The Peptide Antibiotic Corramycin Adopts a β-Hairpin-like Structure and Is Inactivated by the Kinase ComG

The rapid development of antibiotic resistance, especially among difficult-to-treat Gram-negative bacteria, is recognized as a serious and urgent threat to public health. The detection and characterization of novel resistance mechanisms are essential to better predict the spread and evolution of antibiotic resistance. Corramycin is a novel and modified peptidic antibiotic with activity against several Gram-negative pathogens. We demonstrate that the kinase ComG, part of the corramycin biosynthetic gene cluster, phosphorylates and thereby inactivates corramycin, leading to the resistance of the host. Remarkably, we found that the closest structural homologues of ComG are aminoglycoside phosphotransferases; however, ComG shows no activity toward this class of antibiotics. The crystal structure of ComG in complex with corramycin reveals that corramycin adopts a β-hairpin-like structure and allowed us to define the changes leading to a switch in substrate from sugar to peptide. Bioinformatic analyses suggest a limited occurrence of ComG-like proteins, which along with the absence of cross-resistance to clinically used drugs positions corramycin as an attractive antibiotic for further development.

Elucidation of unusual biosynthesis and DnaN-targeting mode of action of potent anti-tuberculosis antibiotics Mycoplanecins

DNA polymerase III sliding clamp (DnaN) was recently validated as a new anti-tuberculosis target employing griselimycins. Three (2 S,4 R)-4-methylproline moieties of methylgriselimycin play significant roles in target binding and metabolic stability. Here, we identify the mycoplanecin biosynthetic gene cluster by genome mining using bait genes from the 4-methylproline pathway. We isolate and structurally elucidate four mycoplanecins comprising scarce homo-amino acids and 4-alkylprolines. Evaluating mycoplanecin E against Mycobacterium tuberculosis surprisingly reveals an excitingly low minimum inhibition concentration at 83 ng/mL, thus outcompeting griselimycin by approximately 24-fold. We show that mycoplanecins bind DnaN with nanomolar affinity and provide a co-crystal structure of mycoplanecin A-bound DnaN. Additionally, we reconstitute the biosyntheses of the unusual L-homoleucine, L-homonorleucine, and (2 S,4 R)-4-ethylproline building blocks by characterizing in vitro the full set of eight enzymes involved. The biosynthetic study, bioactivity evaluation, and drug target validation of mycoplanecins pave the way for their further development to tackle multidrug-resistant mycobacterial infections.

Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis

BACKGROUND

Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for analyzing large-scale bacterial AMR data. However, ML methods often ignore evolutionary relationships among bacterial strains, which can greatly impact performance of the ML methods, especially if resistance-associated features are attempted to be detected. Genome-wide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature.

RESULTS

In this work, we introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models' performance. We applied our pipeline to publicly available AMR data from PATRIC database for Mycobacterium tuberculosis against six common antibiotics.

CONCLUSIONS

Using our pipeline, we re-discovered known resistance-associated mutations as well as new candidate mutations which can be related to resistance and not previously reported in the literature. We demonstrated that taking into account phylogenetic relationships not only improves the model performance, but also yields more biologically relevant predicted most contributing resistance markers.

PanPA: generation and alignment of panproteome graphs

Motivation

Compared to eukaryotes, prokaryote genomes are more diverse through different mechanisms, including a higher mutation rate and horizontal gene transfer. Therefore, using a linear representative reference can cause a reference bias. Graph-based pangenome methods have been developed to tackle this problem. However, comparisons in DNA space are still challenging due to this high diversity. In contrast, amino acid sequences have higher similarity due to evolutionary constraints, whereby a single amino acid may be encoded by several synonymous codons. Coding regions cover the majority of the genome in prokaryotes. Thus, panproteomes present an attractive alternative leveraging the higher sequence similarity while not losing much of the genome in non-coding regions.

Results

We present PanPA, a method that takes a set of multiple sequence alignments of protein sequences, indexes them, and builds a graph for each multiple sequence alignment. In the querying step, it can align DNA or amino acid sequences back to these graphs. We first showcase that PanPA generates correct alignments on a panproteome from 1350 Escherichia coli. To demonstrate that panproteomes allow comparisons at longer phylogenetic distances, we compare DNA and protein alignments from 1073 Salmonella enterica assemblies against E.coli reference genome, pangenome, and panproteome using BWA, GraphAligner, and PanPA, respectively; with PanPA aligning around 22% more sequences. We also aligned a DNA short-reads whole genome sequencing (WGS) sample from S.enterica against the E.coli reference with BWA and the panproteome with PanPA, where PanPA was able to find alignment for 68% of the reads compared to 5% with BWA.

Availalability and implementation

PanPA is available at https://github.com/fawaz-dabbaghieh/PanPA.

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.

Unusual peptide-binding proteins guide pyrroloindoline alkaloid formation in crocagin biosynthesis

Ribosomally synthesized and post-translationally modified peptide natural products have provided many highly unusual scaffolds. This includes the intriguing alkaloids crocagins, which possess a tetracyclic core structure and whose biosynthesis has remained enigmatic. Here we use in vitro experiments to demonstrate that three proteins, CgnB, CgnC and CgnE, are sufficient for the production of the hallmark tetracyclic crocagin core from the precursor peptide CgnA. The crystal structures of the homologues CgnB and CgnE reveal them to be the founding members of a peptide-binding protein family and allow us to rationalize their distinct functions. We further show that the hydrolase CgnD liberates the crocagin core scaffold, which is subsequently N-methylated by CgnL. These insights allow us to propose a biosynthetic scheme for crocagins. Bioinformatic analyses based on these data led to the discovery of related biosynthetic pathways that may provide access to a structurally diverse family of peptide-derived pyrroloindoline alkaloids.

GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES

Glycans are important polysaccharides on cellular surfaces that are bound to glycoproteins and glycolipids. These are one of the most common post-translational modifications of proteins in eukaryotic cells. They play important roles in protein folding, cell-cell interactions, and other extracellular processes. Changes in glycan structures may influence the course of different diseases, such as infections or cancer. Glycans are commonly represented using the IUPAC-condensed notation. IUPAC-condensed is a textual representation of glycans operating on the same topological level as the Symbol Nomenclature for Glycans (SNFG) that assigns colored, geometrical shapes to the main monomers. These symbols are then connected in tree-like structures, visualizing the glycan structure on a topological level. Yet for a representation on the atomic level, notations such as SMILES should be used. To our knowledge, there is no easy-to-use, general, open-source, and offline tool to convert the IUPAC-condensed notation to SMILES. Here, we present the open-access Python package GlyLES for the generalizable generation of SMILES representations out of IUPAC-condensed representations. GlyLES uses a grammar to read in the monomer tree from the IUPAC-condensed notation. From this tree, the tool can compute the atomic structures of each monomer based on their IUPAC-condensed descriptions. In the last step, it merges all monomers into the atomic structure of a glycan in the SMILES notation. GlyLES is the first package that allows conversion from the IUPAC-condensed notation of glycans to SMILES strings. This may have multiple applications, including straightforward visualization, substructure search, molecular modeling and docking, and a new featurization strategy for machine-learning algorithms. GlyLES is available at https://github.com/kalininalab/GlyLES.

