESULTS: We generated an initial set of attributes as well as their respective instances. To improve this initial set, we applied two selection strategies. The first was based on our context-based approach while the second used the CFS (Correlation-based Feature Selection) machine learning algorithm. Additionally, we produced an extra dataset containing features selected by combining our context strategy and the CFS algorithm. To demonstrate the effectiveness of the proposed method, we evaluated its performance based on various predictive (RMSE, MAE, Correlation, and Nodes) and context (Precision, Recall and FScore) measures. CONCLUSIONS: Statistical analysis of the results shows that the proposed context-based data preprocessing approach significantly improves predictive and context measures and outperforms the CFS algorithm. Context-based data preprocessing improves mining results by producing superior interpretable models, which makes it well-suited for practical applications in molecular docking simulations using FFR models.

Apoptotic events induced by maleimides on human acute leukemia cell lines.

Cyclic imides are known for their antitumor activity, especially the naphthalimide derivatives, such as Mitonafide and Amonafide. Recently, we have demonstrated the cytotoxic effect of a series of naphthalimide derivatives against B16F10 melanoma cells. On the basis of this fact, we have developed a study starting from the synthesis of different cyclic imides and the evaluation of their cytotoxic properties on human acute leukemia cells (K562 and Jurkat). Initially, a screening test was conducted to select the compound with the best cytotoxic effect, using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. After this selection, structural modifications were performed in the most active compound to obtain five more derivatives. All compounds presented a good cytotoxic effect. The results of cell cycle analysis, fluorescence microscopy, and Annexin V-FITC assay confirmed that the cells observed in the sub-G0/G1 phase were undergoing apoptosis. From this set of results, cyclic imides 8, 10, and 12 were selected for the evaluation of the mechanisms involved in the apoptotic process. The results demonstrate the involvement of the intrinsic pathway of apoptosis, evidenced by the reduction in mitochondrial potential, an increase in the level of AIF protein expression, a decreased level of expression of anti-apoptotic Bcl-2 protein, and an increased level of expression of pro-apoptotic protein Bax in both K562 and Jurkat cells treated with cyclic imides (8, 10, and 12). Furthermore, cyclic imides 8 and 10 caused an increase in the level of Fas expression in Jurkat cells, indicating the additional involvement of the extrinsic apoptosis pathway. The compounds (8, 10, and 12) also caused a decreased level of expression of anti-apoptotic protein survivin. The biological effects observed with these cyclic imide derivatives in this study suggest promising applications against acute leukemia.

Incidence of decreased hip range of motion in youth soccer players and response to a stretching program: a randomized clinical trial.

CONTEXT: After years of focusing on the management of anterior cruciate ligament (ACL) injuries, the most common soccer-related injuries, the orthopedic community has concluded that soccer players have a wide range of variation in joint biomechanics and has thus started to focus research efforts on the morphological factors that might contribute to ACL trauma. One such factor is decreased hip-rotation range of motion (ROM), which may be due to compensatory musculoskeletal changes occurring in response to longstanding soccer practice since childhood. OBJECTIVE: This study sought to assess decreased hip rotation and the influence of stretching exercises on the behavior of the hip joint in players of the youth soccer categories of a Brazilian soccer team. DESIGN: Randomized clinical trial. SETTING: University hospital. PATIENTS: 262 male soccer players. INTERVENTIONS: Subjects were randomly allocated into 2 groups-control or a stretching program. MAIN OUTCOME MEASURES: Subjects were reassessed after 12 wk. RESULTS: The findings suggest that hip-rotation ROM decreases over the years in soccer players. In the study sample, adherence to a stretching program improved only external hip-rotation ROM in the nondominant limb. CONCLUSION: Playing soccer can restrict rotation ROM of the hip, and adherence to stretching exercises may decrease the harmful effects on the hip joints.

Bambu and its applications in the discovery of active molecules against melanoma.

