The accuracy of protein structure alignment servers

Machine learning for the identification of respiratory viral attachment machinery from sequences data

At the outset of an emergent viral respiratory pandemic, sequence data is among the first molecular information available. As viral attachment machinery is a key target for therapeutic and prophylactic interventions, rapid identification of viral "spike" proteins from sequence can significantly accelerate the development of medical countermeasures. For six families of respiratory viruses, covering the vast majority of airborne and droplet-transmitted diseases, host cell entry is mediated by the binding of viral surface glycoproteins that interact with a host cell receptor. In this report it is shown that sequence data for an unknown virus belonging to one of the six families above provides sufficient information to identify the protein(s) responsible for viral attachment. Random forest models that take as input a set of respiratory viral sequences can classify the protein as "spike" vs. non-spike based on predicted secondary structure elements alone (with 97.3% correctly classified) or in combination with N-glycosylation related features (with 97.0% correctly classified). Models were validated through 10-fold cross-validation, bootstrapping on a class-balanced set, and an out-of-sample extra-familial validation set. Surprisingly, we showed that secondary structural elements and N-glycosylation features were sufficient for model generation. The ability to rapidly identify viral attachment machinery directly from sequence data holds the potential to accelerate the design of medical countermeasures for future pandemics. Furthermore, this approach may be extendable for the identification of other potential viral targets and for viral sequence annotation in general in the future.

GADP-align: A genetic algorithm and dynamic programming-based method for structural alignment of proteins

Introduction: Similarity analysis of protein structure is considered as a fundamental step to give insight into the relationships between proteins. The primary step in structural alignment is looking for the optimal correspondence between residues of two structures to optimize the scoring function. An exhaustive search for finding such a correspondence between two structures is intractable.

Methods: In this paper, a hybrid method is proposed, namely GADP-align, for pairwise protein structure alignment. The proposed method looks for an optimal alignment using a hybrid method based on a genetic algorithm and an iterative dynamic programming technique. To this end, the method first creates an initial map of correspondence between secondary structure elements (SSEs) of two proteins. Then, a genetic algorithm combined with an iterative dynamic programming algorithm is employed to optimize the alignment.

Results: The GADP-align algorithm was employed to align 10 ‘difficult to align’ protein pairs in order to evaluate its performance. The experimental study shows that the proposed hybrid method produces highly accurate alignments in comparison with the methods using exactly the dynamic programming technique. Furthermore, the proposed method prevents the local optimal traps caused by the unsuitable initial guess of the corresponding residues.

Conclusion: The findings of this paper demonstrate that employing the genetic algorithm along with the dynamic programming technique yields highly accurate alignments between a protein pair by exploring the global alignment and avoiding trapping in local alignments.

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.