MetaProFi: an ultrafast chunked Bloom filter for storing and querying protein and nucleotide sequence data for accurate identification of functionally relevant genetic variants

MOTIVATION

Bloom filters are a popular data structure that allows rapid searches in large sequence datasets. So far, all tools work with nucleotide sequences; however, protein sequences are conserved over longer evolutionary distances, and only mutations on the protein level may have any functional significance.

RESULTS

We present MetaProFi, a Bloom filter-based tool that, for the first time, offers the functionality to build indexes of amino acid sequences and query them with both amino acid and nucleotide sequences, thus bringing sequence comparison to the biologically relevant protein level. MetaProFi implements additional efficient engineering solutions, such as a shared memory system, chunked data storage and efficient compression. In addition to its conceptual novelty, MetaProFi demonstrates state-of-the-art performance and excellent memory consumption-to-speed ratio when applied to various large datasets.

AVAILABILITY AND IMPLEMENTATION

Source code in Python is available at https://github.com/kalininalab/metaprofi.

Simulated Tempering-Enhanced Umbrella Sampling Improves Convergence of Free Energy Calculations of Drug Membrane Permeation

Molecular dynamics simulations have been widely used to study solute permeation across biological membranes. The potential of mean force (PMF) for solute permeation is typically computed using enhanced sampling techniques such as umbrella sampling (US). For bulky drug-like permeants, however, obtaining converged PMFs remains challenging and often requires long simulation times, resulting in an unacceptable computational cost. Here, we augmented US with simulated tempering (ST), an extended-ensemble technique that consists in varying the temperature of the system along a pre-defined temperature ladder. Simulated tempering-enhanced US (STeUS) was employed to improve the convergence of PMF calculations for the permeation of methanol and three common drug molecules. To obtain sufficient sampling of the umbrella histograms, which were computed only from the ground temperature, we modified the simulation time fraction spent at the ground temperature between 1/K and 50%, where K is the number of ST temperature states. We found that STeUS accelerates convergence, when compared to standard US, and that the benefit of STeUS is system-dependent. For bulky molecules, for which standard US poorly converged, the application of ST was highly successful, leading to a more than fivefold accelerated convergence of the PMFs. For the small methanol solute, for which conventional US converges moderately, the application of ST is only beneficial if 50% of the STeUS simulation time is spent at the ground temperature. This study establishes STeUS as an efficient and simple method for PMF calculations, thereby strongly reducing the computational cost of routine high-throughput studies of drug permeability.

Modeling the Effect of Hydrophobicity on the Passive Permeation of Solutes across a Bacterial Model Membrane

Passive diffusion across biomembranes is an important mechanism of permeation for multiple drugs, including antibiotics. However, this process is frequently neglected while studying drug uptake and, in our view, warrants further investigation. Here, we apply molecular dynamics simulations to investigate the impact of changes in molecular hydrophobicity on the permeability of a series of inhibitors of the quorum sensing of Pseudomonas aeruginosa, previously discovered by us, across a membrane model. Overall, we show that permeation across this membrane model does not correlate with the molecule's hydrophobicity. We demonstrate that using a simple model for permeation, based on the difference between the maximum and minimum of the free energy profile, outperforms the inhomogeneous solubility-diffusion model, yielding a permeability ranking that better agrees with the experimental results, especially for hydrophobic permeants. The calculated differences in permeability could not explain differences in in bacterio activity. Nevertheless, substantial differences in molecular orientation along the permeation pathway correlate with the in bacterio activity, emphasizing the importance of analyzing, at an atomistic level, the permeation pathway of these solutes.

d-StructMAn: Containerized structural annotation on the scale from genetic variants to whole proteomes

Background

Structural annotation of genetic variants in the context of intermolecular interactions and protein stability can shed light onto mechanisms of disease-related phenotypes. Three-dimensional structures of related proteins in complexes with other proteins, nucleic acids, or ligands enrich such functional interpretation, since intermolecular interactions are well conserved in evolution.

Results

We present d-StructMAn, a novel computational method that enables structural annotation of local genetic variants, such as single-nucleotide variants and in-frame indels, and implements it in a highly efficient and user-friendly tool provided as a Docker container. Using d-StructMAn, we annotated several very large sets of human genetic variants, including all variants from ClinVar and all amino acid positions in the human proteome. We were able to provide annotation for more than 46% of positions in the human proteome representing over 60% proteins.

Conclusions

d-StructMAn is the first of its kind and a highly efficient tool for structural annotation of protein-coding genetic variation in the context of observed and potential intermolecular interactions. d-StructMAn is readily applicable to proteome-scale datasets and can be an instrumental building machine-learning tool for predicting genotype-to-phenotype relationships.

SPCS1-Dependent E2-p7 processing determines HCV Assembly efficiency

Recent studies identified signal peptidase complex subunit 1 (SPCS1) as a proviral host factor for Flaviviridae viruses, including HCV. One of the SPCS1’s roles in flavivirus propagation was attributed to its regulation of signal peptidase complex (SPC)-mediated processing of flavivirus polyprotein, especially C-prM junction. However, whether SPCS1 also regulates any SPC-mediated processing sites within HCV polyprotein remains unclear. In this study, we determined that loss of SPCS1 specifically impairs the HCV E2-p7 processing by the SPC. We also determined that efficient separation of E2 and p7, regardless of its dependence on SPC-mediated processing, leads to SPCS1 dispensable for HCV assembly These results suggest that SPCS1 regulates HCV assembly by facilitating the SPC-mediated processing of E2-p7 precursor. Structural modeling suggests that intrinsically delayed processing of the E2-p7 is likely caused by the structural rigidity of p7 N-terminal transmembrane helix-1 (p7/TM1/helix-1), which has mostly maintained membrane-embedded conformations during molecular dynamics (MD) simulations. E2-p7-processing-impairing p7 mutations narrowed the p7/TM1/helix-1 bending angle against the membrane, resulting in closer membrane embedment of the p7/TM1/helix-1 and less access of E2-p7 junction substrate to the catalytic site of the SPC, located well above the membrane in the ER lumen. Based on these results we propose that the key mechanism of action of SPCS1 in HCV assembly is to facilitate the E2-p7 processing by enhancing the E2-p7 junction site presentation to the SPC active site. By providing evidence that SPCS1 facilitates HCV assembly by regulating SPC-mediated cleavage of E2-p7 junction, equivalent to the previously established role of this protein in C-prM junction processing in flavivirus, this study establishes the common role of SPCS1 in Flaviviridae family virus propagation as to exquisitely regulate the SPC-mediated processing of specific, suboptimal target sites.

