RESUMEN

Dynamic interactions between transcription factors govern changes in gene expression that mediate changes in cell state accompanying injury response and regeneration. Transcription factors frequently function as obligate dimers whose activity is often modulated by post-translational modifications. These critical and often transient interactions are not easily detected by traditional methods to investigate protein-protein interactions. This chapter discusses the design and validation of a fusion protein involving a transcription factor tethered to a proximity labeling ligase, APEX2. In this technique, proteins are biotinylated within a small radius of the transcription factor of interest, regardless of time of interaction. Here we discuss the validations required to ensure proper functioning of the transcription factor proximity labeling tool and the sample preparation of biotinylated proteins for mass spectrometry analysis of putative protein interactors.

Asunto(s)

Biotinilación , ADN-(Sitio Apurínico o Apirimidínico) Liasa , Mapeo de Interacción de Proteínas , Factores de Transcripción , Mapeo de Interacción de Proteínas/métodos , Humanos , Factores de Transcripción/metabolismo , ADN-(Sitio Apurínico o Apirimidínico) Liasa/metabolismo , ADN-(Sitio Apurínico o Apirimidínico) Liasa/química , Proteínas Recombinantes de Fusión/metabolismo , Proteínas Recombinantes de Fusión/genética , Unión Proteica , Espectrometría de Masas/métodos , Procesamiento Proteico-Postraduccional , Endonucleasas , Enzimas Multifuncionales

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Many protein-protein interactions (PPIs) affect the ways in which small molecules bind to their constituent proteins, which can impact drug efficacy and regulatory mechanisms. While recent advances have improved our ability to independently predict both PPIs and ligand-protein interactions (LPIs), a comprehensive understanding of how PPIs affect LPIs is still lacking. Here, we examined 63 pairs of ligand-protein complexes in a benchmark dataset for protein-protein docking studies and quantified six typical effects of PPIs on LPIs. A multi-chain dynamics perturbation analysis method, called mcDPA, was developed to model these effects and used to predict small-molecule binding regions in protein-protein complexes. Our results illustrated that the mcDPA can capture the impact of PPI on LPI to varying degrees, with six similar changes in its predicted ligand-binding region. The calculations showed that 52% of the examined complexes had prediction accuracy at or above 50%, and 55% of the predictions had a recall of not less than 50%. When applied to 33 FDA-approved protein-protein-complex-targeting drugs, these numbers improved to 60% and 57% for the same accuracy and recall rates, respectively. The method developed in this study may help to design drug-target interactions in complex environments, such as in the case of protein-protein interactions.

Asunto(s)

Simulación del Acoplamiento Molecular , Unión Proteica , Proteínas , Ligandos , Proteínas/metabolismo , Proteínas/química , Simulación de Dinámica Molecular , Sitios de Unión

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Pathological cardiac hypertrophy is the primary cause of heart failure, yet its underlying mechanisms remain incompletely understood. Transmembrane protein 100 (TMEM100) plays a role in various disorders, such as nervous system disease, pain and tumorigenesis, but its function in pathological cardiac hypertrophy is still unknown. In this study, we observed that TMEM100 is upregulated in cardiac hypertrophy. Functional investigations have shown that adeno-associated virus 9 (AAV9) mediated-TMEM100 overexpression mice attenuates transverse aortic constriction (TAC)-induced cardiac hypertrophy, including cardiomyocyte enlargement, cardiac fibrosis, and impaired heart structure and function. We subsequently demonstrated that adenoviral TMEM100 (AdTMEM100) mitigates phenylephrine (PE)-induced cardiomyocyte hypertrophy and downregulates the expression of cardiac hypertrophic markers in vitro, whereas TMEM100 knockdown exacerbates cardiomyocyte hypertrophy. The RNA sequences of the AdTMEM100 group and control group revealed that TMEM100 was involved in oxidative stress and the MAPK signaling pathway after PE stimulation. Mechanistically, we revealed that the transmembrane domain of TMEM100 (amino acids 53-75 and 85-107) directly interacts with the C-terminal region of TAK1 (amino acids 1-300) and inhibits the phosphorylation of TAK1 and its downstream molecules JNK and p38. TAK1-binding-defective TMEM100 failed to inhibit the activation of the TAK1-JNK/p38 pathway. Finally, the application of a TAK1 inhibitor (iTAK1) revealed that TAK1 is necessary for TMEM100-mediated cardiac hypertrophy. In summary, TMEM100 protects against pathological cardiac hypertrophy through the TAK1-JNK/p38 pathway and may serve as a promising target for the treatment of cardiac hypertrophy.

