Structure and folding properties of neurophysin and its peptide complexes: biological implications

Abstract Thymic central tolerance eliminates most immature T cells with autoreactive T cell receptors (TCR) that recognize self MHC/peptide complexes. Regardless, an unknown number of autoreactive CD4+Foxp3− T cells escape negative selection and in the periphery require continuous suppression by CD4+Foxp3+ regulatory cells (Tregs). Here, we compare immune repertoires of Treg-deficient and Treg-sufficient mice to find Tregs continuously constraining one-third of mature CD4+Foxp3− cells from converting to pathogenic effectors in healthy mice. These dormant pathogenic clones frequently express TCRs activatable by ubiquitous autoantigens presented by class II MHCs on conventional dendritic cells, including self-peptides that select them in the thymus. Our data thus suggest that identification of most potentially autoreactive CD4+ T cells in the peripheral repertoire is critical to harness or redirect these cells for therapeutic advantage.

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An automated protocol for modelling peptide substrates to proteases

BMC Bioinformatics ◽

10.1186/s12859-020-03931-6 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Rodrigo Ochoa ◽

Mikhail Magnitov ◽

Roman A. Laskowski ◽

Pilar Cossio ◽

Janet M. Thornton

Keyword(s):

Substrate Recognition ◽

Accessible Surface Area ◽

Conformational Sampling ◽

Structural Determinants ◽

Peptide Substrates ◽

The Family ◽

Protease Substrate ◽

Peptide Complexes ◽

Accessible Surface ◽

Automated Protocol

Abstract 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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Interaction of Temporin-L Analogues with the E. coli FtsZ Protein

Antibiotics ◽

10.3390/antibiotics10060704 ◽

2021 ◽

Vol 10 (6) ◽

pp. 704

Author(s):

Angela Di Somma ◽

Carolina Canè ◽

Antonio Moretta ◽

Angela Duilio

Keyword(s):

Protein Interactions ◽

Bacterial Infections ◽

Antibacterial Properties ◽

Bacterial Cell Division ◽

Structural Determinants ◽

E Coli ◽

Functional Studies ◽

Division Process ◽

Z Ring ◽

Peptide Complexes

The research of new therapeutic agents to fight bacterial infections has recently focused on the investigation of antimicrobial peptides (AMPs), the most common weapon that all organisms produce to prevent invasion by external pathogens. Among AMPs, the amphibian Temporins constitute a well-known family with high antibacterial properties against Gram-positive and Gram-negative bacteria. In particular, Temporin-L was shown to affect bacterial cell division by inhibiting FtsZ, a tubulin-like protein involved in the crucial step of Z-ring formation at the beginning of the division process. As FtsZ represents a leading target for new antibacterial compounds, in this paper we investigated in detail the interaction of Temporin L with Escherichia coli FtsZ and designed two TL analogues in an attempt to increase peptide-protein interactions and to better understand the structural determinants leading to FtsZ inhibition. The results demonstrated that the TL analogues improved their binding to FtsZ, originating stable protein-peptide complexes. Functional studies showed that both peptides were endowed with a high capability of inhibiting both the enzymatic and polymerization activities of the protein. Moreover, the TL analogues were able to inhibit bacterial growth at low micromolar concentrations. These observations may open up the way to the development of novel peptide or peptidomimetic drugs tailored to bind FtsZ, hampering a crucial process of bacterial life that might be proposed for future pharmaceutical applications.

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Synthesis, characterization and hybridization studies of an alternate nucleo-ε/γ-peptide: complexes formation with natural nucleic acids

Amino Acids ◽

10.1007/s00726-008-0214-7 ◽

2008 ◽

Vol 38 (1) ◽

pp. 103-111 ◽

Cited By ~ 21

Author(s):

G. N. Roviello ◽

D. Musumeci ◽

C. Pedone ◽

E. M. Bucci

Keyword(s):

Nucleic Acids ◽

Peptide Complexes

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Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

Molecules ◽

10.3390/molecules26113293 ◽

2021 ◽

Vol 26 (11) ◽

pp. 3293

Author(s):

Mateusz Zalewski ◽

Sebastian Kmiecik ◽

Michał Koliński

Keyword(s):

Molecular Dynamics ◽

Geometry Optimization ◽

Computational Prediction ◽

Md Simulations ◽

Coarse Grained ◽

Ligand Interaction ◽

Vast Number ◽

Docking Simulations ◽

Peptide Models ◽

Peptide Complexes

One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.

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