MutationExplorer: a webserver for mutation of proteins and 3D visualization of energetic impacts.

The possible effects of mutations on stability and function of a protein can only be understood in the context of protein 3D structure. The MutationExplorer webserver maps sequence changes onto protein structures and allows users to study variation by inputting sequence changes. As the user enters variants, the 3D model evolves, and estimated changes in energy are highlighted. In addition to a basic per-residue input format, MutationExplorer can also upload an entire replacement sequence. Previously the purview of desktop applications, such an upload can back-mutate PDB structures to wildtype sequence in a single step. Another supported variation source is human single nucelotide polymorphisms (SNPs), genomic coordinates input in VCF format. Structures are flexibly colorable, not only by energetic differences, but also by hydrophobicity, sequence conservation, or other biochemical profiling. Coloring by interface score reveals mutation impacts on binding surfaces. MutationExplorer strives for efficiency in user experience. For example, we have prepared 45 000 PDB depositions for instant retrieval and initial display. All modeling steps are performed by Rosetta. Visualizations leverage MDsrv/Mol*. MutationExplorer is available at: http://proteinformatics.org/mutation_explorer/.

MUTATIONEXPLORER- A WEBSERVER FOR MUTATION OF PROTEINS AND 3D VISUALIZATION OF ENERGETIC IMPACTS.

The possible effects of mutations on stability and function of a protein can only be understood in the context of protein 3D structure. The MutationExplorer webserver maps sequence changes onto protein structures and allows users to study variation by inputting sequence changes. As the user enters variants, the 3D model evolves, and estimated changes in energy are highlighted. In addition to a basic per-residue input format, MutationExplorer can also upload an entire replacement sequence. Previously the purview of desktop applications, such an upload can back-mutate PDB structures to wildtype sequence in a single step. Another supported variation source is human single nucelotide polymorphisms (SNPs), genomic coordinates input in VCF format.

SmoothT-a server constructing low-energy pathways from conformational ensembles for interactive visualization and enhanced sampling.

MOTIVATION: The SmoothT software and webservice offers the construction of pathways from an ensemble of conformations. The user provides an archive of molecule conformations in Protein Databank (PDB) format, from which a starting and a final conformation need to be selected. The individual PDB files need to contain an energy value or score, estimating the quality of the respective confirmation. Additionally, the user has to provide a root-mean-square deviation (RMSD) cut-off, below which conformations are considered neighboring. From this, SmoothT constructs a graph that connects similar conformations. RESULTS: SmoothT returns the energetically most favorable pathway within in this graph. This pathway is directly displayed as interactive animation using the NGL viewer. Simultaneously, the energy along the pathway is plotted, highlighting the conformation that is currently displayed in the 3D window. AVAILABILITY AND IMPLEMENTATION: SmoothT is available as webservice at: http://proteinformatics.org/smoothT. Examples, a tutorial, and FAQs can be found there. Ensembles up to 2 GB (compressed) can be uploaded. Results will be stored for 5 days. The server is completely free and requires no registration. The C++ source code is available at: https://github.com/starbeachlab/smoothT.

Predicting 2H NMR acyl chain order parameters with graph neural networks.

2H NMR order parameters of the acyl chain of phospholipid membranes are an important indicator of the effects of molecules on membrane order, mobility, and permeability. So far, the evaluation procedures are case-by-case studies for every type of small molecule with certain types of membranes. Rapid screening of the effects of a variety of drugs would be invaluable if it were possible. Unfortunately, to date there is no practical or theoretical approach to this as there is with other experimental parameters, e.g., chemical shifts from 1H and 13C NMR. We aim to remedy this situation by introducing a model based on graph neural networks (GNN) capable of predicting 2H NMR order parameters of lipid membranes in the presence of different molecules based on learned molecular features. Rapid prediction of these parameters would allow fast assessment of potential effects of drugs on lipid membranes, which is important for further drug development and provides insight into potential side effects. We conclude that the graph network-based model presented in this work can predict order parameters with sufficient accuracy, and we are confident that the concepts presented are a suitable basis for future research. We also make our model available to the public as a web application at https://proteinformatics.uni-leipzig.de/g2r/.

AlignMe: an update of the web server for alignment of membrane protein sequences.

The AlignMe web server is dedicated to accurately aligning sequences of membrane proteins, a particularly challenging task due to the strong evolutionary divergence and the low compositional complexity of hydrophobic membrane-spanning proteins. AlignMe can create pairwise alignments of either two primary amino acid sequences or two hydropathy profiles. The web server for AlignMe has been continuously available for >10 years, supporting 1000s of users per year. Recent improvements include anchoring, multiple submissions, and structure visualization. Anchoring is the ability to constrain a position in an alignment, which allows expert information about related residues in proteins to be incorporated into an alignment without manual modification. The original web interface to the server limited the user to one alignment per submission, hindering larger scale studies. Now, batches of alignments can be initiated with a single submission. Finally, to provide structural context for the relationship between proteins, sequence similarity can now be mapped onto one or more structures (or structural models) of the proteins being aligned, by links to MutationExplorer, a web-based visualization tool. Together with a refreshed user interface, these features further enhance an important resource in the membrane protein community. The AlignMe web server is freely available at https://www.bioinfo.mpg.de/AlignMe/.