Asunto(s)

Cardiomegalia , Quinasas Quinasa Quinasa PAM , Proteínas de la Membrana , Miocitos Cardíacos , Animales , Cardiomegalia/genética , Cardiomegalia/metabolismo , Cardiomegalia/patología , Proteínas de la Membrana/metabolismo , Proteínas de la Membrana/genética , Miocitos Cardíacos/metabolismo , Miocitos Cardíacos/patología , Quinasas Quinasa Quinasa PAM/metabolismo , Quinasas Quinasa Quinasa PAM/genética , Ratones , Ratones Endogámicos C57BL , Masculino , Progresión de la Enfermedad , Humanos , Fenilefrina/farmacología , Sistema de Señalización de MAP Quinasas , Estrés Oxidativo

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The significant reduction in cassava (Manihot esculenta Crantz) yields attributed to cassava bacterial blight (CBB) constitutes an urgent matter demanding prompt attention. The current study centered on the MebHLH149 transcription factor, which is acknowledged to be reactive to CBB and exhibits augmented expression levels, as indicated by laboratory transcriptome data. Our exploration, encompassing Xanthomonas phaseoli pv. manihotis strain CHN01 (Xpm CHN01) and hormone stress, disclosed that the MebHLH149 gene interacts with the pathogen at the early stage of infection. Furthermore, the MebHLH149 gene has been discovered to be responsive to the plant hormones abscisic acid (ABA), methyl jasmonate (MeJA), and salicylic acid (SA), intimating a potential role in the signaling pathways mediated by these hormones. An analysis of the protein's subcellular localization suggested that MebHLH149 is predominantly located within the nucleus. Through virus-induced gene silencing (VIGS) in cassava, we discovered that MebHLH149-silenced plants manifested higher disease susceptibility, less ROS accumulation, and significantly larger leaf spot areas compared to control plants. The proteins MePRE5 and MePRE6, which are predicted to interact with MebHLH149, demonstrated complementary downregulation and upregulation patterns in response to silencing and overexpression of the MebHLH149 gene. This implies a potential interaction between MebHLH149 and these proteins. Both MePRE5 and MePRE6 genes are involved in the initial immune response to CBB. Notably, MebHLH149 was identified as a protein that physically interacts with MePRE5 and MePRE6. Based on these findings, it is hypothesized that the MebHLH149 gene likely functions as a positive regulator in the defense mechanisms of cassava against CBB.

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Autophagy is a catabolic process that was described to play a critical role in advanced stages of cancer, wherein it maintains tumor cell homeostasis and growth by supplying nutrients. Autophagy is also described to support alternative cellular trafficking pathways, providing a non-canonical autophagy-dependent inflammatory cytokine secretion mechanism. Therefore, autophagy inhibitors have high potential in the treatment of cancer and acute inflammation. In our study, we identified compound 1 as an inhibitor of the ATG12-ATG3 protein-protein interaction. We focused on the systematic modification of the original hit 1, a casein kinase 2 (CK2) inhibitor, to find potent disruptors of ATG12-ATG3 protein-protein interaction. A systematic modification of the hit structure led us to a wide plethora of compounds that maintain its ATG12-ATG3 inhibitory activity, which could act as a viable starting point to design new compounds with diverse therapeutic applications.

