HotSpot Wizard 3.0: Automated design of site-specific mutations and smart libraries

HotSpot Wizard is an interactive web server for prediction of amino acid residues suitable for mutagenesis and construction of libraries of mutants with modified activity, specificity or stability [1]. Positions suitable for mutagenesis are evaluated based on protein structure using a combination of structural, functional and evolutionary information obtained from 7 internet databases and 22 computational tools [2]. The application was designed with an emphasis on an easy usage without the necessity of advanced knowledge of the studied system. This is the reason for the setting of all default values of the parameters based on the extensive analysis to appropriately represent a wide spectrum of input data. Four different strategies are automatically evaluated for every protein structure. Analysis of the results is being run directly in the web interface, which provides user-friendly visualization tool. Moreover, HotSpot Wizard provides a module for the design of a construction of protein mutant library with the support of an automatic detection of suitable target amino acids and corresponding degenerative codons. There are several new features for the version 3.0 to be released early 2018. Stability of single-point or multiple-point mutant can be predicted using the Rosetta scoring function [3]. Users can newly enter also protein sequence as the input for calculation. Then searching for structures or models in the databases of experimental structures or depositories of homology models is performed. The users can also run homology modelling using the programs Modeller [4] and I-Tasser [5]. The current version of the application is freely available for academic users at http://loschmidt.chemi.muni.cz/hotspotwizard. 1. Pavelka, A., Chovancova, E., Damborsky, J., 2009: HotSpot Wizard: a Web Server for Identification of Hot Spots in Protein Engineering. Nucleic Acids Research 37: W376-W383. 2. Bendl, J., Stourac, J., Sebestova, E., Vavra, O., Musil, M., Brezovsky, J., Damborsky, J., 2016: HotSpot Wizard 2: Automated Design of Site-Specific Mutations and Smart Libraries in Protein Engineering. Nucleic Acids Research 44: W479-W487. 3. Kellogg, E.H., Leaver-Fay, A., Baker, D., 2011: Role of Conformational Sampling in Computing Mutation-induced Changes in Protein Structure and Stability. Proteins 79: 830-838. 4. Sali, A., Blundell, T.L., 1993: Comparative Protein Modelling by Satisfaction of Spatial Restraints. Journal of Molecular Biology 234: 779-815. 5. Zhang, Y., 2008: I-TASSER Server for Protein 3D Structure Prediction. BMC Bioinformatics 9: 40

SoluProt: prediction of soluble protein expression in Escherichia coli

Motivation: Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Escherichia coli using only sequence information could reduce the cost of experimental studies by enabling prioritization of highly soluble proteins. Results: A new tool for sequence-based prediction of soluble protein expression in E.coli, SoluProt, was created using the gradient boosting machine technique with the TargetTrack database as a training set. When evaluated against a balanced independent test set derived from the NESG database, SoluProt's accuracy of 58.5% and AUC of 0.62 exceeded those of a suite of alternative solubility prediction tools. There is also evidence that it could significantly increase the success rate of experimental protein studies

EnzymeMiner: automated mining of soluble enzymes with diverse structures, catalytic properties and stabilities

Millions of protein sequences are being discovered at an incredible pace, representing an inexhaustible source of biocatalysts. Despite genomic databases growing exponentially, classical biochemical characterization techniques are time-demanding, cost-ineffective and low-throughput. Therefore, computational methods are being developed to explore the unmapped sequence space efficiently. Selection of putative enzymes for biochemical characterization based on rational and robust analysis of all available sequences remains an unsolved problem. To address this challenge, we have developed EnzymeMiner-a web server for automated screening and annotation of diverse family members that enables selection of hits for wet-lab experiments. EnzymeMiner prioritizes sequences that are more likely to preserve the catalytic activity and are heterologously expressible in a soluble form in Escherichia coli. The solubility prediction employs the in-house SoluProt predictor developed using machine learning. EnzymeMiner reduces the time devoted to data gathering, multi-step analysis, sequence prioritization and selection from days to hours. The successful use case for the haloalkane dehalogenase family is described in a comprehensive tutorial available on the EnzymeMiner web page

EnzymeMiner: Exploration of sequence space of enzymes

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FireProt: Web server for automated design of thermostable proteins

Stable proteins are used in numerous biomedical and biotechnological applications. Unfortunately, naturally occurring proteins cannot usually withstand the harsh industrial environment, since they are mostly evolved to function at mild conditions. Therefore, there is a continuous interest in increasing protein stability to enhance their industrial potential. A number of in silico tools for the prediction of the effect of mutations on protein stability have been developed recently. However, only single-point mutations with a small effect on protein stability are typically predicted with the existing tools and have to be followed by laborious protein expression, purification, and characterization. A much higher degree of stabilization can be achieved by the construction of the multiple-point mutants. Here, we present the FireProt method [1] and the web server [2] for the automated design of multiple-point mutant proteins that combines structural and evolutionary information in its calculation core. FireProt utilizes sixteen bioinformatics tools, including several force field calculations. Highly reliable designs of the thermostable proteins are constructed by two distinct protein engineering strategies, based on the energy and evolution approaches and the multiple-point mutants are checked for the potentially antagonistic effects in the designed protein structure. Furthermore, time demands of the FireProt method are radically decreased by the utilization of the smart knowledge-based filters, protocol optimization, and effective parallelization. The server is complemented with an interactive, easy-to-use interface that allows users to directly analyze and optionally modify designed thermostable proteins. The server is freely available at http://loschmidt.chemi.muni.cz/fireprot. 1. Bednar, D., Beerens, K., Sebestova, E., Bendl, J., Khare, S., Chaloupkova, R., Prokop, Z., Brezovsky, J., Baker, D., Damborsky, J., 2015: FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants. PLOS Computational Biology 11: e1004556. 2. Musil, M., Stourac, J., Bendl, J., Brezovsky, J., Prokop, Z., Zendulka, J., Martinek, T., Bednar, D., Damborsky, J., 2017, FireProt: Web Server for Automated Design of Thermostable Proteins, Nucleic Acids Research, in press, doi: 10.1093/nar/gkx285

