Apoptosis Genes as a Key to Identification of Inverse Comorbidity of Huntington's Disease and Cancer.

Cancer and neurodegenerative disorders present overwhelming challenges for healthcare worldwide. Epidemiological studies showed a decrease in cancer rates in patients with neurodegenerative disorders, including the Huntington disease (HD). Apoptosis is one of the most important processes for both cancer and neurodegeneration. We suggest that genes closely connected with apoptosis and associated with HD may affect carcinogenesis. We applied reconstruction and analysis of gene networks associated with HD and apoptosis and identified potentially important genes for inverse comorbidity of cancer and HD. The top 10 high-priority candidate genes included APOE, PSEN1, INS, IL6, SQSTM1, SP1, HTT, LEP, HSPA4, and BDNF. Functional analysis of these genes was carried out using gene ontology and KEGG pathways. By exploring genome-wide association study results, we identified genes associated with neurodegenerative and oncological disorders, as well as their endophenotypes and risk factors. We used publicly available datasets of HD and breast and prostate cancers to analyze the expression of the identified genes. Functional modules of these genes were characterized according to disease-specific tissues. This integrative approach revealed that these genes predominantly exert similar functions in different tissues. Apoptosis along with lipid metabolism dysregulation and cell homeostasis maintenance in the response to environmental stimulus and drugs are likely key processes in inverse comorbidity of cancer in patients with HD. Overall, the identified genes represent the promising targets for studying molecular relations of cancer and HD.

Differentially Expressed Genes and Molecular Susceptibility to Human Age-Related Diseases.

Mainstream transcriptome profiling of susceptibility versus resistance to age-related diseases (ARDs) is focused on differentially expressed genes (DEGs) specific to gender, age, and pathogeneses. This approach fits in well with predictive, preventive, personalized, participatory medicine and helps understand how, why, when, and what ARDs one can develop depending on their genetic background. Within this mainstream paradigm, we wanted to find out whether the known ARD-linked DEGs available in PubMed can reveal a molecular marker that will serve the purpose in anyone's any tissue at any time. We sequenced the periaqueductal gray (PAG) transcriptome of tame versus aggressive rats, identified rat-behavior-related DEGs, and compared them with their known homologous animal ARD-linked DEGs. This analysis yielded statistically significant correlations between behavior-related and ARD-susceptibility-related fold changes (log2 values) in the expression of these DEG homologs. We found principal components, PC1 and PC2, corresponding to the half-sum and the half-difference of these log2 values, respectively. With the DEGs linked to ARD susceptibility and ARD resistance in humans used as controls, we verified these principal components. This yielded only one statistically significant common molecular marker for ARDs: an excess of Fcγ receptor IIb suppressing immune cell hyperactivation.

Candidate SNP Markers Significantly Altering the Affinity of TATA-Binding Protein for the Promoters of Human Hub Genes for Atherogenesis, Atherosclerosis and Atheroprotection.

Atherosclerosis is a systemic disease in which focal lesions in arteries promote the build-up of lipoproteins and cholesterol they are transporting. The development of atheroma (atherogenesis) narrows blood vessels, reduces the blood supply and leads to cardiovascular diseases. According to the World Health Organization (WHO), cardiovascular diseases are the leading cause of death, which has been especially boosted since the COVID-19 pandemic. There is a variety of contributors to atherosclerosis, including lifestyle factors and genetic predisposition. Antioxidant diets and recreational exercises act as atheroprotectors and can retard atherogenesis. The search for molecular markers of atherogenesis and atheroprotection for predictive, preventive and personalized medicine appears to be the most promising direction for the study of atherosclerosis. In this work, we have analyzed 1068 human genes associated with atherogenesis, atherosclerosis and atheroprotection. The hub genes regulating these processes have been found to be the most ancient. In silico analysis of all 5112 SNPs in their promoters has revealed 330 candidate SNP markers, which statistically significantly change the affinity of the TATA-binding protein (TBP) for these promoters. These molecular markers have made us confident that natural selection acts against underexpression of the hub genes for atherogenesis, atherosclerosis and atheroprotection. At the same time, upregulation of the one for atheroprotection promotes human health.