Vitamin D Intake May Reduce SARS-CoV-2 Infection Morbidity in Health Care Workers

In the last 2 years, observational studies have shown that a low 25-hydroxyvitamin D (25(OH)D) level affected the severity of infection with the novel coronavirus (COVID-19). This study aimed to analyze the potential effect of vitamin D supplementation in reducing SARS-CoV-2 infection morbidity and severity in health care workers. Of 128 health care workers, 91 (consisting of 38 medical doctors (42%), 38 nurses (42%), and 15 medical attendants (16%)) were randomized into two groups receiving vitamin D supplementation. Participants of group I (n = 45) received water-soluble cholecalciferol at a dose of 50,000 IU/week for 2 consecutive weeks, followed by 5000 IU/day for the rest of the study. Participants of group II (n = 46) received water-soluble cholecalciferol at a dose of 2000 IU/day. For both groups, treatment lasted 3 months. Baseline serum 25(OH)D level in health care workers varied from 3.0 to 65.1 ng/mL (median, 17.7 (interquartile range, 12.2; 24.7) ng/mL). Vitamin D deficiency, insufficiency, and normal vitamin D status were diagnosed in 60%, 30%, and 10%, respectively. Only 78 subjects completed the study. Vitamin D supplementation was associated with an increase in serum 25(OH)D level, but only intake of 5000 IU/day was accompanied by normalization of serum 25(OH)D level, which occurred in 53% of cases. Neither vitamin D intake nor vitamin D deficiency/insufficiency were associated with a decrease in SARS-CoV-2 morbidity (odds ratio = 2.27; 95% confidence interval, 0.72 to 7.12). However, subjects receiving high-dose vitamin D had only asymptomatic SARS-CoV-2 in 10 (26%) cases; at the same time, participants who received 2000 IU/day showed twice as many SARS-CoV-2 cases, with mild clinical features in half of them.

Epistatic interactions promote persistence of NS3-Q80K in HCV infection by compensating for protein folding instability

The Q80K polymorphism in the NS3-4A protease of the hepatitis C virus is associated with treatment failure of direct-acting antiviral agents. This polymorphism is highly prevalent in genotype 1a infections and stably transmitted between hosts. Here, we investigated the underlying molecular mechanisms of evolutionarily conserved coevolving amino acids in NS3-Q80K and revealed potential implications of epistatic interactions in immune escape and variants persistence. Using purified protein, we characterized the impact of epistatic amino acid substitutions on the physicochemical properties and peptide cleavage kinetics of the NS3-Q80K protease. We found that Q80K destabilized the protease protein fold (p < 0.0001). Although NS3-Q80K showed reduced peptide substrate turnover (p < 0.0002), replicative fitness in an H77S.3 cell culture model of infection was not significantly inferior to the WT virus. Epistatic substitutions at residues 91 and 174 in NS3-Q80K stabilized the protein fold (p < 0.0001) and leveraged the WT protease stability. However, changes in protease stability inversely correlated with enzymatic activity. In infectious cell culture, these secondary substitutions were not associated with a gain of replicative fitness in NS3-Q80K variants. Using molecular dynamics, we observed that the total number of residue contacts in NS3-Q80K mutants correlated with protein folding stability. Changes in the number of contacts reflected the compensatory effect on protein folding instability by epistatic substitutions. In summary, epistatic substitutions in NS3-Q80K contribute to viral fitness by mechanisms not directly related to RNA replication. By compensating for protein-folding instability, epistatic interactions likely protect NS3-Q80K variants from immune cell recognition.

DIGGER: exploring the functional role of alternative splicing in protein interactions

Alternative splicing plays a major role in regulating the functional repertoire of the proteome. However, isoform-specific effects to protein-protein interactions (PPIs) are usually overlooked, making it impossible to judge the functional role of individual exons on a systems biology level. We overcome this barrier by integrating protein-protein interactions, domain-domain interactions and residue-level interactions information to lift exon expression analysis to a network level. Our user-friendly database DIGGER is available at https://exbio.wzw.tum.de/digger and allows users to seamlessly switch between isoform and exon-centric views of the interactome and to extract sub-networks of relevant isoforms, making it an essential resource for studying mechanistic consequences of alternative splicing.

[Indicators of oral fluid and their correction by means of hygiene in elderly people with general somatic diseases.]

The results of the study of oral fluid in older persons with somatic pathology, which was followed for 1 month, are presented. The acid-base state of the oral fluid was evaluated, and the viscosity of the oral fluid was determined. According to the results of the study of oral fluid and its correction by means of hygiene in older persons with somatic diseases, the dynamics of the indicators of the acid-base state of the oral fluid, its shift to the alkaline side and the positive dynamics of the effect of the viscosity of the oral fluid were noted. To ensure that the risk of adverse effects from changes in the state of the oral fluid is reduced, a joint approach involving all health professionals is needed, taking into account the determinants of health and ensuring the development of effective methods for the prevention of dental diseases in older persons.

Characterization of the Stereoselective P450 Enzyme BotCYP Enables the In Vitro Biosynthesis of the Bottromycin Core Scaffold

Bottromycins are ribosomally synthesized and post-translationally modified peptide natural product antibiotics that are effective against high-priority human pathogens such as methicillin-resistant Staphylococcus aureus. The total synthesis of bottromycins involves at least 17 steps, with a poor overall yield. Here, we report the characterization of the cytochrome P450 enzyme BotCYP from a bottromycin biosynthetic gene cluster. We determined the structure of a close BotCYP homolog and used our data to conduct the first large-scale survey of P450 enzymes associated with RiPP biosynthetic gene clusters. We demonstrate that BotCYP converts a C-terminal thiazoline to a thiazole via an oxidative decarboxylation reaction and provides stereochemical resolution for the pathway. Our data enable the two-pot in vitro production of the bottromycin core scaffold and may allow the rapid generation of bottromycin analogues for compound development.

Resistance-associated substitutions in patients with chronic hepatitis C virus genotype 4 infection

Data on the prevalence of resistance-associated substitutions (RASs) and their implications for treatment with direct-acting antivirals (DAAs) are sparse in European patients with HCV genotype 4. This study investigated RASs before and after DAA failure in different genotype 4 subtypes and evaluated retreatment efficacies. Samples of 195 genotype 4-infected patients were collected in the European Resistance Database and investigated for NS3, NS5A and NS5B RASs. Retreatment efficacies in DAA failure patients were analysed retrospectively. After NS5A inhibitor (NS5Ai) failure, subtype 4r was frequent (30%) compared to DAA-naïve patients (5%) and the number of NS5A RASs was significantly higher in subtype 4r compared to 4a or 4d (median three RASs vs no or one RAS, respectively, P < .0001). RASsL28V, L30R and M31L pre-existed in subtype 4r and were maintained after NS5Ai failure. Typical subtype 4r RASs were located in subdomain 1a of NS5A, close to membrane interaction and protein-protein interaction sites that are responsible for multimerization and hence viral replication. Retreatment of 37 DAA failure patients was highly effective with 100% SVR in prior SOF/RBV, PI/SOF and PI/NS5Ai failures. Secondary virologic failures were rare (n = 2; subtype 4d and 4r) and only observed in prior NS5Ai/SOF failures (SVR 90%). In conclusion, subtype 4r harboured considerably more RASs compared to other subtypes. A resistance-tailored retreatment using first- and second-generation DAAs was highly effective with SVR rates ≥90% across all subtypes and first-line treatment regimens.

