PconsFold: improved contact predictions improve protein models

Motivation: Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to predict the structure of many protein families. However, since the first studies contact prediction methods have improved. Here, we ask how much the final models are improved if improved contact predictions are used. Results: In a small benchmark of 15 proteins, we show that the TM-scores of top-ranked models are improved by on average 33% using PconsFold compared with the original version of EVfold. In a larger benchmark, we find that the quality is improved with 15–30% when using PconsC in comparison with earlier contact prediction methods. Further, using Rosetta instead of CNS does not significantly improve global model accuracy, but the chemistry of models generated with Rosetta is improved. Availability: PconsFold is a fully automated pipeline for ab initio protein structure prediction based on evolutionary information. PconsFold is based on PconsC contact prediction and uses the Rosetta folding protocol. Due to its modularity, the contact prediction tool can be easily exchanged. The source code of PconsFold is available on GitHub at https://www.github.com/ElofssonLab/pcons-fold under the MIT license. PconsC is available from http://c.pcons.net/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Type III secretion inhibitors for the management of bacterial plant diseases

The identification of chemical compounds that prevent and combat bacterial diseases is fundamental for crop production. Bacterial virulence inhibitors are a promising alternative to classical control treatments, because they have a low environmental impact and are less likely to generate bacterial resistance. The major virulence determinant of most animal and plant bacterial pathogens is the type III secretion system (T3SS). In this work, we screened nine plant extracts and 12 isolated compounds including molecules effective against human pathogens for their capacity to inhibit the T3SS of plant pathogens and for their applicability as virulence inhibitors for crop protection. The screen was performed using a luminescent reporter system developed in the model pathogenic bacterium Ralstonia solanacearum. Five synthetic molecules, one natural product and two plant extracts were found to down‐regulate T3SS transcription, most through the inhibition of the regulator hrpB. In addition, for three of the molecules, corresponding to salicylidene acylhydrazide derivatives, the inhibitory effect caused a dramatic decrease in the secretion capacity, which was translated into impaired plant responses. These candidate virulence inhibitors were then tested for their ability to protect plants. We demonstrated that salicylidene acylhydrazides can limit R. solanacearum multiplication in planta and protect tomato plants from bacterial speck caused by Pseudomonas syringae pv. tomato. Our work validates the efficiency of transcription reporters to discover compounds or natural product extracts that can be potentially applied to prevent bacterial plant diseases

Ranking models of transmembrane β-barrel proteins using Z-coordinate predictions

Motivation: Transmembrane β-barrels exist in the outer membrane of gram-negative bacteria as well as in chloroplast and mitochondria. They are often involved in transport processes and are promising antimicrobial drug targets. Structures of only a few β-barrel protein families are known. Therefore, a method that could automatically generate such models would be valuable. The symmetrical arrangement of the barrels suggests that an approach based on idealized geometries may be successful

Genomic evolution and complexity of the Anaphase-promoting Complex (APC) in land plants

<p>Abstract</p> <p>Background</p> <p>The orderly progression through mitosis is regulated by the Anaphase-Promoting Complex (APC), a large multiprotein E₃ubiquitin ligase that targets key cell-cycle regulators for destruction by the 26 S proteasome. The APC is composed of at least 11 subunits and associates with additional regulatory activators during mitosis and interphase cycles. Despite extensive research on APC and activator functions in the cell cycle, only a few components have been functionally characterized in plants.</p> <p>Results</p> <p>Here, we describe an in-depth search for APC subunits and activator genes in the Arabidopsis, rice and poplar genomes. Also, searches in other genomes that are not completely sequenced were performed. Phylogenetic analyses indicate that some APC subunits and activator genes have experienced gene duplication events in plants, in contrast to animals. Expression patterns of paralog subunits and activators in rice could indicate that this duplication, rather than complete redundancy, could reflect initial specialization steps. The absence of subunit APC7 from the genome of some green algae species and as well as from early metazoan lineages, could mean that APC7 is not required for APC function in unicellular organisms and it may be a result of duplication of another tetratricopeptide (TPR) subunit. Analyses of TPR evolution suggest that duplications of subunits started from the central domains.</p> <p>Conclusions</p> <p>The increased complexity of the APC gene structure, tied to the diversification of expression paths, suggests that land plants developed sophisticated mechanisms of APC regulation to cope with the sedentary life style and its associated environmental exposures.</p