Asunto(s)

Proteínas Relacionadas con la Autofagia , Bibliotecas de Moléculas Pequeñas , Relación Estructura-Actividad , Humanos , Bibliotecas de Moléculas Pequeñas/química , Bibliotecas de Moléculas Pequeñas/farmacología , Bibliotecas de Moléculas Pequeñas/síntesis química , Proteínas Relacionadas con la Autofagia/metabolismo , Proteínas Relacionadas con la Autofagia/antagonistas & inhibidores , Unión Proteica , Estructura Molecular , Autofagia/efectos de los fármacos , Relación Dosis-Respuesta a Droga , Quinasa de la Caseína II/antagonistas & inhibidores , Quinasa de la Caseína II/metabolismo

RESUMEN

Coronavirus nonstructural protein 2 (Nsp2) is regarded as a virulence determinant and plays a critical role in virus replication, and innate immunity. Screening and identifying host cell proteins that interact with viral proteins is an effective way to reveal the functions of viral proteins. In this study, the host proteins that interacted with transmissible gastroenteritis virus (TGEV) Nsp2 were identified using immunoprecipitation combined with LC-MS/MS. 77 host cell proteins were identified as putative Nsp2 interaction host cell proteins and a protein-protein interaction (PPI) was constructed. The identified proteins were found to be associated with various subcellular locations and functional categories through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. It is hypothesized that the host cell proteins interacting with TGEV Nsp2 are mainly involved in the formation of the cytoplasmic translation initiation complex, mRNA binding, ribosomes, and proteasomes. Among these, the ATP5B, a core subunit of the mitochondrial ATP synthase was further studied. The Coimmunoprecipitation (Co-IP) and indirect immunofluorescence (IFA) results confirmed that TGEV Nsp2 interacted with ATP5B. Furthermore, the downregulation of ATP5B expression was found to promote TGEV replication, suggesting that ATP5B might function as a negative regulator of TGEV replication. Collectively, our results offer additional insights into the functions of Nsp2 and provide a novel antiviral target against TGEV.

Asunto(s)

ATPasas de Translocación de Protón Mitocondriales , Virus de la Gastroenteritis Transmisible , Proteínas no Estructurales Virales , Replicación Viral , Virus de la Gastroenteritis Transmisible/genética , Animales , Proteínas no Estructurales Virales/metabolismo , Proteínas no Estructurales Virales/genética , Porcinos , ATPasas de Translocación de Protón Mitocondriales/metabolismo , ATPasas de Translocación de Protón Mitocondriales/genética , Humanos , Interacciones Huésped-Patógeno , Gastroenteritis Porcina Transmisible/virología , Gastroenteritis Porcina Transmisible/genética , Línea Celular , Inmunoprecipitación , Espectrometría de Masas en Tándem

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Cancer classification is crucial for effective patient treatment, and recent years have seen various methods emerge based on protein expression levels. However, existing methods oversimplify by assuming uniform interaction strengths and neglecting intermediate influences among proteins. Addressing these limitations, GATDE employs a graph attention network enhanced with diffusion on protein-protein interactions. By constructing a weighted protein-protein interaction network, GATDE captures the diversity of these interactions and uses a diffusion process to assess multi-hop influences between proteins. This information is subsequently incorporated into the graph attention network, resulting in precise cancer classification. Experimental results on breast cancer and pan-cancer datasets demonstrate that GATDE surpasses current leading methods. Additionally, in-depth case studies further validate the effectiveness of the diffusion process and the attention mechanism, highlighting GATDE's robustness and potential for real-world applications.

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Plant phytochromes perceive red and far-red light to elicit adaptations to the changing environment. Downstream physiological responses revolve around red-light-induced interactions with phytochrome-interacting factors (PIF). Phytochromes double as thermoreceptors, owing to the pronounced temperature dependence of thermal reversion from the light-adapted Pfr to the dark-adapted Pr state. Here, we assess whether thermoreception may extend to the phytochrome:PIF interactions. While the association between Arabidopsis (Arabidopsis thaliana) PHYTOCHROME B (PhyB) and several PHYTOCHROME-INTERACTING FACTOR (PIF) variants moderately accelerates with temperature, the dissociation does more so, thus causing net destabilization of the phytochrome:PIF complex. Markedly different temperature profiles of PIF3 and PIF6 might underlie stratified temperature responses in plants. Accidentally, we identify a photoreception mechanism under strong continuous light, where the extent of phytochrome:PIF complexation decreases with red-light intensity rather than increases. Mathematical modeling rationalizes this attenuation mechanism and ties it to rapid red-light-driven Pr⇄Pfr interconversion and complex dissociation out of Pr. Varying phytochrome abundance, e.g., during diurnal and developmental cycles, and interaction dynamics, e.g., across different PIFs, modify the nature and extent of attenuation, thus permitting light-response profiles more malleable than possible for the phytochrome Pr⇄Pfr interconversion alone. Our data and analyses reveal a photoreception mechanism with implications for plant physiology, optogenetics, and biotechnological applications.

