AntiVPP 1.0: A portable tool for prediction of antiviral peptides

Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity and constitute excellent alternatives for the treatment of viral infections. In the present study, we developed AntiVPP 1.0, an accurate bioinformatic tool that uses the Random Forest algorithm for antiviral peptide predictions. The model of AntiVPP 1.0 for antiviral peptide predictions uses several features of 1088 peptides for training and validation. During the validation of the model we achieved the TPR = 0.87, SPC = 0.97, ACC = 0.93 and MCC = 0.87 performance measures, which were indicative of a robust model. AntiVPP 1.0 is a fast, accurate and intuitive software focused on the assessment of antiviral peptides candidates. AntiVPP 1.0 is available at https://github.com/bio-coding/AntiVPP.

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Random Forest algorithm was used for antiviral peptides prediction.

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AntiVPP 1.0 can be used for assessing various physical and chemical properties of antiviral peptides.

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Anti VPP 1.0 is a software with a simple interface and a high performance for academic and commercial purposes.

The CatSper channel is present and plays a key role in sperm motility of the Atlantic salmon (Salmo salar)

Among all the Ca²⁺ channels, CatSper channels have been one of the most studied in sperm of different species due to their demonstrated role in the fertilization process. In fish sperm, the calcium channel plays a key role in sperm activation. However, the functionality of the CatSper channels has not been studied in any of the fish species. For the first time, we studied the relationship of the CatSper channel with sperm motility in a fish, using Atlantic salmon (Salmo salar) as the model. The results of our study showed that the CatSper channel in Salmo salar has chemical-physical characteristics similar to those reported for mammalian CatSper channels. In this work, it was shown that Salmo salar CatSper 3 protein has a molecular weight of approximately 55-kDa similar to Homo sapiens CatSper 3. In silico analyses suggest that this channel forms a heterotetramer sensitive to the specific inhibitor HC-056456, with a binding site in the center of the pore of the CatSper channel, hindering or preventing the influx of Ca²⁺ ions. The in vitro assay of the sperm motility inhibition of Salmo salar with the inhibitor HC-056456 showed that sperm treated with this inhibitor significantly reduced the total and progressive motility (p < .0001), demonstrating the importance of this ionic channel for this cell. The complementation of the in silico and in vitro analyses of the present work demonstrates that the CatSper channel plays a key role in the regulation of sperm motility in Atlantic salmon.

PPLK+C: A Bioinformatics Tool for Predicting Peptide Ligands of Potassium Channels Based on Primary Structure Information

Potassium channels play a key role in regulating the flow of ions through the plasma membrane, orchestrating many cellular processes including cell volume regulation, hormone secretion and electrical impulse formation. Ligand peptides of potassium channels are molecules used in basic and applied research and are now considered promising alternatives in the treatment of many diseases, such as cardiovascular diseases and cancer. Currently, there are various bioinformatics tools focused on the prediction of peptides with different activities. However, none of the current tools can predict ligand peptides of potassium channels. In this work, we developed a tool called PPLK⁺C; this is the first tool that can predict peptide ligands of potassium channels. We also evaluated several amino acid molecular features and four machine-learning algorithms for the prediction of potassium channel ligand peptides: random forest, nearest neighbors, support vector machine and artificial neural network. All the biological data used in this study for training and validating models were obtained from peptides with experimentally verified activity. PPLK⁺C is a bioinformatics software written in the Python programming language, which showed a high predictive capacity with a model generated with the random forest algorithm: 0.77 sensitivity, 0.94 specificity, 0.91 accuracy and 0.70 Matthews correlation coefficient. PPLK⁺C is a novel tool with a friendly interface that can be used for the discovery of novel ligand peptides of potassium channels with high reliability, using only primary structure information.

Role of voltage-gated L-type calcium channel in the spermatozoa motility of Atlantic salmon (Salmo salar)

Ca²⁺ cations play a key role in the initiation of spermatozoa motility in Atlantic salmon (Salmo salar). In this study we assess the importance of the voltage-gated L-type calcium channels in the spermatozoa motility of Atlantic salmon by combined in vitro and in silico approaches. The results of this study showed that as in other fish species, voltage-gated L-type calcium channels are significant in the spermatozoa motility of Salmo salar. The in vitro assays showed that total and progressive motilities decrease significantly (****p < .001) when Salmo salar spermatozoa are treated with verapamil, which has its binding site in the pore of the voltage-gated L-type calcium channel according to the in silico analysis.