Docking interactions determine early cleavage events in insulin proteolysis by pepsin: Experiment and simulation

Integrative modeling of diverse protein-peptide systems using CABS-dock

The CABS model can be applied to a wide range of protein-protein and protein-peptide molecular modeling tasks, such as simulating folding pathways, predicting structures, docking, and analyzing the structural dynamics of molecular complexes. In this work, we use the CABS-dock tool in two diverse modeling tasks: 1) predicting the structures of amyloid protofilaments and 2) identifying cleavage sites in the peptide substrates of proteolytic enzymes. In the first case, simulations of the simultaneous docking of amyloidogenic peptides indicated that the CABS model can accurately predict the structures of amyloid protofilaments which have an in-register parallel architecture. Scoring based on a combination of symmetry criteria and estimated interaction energy values for bound monomers enables the identification of protofilament models that closely match their experimental structures for 5 out of 6 analyzed systems. For the second task, it has been shown that CABS-dock coarse-grained docking simulations can be used to identify the positions of cleavage sites in the peptide substrates of proteolytic enzymes. The cleavage site position was correctly identified for 12 out of 15 analyzed peptides. When combined with sequence-based methods, these docking simulations may lead to an efficient way of predicting cleavage sites in degraded proteins. The method also provides the atomic structures of enzyme-substrate complexes, which can give insights into enzyme-substrate interactions that are crucial for the design of new potent inhibitors.

Purification and characterization of Lactobacillus plantarum-derived bacteriocin with activity against Staphylococcus argenteus planktonic cells and biofilm

Bacteriocins inhibit various foodborne bacteria in planktonic and biofilm forms. However, bacteriocins with antibacterial and antibiofilm activity against Staphylococcus argenteus, a pathogen that can cause food poisoning, are still poorly known. Here, the novel bacteriocin LSB1 derived from Lactobacillus plantarum CGMCC 1.12934 was purified and characterized extensively. LSB1 had a molecular weight of 1425.78 Da and an amino acid sequence of YIFVTGGVVSSLGK. Moreover, LSB1 exhibited excellent stability under heat and acid-base stress and presented sensitivity to pepsin and proteinase K. LSB1 exhibited an extensive antimicrobial spectrum against both Gram-positive and Gram-negative bacteria. Minimum inhibitory concentration of LSB1 against S. argenteus_70917 was 10.36 µg/ml, which was lower than that of most of the previously found bacteriocins against Staphylococcus strains. Furthermore, LSB1 significantly inhibited S. argenteus_70917 planktonic cells (p < 0.01) and decreased their viability. Scanning electron microscopy analysis revealed that cell membrane permeability of S. argenteus_70917 upon exposure to LSB1 showed leakage of cytoplasmic contents and rupture, leading to cell death. In addition, biofilm formation ability of S. argenteus_70917 was significantly (p < 0.01) impaired by LSB1, with the percent inhibition of 35% at 10 µg/ml and 80% at 20 µg/ml. Overall, this study indicates that LSB1 can be considered a potential antibacterial agent in the control of S. argenteus in both planktonic and biofilm states. PRACTICAL APPLICATION: Foodborne pathogenic bacteria, such as Staphylococcus argenteus, and their biofilms represent potential risks for food safety. In recent years, customers' demand for "natural" products has increased food control. This study describes the novel bacteriocin LSB1 produced by the lactic acid bacterium species Lactobacillus plantarum. LSB1 showed strong antibacterial and antibiofilm activity against S. argenteus as well as thermal and acid-alkaline stability. Furthermore, the mechanisms of action of LSB1 on S. argenteus were preliminarily explored. These results indicate that LSB1 might be potentially used as an effective and natural food preservative.

Multiscale Modeling of Amyloid Fibrils Formed by Aggregating Peptides Derived from the Amyloidogenic Fragment of the A-Chain of Insulin

Computational prediction of molecular structures of amyloid fibrils remains an exceedingly challenging task. In this work, we propose a multi-scale modeling procedure for the structure prediction of amyloid fibrils formed by the association of ACC_1-13 aggregation-prone peptides derived from the N-terminal region of insulin’s A-chain. First, a large number of protofilament models composed of five copies of interacting ACC_1-13 peptides were predicted by application of CABS-dock coarse-grained (CG) docking simulations. Next, the models were reconstructed to all-atom (AA) representations and refined during molecular dynamics (MD) simulations in explicit solvent. The top-scored protofilament models, selected using symmetry criteria, were used for the assembly of long fibril structures. Finally, the amyloid fibril models resulting from the AA MD simulations were compared with atomic force microscopy (AFM) imaging experimental data. The obtained results indicate that the proposed multi-scale modeling procedure is capable of predicting protofilaments with high accuracy and may be applied for structure prediction and analysis of other amyloid fibrils.