A shift of dynamic equilibrium between the KIT active and inactive states causes drug resistance

Tyrosine phosphorylation, a highly regulated post-translational modification, is carried out by the enzyme tyrosine kinase (TK). TKs are important mediators in signaling cascades, facilitating diverse biological processes in response to stimuli. TKs may acquire mutations leading to malignancy and are viable targets for anti-cancer drugs. Mast/stem cell growth factor receptor KIT is a TK involved in cell differentiation, whose dysregulation leads to various types of cancer, including gastrointestinal stromal tumors, leukemia, and melanoma. KIT can be targeted by a range of inhibitors that predominantly bind to the inactive state of the enzyme. A mutation Y823D in the activation loop of KIT is known to be responsible for the loss of sensitivity to some drugs in metastatic tumors. We used all-atom molecular dynamics simulations to study the impact of Y823D on the KIT conformation and dynamics and compared it to the effect of phosphorylation of Y823. We simulated in total 6.4 μs of wild-type, mutant and phosphorylated KIT in the active- and inactive-state conformations. We found that Y823D affects the protein dynamics differently: in the active state, the mutation increases the protein stability, whereas in the inactive state it induces local destabilization, thus shifting the dynamic equilibrium towards the active state, altering the communication between distant regulatory regions. The observed dynamics of the Y823D mutant is similar to the dynamics of KIT phosphorylated at position Y823, thus we hypothesize that this mutation mimics a constitutively active kinase, which is not responsive to inhibitors that bind its inactive conformation.

SphereCon-a method for precise estimation of residue relative solvent accessible area from limited structural information

MOTIVATION

In proteins, solvent accessibility of individual residues is a factor contributing to their importance for protein function and stability. Hence one might wish to calculate solvent accessibility in order to predict the impact of mutations, their pathogenicity and for other biomedical applications. A direct computation of solvent accessibility is only possible if all atoms of a protein three-dimensional structure are reliably resolved.

RESULTS

We present SphereCon, a new precise measure that can estimate residue relative solvent accessibility (RSA) from limited data. The measure is based on calculating the volume of intersection of a sphere with a cone cut out in the direction opposite of the residue with surrounding atoms. We propose a method for estimating the position and volume of residue atoms in cases when they are not known from the structure, or when the structural data are unreliable or missing. We show that in cases of reliable input structures, SphereCon correlates almost perfectly with the directly computed RSA, and outperforms other previously suggested indirect methods. Moreover, SphereCon is the only measure that yields accurate results when the identities of amino acids are unknown. A significant novel feature of SphereCon is that it can estimate RSA from inter-residue distance and contact matrices, without any information about the actual atom coordinates.

AVAILABILITY AND IMPLEMENTATION

https://github.com/kalininalab/spherecon.

CONTACT

alexander.gress@helmholtz-hips.de.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Non-active site mutants of HIV-1 protease influence resistance and sensitisation towards protease inhibitors

Background

HIV-1 can develop resistance to antiretroviral drugs, mainly through mutations within the target regions of the drugs. In HIV-1 protease, a majority of resistance-associated mutations that develop in response to therapy with protease inhibitors are found in the protease’s active site that serves also as a binding pocket for the protease inhibitors, thus directly impacting the protease-inhibitor interactions. Some resistance-associated mutations, however, are found in more distant regions, and the exact mechanisms how these mutations affect protease-inhibitor interactions are unclear. Furthermore, some of these mutations, e.g. N88S and L76V, do not only induce resistance to the currently administered drugs, but contrarily induce sensitivity towards other drugs. In this study, mutations N88S and L76V, along with three other resistance-associated mutations, M46I, I50L, and I84V, are analysed by means of molecular dynamics simulations to investigate their role in complexes of the protease with different inhibitors and in different background sequence contexts.

Results

Using these simulations for alchemical calculations to estimate the effects of mutations M46I, I50L, I84V, N88S, and L76V on binding free energies shows they are in general in line with the mutations’ effect on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. For the primary mutation L76V, however, the presence of a background mutation M46I in our analysis influences whether the unfavourable effect of L76V on inhibitor binding is sufficient to outweigh the accompanying reduction in catalytic activity of the protease. Finally, we show that L76V and N88S changes the hydrogen bond stability of these residues with residues D30/K45 and D30/T31/T74, respectively.

Conclusions

We demonstrate that estimating the effect of both binding pocket and distant mutations on inhibitor binding free energy using alchemical calculations can reproduce their effect on the experimentally measured \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$IC_{50}$$\end{document}IC50 values. We show that distant site mutations L76V and N88S affect the hydrogen bond network in the protease’s active site, which offers an explanation for the indirect effect of these mutations on inhibitor binding. This work thus provides valuable insights on interplay between primary and background mutations and mechanisms how they affect inhibitor binding.

[Study of the functional state of the periodontium in older persons and its correction by means of oral hygiene.]

The study involved 258 older persons with generalized chronic periodontitis, who were monitored for a month. For an in-depth study of the properties and effectiveness of toothpastes recommended for older and elderly people with preventive anti-inflammatory purpose, tests were conducted to determine the true characteristics and properties of the studied pastes. Periodontal indices PMA and PI were used to study the anti-inflammatory effect of toothpastes. The most pronounced anti-inflammatory effect was revealed in the samples, the active components of which were oat extract, thymol, anise and essential oils of tea tree, as well as eucalyptus. Proper selection of means of individual oral hygiene and the development of «Individual hygienic program of prevention of chronic generalized periodontitis in older and elderly people» can reduce the phenomenon of inflammation in the periodontium, the development of mediators of inflammation and improve dental health of older and elderly people.

Adenosine-to-Inosine RNA Editing in Mouse and Human Brain Proteomes

Proteogenomics is based on the use of customized genome or RNA sequencing databases for interrogation of shotgun proteomics data in search for proteome-level evidence of genome variations or RNA editing. In this work, the products of adenosine-to-inosine RNA editing in human and murine brain proteomes are identified using publicly available brain proteome LC-MS/MS datasets and an RNA editome database compiled from several sources. After filtering of false-positive results, 20 and 37 sites of editing in proteins belonging to 14 and 32 genes are identified for murine and human brain proteomes, respectively. Eight sites of editing identified with high spectral counts overlapped between human and mouse brain samples. Some of these sites have been previously reported using orthogonal methods, such as α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptors, CYFIP2, coatomer alpha. Also, differential editing between neurons and microglia is demonstrated in this work for some of the proteins from primary murine brain cell cultures. Because many edited sites are still not characterized functionally at the protein level, the results provide a necessary background for their further analysis in normal and diseased cells and tissues using targeted proteomic approaches.