RESUMEN

Lytic phages control the timepoint of host cell lysis by timing the holin-mediated release of cell wall-degrading endolysins. In phage T4, the antiholin RI inhibits the holin T, thereby preventing the early release of the T4 endolysin and lysis. The antiholin achieves lysis inhibition (LIN) in response to phage superinfections, thereby increasing the chance for lysis in an environment with a lower phage concentration. The holin T consists of a small N-terminal cytoplasmic domain, a transmembrane helix, and a periplasmic C-terminal domain. The antiholin is targeted to the periplasm by a cleavable signal peptide. Recently, the periplasmic soluble domains of the holin and the antiholin were found to form T2/RI2 tetramers in crystals. To investigate the functional relevance of this complex, we reconstituted LIN in a phage-free system, using only RI, T, and endolysin, and combined targeted mutagenesis with functional analyses. Inactivation of the RI signal peptide cleavage site did not abolish LIN, indicating that RI can function in a membrane-bound state, which argued against the tetramer. This led to analyses showing that only one of the two T/RI interfaces in the tetramer is physiologically relevant, which is also the only interaction site predicted by AlphaFold2. Some holin mutations at this interaction site prevented lysis, suggesting that the RI interaction likely acts by blocking the holin oligomerization required for hole formation. We conclude that LIN is mediated by a dimeric T/RI complex that, unlike the tetramer, can be easily formed when both partners are membrane-anchored.

RESUMEN

Elevated levels of Inter-alpha-trypsin-inhibitor heavy chain 4 (ITIH4) have grabbed attention in rheumatoid arthritis (RA) pathogenesis, though its precise mechanisms remain unexplored. To elucidate these mechanisms, a comprehensive strategy employing network pharmacology and molecular docking was utilized. RA targets were sourced from the DisGeNET Database while interacting targets of ITIH4 were retrieved from the STRING and Literature databases. Venny 2.1 was used to identify overlapping genes, followed by Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) through Cytoscape 3.10.2 software, and molecular docking was performed in the ClusPro server. The study identified 18 interacting proteins of ITIH4 associated with RA, demonstrating their major involvement in the chemokine signaling pathway by enrichment analysis. Molecular docking of ITIH4 with the 18 proteins revealed that C-X-C chemokine-receptor type 4 (CXCR4), a major protein associated with chemokine signaling, has the highest binding affinity with ITIH4 with energy -1705.7 kcal/mol forming 3 Hydrogen bonds in the active site pocket of ITIH4 with His441, Arg288, Asp443 amino acids. The effect of ITIH4 on CXCR4 was analyzed via knockdown studies in rheumatoid arthritis fibroblast-like synoviocytes (RA-FLS), demonstrating the significant downregulation of CXCR4 protein expression validated by Western blot in RA-FLS. In conclusion, it was speculated that CXCR4 might serve as a potential receptor for ITIH4 to activate the chemokine signaling, exacerbating RA pathogenesis.

RESUMEN

Proximity ligation assay has been widely used to detect protein-protein interaction in cells and tissues. While with great sensitivity, its specificity was often neglected. Here, we report the existence of varying levels of false positives observed with this assay and provide suggestions to minimize false positives for more accurate detection of protein-protein interactions, especially for membrane proteins.

