Interpreting Mass Spectra Differing from Their Peptide Models by Several Modifications

Background: In proteomics, mass spectra representing peptides carrying multiple unknown modifications are particularly difficult to interpret. This issue results in a large number of unidentified spectra.Methods: We developed SpecGlob, a dynamic programming algorithm that aligns pairs of spectra – each pair given by a Peptide-Spectrum Match (PSM) – provided by any Open Modification Search (OMS) method. For each PSM, SpecGlob computes the best alignment according to a given score system, interpreting the mass delta within the PSM as one or several unspecified modification(s). All the alignments are provided in a file, using a specific syntax. These alignments are then post-processed by an additional algorithm, which aims at interpreting the detected modifications.Results: Using a large collection of theoretical spectra generated from the human proteome, we demonstrate that running SpecGlob as a post-analysis of an OMS method can significantly increase the number of correctly interpreted spectra, since SpecGlob is able to infer several, and possibly many, modifications. The post-processing algorithm is able to interpret unambiguously most of the modifications detected by SpecGlob in PSMs. In addition, we performed an extensive analysis to provide insight into the potential reasons for incomplete or erroneous interpretations that may remain after alignments of PSMs.Conclusion: SpecGlob is able to correctly align spectra that differ by one or more modification(s) without any a priori. Since SpecGlob explores all possible alignments that may explain the mass delta within a PSM, it reduces interpretation errors generated by incorrect assumptions about the modifications present in the sample or the number and the specificity of modifications carried by peptides. Our results demonstrate that SpecGlob should be relevant to align experimental spectra, even if this consists in a more challenging task.

Synthetic NAC 71-82 Peptides Designed to Produce Fibrils with Different Protofilament Interface Contacts

Alpha-synucleinopathies are featured by fibrillar inclusions in brain cells. Although α-synuclein fibrils display structural diversity, the origin of this diversity is not fully understood. We used molecular dynamics simulations to design synthetic peptides, based on the NAC 71-82 amino acid fragment of α-synuclein, that govern protofilament contacts and generation of twisted fibrillar polymorphs. Four peptides with structures based on either single or double fragments and capped or non-capped ends were selected for further analysis. We determined the fibrillar yield and the structures from these peptides found in the solution after fibrillisation using protein concentration determination assay and circular dichroism spectroscopy. In addition, we characterised secondary structures formed by individual fibrillar complexes using laser-tweezers Raman spectroscopy. Results suggest less mature fibrils, based on the lower relative β-sheet content for double- than single-fragment peptide fibrils. We confirmed this structural difference by TEM analysis which revealed, in addition to short protofibrils, more elongated, twisted and rod-like fibril structures in non-capped and capped double-fragment peptide systems, respectively. Finally, time-correlated single-photon counting demonstrated a difference in the Thioflavin T fluorescence lifetime profiles upon fibril binding. It could be proposed that this difference originated from morphological differences in the fibril samples. Altogether, these results highlight the potential of using peptide models for the generation of fibrils that share morphological features relevant for disease, e.g., twisted and rod-like polymorphs.

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.

Revisiting the interaction of heme with hemopexin

In hemolytic disorders, erythrocyte lysis results in massive release of hemoglobin and, subsequently, toxic heme. Hemopexin is the major protective factor against heme toxicity in human blood and currently considered for therapeutic use. It has been widely accepted that hemopexin binds heme with extraordinarily high affinity of <1 pM in a 1:1 ratio. However, several lines of evidence point to a higher stoichiometry and lower affinity than determined 50 years ago. Here, we re-analyzed these data. SPR and UV/Vis spectroscopy were used to monitor the interaction of heme with the human protein. The heme-binding sites of hemopexin were characterized using hemopexin-derived peptide models and competitive displacement assays. We obtained a K D value of 0.32 ± 0.04 nM and the ratio for the interaction was determined to be 1:1 at low heme concentrations and at least 2:1 (heme:hemopexin) at high concentrations. We were able to identify two yet unknown potential heme-binding sites on hemopexin. Furthermore, molecular modelling with a newly created homology model of human hemopexin suggested a possible recruiting mechanism by which heme could consecutively bind several histidine residues on its way into the binding pocket. Our findings have direct implications for the potential administration of hemopexin in hemolytic disorders.