[The detection of antibodies to HCV F protein with immune enzyme analysis using synthetic peptide.]

Alternative reading frame encoding a single protein known as protein F or core + 1 / ARFP is located in the core region of the hepatitis C virus (HCV) genome. The presence of antibodies to the F protein of HCV in the serum of patients with chronic hepatitis C indicates the expression of this protein in vivo. In this study, to determine antibodies to the F protein of HCV in serum samples the methodology of the enzyme immunoassay (ELISA) was developed using the synthetic peptide F10 corresponding to the antigenic determinant of the F protein of the HCV subtype 1b. The immunogenicity and immunochemical specificity of synthetic F10 peptide has been demonstrated in laboratory animals (mice).

Targeting actin inhibits repair of doxorubicin-induced DNA damage: a novel therapeutic approach for combination therapy

Severe side effects often restrict clinical application of the widely used chemotherapeutic drug doxorubicin. In order to decrease required substance concentrations, new concepts for successful combination therapy are needed. Since doxorubicin causes DNA damage, combination with compounds that modulate DNA repair could be a promising strategy. Very recently, a role of nuclear actin for DNA damage repair has been proposed, making actin a potential target for cancer therapy in combination with DNA-damaging therapeutics. This is of special interest, since actin-binding compounds have not yet found their way into clinics. We find that low-dose combination treatment of doxorubicin with the actin polymerizer chondramide B (ChB) synergistically inhibits tumor growth in vivo. On the cellular level we demonstrate that actin binders inhibit distinctive double strand break (DSB) repair pathways. Actin manipulation impairs the recruitment of replication factor A (RPA) to the site of damage, a process crucial for homologous recombination. In addition, actin binders reduce autophosphorylation of DNA-dependent protein kinase (DNA-PK) during nonhomologous end joining. Our findings substantiate a direct involvement of actin in nuclear DSB repair pathways, and propose actin as a therapeutic target for combination therapy with DNA-damaging agents such as doxorubicin.

Relative Principal Components Analysis: Application to Analyzing Biomolecular Conformational Changes

A new method termed “Relative Principal Components Analysis” (RPCA) is introduced that extracts optimal relevant principal components to describe the change between two data samples representing two macroscopic states. The method is widely applicable in data-driven science. Calculating the components is based on a physical framework that introduces the objective function (the Kullback–Leibler divergence) appropriate for quantifying the change of the macroscopic state affected by the changes in the microscopic features. To demonstrate the applicability of RPCA, we analyze the thermodynamically relevant conformational changes of the protein HIV-1 protease upon binding to different drug molecules. In this case, the RPCA method provides a sound thermodynamic foundation for analyzing the binding process and thus characterizing both the collective and the locally relevant conformational changes. Moreover, the relevant collective conformational changes can be reconstructed from the informative latent variables to exhibit both the enhanced and the restricted conformational fluctuations upon ligand association.

Adaptation of a Bacterial Multidrug Resistance System Revealed by the Structure and Function of AlbA

To combat the rise of antimicrobial resistance, the discovery of new antibiotics is paramount. Albicidin and cystobactamid are related natural product antibiotics with potent activity against Gram-positive and, crucially, Gram-negative pathogens. AlbA has been reported to neutralize albicidin by binding it with nanomolar affinity. To understand this potential resistance mechanism, we determined structures of AlbA and its complex with albicidin. The structures revealed AlbA to be comprised of two domains, each unexpectedly resembling the multiantibiotic neutralizing protein TipA. Binding of the long albicidin molecule was shared pseudosymmetrically between the two domains. The structure also revealed an unexpected chemical modification of albicidin, which we demonstrate to be promoted by AlbA, and to reduce albicidin potency; we propose a mechanism for this reaction. Overall, our findings suggest that AlbA arose through internal duplication in an ancient TipA-like gene, leading to a new binding scaffold adapted to the sequestration of long-chain antibiotics.

Epistatic Interactions in NS5A of Hepatitis C Virus Suggest Drug Resistance Mechanisms

Hepatitis C virus (HCV) causes a major health burden and can be effectively treated by direct-acting antivirals (DAAs). The non-structural protein 5A (NS5A), which plays a role in the viral genome replication, is one of the DAAs’ targets. Resistance-associated viruses (RAVs) harbouring NS5A resistance-associated mutations (RAMs) have been described at baseline and after therapy failure. A mutation from glutamine to arginine at position 30 (Q30R) is a characteristic RAM for the HCV sub/genotype (GT) 1a, but arginine corresponds to the wild type in the GT-1b; still, GT-1b strains are susceptible to NS5A-inhibitors. In this study, we show that GT-1b strains with R30Q often display other specific NS5A substitutions, particularly in positions 24 and 34. We demonstrate that in GT-1b secondary substitutions usually happen after initial R30Q development in the phylogeny, and that the chemical properties of the corresponding amino acids serve to restore the positive charge in this region, acting as compensatory mutations. These findings may have implications for RAVs treatment.

Consistent Prediction of Mutation Effect on Drug Binding in HIV-1 Protease Using Alchemical Calculations

Despite a large number of antiretroviral drugs targeting HIV-1 protease for inhibition, mutations in this protein during the course of patient treatment can render them inefficient. This emerging resistance inspired numerous computational studies of the HIV-1 protease aimed at predicting the effect of mutations on drug binding in terms of free binding energy Δ G, as well as in mechanistic terms. In this study, we analyze ten different protease-inhibitor complexes carrying major resistance-associated mutations (RAMs) G48V, I50V, and L90M using molecular dynamics simulations. We demonstrate that alchemical free energy calculations can consistently predict the effect of mutations on drug binding. By explicitly probing different protonation states of the catalytic aspartic dyad, we reveal the importance of the correct choice of protonation state for the accuracy of the result. We also provide insight into how different mutations affect drug binding in their specific ways, with the unifying theme of how all of them affect the crucial drug binding regions of the protease.

Patterns of amino acid conservation in human and animal immunodeficiency viruses

MOTIVATION

Due to their high genomic variability, RNA viruses and retroviruses present a unique opportunity for detailed study of molecular evolution. Lentiviruses, with HIV being a notable example, are one of the best studied viral groups: hundreds of thousands of sequences are available together with experimentally resolved three-dimensional structures for most viral proteins. In this work, we use these data to study specific patterns of evolution of the viral proteins, and their relationship to protein interactions and immunogenicity.

