Mapping the Protein Fold Universe Using the CamTube Force Field in Molecular Dynamics Simulations

It has been recently shown that the coarse-graining of the structures of polypeptide chains as self-avoiding tubes can provide an effective representation of the conformational space of proteins. In order to fully exploit the opportunities offered by such a \u2018tube model\u2019 approach, we present here a strategy to combine it with molecular dynamics simulations. This strategy is based on the incorporation of the \u2018CamTube\u2019 force field into the Gromacs molecular dynamics package. By considering the case of a 60-residue polyvaline chain, we show that CamTube molecular dynamics simulations can comprehensively explore the conformational space of proteins. We obtain this result by a 20 \u3bcs metadynamics simulation of the polyvaline chain that recapitulates the currently known protein fold universe. We further show that, if residue-specific interaction potentials are added to the CamTube force field, it is possible to fold a protein into a topology close to that of its native state. These results illustrate how the CamTube force field can be used to explore efficiently the universe of protein folds with good accuracy and very limited computational cost

Structural characterization of the interaction of α-synuclein nascent chains with the ribosomal surface and trigger factor

The ribosome is increasingly becoming recognized as a key hub for integrating quality control processes associated with protein biosynthesis and cotranslational folding (CTF). The molecular mechanisms by which these processes take place, however, remain largely unknown, in particular in the case of intrinsically disordered proteins (IDPs). To address this question, we studied at a residue-specific level the structure and dynamics of ribosome-nascent chain complexes (RNCs) of α-synuclein (αSyn), an IDP associated with Parkinson’s disease (PD). Using solution-state nuclear magnetic resonance (NMR) spectroscopy and coarse-grained molecular dynamics (MD) simulations, we find that, although the nascent chain (NC) has a highly disordered conformation, its N-terminal region shows resonance broadening consistent with interactions involving specific regions of the ribosome surface. We also investigated the effects of the ribosome-associated molecular chaperone trigger factor (TF) on αSyn structure and dynamics using resonance broadening to define a footprint of the TF–RNC interactions. We have used these data to construct structural models that suggest specific ways by which emerging NCs can interact with the biosynthesis and quality control machinery

pKa Modulation of the Acid/Base Catalyst within GH32 and GH68: A Role in Substrate/Inhibitor Specificity?

Glycoside hydrolases of families 32 (GH32) and 68 (GH68) belong to clan GH-J, containing hydrolytic enzymes (sucrose/fructans as donor substrates) and fructosyltransferases (sucrose/fructans as donor and acceptor substrates). In GH32 members, some of the sugar substrates can also function as inhibitors, this regulatory aspect further adding to the complexity in enzyme functionalities within this family. Although 3D structural information becomes increasingly available within this clan and huge progress has been made on structure-function relationships, it is not clear why some sugars bind as inhibitors without being catalyzed. Conserved aspartate and glutamate residues are well known to act as nucleophile and acid/bases within this clan. Based on the available 3D structures of enzymes and enzyme-ligand complexes as well as docking simulations, we calculated the pKa of the acid-base before and after substrate binding. The obtained results strongly suggest that most GH-J members show an acid-base catalyst that is not sufficiently protonated before ligand entrance, while the acid-base can be fully protonated when a substrate, but not an inhibitor, enters the catalytic pocket. This provides a new mechanistic insight aiming at understanding the complex substrate and inhibitor specificities observed within the GH-J clan. Moreover, besides the effect of substrate entrance on its own, we strongly suggest that a highly conserved arginine residue (in the RDP motif) rather than the previously proposed Tyr motif (not conserved) provides the proton to increase the pKa of the acid-base catalyst

Disulfiram-induced cytotoxicity and endo-lysosomal sequestration of zinc in breast cancer cells

