PyLink: a PyMOL plugin to identify links

Plasma proteome responses in zebrafish following λ-carrageenan-Induced inflammation are mediated by PMN leukocytes and correlate highly with their human counterparts

Regulation of inflammation is a critical process for maintaining physiological homeostasis. The λ-carrageenan (λ-CGN) is a mucopolysaccharide extracted from the cell wall of red algae (Chondrus crispus) capable of inducing acute intestinal inflammation, which is translated into the production of acute phase reactants secreted into the blood circulation. However, the associated mechanisms in vertebrates are not well understood. Here, we investigated the crucial factors behind the inflammatory milieu of λ-CGN-mediated inflammation administered at 0, 1.75, and 3.5% (v/w) by i.p. injection into the peritoneal cavity of adult zebrafish (ZF) (Danio rerio). We found that polymorphonuclear leukocytes (neutrophils) and lymphocytes infiltrating the ZF peritoneal cavity had short-term persistence. Nevertheless, they generate a strong pattern of inflammation that affects systemically and is enough to produce edema in the cavity. Consistent with these findings, cell infiltration, which causes notable tissue changes, resulted in the overexpression of several acute inflammatory markers at the protein level. Using reversed-phase high-performance liquid chromatography followed by a hybrid linear ion-trap mass spectrometry shotgun proteomic approach, we identified 2938 plasma proteins among the animals injected with PBS and 3.5% λ-CGN. First, the bioinformatic analysis revealed the composition of the plasma proteome. Interestingly, 72 commonly expressed proteins were recorded among the treated and control groups, but, surprisingly, 2830 novel proteins were differentially expressed exclusively in the λ-CGN-induced group. Furthermore, from the commonly expressed proteins, compared to the control group 62 proteins got a significant (p < 0.05) upregulation in the λ-CGN-treated group, while the remaining ten proteins were downregulated. Next, we obtained the major protein-protein interaction networks between hub protein clusters in the blood plasma of the λ-CGN induced group. Moreover, to understand the molecular underpinnings of these effects based on the unveiled protein sets, we performed a bioinformatic structural similarity analysis and generated overlapping 3D reconstructions between ZF and humans during acute inflammation. Biological pathway analysis pointed to the activation and abundance of diverse classical immune and acute phase reactants, several catalytic enzymes, and varied proteins supporting the immune response. Together, this information can be used for testing and finding novel pharmacological targets to treat human intestinal inflammatory diseases.

Identification of Immunogenic Linear B-Cell Epitopes in C. burnetii Outer Membrane Proteins Using Immunoinformatics Approaches Reveals Potential Targets of Persistent Infections

Coxiella burnetii is a global, highly infectious intracellular bacterium, able to infect a wide range of hosts and to persist for months in the environment. It is the etiological agent of Q fever—a zoonosis of global priority. Currently, there are no national surveillance data on C. burnetii’s seroprevalence for any South American country, reinforcing the necessity of developing novel and inexpensive serological tools to monitor the prevalence of infections among humans and animals—especially cattle, goats, and sheep. In this study, we used immunoinformatics and computational biology tools to predict specific linear B-cell epitopes in three C. burnetii outer membrane proteins: OMP-H (CBU_0612), Com-1 (CBU_1910), and OMP-P1 (CBU_0311). Furthermore, predicted epitopes were tested by ELISA, as synthetic peptides, against samples of patients reactive to C. burnetii in indirect immunofluorescence assay, in order to evaluate their natural immunogenicity. In this way, two linear B-cell epitopes were identified in each studied protein (OMP-H_(51–59), OMP-H_(91–106), Com-1_(57–76), Com-1_(191–206), OMP-P1_(197–209), and OMP-P1_(215–227)); all of them were confirmed as naturally immunogenic by the presence of specific antibodies in 77% of studied patients against at least one of the identified epitopes. Remarkably, a higher frequency of endocarditis cases was observed among patients who presented an intense humoral response to OMP-H and Com-1 epitopes. These data confirm that immunoinformatics applied to the identification of specific B-cell epitopes can be an effective strategy to improve and accelerate the development of surveillance tools against neglected diseases.

Topoly: Python package to analyze topology of polymers

The increasing role of topology in (bio)physical properties of matter creates a need for an efficient method of detecting the topology of a (bio)polymer. However, the existing tools allow one to classify only the simplest knots and cannot be used in automated sample analysis. To answer this need, we created the Topoly Python package. This package enables the distinguishing of knots, slipknots, links and spatial graphs through the calculation of different topological polynomial invariants. It also enables one to create the minimal spanning surface on a given loop, e.g. to detect a lasso motif or to generate random closed polymers. It is capable of reading various file formats, including PDB. The extensive documentation along with test cases and the simplicity of the Python programming language make it a very simple to use yet powerful tool, suitable even for inexperienced users. Topoly can be obtained from https://topoly.cent.uw.edu.pl.

PyVibMS: a PyMOL plugin for visualizing vibrations in molecules and solids

Visualizing vibrational motions calculated with different ab initio packages requires dedicated post-processing tools. Here, we present a PyMOL plugin called PyVibMS for visualizing the vibrational motions for both molecular and solid systems calculated by mainstream quantum chemical computer programs including Gaussian, Q-Chem, VASP, and CRYSTAL. Benefiting from the continuing development of the PyMOL platform, PyVibMS provides powerful functionalities and user-friendly interface. PyVibMS was written in Python and its open-source nature makes it flexible and sustainable. As an example, the motions of the Konkoli-Cremer local vibrational modes are shown in this work for the first time. PyVibMS is freely available at https://github.com/smutao/PyVibMS . Graphical abstract In this work, a PyMOL plugin named PyVibMS is developed to visualize molecular and lattice vibrations.

GLN: a method to reveal unique properties of lasso type topology in proteins

Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a matrix diagram-for a pair of a loop and a tail-to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a matrix diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.

On folding of entangled proteins: knots, lassos, links and θ-curves

Around 6% of protein structures deposited in the PDB are entangled, forming knots, slipknots, lassos, links, and θ-curves. In each of these cases, the protein backbone weaves through itself in a complex way, and at some point passes through a closed loop, formed by other regions of the protein structure. Such a passing can be interpreted as crossing a topological barrier. How proteins overcome such barriers, and therefore different degrees of frustration, challenged scientists and has shed new light on the field of protein folding. In this review, we summarize the current knowledge about the free energy landscape of proteins with non-trivial topology. We describe identified mechanisms which lead proteins to self-tying. We discuss the influence of excluded volume, such as crowding and chaperones, on tying, based on available data. We briefly discuss the diversity of topological complexity of proteins and their evolution. We also list available tools to investigate non-trivial topology. Finally, we formulate intriguing and challenging questions at the boundary of biophysics, bioinformatics, biology, and mathematics, which arise from the discovery of entangled proteins.