Prestin (SLC26A5) is a member of the SLC26/SulP anion transporter family. Its unique quasi-piezoelectric mechanical activity generates fast cellular motility of cochlear outer hair cells, a key process underlying active amplification in the mammalian ear. Despite its established physiological role, it is essentially unknown how prestin can generate mechanical force, since structural information on SLC26/SulP proteins is lacking. Here we derive a structural model of prestin and related transporters by combining homology modelling, MD simulations and cysteine accessibility scanning. Prestin’s transmembrane core region is organized in a 7+7 inverted repeat architecture. The model suggests a central cavity as the substrate-binding site located midway of the anion permeation pathway, which is supported by experimental solute accessibility and mutational analysis. Anion binding to this site also controls the electromotile activity of prestin. The combined structural and functional data provide a framework for understanding electromotility and anion transport by SLC26 transporters.

Molecular recognition is a crucial issue when aiming to interpret the mechanism of known active substances as well as to develop novel active candidates. Unfortunately, simulating the binding process is still a challenging task because it requires classical MD experiments in a long microsecond time scale that are affordable only with a high-level computational capacity. In order to overcome this limiting factor, we have recently implemented an alternative MD approach, named supervised molecular dynamics (SuMD), and successfully applied it to G protein-coupled receptors (GPCRs). SuMD enables the investigation of ligand-receptor binding events independently from the starting position, chemical structure of the ligand, and also from its receptor binding affinity. In this article, we present an extension of the SuMD application domain including different types of proteins in comparison with GPCRs. In particular, we have deeply analyzed the ligand-protein recognition pathways of six different case studies that we grouped into two different classes: globular and membrane proteins. Moreover, we introduce the SuMD-Analyzer tool that we have specifically implemented to help the user in the analysis of the SuMD trajectories. Finally, we emphasize the limit of the SuMD applicability domain as well as its strengths in analyzing the complexity of ligand-protein recognition pathways.

Peptides have gained increased interest as therapeutic agents during recent years. The high specificity and relatively low toxicity of peptide drugs derive from their extremely tight binding to their targets. Indeed, understanding the molecular mechanism of protein-peptide recognition has important implications in the fields of biology, medicine, and pharmaceutical sciences. Even if crystallography and nuclear magnetic resonance are offering valuable atomic insights into the assembling of the protein-peptide complexes, the mechanism of their recognition and binding events remains largely unclear. In this work we report, for the first time, the use of a supervised molecular dynamics approach to explore the possible protein-peptide binding pathways within a timescale reduced up to three orders of magnitude compared with classical molecular dynamics. The better and faster understating of the protein-peptide recognition pathways could be very beneficial in enlarging the applicability of peptide-based drug design approaches in several biotechnological and pharmaceutical fields.

Background: DJ-1, a protein involved in PD, protects neurons by acting as an oxidative stress sensor. Results: Through adduct formation on DJ-1 cysteines, DAQs induce both structural perturbations and uncoupling of the sensor function. Conclusion: Cys-53 is the most reactive, but Cys-106 modification induces the most severe effects. Significance: A correlation between DJ-1 DAQ-dependent impairment and the degeneration of dopaminergic neurons observed in PD is suggested.

Background:We sought to identify novel peptide sequences that interact at the BH3 binding groove of Mcl-1. Results: We identified a peptide that binds to Mcl-1 in a reverse orientation compared with canonical BH3 peptides. Conclusion:The peptide binds to Mcl-1 selectively over other Bcl-2 proteins. Significance: The novel sequence is useful in identifying Mcl-1 binding partners and for developing possible therapeutics.