RESULTS

We propose a method for identification of two types of surface residues clusters with abnormal conservation: extremely conserved and extremely variable clusters. We identify them on the surface of proteins from HIV and other animal immunodeficiency viruses. Both types of clusters are overrepresented on the interaction interfaces of viral proteins with other proteins, nucleic acids or low molecular-weight ligands, both in the viral particle and between the virus and its host. In the immunodeficiency viruses, the interaction interfaces are not more conserved than the corresponding proteins on an average, and we show that extremely conserved clusters coincide with protein-protein interaction hotspots, predicted as the residues with the largest energetic contribution to the interaction. Extremely variable clusters have been identified here for the first time. In the HIV-1 envelope protein gp120, they overlap with known antigenic sites. These antigenic sites also contain many residues from extremely conserved clusters, hence representing a unique interacting interface enriched both in extremely conserved and in extremely variable clusters of residues. This observation may have important implication for antiretroviral vaccine development.

AVAILABILITY AND IMPLEMENTATION

A Python package is available at https://bioinf.mpi-inf.mpg.de/publications/viral-ppi-pred/

CONTACT

voitenko@mpi-inf.mpg.de or kalinina@mpi-inf.mpg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Elucidating the energetic contributions to the binding free energy

New exact equations are derived for the terms contributing to the binding free energy (ΔG⁰) of a ligand-receptor pair using our recently introduced formalism which we here call perturbation-divergence formalism (PDF). Specifically, ΔG⁰ equals the sum of the average of the perturbation (pertaining to new interactions) and additional dissipative terms. The average of the perturbation includes the sum of the average receptor-ligand interactions and the average of the change of solvation energies upon association. The Kullback-Leibler (KL) divergence quantifies the energetically dissipative terms, which are due to the configurational changes and, using the chain rule of KL divergence, can be decomposed into (i) dissipation due to limiting the external liberation (translation and rotation) of the ligand relative to the receptor and (ii) dissipation due to conformational (internal) changes inside the receptor and the ligand. We also identify all exactly canceling energetic terms which do not contribute to ΔG⁰. Furthermore, the PDF provides a new approach towards dimensionality reduction in the representation of the association process and towards relating the dynamic (high dimensional) with the thermodynamic (one-dimensional) changes.

How Molecular Conformational Changes Affect Changes in Free Energy

A simple quantitative relationship between the molecular conformational changes and the corresponding changes in the free energy is presented. The change in free energy is the sum of that part of the enthalpic change that is due to the externally applied work (perturbation) and of that part of the entropic change, termed dissipative entropy, that is related to the conformational changes. The dissipative entropy is equivalent to the relative entropy, a concept from information theory, between the distributions of the conformations in the initial and the final states. The remaining change in entropy (nondissipative) cancels exactly with the remaining enthalpic change. The calculation of the dissipative entropy is demonstrated to pose the main difficulty in free energy computation. The straightforward decomposition of the dissipative entropy into contributions from different parts of the system promises to improve the understanding of the role of conformational changes in biochemical reactions.

BALL-SNPgp-from genetic variants toward computational diagnostics

In medical research, it is crucial to understand the functional consequences of genetic alterations, for example, non-synonymous single nucleotide variants (nsSNVs). NsSNVs are known to be causative for several human diseases. However, the genetic basis of complex disorders such as diabetes or cancer comprises multiple factors. Methods to analyze putative synergetic effects of multiple such factors, however, are limited. Here, we concentrate on nsSNVs and present BALL-SNPgp, a tool for structural and functional characterization of nsSNVs, which is aimed to improve pathogenicity assessment in computational diagnostics. Based on annotated SNV data, BALL-SNPgp creates a three-dimensional visualization of the encoded protein, collects available information from different resources concerning disease relevance and other functional annotations, performs cluster analysis, predicts putative binding pockets and provides data on known interaction sites.

AVAILABILITY AND IMPLEMENTATION

BALL-SNPgp is based on the comprehensive C ++ framework Biochemical Algorithms Library (BALL) and its visualization front-end BALLView. Our tool is available at www.ccb.uni-saarland.de/BALL-SNPgp

CONTACT

ballsnp@milaman.cs.uni-saarland.de.

StructMAn: annotation of single-nucleotide polymorphisms in the structural context

The next generation sequencing technologies produce unprecedented amounts of data on the genetic sequence of individual organisms. These sequences carry a substantial amount of variation that may or may be not related to a phenotype. Phenotypically important part of this variation often comes in form of protein-sequence altering (non-synonymous) single nucleotide variants (nsSNVs). Here we present StructMAn, a Web-based tool for annotation of human and non-human nsSNVs in the structural context. StructMAn analyzes the spatial location of the amino acid residue corresponding to nsSNVs in the three-dimensional (3D) protein structure relative to other proteins, nucleic acids and low molecular-weight ligands. We make use of all experimentally available 3D structures of query proteins, and also, unlike other tools in the field, of structures of proteins with detectable sequence identity to them. This allows us to provide a structural context for around 20% of all nsSNVs in a typical human sequencing sample, for up to 60% of nsSNVs in genes related to human diseases and for around 35% of nsSNVs in a typical bacterial sample. Each nsSNV can be visualized and inspected by the user in the corresponding 3D structure of a protein or protein complex. The StructMAn server is available at http://structman.mpi-inf.mpg.de.

The Role of Conformational Changes in Molecular Recognition

Conformational changes of molecules are crucial elements in many biochemical processes, and also in molecular recognition. Here, we present a novel exact mathematical equation for the binding free energy of a receptor-ligand pair. It shows that the energetic contribution due to conformational changes upon molecular recognition is defined by the so-called Kullback-Leibler (KL) divergence between the probability distributions of the conformational ensemble of the biomolecule in the bound and free states. We show that conformational changes always contribute positively to the change in free energy and therefore disfavor the association process. Using the example of ligands binding to a flexible cavity of T4 lysozyme, we illustrate that, due to enthalpy-entropy compensation, the conformational entropy is a misleading quantity for assessing the conformational contribution to the binding free energy, in contrast to the KL divergence, which is the correct quantity to use in this context.

[Phylodynamic of HCV Populations]

Hepatitis C virus is an actual public health problem worldwide since its discovering in 1989. It is explained not only by the wide spreading and frequent adverse outcomes of disease, the lack of effective preventive vaccine, but also by the high genetic variability of the virus. The current review summarizes the results of phylodynamic and phylogeographic studies of different HCV populations that allowed to characterize epidemic processes, to analyze the divergence of HCV into genotypes and subtypes, and to determine the geographic origin of the current HCV epidemic variants.