Plant Biology and Biotechnology: Focus on Genomics and Bioinformatics.

The study of molecular mechanisms of plant stress response is important for agrobiotechnology applications as it was discussed at series of recent bioinformatics conferences [...].

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition.

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.

ANDDigest: a new web-based module of ANDSystem for the search of knowledge in the scientific literature.

BACKGROUND: The rapid growth of scientific literature has rendered the task of finding relevant information one of the critical problems in almost any research. Search engines, like Google Scholar, Web of Knowledge, PubMed, Scopus, and others, are highly effective in document search; however, they do not allow knowledge extraction. In contrast to the search engines, text-mining systems provide extraction of knowledge with representations in the form of semantic networks. Of particular interest are tools performing a full cycle of knowledge management and engineering, including automated retrieval, integration, and representation of knowledge in the form of semantic networks, their visualization, and analysis. STRING, Pathway Studio, MetaCore, and others are well-known examples of such products. Previously, we developed the Associative Network Discovery System (ANDSystem), which also implements such a cycle. However, the drawback of these systems is dependence on the employed ontologies describing the subject area, which limits their functionality in searching information based on user-specified queries. RESULTS: The ANDDigest system is a new web-based module of the ANDSystem tool, permitting searching within PubMed by using dictionaries from the ANDSystem tool and sets of user-defined keywords. ANDDigest allows performing the search based on complex queries simultaneously, taking into account many types of objects from the ANDSystem's ontology. The system has a user-friendly interface, providing sorting, visualization, and filtering of the found information, including mapping of mentioned objects in text, linking to external databases, sorting of data by publication date, citations number, journal H-indices, etc. The system provides data on trends for identified entities based on dynamics of interest according to the frequency of their mentions in PubMed by years. CONCLUSIONS: The main feature of ANDDigest is its functionality, serving as a specialized search for information about multiple associative relationships of objects from the ANDSystem's ontology vocabularies, taking into account user-specified keywords. The tool can be applied to the interpretation of experimental genetics data, the search for associations between molecular genetics objects, and the preparation of scientific and analytical reviews. It is presently available at https://anddigest.sysbio.ru/ .

Young «oil site¼ of the Uzon Caldera as a habitat for unique microbial life.

BACKGROUND: The Uzon Caldera is one of the places on our planet with unique geological, ecological, and microbiological characteristics. Uzon oil is the youngest on Earth. Uzon oil has unique composition, with low proportion of heavy fractions and relatively high content of saturated hydrocarbons. Microbial communities of the «oil site¼ have a diverse composition and live at high temperatures (up to 97 °C), significant oscillations of Eh and pH, and high content of sulfur, sulfides, arsenic, antimony, and mercury in water and rocks. RESULTS: The study analyzed the composition, structure and unique genetics characteristics of the microbial communities of the oil site, analyzed the metabolic pathways in the communities. Metabolic pathways of hydrocarbon degradation by microorganisms have been found. The study found statistically significant relationships between geochemical parameters, taxonomic composition and the completeness of metabolic pathways. It was demonstrated that geochemical parameters determine the structure and metabolic potential of microbial communities. CONCLUSIONS: There were statistically significant relationships between geochemical parameters, taxonomic composition, and the completeness of metabolic pathways. It was demonstrated that geochemical parameters define the structure and metabolic potential of microbial communities. Metabolic pathways of hydrocarbon oxidation was found to prevail in the studied communities, which corroborates the hypothesis on abiogenic synthesis of Uzon hydrothermal petroleum.

The story of the lost twins: decoding the genetic identities of the Kumhar and Kurcha populations from the Indian subcontinent.