ProteinPrompt: a webserver for predicting protein-protein interactions.

Motivation: Protein-protein interactions (PPIs) play an essential role in a great variety of cellular processes and are therefore of significant interest for the design of new therapeutic compounds as well as the identification of side effects due to unexpected binding. Here, we present ProteinPrompt, a webserver that uses machine learning algorithms to calculate specific, currently unknown PPIs. Our tool is designed to quickly and reliably predict contact propensities based on an input sequence in order to scan large sequence libraries for potential binding partners, with the goal to accelerate and assure the quality of the laborious process of drug target identification. Results: We collected and thoroughly filtered a comprehensive database of known binders from several sources, which is available as download. ProteinPrompt provides two complementary search methods of similar accuracy for comparison and consensus building. The default method is a random forest (RF) algorithm that uses the auto-correlations of seven amino acid scales. Alternatively, a graph neural network (GNN) implementation can be selected. Additionally, a consensus prediction is available. For each query sequence, potential binding partners are identified from a protein sequence database. The proteom of several organisms are available and can be searched for binders. To evaluate the predictive power of the algorithms, we prepared a test dataset that was rigorously filtered for redundancy. No sequence pairs similar to the ones used for training were included in this dataset. With this challenging dataset, the RF method achieved an accuracy rate of 0.88 and an area under the curve of 0.95. The GNN achieved an accuracy rate of 0.86 using the same dataset. Since the underlying learning approaches are unrelated, comparing the results of RF and GNNs reduces the likelihood of errors. The consensus reached an accuracy of 0.89. Availability and implementation: ProteinPrompt is available online at: http://proteinformatics.org/ProteinPrompt, where training and test data used to optimize the methods are also available. The server makes it possible to scan the human proteome for potential binding partners of an input sequence within minutes. For local offline usage, we furthermore created a ProteinPrompt Docker image which allows for batch submission: https://gitlab.hzdr.de/proteinprompt/ProteinPrompt. In conclusion, we offer a fast, accurate, easy-to-use online service for predicting binding partners from an input sequence.

Voronoia 4-ever.

We present an updated version of the Voronoia service that enables fully automated analysis of the atomic packing density of macromolecules. Voronoia combines previous efforts to analyse 3D protein and RNA structures into a single service, combined with state-of-the-art online visualization. Voronoia uses the Voronoi cell method to calculate the free space between neighbouring atoms to estimate van der Waals interactions. Compared to other methods that derive van der Waals interactions by calculating solvent-free surfaces, it explicitly considers volume or packing defects. Large internal voids refer either to water molecules or ions unresolved by X-ray crystallography or cryo-EM, cryptic ligand binding pockets, or parts of a structural model that require further refinement. Voronoia is, therefore mainly used for functional analyses of 3D structures and quality assessments of structural models. Voronoia 4-ever updates the database of precomputed packing densities of PDB entries, allows uploading multiple structures, adds new filter options and facilitates direct access to the results through intuitive display with the NGL viewer. Voronoia is available at: htttp://proteinformatics.org/voronoia.

Mutations in global regulators lead to metabolic selection during adaptation to complex environments.

Adaptation to ecologically complex environments can provide insights into the evolutionary dynamics and functional constraints encountered by organisms during natural selection. Adaptation to a new environment with abundant and varied resources can be difficult to achieve by small incremental changes if many mutations are required to achieve even modest gains in fitness. Since changing complex environments are quite common in nature, we investigated how such an epistatic bottleneck can be avoided to allow rapid adaptation. We show that adaptive mutations arise repeatedly in independently evolved populations in the context of greatly increased genetic and phenotypic diversity. We go on to show that weak selection requiring substantial metabolic reprogramming can be readily achieved by mutations in the global response regulator arcA and the stress response regulator rpoS. We identified 46 unique single-nucleotide variants of arcA and 18 mutations in rpoS, nine of which resulted in stop codons or large deletions, suggesting that subtle modulations of ArcA function and knockouts of rpoS are largely responsible for the metabolic shifts leading to adaptation. These mutations allow a higher order metabolic selection that eliminates epistatic bottlenecks, which could occur when many changes would be required. Proteomic and carbohydrate analysis of adapting E. coli populations revealed an up-regulation of enzymes associated with the TCA cycle and amino acid metabolism, and an increase in the secretion of putrescine. The overall effect of adaptation across populations is to redirect and efficiently utilize uptake and catabolism of abundant amino acids. Concomitantly, there is a pronounced spread of more ecologically limited strains that results from specialization through metabolic erosion. Remarkably, the global regulators arcA and rpoS can provide a "one-step" mechanism of adaptation to a novel environment, which highlights the importance of global resource management as a powerful strategy to adaptation.