RESUMEN

OBJECTIVES: Signal transducer and activator of transcription 3 (STAT3) is one of the key proliferation mechanism-related proteins that helps in oral squamous cell carcinoma (OSCC) progression. Immune evasion by STAT3 is mediated by the JAK2/STAT3/PDL1 signaling axis. Based on previous findings, we hypothesized that STAT3-binding partners participate in the inhibition of anti-tumor activity in OSCC. METHODS: A 3D cancer-immune co-culture model was constructed using oral cancer cell lines SCC4, SCC9, SCC25, and CAL27 and normal oral cell line OKF6. The cells were co-cultured with natural killer (NK-92) and Jurkat cells. The target protein STAT3 was chosen based on SWATH data, and co-immunoprecipitation (Co-IP)-based proteomics was conducted. The Co-IP LC-MS/MS output was analyzed to determine the protein interaction network, gene ontology, pathway analysis, and protein cluster annotation. RESULTS: STAT3 in oral cancer cell lines interacts with the epidermal growth factor receptor (EGFR) and other proteins that participate in proliferation and immune mechanisms. Proteome analysis showed that some STAT3-binding proteins found in this study are known immune system regulators. CONCLUSION: Overall, STAT3 interactive proteins regulate the immune system in oral squamous cell carcinoma cells.

RESUMEN

Colon cancer is a significant public health issue, and a deeper understanding of the molecular fundamentals [16] ehind is required to improve sensitivity and curability. This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein "Relatively of liver tumorigenesis", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. The gene ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. Furthermore, survival analysis displayed that there was a strong correlation between NDUFAF4 expression and the patients' longevity suggesting that this factor may be important in colon cancer prognosis as well. The TCGA data proved that NDUFAF4 is elevated in colon cancer making the results of the analysis reported credible. All of the above justified the understanding of the role and importance of NDUFAF4 in treating each colon cancer patient as a molecular target. The findings help in understanding the colon cancer pathogenesis and suggest ways for developing more efficient diagnosis and treatment of the disease. SIGNIFICANCE: This research explored the gene NDUFAF4 as a target of concern due to its link to a mitochondrial function and protein "Relatively of liver tumorigenesis", which remains unclear is attributable to its inclusion into the complex I (CI) pathway. Using a comprehensive approach to Gene Ontology analysis, Protein-Protein Interaction network modelling, survival analysis, KEGG pathway analysis, and validation using TCGA data, we identified the activities of NDUFAF4 in colon cancer. The Gene Ontology analysis, in turn, showed that NDUFAF4 is a key player in several critical biological phases linked to mitochondrial function and energy metabolism. The construction of the PPI network illustrates the interactors of NDUFAF4, the functional association protein within the cellular regulatory networks. In addition, survival analysis indicated that there was a considerable relationship between the expression of NDUFAF4 and patient survival, indicating its potential role as a prognostic factor in colon cancer. KEGG pathway analysis suggested that NDUFAF4 plays a role in thermogenesis and mitochondrial biogenesis, biological processes that should be targeted due to their implication in cellular metabolism and cancer onset. The use of TCGA information confirmed the upregulation of NDUFAF4 in colon cancer, thus making the findings of the analysis reported dependable. Overall, our study provided necessary information on the role and significance of NDUFAF4, a potential molecular target in colon cancer cases. These present findings enhance our knowledge of the pathogenesis of colon cancer and open new opportunities for designing novel diagnostic and therapeutic approaches to improve patient outcomes.

RESUMEN

Introduction: Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, we used bioinformatics analysis to identify potential biomarkers and therapeutic targets for ESCC. Methodology: Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained by comprehensively analyzing publicly available RNA-seq datasets from the TCGA and GTEX. Gene Ontology (GO) annotation and Reactome pathway analysis identified the biological roles of the DEGs. Moreover, the Cytoscape 3.10.1 platform and subsidiary tools such as CytoHubba were used to visualize the DEGs' protein-protein interaction (PPI) network and identify hub genes, Furthermore our results are validated by using Single-cell RNA analysis. Results: Identification of 2524 genes exhibiting altered expression enriched in pathways including keratinization, epidermal cell differentiation, G alpha(s) signaling events, and biological process of cell proliferation and division, extracellular matrix (ECM) disassembly, and muscle function. Moreover, upregulation of hallmarks E2F targets, G2M checkpoints, and TNF signaling. CytoHubba revealed 20 hub genes that had a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of four genes, CDK1 MAD2L1, PLK1, and TOP2A, were associated with critical dependence for cell survival in ESCC cell lines, as indicated by CRISPR dependency scores, gene expression data, and cell line metadata. We also identify the molecules targeting these essential hub genes, among which GSK461364 is a promising inhibitor of PLK1, BMS265246, and Valrubicin inhibitors of CDK1 and TOP2A, respectively. Moreover, we identified that elevated expression of MMP9 is associated with worse overall survival in ESCC patients, which may serve as potential prognostic biomarker or therapeutic target for ESCC. The single-cell RNA analysis showed MMP9 is highly expressed in myeloid, fibroblast, and epithelial cells, but low in T cells, endothelial cells, and B cells. This suggests MMP9's role in tumor progression and matrix remodeling, highlighting its potential as a prognostic marker and therapeutic target. Discussion: Our study identified key hub genes in ESCC, assessing their potential as therapeutic targets and biomarkers through detailed expression and dependency analyses. Notably, MMP9 emerged as a significant prognostic marker with high expression correlating with poor survival, underscoring its potential for targeted therapy. These findings enhance our understanding of ESCC pathogenesis and highlight promising avenues for treatment.