BACKGROUND: The population structure of the Indian subcontinent is a tapestry of extraordinary diversity characterized by the amalgamation of autochthonous and immigrant ancestries and rigid enforcement of sociocultural stratification. Here we investigated the genetic origin and population history of the Kumhars, a group of people who inhabit large parts of northern India. We compared 27 previously published Kumhar SNP genotype data sampled from Uttar Pradesh in north India to various modern day and ancient populations. RESULTS: Various approaches such as Principal Component Analysis (PCA), Admixture, TreeMix concurred that Kumhars have high ASI ancestry, minimal Steppe component and high genomic proximity to the Kurchas, a small and relatively little-known population found ~ 2500 km away in Kerala, south India. Given the same, biogeographical mapping using Geographic Population Structure (GPS) assigned most Kumhar samples in areas neighboring to those where Kurchas are found in south India. CONCLUSIONS: We hypothesize that the significant genomic similarity between two apparently distinct modern-day Indian populations that inhabit well separated geographical areas with no known overlapping history or links, likely alludes to their common origin during or post the decline of the Indus Valley Civilization (estimated by ALDER). Thereafter, while they dispersed towards opposite ends of the Indian subcontinent, their genomic integrity and likeness remained preserved due to endogamous social practices. Our findings illuminate the genomic history of two Indian populations, allowing a glimpse into one or few of numerous of human migrations that likely occurred across the Indian subcontinent and contributed to shape its varied and vibrant evolutionary past.

A new version of the ANDSystem tool for automatic extraction of knowledge from scientific publications with expanded functionality for reconstruction of associative gene networks by considering tissue-specific gene expression.

BACKGROUND: Consideration of tissue-specific gene expression in reconstruction and analysis of molecular genetic networks is necessary for a proper description of the processes occurring in a specified tissue. Currently, there are a number of computer systems that allow the user to reconstruct molecular-genetic networks using the data automatically extracted from the texts of scientific publications. Examples of such systems are STRING, Pathway Commons, MetaCore and Ingenuity. The MetaCore and Ingenuity systems permit taking into account tissue-specific gene expression during the reconstruction of gene networks. Previously, we developed the ANDSystem tool, which also provides an automated extraction of knowledge from scientific texts and allows the reconstruction of gene networks. The main difference between our system and other tools is in the different types of interactions between objects, which makes the ANDSystem complementary to existing well-known systems. However, previous versions of the ANDSystem did not contain any information on tissue-specific expression. RESULTS: A new version of the ANDSystem has been developed. It offers the reconstruction of associative gene networks while taking into account the tissue-specific gene expression. The ANDSystem knowledge base features information on tissue-specific expression for 272 tissues. The system allows the reconstruction of combined gene networks, as well as performing the filtering of genes from such networks using the information on their tissue-specific expression. As an example of the application of such filtering, the gene network of the extrinsic apoptotic signaling pathway was analyzed. It was shown that considering different tissues can lead to changes in gene network structure, including changes in such indicators as betweenness centrality of vertices, clustering coefficient, network centralization, network density, etc. CONCLUSIONS: The consideration of tissue specificity can play an important role in the analysis of gene networks, in particular solving the problem of finding the most significant central genes. Thus, the new version of ANDSystem can be employed for a wide range of tasks related to biomedical studies of individual tissues. It is available at http://www-bionet.sscc.ru/and/cell /.

Delineating the role of c-FLIP/NEMO interaction in the CD95 network via rational design of molecular probes.

BACKGROUND: Structural homology modeling supported by bioinformatics analysis plays a key role in uncovering new molecular interactions within gene regulatory networks. Here, we have applied this powerful approach to analyze the molecular interactions orchestrating death receptor signaling networks. In particular, we focused on the molecular mechanisms of CD95-mediated NF-κB activation and the role of c-FLIP/NEMO interaction in the induction of this pathway. RESULTS: To this end, we have created the homology model of the c-FLIP/NEMO complex using the reported structure of the v-FLIP/NEMO complex, and rationally designed peptides targeting this complex. The designed peptides were based on the NEMO structure. Strikingly, the experimental in vitro validation demonstrated that the best inhibitory effects on CD95-mediated NF-κB activation are exhibited by the NEMO-derived peptides with the substitution D242Y of NEMO. Furthermore, we have assumed that the c-FLIP/NEMO complex is recruited to the DED filaments formed upon CD95 activation and validated this assumption in silico. Further insight into the function of c-FLIP/NEMO complex was provided by the analysis of evolutionary conservation of interacting regions which demonstrated that this interaction is common in distinct mammalian species. CONCLUSIONS: Taken together, using a combination of bioinformatics and experimental approaches we obtained new insights into CD95-mediated NF-κB activation, providing manifold possibilities for targeting the death receptor network.