PURPOSE OR OBJECTIVE: Melanoma is one of the most dangerous forms of skin cancer and the discovery of novel drugs is an ongoing effort. Quantitative Structure Activity Relationship (QSAR) is a computational method that allows the estimation of the properties of a molecule, including its biological activity. QSAR models have been widely employed in the search for potential drug candidates, but also for agrochemicals and other molecules with applications in different branches of the industry. Here we present Bambu, a simple command line tool to generate QSAR models from high-throughput screening bioassays datasets. METHODS: The tool was developed using the Python programming language and relies mainly on RDKit for molecule data manipulation, FLAML for automated machine learning and the PubChem REST API for data retrieval. As a proof-of-concept we have employed the tool to generate QSAR models for melanoma cell growth inhibition based on HTS data and used them to screen libraries of FDA-approved drugs and natural compounds. Additionally, Bambu was compared to QSAR-Co, another automated tool for QSAR model generation. RESULTS: based on the developed tool we were able to produce QSAR models and identify a wide variety of molecules with potential melanoma cell growth inhibitors, many of which with anti-tumoral activity already described. The QSAR models are available through the URL http://caramel.ufpel.edu.br, and all data and code used to generate its models are available at Zenodo (https://doi.org/10.5281/zenodo.7495214). Bambu source code is available at GitHub (https://github.com/omixlab/bambu-v2). In the benchmark, Bambu was able to produce models with higher accuracy, recall, F1 and ROC AUC when compared to QSAR-Co for the selected datasets. CONCLUSIONS: Bambu is an free and open source tool which facilitates the creation of QSAR models and can be futurely applied in a wide variety of drug discovery projects.

Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.

BACKGROUND: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. RESULTS: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. CONCLUSIONS: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Phylogenetic analysis, computer modeling and catalytic prediction of an Amazonian soil ß-glucosidase against a soybean saponin.

Saponins are amphipathic glycosides with detergent properties present in vegetables. These compounds, when ingested, can cause difficulties in absorbing nutrients from food and even induce inflammatory processes in the intestine. There is already some evidence that saponins can be degraded by ß-glucosidases of the GH3 family. In the present study, we evaluated, through computational tools, the possibility of a ß-glucosidase (AMBGL17) obtained from a metagenomic analysis of the Amazonian soil, to catalytically interact with a saponin present in soybean. For this, the amino acid sequence of AMBGL17 was used in a phylogenetic analysis to estimate its origin and to determine its three-dimensional structure. The 3D structure of the enzyme was used in a molecular docking analysis to evaluate its interaction with soy saponin as a ligand. The results of the phylogenetic analysis showed that AMBGL17 comes from a microorganism of the phylum Chloroflexi, probably related to species of the order Aggregatinales. Molecular docking showed that soybean saponin can interact with the catalytic site of AMBGL17, with the amino acid GLY345 being important in this catalytic interaction, especially with a ß-1,2 glycosidic bond present in the carbohydrate portion of saponin. In conclusion, AMBGL17 is an enzyme with interesting biotechnological potential in terms of mitigating the anti-nutritional and pro-inflammatory effects of saponins present in vegetables used for human and animal food.

Chemoprotection mediated by açaí berry (Euterpe oleracea) in white shrimp Litopenaeus vannamei exposed to the cyanotoxin saxitoxin analyzed by in vivo assays and docking modeling.

Saxitoxin (STX) is a neurotoxic cyanotoxin that also generate reactive oxygen species, leading to a situation of oxidative stress and altered metabolism. The Amazonian fruit açaí Euterpe oleracea possesses a high concentration of antioxidant molecules, a fact that prompted us to evaluate its chemoprotection activity against STX toxicity (obtained from samples of Trichodesmium sp. collected in the environment) in the shrimp Litopenaeus vannamei. For 30 days, shrimps were maintained in 16 aquaria containing 10 shrimps (15% salinity, pH 8.0, 24 °C, 12C/12D photoperiod) and fed twice daily with a diet supplemented with lyophilized açaí pulp (10%), in addition to the control diet. After, shrimps (7.21 ± 0.04 g) were exposed to the toxin added to the feed for 96 h. Four treatments were defined: CTR (control diet), T (lyophilized powder of Trichodesmium sp. 0.8 µg/g), A (10% of açaí) and the combination T + A. HPLC analysis showed predominance of gonyautoxin-1 concentrations (GTX-1) and gonyautoxin-4 concentrations (GTX-4). The results of molecular docking simulations indicated that all variants of STX, including GTX-1, can be a substrate of isoform mu of the glutathione-S-transferase (GST) enzyme since these molecules obtained similar values of estimated Free Energy of Binding (FEB), as well as similar final positions on the binding site. GSH levels were reduced in muscle tissues of shrimp in the T, A, and T + A treatments. Increased GST activity was observed in shrimp hepatopancreas of the T treatment and the gills of the A and T + A treatments. A decrease of protein sulfhydryl groups (P-SH) was observed in gills of shrimps from T + A treatment. A reduction in malondialdehyde (MDA) levels was registered in the hepatopancreas of the T + A treatment in respect to the Control, T, and A treatments. The use of açaí supplements in L. vannamei feed was able to partially mitigate the toxic effects caused by Trichodesmium sp. extracts, and points to mu GST isoform as a key enzyme for saxitoxin detoxification in L. vannamei, an issue that deserves further investigation.