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Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to enhance accuracy of the biomarker discovery. However, previous ML-based studies often overlook interactions between proteins, which are crucial in complex disorders like dementia. While protein-protein interactions (PPIs) have been used in network models, these models often fail to fully capture the diverse properties of PPIs due to their local awareness. This drawback increases the chance of neglecting critical components and magnifying the impact of noisy interactions. In this study, we propose a novel graph-based ML model for dementia subtype diagnosis, the graph propagational network (GPN). By propagating the independent effect of plasma proteins on PPI network, the GPN extracts the globally interactive effects between proteins. Experimental results showed that the interactive effect between proteins yielded to further clarify the differences between dementia subtype groups and contributed to the performance improvement where the GPN outperformed existing methods by 10.4% on average.

Asunto(s)

Biomarcadores , Proteínas Sanguíneas , Demencia , Aprendizaje Automático , Mapas de Interacción de Proteínas , Humanos , Demencia/metabolismo , Demencia/diagnóstico , Proteínas Sanguíneas/metabolismo , Mapeo de Interacción de Proteínas/métodos , Algoritmos , Biología Computacional/métodos

RESUMEN

COVID-19 has caused millions of deaths and many times more infections worldwide, emphasizing the unpreparedness of the global health system in the face of new infections and the key role for vaccines and therapeutics, including virus-neutralizing antibodies, in prevention and containment of the disease. Continuous evolution of the SARS-CoV-2 coronavirus has been causing its new variants to evade the action of the immune system, which highlighted the importance of detailed knowledge of the epitopes of already selected potent virus-neutralizing antibodies. A single-chain antibody ("nanobody") targeting the SARS-CoV-2 receptor-binding domain (RBD), clone P2C5, had exhibited robust virus-neutralizing activity against all SARS-CoV-2 variants and, being a major component of the anti-COVID-19 formulation "GamCoviMab", had successfully passed Phase I of clinical trials. However, after the emergence of the Delta and XBB variants, a decrease in the neutralizing activity of this nanobody was observed. Here we report on the successful crystal structure determination of the RBD:P2C5 complex at 3.1 Å, which revealed the intricate protein-protein interface, sterically occluding full ACE2 receptor binding by the P2C5-neutralized RBD. Moreover, the structure revealed the developed RBD:P2C5 interface centered around residues Leu452 and Phe490, thereby explaining the evasion of the Delta or Omicron XBB, but not Omicron B.1.1.529 variant, as a result of the single L452R or F490S mutations, respectively, from the action of P2C5. The structure obtained is expected to foster nanobody engineering in order to rescue neutralization activity and will facilitate epitope mapping for other neutralizing nanobodies by competition assays.

Asunto(s)

Anticuerpos Neutralizantes , SARS-CoV-2 , Anticuerpos de Dominio Único , Glicoproteína de la Espiga del Coronavirus , SARS-CoV-2/inmunología , SARS-CoV-2/efectos de los fármacos , Anticuerpos de Dominio Único/inmunología , Anticuerpos de Dominio Único/química , Anticuerpos de Dominio Único/farmacología , Anticuerpos Neutralizantes/inmunología , Anticuerpos Neutralizantes/química , Humanos , Glicoproteína de la Espiga del Coronavirus/inmunología , Glicoproteína de la Espiga del Coronavirus/química , Glicoproteína de la Espiga del Coronavirus/genética , Glicoproteína de la Espiga del Coronavirus/metabolismo , Anticuerpos Antivirales/inmunología , COVID-19/inmunología , COVID-19/virología , Dominios Proteicos , Unión Proteica , Epítopos/inmunología , Epítopos/química , Modelos Moleculares , Evasión Inmune , Enzima Convertidora de Angiotensina 2/metabolismo , Enzima Convertidora de Angiotensina 2/química , Enzima Convertidora de Angiotensina 2/inmunología , Sitios de Unión

