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.