Spatial Structure and Activity of Synthetic Fragments of Lynx1 and of Nicotinic Receptor Loop C Models

Lynx1, membrane-bound protein co-localized with the nicotinic acetylcholine receptors (nAChRs) and regulates their function, is a three-finger protein (TFP) made of three β-structural loops, similarly to snake venom α-neurotoxin TFPs. Since the central loop II of α-neurotoxins is involved in binding to nAChRs, we have recently synthesized the fragments of Lynx1 central loop, including those with the disulfide between Cys residues introduced at N- and C-termini, some of them inhibiting muscle-type nAChR similarly to the whole-size water-soluble Lynx1 (ws-Lynx1). Literature shows that the main fragment interacting with TFPs is the C-loop of both nAChRs and acetylcholine binding proteins (AChBPs) while some ligand-binding capacity is preserved by analogs of this loop, for example, by high-affinity peptide HAP. Here we analyzed the structural organization of these peptide models of ligands and receptors and its role in binding. Thus, fragments of Lynx1 loop II, loop C from the Lymnaea stagnalis AChBP and HAP were synthesized in linear and Cys-cyclized forms and structurally (CD and NMR) and functionally (radioligand assay on Torpedo nAChR) characterized. Connecting the C- and N-termini by disulfide in the ws-Lynx1 fragment stabilized its conformation which became similar to the loop II within the 1H-NMR structure of ws-Lynx1, the activity being higher than for starting linear fragment but lower than for peptide with free cysteines. Introduced disulfides did not considerably change the structure of HAP and of loop C fragments, the former preserving high affinity for α-bungarotoxin, while, surprisingly, no binding was detected with loop C and its analogs.

In-silico Analysis of Porcine and Recombinant Insulin Activity on Glycogen

The study focuses on the anti-diabetic activity by molecular simulation of Recombinant Insulin, Porcine Insulin, and Glycogen. The sequence of these three molecules was retrieved, and 3D structures were modeled. A total of two different molecular simulations were carried out. The simulations were done using Autodock software. Initially, the downloaded PDB structures were docked with glycogen and the second between the active site peptide models of both insulin molecules based on castP prediction with glycogen molecule. The results were analyzed by the Ramachandran plot for model prediction, and the binding energy was set as criteria to determine the best-docked model. The binding energy of recombinant insulin, porcine insulin with glycogen was 0.32 and -1.09, respectively. Similarly, the binding energy for peptide models with a glycogen molecule was found to be +1.09 and +6.76, respectively. Based on the results, it was concluded that recombinant insulin has a higher affinity than porcine insulin.

Revisiting the interaction of heme with hemopexin: Recommendations for the responsible use of an emerging drug

In hemolytic disorders, erythrocyte lysis results in massive release of hemoglobin and, subsequently, toxic heme. Hemopexin is the major protective factor against heme toxicity in human blood and currently considered for therapeutic use. It has been widely accepted that hemopexin binds heme with extraordinarily high affinity in a 1:1 ratio. Here we show that hemopexin binds heme with lower affinity than previously assumed and that the interaction ratio tends to 2:1 (heme:hemopexin) or above. The heme-binding sites of hemopexin were characterized using hemopexin-derived peptide models and competitive displacement assays. In addition, in silico molecular modelling with a newly created homology model of human hemopexin allowed us to propose a recruiting mechanism by which heme consecutively binds to several histidine residues and is finally funnelled into the high-affinity binding pocket. Our findings have direct implications for the biomedical application of hemopexin and its potential administration in hemolytic disorders.

Off-pathway 3D-structure provides protection against spontaneous Asn/Asp isomerization: shielding proteins Achilles heel

Spontaneous deamidation prompted backbone isomerization of Asn/Asp residues resulting in – most cases – the insertion of an extra methylene group into the backbone poses a threat to the structural integrity of proteins. Here we present a systematical analysis of how temperature, pH, presence of charged residues, but most importantly backbone conformation and dynamics affect isomerization rates as determined by nuclear magnetic resonance in the case of designed peptide-models. We demonstrate that restricted mobility (such as being part of a secondary structural element) may safeguard against isomerization, but this protective factor is most effective in the case of off-pathway folds which can slow the reaction by several magnitudes compared to their on-pathway counterparts. We show that the geometric descriptors of the initial nucleophilic attack of the isomerization can be used to classify local conformation and contribute to the design of stable protein drugs, antibodies or the assessment of the severity of mutations.