Design, Synthesis and Molecular Modeling Study of Conjugates of ADP and Morpholino Nucleosides as A Novel Class of Inhibitors of PARP-1, PARP-2 and PARP-3.

We report on the design, synthesis and molecular modeling study of conjugates of adenosine diphosphate (ADP) and morpholino nucleosides as potential selective inhibitors of poly(ADP-ribose)polymerases-1, 2 and 3. Sixteen dinucleoside pyrophosphates containing natural heterocyclic bases as well as 5-haloganeted pyrimidines, and mimicking a main substrate of these enzymes, nicotinamide adenine dinucleotide (NAD+)-molecule, have been synthesized in a high yield. Morpholino nucleosides have been tethered to the ß-phosphate of ADP via a phosphoester or phosphoramide bond. Screening of the inhibiting properties of these derivatives on the autopoly(ADP-ribosyl)ation of PARP-1 and PARP-2 has shown that the effect depends upon the type of nucleobase as well as on the linkage between ADP and morpholino nucleoside. The 5-iodination of uracil and the introduction of the P-N bond in NAD+-mimetics have shown to increase inhibition properties. Structural modeling suggested that the P-N bond can stabilize the pyrophosphate group in active conformation due to the formation of an intramolecular hydrogen bond. The most active NAD+ analog against PARP-1 contained 5-iodouracil 2'-aminomethylmorpholino nucleoside with IC50 126 ± 6 µM, while in the case of PARP-2 it was adenine 2'-aminomethylmorpholino nucleoside (IC50 63 ± 10 µM). In silico analysis revealed that thymine and uracil-based NAD+ analogs were recognized as the NAD+-analog that targets the nicotinamide binding site. On the contrary, the adenine 2'-aminomethylmorpholino nucleoside-based NAD+ analogs were predicted to identify as PAR-analogs that target the acceptor binding site of PARP-2, representing a novel molecular mechanism for selective PARP inhibition. This discovery opens a new avenue for the rational design of PARP-1/2 specific inhibitors.

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

BACKGROUND: Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. RESULTS: We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. CONCLUSIONS: FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of experimental gene sets, both for different global networks and for different types of interactions. Using examples of thyroid cancer and apoptosis networks, we have shown that the links over-represented in the analyzed network in comparison with the random ones make possible a biological interpretation of the original gene/protein sets. The FunGeneNet web tool for assessment of the functional enrichment of networks is available at http://www-bionet.sscc.ru/fungenenet/ .

Molecular mechanisms underlying the impact of mutations in SOD1 on its conformational properties associated with amyotrophic lateral sclerosis as revealed with molecular modelling.

BACKGROUND: So far, little is known about the molecular mechanisms of amyotrophic lateral sclerosis onset and progression caused by SOD1 mutations. One of the hypotheses is based on SOD1 misfolding resulting from mutations and subsequent deposition of its cytotoxic aggregates. This hypothesis is complicated by the fact that known SOD1 mutations of similar clinical effect could be distributed over the whole protein structure. RESULTS: In this work, a measure of hydrogen bond stability in conformational states was studied with elastic network analysis of 35 SOD1 mutants. Twenty-eight hydrogen bonds were detected in nine of 35 mutants with their stability being significantly different from that with the wild-type. These hydrogen bonds were formed by the amino acid residues known from the literature to be located in contact between SOD1 aggregates. Additionally, residues disposed between copper binding sites of both protein subunits were found from the models to form a stiff core, which can be involved in mechanical impulse transduction between these active centres. CONCLUSIONS: The modelling highlights that both stability of the copper binding site and stability of the dimer can play an important role in ALS progression.

Correction to: selected articles from Belyaev Conference 2017: structural biology.

After publication of the article [1], it has been brought to our attention that there is a discrepancy between the publication date on the pdf and online formats. The date on the pdf is 6th February 2018 and online is 5th February 2018. The correct publication date is the one on the pdf, 6th February 2018.