[VIRAL HEPATITIS C: EVOLUTION OF THE EPIDEMIOLOGIC PROCESS, EVOLUTION OF THE VIRUS]

Periodization of the evolution of epidemic process of hepatitis C is given based on the results of phylodynamic, phylogeographic, historic and demographic studies: invasion of the virus into European and North-American population in 1700-1850; primary activation of the epidemic process in the years of the World War 1; expansive giowth of prevalence in 40--60s of the 20th century due to mass parenteral interventions; new rise due to heroine drug abuse in 60--80s of the 20th century; manifold reduction of incidence of acute hepatitis C in industrial countries for the last 10-15 years as a result of general medical measures of prevention of hemocontact infec-tions. A problem of possibility of hepatitis C management and necessity of evaluation of effectiveness of existing prophylaxis measures involving quantitative analytical methods of epidemiology is discussed. Data from phylogenetic studies on stages of hepatitis C virus evolution (HCV) are provided: division of its root genetic lineage with homologous hepaciviruses of animals 985--2013 years ago; division of HCV into genotypes 500--2000 years ago; division of genotypes into subtypes 70--300 years ago. Contribution of mutations and genetic recombinations into HCV evolution is discussed. Genotyping is stated as an inefficient approach for determination of pathogenicity determinants, immune evasion, non-responsiveness to therapy, as well as search for predictors of infection outcome. A necessity of genomic approach for these aims is justified, as well as for risk monitoring, ensuing from continuing evolution and biodiversity of HCV and other hepaciviruses.

Systematic discovery of linear binding motifs targeting an ancient protein interaction surface on MAP kinases

Mitogen‐activated protein kinases (MAPK) are broadly used regulators of cellular signaling. However, how these enzymes can be involved in such a broad spectrum of physiological functions is not understood. Systematic discovery of MAPK networks both experimentally and in silico has been hindered because MAPKs bind to other proteins with low affinity and mostly in less‐characterized disordered regions. We used a structurally consistent model on kinase‐docking motif interactions to facilitate the discovery of short functional sites in the structurally flexible and functionally under‐explored part of the human proteome and applied experimental tools specifically tailored to detect low‐affinity protein–protein interactions for their validation in vitro and in cell‐based assays. The combined computational and experimental approach enabled the identification of many novel MAPK‐docking motifs that were elusive for other large‐scale protein–protein interaction screens. The analysis produced an extensive list of independently evolved linear binding motifs from a functionally diverse set of proteins. These all target, with characteristic binding specificity, an ancient protein interaction surface on evolutionarily related but physiologically clearly distinct three MAPKs (JNK, ERK, and p38). This inventory of human protein kinase binding sites was compared with that of other organisms to examine how kinase‐mediated partnerships evolved over time. The analysis suggests that most human MAPK‐binding motifs are surprisingly new evolutionarily inventions and newly found links highlight (previously hidden) roles of MAPKs. We propose that short MAPK‐binding stretches are created in disordered protein segments through a variety of ways and they represent a major resource for ancient signaling enzymes to acquire new regulatory roles.

Sequence and Structure Analysis of Distantly-Related Viruses Reveals Extensive Gene Transfer between Viruses and Hosts and among Viruses

The origin and evolution of viruses is a subject of ongoing debate. In this study, we provide a full account of the evolutionary relationships between proteins of significant sequence and structural similarity found in viruses that belong to different classes according to the Baltimore classification. We show that such proteins can be found in viruses from all Baltimore classes. For protein families that include these proteins, we observe two patterns of the taxonomic spread. In the first pattern, they can be found in a large number of viruses from all implicated Baltimore classes. In the other pattern, the instances of the corresponding protein in species from each Baltimore class are restricted to a few compact clades. Proteins with the first pattern of distribution are products of so-called viral hallmark genes reported previously. Additionally, this pattern is displayed by the envelope glycoproteins from Flaviviridae and Bunyaviridae and helicases of superfamilies 1 and 2 that have homologs in cellular organisms. The second pattern can often be explained by horizontal gene transfer from the host or between viruses, an example being Orthomyxoviridae and Coronaviridae hemagglutinin esterases. Another facet of horizontal gene transfer comprises multiple independent introduction events of genes from cellular organisms into otherwise unrelated viruses.

Large oligomeric complex structures can be computationally assembled by efficiently combining docked interfaces

Macromolecular oligomeric assemblies are involved in many biochemical processes of living organisms. The benefits of such assemblies in crowded cellular environments include increased reaction rates, efficient feedback regulation, cooperativity and protective functions. However, an atom-level structural determination of large assemblies is challenging due to the size of the complex and the difference in binding affinities of the involved proteins. In this study, we propose a novel combinatorial greedy algorithm for assembling large oligomeric complexes from information on the approximate position of interaction interfaces of pairs of monomers in the complex. Prior information on complex symmetry is not required but rather the symmetry is inferred during assembly. We implement an efficient geometric score, the transformation match score, that bypasses the model ranking problems of state-of-the-art scoring functions by scoring the similarity between the inferred dimers of the same monomer simultaneously with different binding partners in a (sub)complex with a set of pregenerated docking poses. We compiled a diverse benchmark set of 308 homo and heteromeric complexes containing 6 to 60 monomers. To explore the applicability of the method, we considered 48 sets of parameters and selected those three sets of parameters, for which the algorithm can correctly reconstruct the maximum number, namely 252 complexes (81.8%) in, at least one of the respective three runs. The crossvalidation coverage, that is, the mean fraction of correctly reconstructed benchmark complexes during crossvalidation, was 78.1%, which demonstrates the ability of the presented method to correctly reconstruct topology of a large variety of biological complexes.

BALL-SNP: combining genetic and structural information to identify candidate non-synonymous single nucleotide polymorphisms

BACKGROUND

High-throughput genetic testing is increasingly applied in clinics. Next-Generation Sequencing (NGS) data analysis however still remains a great challenge. The interpretation of pathogenicity of single variants or combinations of variants is crucial to provide accurate diagnostic information or guide therapies.

METHODS

To facilitate the interpretation of variants and the selection of candidate non-synonymous polymorphisms (nsSNPs) for further clinical studies, we developed BALL-SNP. Starting from genetic variants in variant call format (VCF) files or tabular input, our tool, first, visualizes the three-dimensional (3D) structure of the respective proteins from the Protein Data Bank (PDB) and highlights mutated residues, automatically. Second, a hierarchical bottom up clustering on the nsSNPs within the 3D structure is performed to identify nsSNPs, which are close to each other. The modular and flexible implementation allows for straightforward integration of different databases for pathogenic and benign variants, but also enables the integration of pathogenicity prediction tools. The collected background information of all variants is presented below the 3D structure in an easily interpretable table format.

RESULTS

First, we integrated different data resources into BALL-SNP, including databases containing information on genetic variants such as ClinVar or HUMSAVAR; third party tools that predict stability or pathogenicity in silico such as I-Mutant2.0; and additional information derived from the 3D structure such as a prediction of binding pockets. We then explored the applicability of BALL-SNP on the example of patients suffering from cardiomyopathies. Here, the analysis highlighted accumulation of variations in the genes JUP, VCL, and SMYD2.