Hydration of biologically relevant tetramethylammonium cation by neutron scattering and molecular dynamics

Neutron scattering and molecular dynamics studies were performed on a concentrated aqueous tetramethylammonium (TMA) chloride solution to gain insight into the hydration shell structure of TMA, which is relevant for understanding its behavior in biological contexts of, e.g., properties of phospholipid membrane headgroups or interactions between DNA and histones. Specifically, neutron diffraction with isotopic substitution experiments were performed on TMA and water hydrogens to extract the specific correlation between hydrogens in TMA ($\mathrm{H_{TMA}}$) and hydrogens in water ($\mathrm{H_{W}}$). Classical molecular dynamics simulations were performed to help interpret the experimental neutron scattering data. Comparison of the hydration structure and simulated neutron signals obtained with various force field flavors (e.g. overall charge, charge distribution, polarity of the CH bonds and geometry) allowed us to gain insight into how sensitive the TMA hydration structure is to such changes and how much the neutron signal can capture them. We show that certain aspects of the hydration, such as the correlation of the hydrogen on TMA to hydrogen on water, showed little dependence on the force field. In contrast, other correlations, such as the ion-ion interactions, showed more marked changes. Strikingly, the neutron scattering signal cannot discriminate between different hydration patterns. Finally, ab initio molecular dynamics was used to examine the three-dimensional hydration structure and thus to benchmark force field simulations. Overall, while neutron scattering has been previously successfully used to improve force fields, in the particular case of TMA we show that it has only limited value to fully determine the hydration structure, with other techniques such as ab initio MD being of a significant help

Prediction model of alcohol intoxication from facial temperature dynamics based on K-means clustering driven by evolutionary computing

Alcohol intoxication is a significant phenomenon, affecting many social areas, including work procedures or car driving. Alcohol causes certain side effects including changing the facial thermal distribution, which may enable the contactless identification and classification of alcohol-intoxicated people. We adopted a multiregional segmentation procedure to identify and classify symmetrical facial features, which reliably reflects the facial-temperature variations while subjects are drinking alcohol. Such a model can objectively track alcohol intoxication in the form of a facial temperature map. In our paper, we propose the segmentation model based on the clustering algorithm, which is driven by the modified version of the Artificial Bee Colony (ABC) evolutionary optimization with the goal of facial temperature features extraction from the IR (infrared radiation) images. This model allows for a definition of symmetric clusters, identifying facial temperature structures corresponding with intoxication. The ABC algorithm serves as an optimization process for an optimal cluster's distribution to the clustering method the best approximate individual areas linked with gradual alcohol intoxication. In our analysis, we analyzed a set of twenty volunteers, who had IR images taken to reflect the process of alcohol intoxication. The proposed method was represented by multiregional segmentation, allowing for classification of the individual spatial temperature areas into segmentation classes. The proposed method, besides single IR image modelling, allows for dynamical tracking of the alcohol-temperature features within a process of intoxication, from the sober state up to the maximum observed intoxication level.Web of Science118art. no. 99

Calcium ions in aqueous solutions: Accurate force field description aided by ab initio molecular dynamics and neutron scattering

International audienc

RBP-Tar – a searchable database for experimental RBP binding sites

Background: RNA-binding proteins (RBPs) play a critical role in regulating gene expression by binding to specific sites on RNA molecules. Identifying these binding sites is crucial for understanding the many functions of RBPs in cellular function, development and disease. Current experimental methods for identifying RBP binding sites, such as ultra-violet (UV) crosslinking and immunoprecipitation (CLIP), and especially the enhanced CLIP (eCLIP) protocol, were developed to identify authentic RBP binding sites experimentally. Methods: To make this data more accessible to the scientific community, we have developed RBP-Tar ( https://ncbr.muni.cz/RBP-Tar), a web server and database that utilises eCLIP data for 167 RBPs mapped on the human genome. The web server allows researchers to easily search and retrieve binding site information by genomic location and RBP name. Use case: Researchers can produce lists of all known RBP binding sites on a gene of interest, or produce lists of binding sites for one RBP on different genomic loci. Conclusions: Our future goal is to continue to populate the web server with additional experimental datasets from CLIP experiments as they become available and processed, making it an increasingly valuable resource for the scientific community.peer-reviewe

Photoelectron spectra of alkali metal–ammonia microjets: From blue electrolyte to bronze metal

Experimental studies of the electronic structure of excess electrons in liquids—archetypal quantum solutes—have been largely restricted to very dilute electron concentrations. We overcame this limitation by applying soft x-ray photoelectron spectroscopy to characterize excess electrons originating from steadily increasing amounts of alkali metals dissolved in refrigerated liquid ammonia microjets. As concentration rises, a narrow peak at ~2 electron volts, corresponding to vertical photodetachment of localized solvated electrons and dielectrons, transforms continuously into a band with a sharp Fermi edge accompanied by a plasmon peak, characteristic of delocalized metallic electrons. Through our experimental approach combined with ab initio calculations of localized electrons and dielectrons, we obtain a clear picture of the energetics and density of states of the ammoniated electrons over the gradual transition from dilute blue electrolytes to concentrated bronze metallic solutions