Computer analysis of protein functional sites projection on exon structure of genes in Metazoa.

BACKGROUND: Study of the relationship between the structural and functional organization of proteins and their coding genes is necessary for an understanding of the evolution of molecular systems and can provide new knowledge for many applications for designing proteins with improved medical and biological properties. It is well known that the functional properties of proteins are determined by their functional sites. Functional sites are usually represented by a small number of amino acid residues that are distantly located from each other in the amino acid sequence. They are highly conserved within their functional group and vary significantly in structure between such groups. According to this facts analysis of the general properties of the structural organization of the functional sites at the protein level and, at the level of exon-intron structure of the coding gene is still an actual problem. RESULTS: One approach to this analysis is the projection of amino acid residue positions of the functional sites along with the exon boundaries to the gene structure. In this paper, we examined the discontinuity of the functional sites in the exon-intron structure of genes and the distribution of lengths and phases of the functional site encoding exons in vertebrate genes. We have shown that the DNA fragments coding the functional sites were in the same exons, or in close exons. The observed tendency to cluster the exons that code functional sites which could be considered as the unit of protein evolution. We studied the characteristics of the structure of the exon boundaries that code, and do not code, functional sites in 11 Metazoa species. This is accompanied by a reduced frequency of intercodon gaps (phase 0) in exons encoding the amino acid residue functional site, which may be evidence of the existence of evolutionary limitations to the exon shuffling. CONCLUSIONS: These results characterize the features of the coding exon-intron structure that affect the functionality of the encoded protein and allow a better understanding of the emergence of biological diversity.

Prediction of tissue-specific effects of gene knockout on apoptosis in different anatomical structures of human brain.

BACKGROUND: An important issue in the target identification for the drug design is the tissue-specific effect of inhibition of target genes. The task of assessing the tissue-specific effect in suppressing gene activity is especially relevant in the studies of the brain, because a significant variability in gene expression levels among different areas of the brain was well documented. RESULTS: A method is proposed for constructing statistical models to predict the potential effect of the knockout of target genes on the expression of genes involved in the regulation of apoptosis in various brain regions. The model connects the expression of the objective group of genes with expression of the target gene by means of machine learning models trained on available expression data. Information about the interactions between target and objective genes is determined by reconstruction of target-centric gene network. STRING and ANDSystem databases are used for the reconstruction of gene networks. The developed models have been used to analyse gene knockout effects of more than 7,500 target genes on the expression of 1,900 objective genes associated with the Gene Ontology category "apoptotic process". The tissue-specific effect was calculated for 12 main anatomical structures of the human brain. Initial values of gene expression in these anatomical structures were taken from the Allen Brain Atlas database. The results of the predictions of the effect of suppressing the activity of target genes on apoptosis, calculated on average for all brain structures, were in good agreement with experimental data on siRNA-inhibition. CONCLUSIONS: This theoretical paper presents an approach that can be used to assess tissue-specific gene knockout effect on gene expression of the studied biological process in various structures of the brain. Genes that, according to the predictions of the model, have the highest values of tissue-specific effects on the apoptosis network can be considered as potential pharmacological targets for the development of drugs that would potentially have strong effect on the specific area of the brain and a much weaker effect on other brain structures. Further experiments should be provided in order to confirm the potential findings of the method.

Molecular analysis of the benthos microbial community in Zavarzin thermal spring (Uzon Caldera, Kamchatka, Russia).