Disulfiram, a clinically used alcohol-deterrent has gained prominence as a potential anti-cancer agent due to its impact on copper-dependent processes. Few studies have investigated zinc effects on disulfiram action, despite it having high affinity for this metal. Here we studied the cytotoxic effects of disulfiram in breast cancer cells, and its relationship with both intra and extracellular zinc. MCF-7 and BT474 cancer cell lines gave a striking time-dependent biphasic cytotoxic response between 0.01 and 10 μM disulfiram. Co-incubation of disulfiram with low-level zinc removed this effect, suggesting that availability of extracellular zinc significantly influences disulfiram efficacy. Live-cell confocal microscopy using fluorescent endocytic probes and the zinc dye Fluozin-3 revealed that disulfiram selectively and rapidly increased zinc levels in endo-lysosomes. Disulfiram also caused spatial disorganization of late endosomes and lysosomes, suggesting they are novel targets for this drug. This relationship between disulfiram toxicity and ionophore activity was consolidated via synthesis of a new disulfiram analog and overall we demonstrate a novel mechanism of disulfiram-cytotoxicity with significant clinical implications for future use as a cancer therapeutic

Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks

BACKGROUND: Protein inter-residue contact maps provide a translation and rotation invariant topological representation of a protein. They can be used as an intermediary step in protein structure predictions. However, the prediction of contact maps represents an unbalanced problem as far fewer examples of contacts than non-contacts exist in a protein structure. In this study we explore the possibility of completely eliminating the unbalanced nature of the contact map prediction problem by predicting real-value distances between residues. Predicting full inter-residue distance maps and applying them in protein structure predictions has been relatively unexplored in the past. RESULTS: We initially demonstrate that the use of native-like distance maps is able to reproduce 3D structures almost identical to the targets, giving an average RMSD of 0.5Å. In addition, the corrupted physical maps with an introduced random error of ±6Å are able to reconstruct the targets within an average RMSD of 2Å. After demonstrating the reconstruction potential of distance maps, we develop two classes of predictors using two-dimensional recursive neural networks: an ab initio predictor that relies only on the protein sequence and evolutionary information, and a template-based predictor in which additional structural homology information is provided. We find that the ab initio predictor is able to reproduce distances with an RMSD of 6Å, regardless of the evolutionary content provided. Furthermore, we show that the template-based predictor exploits both sequence and structure information even in cases of dubious homology and outperforms the best template hit with a clear margin of up to 3.7Å. Lastly, we demonstrate the ability of the two predictors to reconstruct the CASP9 targets shorter than 200 residues producing the results similar to the state of the machine learning art approach implemented in the Distill server. CONCLUSIONS: The methodology presented here, if complemented by more complex reconstruction protocols, can represent a possible path to improve machine learning algorithms for 3D protein structure prediction. Moreover, it can be used as an intermediary step in protein structure predictions either on its own or complemented by NMR restraints

Psychometric properties of the serbian version of the operational and organizational police stress questionnaires

The Police Operational Stress Questionnaire (PSQ-Op) and Police Organizational Stress Questionnaire (PSQ-Org) have been used to assess operational and organizational sources of police officers’ occupational stress. Considering that different cultural and socio-economic environments could affect officers’ perception of operational and organizational stress, country specific psychometric properties and cut-off values should be defined. Therefore, this study aimed to investigate the psychometric properties of the Serbian version of the PSQ-Op and PSQ-Org (i.e., translated in Serbian and adjusted to Serbian culture) and to establish cut-off values for low, moderate and high stress. Methods: The PSQ-Op and PSQ-Org were administered to police officers through the Ministry of Interior of the Republic of Serbia. Participants included 1220 police officers (19.0% female) who correctly completed both questionnaires. Cronbach’s α was used to determine the reliability of instruments. Cut-off values for low, moderate and high stress were defined based on the mean and standard deviation of the sample and using percentile analysis. Prevalence of low, moderate and high stress was calculated according to already established cut-off values as well as those calculated based on the study sample. Results: Both instruments showed high reliability (Cronbach’s α = 0.963 [95% Confidence Interval = 0.957–0.964]). Occupational stress levels (low, moderate and high) were distributed differently (p < 0.001) when categorized according to the cut-off values defined in literature and cut-off values based on the study sample. The cut-off values by mean and standard deviation could be used for PSQ-Op, while cut-off values by percentile analysis could be used for PSQ-Org