Лабораторна установка для дослідження ступеня очищення і пошкодження коренебульбоплодів

Патент України на корисну модель № 79083, МПК B65G 33/00, 2012.Лабораторна установка для дослідження ступеня очищення і пошкодження коренебульбоплодів, що містить раму, на якій з можливістю кутового та вертикального зміщення на підрамах встановлені секція пруткового транспортера-очисника та секція бітерних очисних валів, завантажувальний бункер, причому під секцією пруткового транспортера-очисника та секцією бітерних очисних валів на рамі розташовані поперечні лотки для відбору від сепарованих домішок, яка відрізняється тим, що кутовий зазор між центральною віссю барабана пруткового транспортера-очисника в зоні вивантаження коренебульбоплодів та центральною віссю першого бітерного очисного вала може змінюватись за рахунок використання різних отворів, які виконані на стійці та підрамі, а осьовий зазор – за рахунок кронштейна з отворами, причому над прутковим транспортером-очисником та секцією бітерних очисних валів встановлені вертикальні та похилі еластичні екрани, а для відбору очищених коренебульбоплодів в зоні вивантаження бітерних очисних валів розташована еластична ємність з можливістю вертикального переміщення та фіксації її задньої частини на вертикальному кронштейні

Peripheral Sensory Neuropathy Associates With Micro- or Macroangiopathy: Results from a population-based study of type 2 diabetic patients in Sweden

OBJECTIVE—To assess associations between peripheral sensory neuropathy (PSN) and other diabetes-related complications

Predicting protein-protein binding sites in membrane proteins

<p>Abstract</p> <p>Background</p> <p>Many integral membrane proteins, like their non-membrane counterparts, form either transient or permanent multi-subunit complexes in order to carry out their biochemical function. Computational methods that provide structural details of these interactions are needed since, despite their importance, relatively few structures of membrane protein complexes are available.</p> <p>Results</p> <p>We present a method for predicting which residues are in protein-protein binding sites within the transmembrane regions of membrane proteins. The method uses a Random Forest classifier trained on residue type distributions and evolutionary conservation for individual surface residues, followed by spatial averaging of the residue scores. The prediction accuracy achieved for membrane proteins is comparable to that for non-membrane proteins. Also, like previous results for non-membrane proteins, the accuracy is significantly higher for residues distant from the binding site boundary. Furthermore, a predictor trained on non-membrane proteins was found to yield poor accuracy on membrane proteins, as expected from the different distribution of surface residue types between the two classes of proteins. Thus, although the same procedure can be used to predict binding sites in membrane and non-membrane proteins, separate predictors trained on each class of proteins are required. Finally, the contribution of each residue property to the overall prediction accuracy is analyzed and prediction examples are discussed.</p> <p>Conclusion</p> <p>Given a membrane protein structure and a multiple alignment of related sequences, the presented method gives a prioritized list of which surface residues participate in intramembrane protein-protein interactions. The method has potential applications in guiding the experimental verification of membrane protein interactions, structure-based drug discovery, and also in constraining the search space for computational methods, such as protein docking or threading, that predict membrane protein complex structures.</p

Study of polytopic membrane protein topological organization as a function of membrane lipid composition.

A protocol is described using lipid mutants and thiol-specific chemical reagents to study lipid-dependent and host-specific membrane protein topogenesis by the substituted-cysteine accessibility method as applied to transmembrane domains (SCAM). SCAM is adapted to follow changes in membrane protein topology as a function of changes in membrane lipid composition. The strategy described can be adapted to any membrane system