BACKGROUND: Geothermal areas are of great interest for the study of microbial communities. The results of such investigations can be used in a variety of fields (ecology, microbiology, medicine) to answer fundamental questions, as well as those with practical benefits. Uzon caldera is located in the Uzon-Geyser depression that is situated in the centre of the Karym-Semyachin region of the East Kamchatka graben-synclinorium. The microbial communities of Zavarzin spring are well studied; however, its benthic microbial mat has not been previously described. RESULTS: Pyrosequencing of the V3 region of the 16S rRNA gene was used to study the benthic microbial community of the Zavarzin thermal spring (Uzon Caldera, Kamchatka). The community is dominated by bacteria (>95% of all sequences), including thermophilic, chemoorganotrophic Caldiserica (33.0%) and Dictyoglomi (24.8%). The benthic community and the previously examined planktonic community of Zavarzin spring have qualitatively similar, but quantitatively different, compositions. CONCLUSIONS: In this study, we performed a metagenomic analysis of the benthic microbial mat of Zavarzin spring. We compared this benthic community to microbial communities found in the water and of an integral probe consisting of water and bottom sediments. Various phylogenetic groups of microorganisms, including potentially new ones, represent the full-fledged trophic system of Zavarzin. A thorough geochemical study of the spring was performed.

Time-course human urine proteomics in space-flight simulation experiments.

BACKGROUND: Long-term space travel simulation experiments enabled to discover different aspects of human metabolism such as the complexity of NaCl salt balance. Detailed proteomics data were collected during the Mars105 isolation experiment enabling a deeper insight into the molecular processes involved. RESULTS: We studied the abundance of about two thousand proteins extracted from urine samples of six volunteers collected weekly during a 105-day isolation experiment under controlled dietary conditions including progressive reduction of salt consumption. Machine learning using Self Organizing maps (SOM) in combination with different analysis tools was applied to describe the time trajectories of protein abundance in urine. The method enables a personalized and intuitive view on the physiological state of the volunteers. The abundance of more than one half of the proteins measured clearly changes in the course of the experiment. The trajectory splits roughly into three time ranges, an early (week 1-6), an intermediate (week 7-11) and a late one (week 12-15). Regulatory modes associated with distinct biological processes were identified using previous knowledge by applying enrichment and pathway flow analysis. Early protein activation modes can be related to immune response and inflammatory processes, activation at intermediate times to developmental and proliferative processes and late activations to stress and responses to chemicals. CONCLUSIONS: The protein abundance profiles support previous results about alternative mechanisms of salt storage in an osmotically inactive form. We hypothesize that reduced NaCl consumption of about 6 g/day presumably will reduce or even prevent the activation of inflammatory processes observed in the early time range of isolation. SOM machine learning in combination with analysis methods of class discovery and functional annotation enable the straightforward analysis of complex proteomics data sets generated by means of mass spectrometry.

Insights into pathophysiology of dystropy through the analysis of gene networks: an example of bronchial asthma and tuberculosis.

Co-existence of bronchial asthma (BA) and tuberculosis (TB) is extremely uncommon (dystropic). We assume that this is caused by the interplay between genes involved into specific pathophysiological pathways that arrest simultaneous manifestation of BA and TB. Identification of common and specific genes may be important to determine the molecular genetic mechanisms leading to rare co-occurrence of these diseases and may contribute to the identification of susceptibility genes for each of these dystropic diseases. To address the issue, we propose a new methodological strategy that is based on reconstruction of associative networks that represent molecular relationships between proteins/genes associated with BA and TB, thus facilitating a better understanding of the biological context of antagonistic relationships between the diseases. The results of our study revealed a number of proteins/genes important for the development of both BA and TB.

Targeting type I DED interactions at the DED filament serves as a sensitive switch for cell fate decisions.

Activation of procaspase-8 in the death effector domain (DED) filaments of the death-inducing signaling complex (DISC) is a key step in apoptosis. In this study, a rationally designed cell-penetrating peptide, DEDid, was engineered to mimic the h2b helical region of procaspase-8-DED2 containing a highly conservative FL motif. Furthermore, mutations were introduced into the DEDid binding site of the procaspase-8 type I interface. Additionally, our data suggest that DEDid targets other type I DED interactions such as those of FADD. Both approaches of blocking type I DED interactions inhibited CD95L-induced DISC assembly, caspase activation and apoptosis. We showed that inhibition of procaspase-8 type I interactions by mutations not only diminished procaspase-8 recruitment to the DISC but also destabilized the FADD core of DED filaments. Taken together, this study offers insights to develop strategies to target DED proteins, which may be considered in diseases associated with cell death and inflammation.