CONCLUSION

Software solutions for analyzing high-throughput genomics data are important to support diagnosis and therapy selection. Our tool BALL-SNP, which is freely available at http://www.ccb.uni-saarland.de/BALL-SNP, combines genetic information with an easily interpretable and interactive, graphical representation of amino acid changes in proteins. Thereby relevant information from databases and computational tools is presented. Beyond this, proximity to functional sites or accumulations of mutations with a potential collective effect can be discovered.

[Genome organization and life cycle of the hepatitis c virus]

The review summarizes the current data about the hepatitis C viral genome and polyprotein organization. The functional role of the structural and non-structural viral proteins including their interaction with cellular regulatory proteins and cell structural elements is discussed. Specific peculiarities of the life cycle of the hepatitis C virus important for the understanding of the viral hepatitis C pathogenesis are summarized.

Detection of atypical genes in virus families using a one-class SVM

BACKGROUND

The diversity of viruses, the absence of universally common genes in them, and their ability to act as carriers of genetic material make assessment of evolutionary paths of viral genes very difficult. One important factor contributing to this complexity is horizontal gene transfer.

RESULTS

We explore the possibility for the systematic identification of atypical genes within virus families, including viruses whose genome is not encoded by a double-stranded DNA. Our method is based on gene statistical features that differ in genes that were subject of recent horizontal gene transfer from those of the genome in which they are observed. We employ a one-class SVM approach to detect atypical genes within a virus family basing of their statistical signatures and without explicit knowledge of the source species. The simplicity of the statistical features used makes the method applicable to various viruses irrespective of their genome size or type.

CONCLUSIONS

On simulated data, the method can robustly identify alien genes irrespective of the coding nucleic acid found in a virus. It also compares well to results obtained in related studies for double-stranded DNA viruses. Its value in practice is confirmed by the identification of isolated examples of horizontal gene transfer events that have already been described in the literature. A Python package implementing the method and the results for the analyzed virus families are available at http://svm-agp.bioinf.mpi-inf.mpg.de.

[Possibilities for the improvement of the quality of knowledge and their evaluation in the course of studying clinical medicine]

The authors consider objective and subjective factors exerting negative influence on the quality of knowledge of physicians. The generally accepted methods for its evaluation (testing and rating-systems) have limitations. Testing reflects the level of knowledge with respect to the mode of thinking of its designer while rating mostly characterizes diligence of the trainee. It is proposed to improve the quality of knowledge by teaching the theory of diagnostics and to evaluate the amount of knowledge from the contents of the descriptive part of the medical history. The quality of knowledge can be assessed based on the contents of professional comments on the clinical picture described in the model case history.

Modelling binding between CCR5 and CXCR4 receptors and their ligands suggests the surface electrostatic potential of the co-receptor to be a key player in the HIV-1 tropism

BACKGROUND

CCR5 and CXCR4 are the two membrane-standing proteins that, along with CD4, facilitate entry of HIV particles into the host cell. HIV strains differ in their ability to utilize either CCR5 or CXCR4, and this specificity, also known as viral tropism, is largely determined by the sequence of the V3 loop of the viral envelope protein gp120.

RESULTS

With statistical and docking approaches we have computationally analyzed binding preferences of CCR5 and CXCR4 to both V3 loop sequences of virus strains of different tropism and endogenous ligands.

CONCLUSIONS

We conclude that the tropism cannot be satisfactorily explained by amino-acid interactions alone, and suggest a two-step mechanism, by which initial coreceptor selection and approach of the ligand to the binding pocket is dominated by charge and glycosylation pattern of the viral envelope.

[The natural triterpenoid miliacin prevents methotrexate-induced oxidative stress and normalizes the expression of genes encoding the cytochrome P-450 2E1 isoform and glutathione reductase in the liver]

We studied the role of the natural triterpenoid miliacin (3-3-methoxy-Al8-oleanene) in the regulation of oxidative stress in the liver of (CBAxC57B1(6))F1 mice exposed to methotrexate. Miliacin attenuated methotrexate-induced lipid peroxidation as determined by an attenuation of thiobarbituric acid-reacting products in the liver. Furthermore, miliacin normalized the expression of genes encoding the 2e1 isoform of cytochrome P-450 and glutathione reductase that were dramatically dysregulated by methotrexate. These results established the role of miliacin in modulation of redox genes, thereby providing evidence for a new mechanism of organ protection by this triterpenoid.

[Age peculiarities of the sebaceous glands in the temporal area of the scalp skin in men]

The changes of the sebaceous gland number, size and sebocyte proliferative activity were studied in the temporal area of the scalp skin in the male individuals aged 10 to 70 years (n=77, autopsy material). The minimal number of the sebaceous glands was observed in children. This index rapidly increased thereafter, reaching a peak at 20 years, then gradually decreased. These parameters correlated with the sebaceous gland size, sebocyte proliferative activity and total blood testosterone level. In older men the size of the sebaceous glands was increased.

[Low-manifest infections in children and adolescents with consequences of perinatal damage of nervous system]

AIM

Study the specter of low-manifest infections (LMI) and their role in children and adolescents with diseases of central nervous system (CNS) against the background of consequences of perinatal damage of nervous system (PDNS).

MATERIALS AND METHODS

Infectologic and neurologic examinations were carried out in 42 patients with consequences of PDNS (17 girls and 25 boys, 3 - 15 years). Detection of LMI resulted in etiotropic therapy with evaluation of clinical and laboratory data in dynamics.

RESULTS

In 93% (39/42) of patients causative agents of LMI were diagnosed in various combinations and in various biological materials. Among those: Chlamydia spp.--in 71% of patients, Mycoplasma spp.--in 31%, Ureaplasma urealyticum--in 14% (in total the listed microorganisms were diagnosed in 83% of patients); Herpesviridae family viruses--in 75% (HHV-6--in 67%, VEB--in 36%, CMV--in 11%, HSV-1,2--in 11%). Combination of Chlamydia spp. with HHV-6 (R tetr = +0.61) and with VEB (R tet = +0.74) (P < 0.05) was detected. None of the patients had typical signs of encephalitis clinically or based on MRT. MRT signs of gliosis-atrophic changes in the CNS were detected in all the patients. Reduction of a number of psycho-neurologic and neurologic syndromes was noted in all the patients during LMI therapy.

CONCLUSION

Most of the patients with consequences of PDNS had low-intensity inflammatory-degenerative process in the CNS determined by LMI, first of all by Chlamydia spp. as well as Mycoplasma spp.

Computational identification of novel amino-acid interactions in HIV Gag via correlated evolution

Pairs of amino acid positions that evolve in a correlated manner are proposed to play important roles in protein structure or function. Methods to detect them might fare better with families for which sequences of thousands of closely related homologs are available than families with only a few distant relatives. We applied co-evolution analysis to thousands of sequences of HIV Gag, finding that the most significantly co-evolving positions are proximal in the quaternary structures of the viral capsid. A reduction in infectivity caused by mutating one member of a significant pair could be rescued by a compensatory mutation of the other.