Fast algorithms and heuristics for phylogenomics under ILS and hybridization.

BACKGROUND: Phylogenomic analyses involving whole-genome or multi-locus data often entail dealing with incongruent gene trees. In this paper, we consider two causes of such incongruence, namely, incomplete lineage sorting (ILS) and hybridization, and consider both parsimony and probabilistic criteria for dealing with them. RESULTS: Under the assumption of ILS, computing the probability of a gene tree given a species tree is a very hard problem. We present a heuristic for speeding up the computation, and demonstrate how it scales up computations to data sizes that are not feasible to analyze using current techniques, while achieving very good accuracy. Further, under the assumption of both ILS and hybridization, computing the probability of a gene tree and parsimoniously reconciling it with a phylogenetic network are both very hard problems. We present two exact algorithms for these two problems that speed up existing techniques significantly and enable analyses of much larger data sets than is currently feasible. CONCLUSION: Our heuristics and algorithms enable phylogenomic analyses of larger (in terms of numbers of taxa) data sets than is currently feasible. Further, our methods account for ILS and hybridization, thus allowing analyses of reticulate evolutionary histories.

Functional properties of pea (Pisum sativum, L.) protein isolates modified with chymosin.

In this paper, the effects of limited hydrolysis on functional properties, as well as on protein composition of laboratory-prepared pea protein isolates, were investigated. Pea protein isolates were hydrolyzed for either 15, 30 and 60 min with recombined chymosin (Maxiren). The effect of enzymatic action on solubility, emulsifying and foaming properties at different pH values (3.0; 5.0; 7.0 and 8.0) was monitored. Chymosin can be a very useful agent for improvement of functional properties of isolates. Action of this enzyme caused a low degree of hydrolysis (3.9-4.7%), but improved significantly functional properties of pea protein isolates (PPI), especially at lower pH values (3.0-5.0). At these pH values all hydrolysates had better solubility, emulsifying activity and foaming stability, while longer-treated samples (60 min) formed more stable emulsions at higher pH values (7.0, 8.0) than initial isolates. Also, regardless of pH value, all hydrolysates showed improved foaming ability. A moderate positive correlation between solubility and emulsifying activity index (EAI) (0.74) and negative correlation between solubility and foam stability (-0.60) as well as between foam stability (FS) and EAI (-0.77) were observed. Detected enhancement in functional properties was a result of partial hydrolysis of insoluble protein complexes.

Profile and functional properties of seed proteins from six pea (Pisum sativum) genotypes.

Extractability, extractable protein compositions, technological-functional properties of pea (Pisum sativum) proteins from six genotypes grown in Serbia were investigated. Also, the relationship between these characteristics was presented. Investigated genotypes showed significant differences in storage protein content, composition and extractability. The ratio of vicilin:legumin concentrations, as well as the ratio of vicilin + convicilin: Legumin concentrations were positively correlated with extractability. Our data suggest that the higher level of vicilin and/or a lower level of legumin have a positive influence on protein extractability. The emulsion activity index (EAI) was strongly and positively correlated with the solubility, while no significant correlation was found between emulsion stability (ESI) and solubility, nor between foaming properties and solubility. No association was evident between ESI and EAI. A moderate positive correlation between emulsion stability and foam capacity was observed. Proteins from the investigated genotypes expressed significantly different emulsifying properties and foam capacity at different pH values, whereas low foam stability was detected. It appears that genotype has considerable influence on content, composition and technological-functional properties of pea bean proteins. This fact can be very useful for food scientists in efforts to improve the quality of peas and pea protein products.

Identification of Metals (Heavy and Radioactive) in Drinking Water by an Indirect Analysis Method Based on Scale Tests.

The analysis of water quality, regarding the content of metals, especially heavy and radioactive ones, has been carried out in an indirect way, by testing scale formed in a hot-water heater, using water from the water-supply network of the city of Belgrade - the district of New Belgrade. The determination of the composition and the structure of the scale has resulted in its complete identification, and its crystallochemical formula has been defined. It has unequivocally been established that the obtained results are within the tolerance boundary with the results acquired by a conventional analysis of water, when it is a matter of very low concentrations. The presence of radioactive elements of uranium and strontium in a scale sample has been found and the way of their penetrating its composition and structure has been explained. Applying the fractional extraction method, uranium has been established to be of an anthropogenic origin.