Protein-Protein Docking with Large-Scale Backbone Flexibility Using Coarse-Grained Monte-Carlo Simulations

Most of the protein–protein docking methods treat proteins as almost rigid objects. Only the side-chains flexibility is usually taken into account. The few approaches enabling docking with a flexible backbone typically work in two steps, in which the search for protein–protein orientations and structure flexibility are simulated separately. In this work, we propose a new straightforward approach for docking sampling. It consists of a single simulation step during which a protein undergoes large-scale backbone rearrangements, rotations, and translations. Simultaneously, the other protein exhibits small backbone fluctuations. Such extensive sampling was possible using the CABS coarse-grained protein model and Replica Exchange Monte Carlo dynamics at a reasonable computational cost. In our proof-of-concept simulations of 62 protein–protein complexes, we obtained acceptable quality models for a significant number of cases.

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

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.

Reduction of a disulfide-constrained oligo-glutamate peptide triggers self-assembly of β2-type amyloid fibrils with the chiroptical properties determined by supramolecular chirality

Disulfide bonds prevent aggregation of globular proteins by stabilizing the native state. However, a disulfide bond within a disordered state may accelerate amyloidogenic nucleation by navigating fluctuating polypeptide chains towards an orderly assembly of β-sheets. Here, the self-assembly behavior of Glu-Cys-(Glu)₄-Cys-Glu peptide (E₆C₂), in which an intrachain disulfide bond is engineered into an amyloidogenic homopolypeptide motif, is investigated. To this end, the Thioflavin T (ThT) fluorescence kinetic assay is combined with infrared spectroscopy, circular dichroism (CD), atomic force microscopy (AFM) and Raman scattering measurements. Regardless of whether the disulfide bond is intact or reduced, E₆C₂ monomers remain disordered within a broad range of pH. On the other hand, only reduced E₆C₂ self-assembles into amyloid fibrils with the unique infrared traits indicative of three-center hydrogen bonds involving main-chain carbonyl as a bifurcating acceptor and main-chain NH and side-chain -COOH groups as hydrogen donors: the bonding pattern observed in so-called β₂-fibrils. AFM analysis of β₂-E₆C₂ reveals tightly packed rectangular superstructures whose presence coincides with strong chiroptical properties. Our findings suggest that formation of chiral amyloid superstructures may be a generic process accessible to various substrates, and that the fully extended conformation of a poly-Glu chain is a condition sine qua non for self-assembly of β₂-fibrils.

Docking of peptides to GPCRs using a combination of CABS-dock with FlexPepDock refinement

The structural description of peptide ligands bound to G protein-coupled receptors (GPCRs) is important for the discovery of new drugs and deeper understanding of the molecular mechanisms of life. Here we describe a three-stage protocol for the molecular docking of peptides to GPCRs using a set of different programs: (1) CABS-dock for docking fully flexible peptides; (2) PD2 method for the reconstruction of atomistic structures from C-alpha traces provided by CABS-dock and (3) Rosetta FlexPepDock for the refinement of protein–peptide complex structures and model scoring. We evaluated the proposed protocol on the set of seven different GPCR–peptide complexes (including one containing a cyclic peptide), for which crystallographic structures are available. We show that CABS-dock produces high resolution models in the sets of top-scored models. These sets of models, after reconstruction to all-atom representation, can be further improved by Rosetta high-resolution refinement and/or minimization, leading in most of the cases to sub-Angstrom accuracy in terms of interface root-mean-square-deviation measure.

Enzymes to unravel bioproducts architecture

Enzymes are essential and ubiquitous biocatalysts involved in various metabolic pathways and used in many industrial processes. Here, we reframe enzymes not just as biocatalysts transforming bioproducts but also as sensitive probes for exploring the structure and composition of complex bioproducts, like meat tissue, dairy products and plant materials, in both food and non-food bioprocesses. This review details the global strategy and presents the most recent investigations to prepare and use enzymes as relevant probes, with a focus on glycoside-hydrolases involved in plant deconstruction and proteases and lipases involved in food digestion. First, to expand the enzyme repertoire to fit bioproduct complexity, novel enzymes are mined from biodiversity and can be artificially engineered. Enzymes are further characterized by exploring sequence/structure/dynamics/function relationships together with the environmental factors influencing enzyme interactions with their substrates. Then, the most advanced experimental and theoretical approaches developed for exploring bioproducts at various scales (from nanometer to millimeter) using active and inactive enzymes as probes are illustrated. Overall, combining multimodal and multiscale approaches brings a better understanding of native-form or transformed bioproduct architecture and composition, and paves the way to mainstream the use of enzymes as probes.