RESUMEN

The use of computational methods in drug discovery research has increased substantially in recent years. Computational chemistry techniques, such as quantum chemical calculations and molecular dynamics simulations, continue to be widely used. In this review, we focused on drug discovery-related studies that employ fragment molecular orbital methods. Furthermore, we focused on inhibitor discovery, protein-protein interaction analysis, including antigen-antibody interaction analysis, and integration with molecular dynamics simulations.

Asunto(s)

Descubrimiento de Drogas , Simulación de Dinámica Molecular , Humanos , Teoría Cuántica , Proteínas/química , Proteínas/antagonistas & inhibidores , Proteínas/metabolismo , Unión Proteica

RESUMEN

Inhibition of CD95/Fas activation is currently under clinical investigation as a therapy for glioblastoma multiforme and preclinical studies suggest that disruption of the CD95-CD95L interaction could also be a strategy to treat inflammatory and neurodegenerative disorders. Besides neutralizing anti-CD95L/FasL antibodies, mainly CD95ed-Fc, a dimeric Fc fusion protein of the extracellular domain of CD95 (CD95ed), is used to prevent CD95 activation. In view of the fact that full CD95 activation requires CD95L-induced CD95 trimerization and clustering of the resulting liganded CD95 trimers, we investigated whether fusion proteins of the extracellular domain of CD95 with a higher valency than CD95ed-Fc have an improved CD95L-neutralization capacity. We evaluated an IgG1(N297A)-based tetravalent CD95ed fusion protein which was obtained by replacing the variable domains of IgG1(N297A) with CD95ed (CD95ed-IgG1(N297A)) and a hexavalent variant obtained by fusion of CD95ed with a TNC-Fc(DANA) scaffold (CD95ed-TNC-Fc(DANA)) promoting hexamerization. The established N297A and DANA mutations were used to minimize FcγR binding of the constructs under maintenance of neonatal Fc receptor (FcRn) binding. Size exclusion high-performance liquid chromatography indicated effective assembly of CD95ed-IgG1(N297A). More important, CD95ed-IgG1(N297A) was much more efficient than CD95ed-Fc in protecting cells from cell death induction by human and murine CD95L. Surprisingly, despite its hexavalent structure, CD95ed-TNC-Fc(DANA) displayed an at best minor improvement of the capacity to neutralize CD95L suggesting that besides valency, other factors, such as spatial organization and agility of the CD95ed domains, play also a role in neutralization of CD95L trimers by CD95ed fusion proteins. More studies are now required to evaluate the superior CD95L-neutralizing capacity of CD95ed-IgG1(N297A) in vivo.

RESUMEN

Background: Risperidone is one of the most reliable and effective antipsychotics for schizophrenia treatment. However, the mechanism of action of risperidone is not yet fully understood. Traf2 and Nck-interacting protein kinase (TNIK), a schizophrenia susceptibility gene, is associated with risperidone treatment response. Our previous in vitro experiments confirmed that downregulated TNIK affected the effect of risperidone on downstream targets. However, the effect of downregulated TNIK on risperidone-induced molecular expression remains to be further explored. Methods: Transcriptome analysis was performed on U251 cells subjected to risperidone, TNIK siRNA, and no treatment, respectively. Compared to the no-treatment group, two groups of DEGs were screened out and then intersected with the schizophrenia-related genes to screen the cross-talk genes. Those DEGs were analyzed using GO and KEGG. STRING and Cytoscape were used to construct a protein-protein interaction (PPI) network for the cross-talk gene. Results: The results showed that the parathyroid hormone synthesis, secretion, and action were significantly enriched after risperidone treatment. Downregulated TNIK could have an impact on the collagen-containing extracellular matrix, signaling receptor activator activity, and PI3K-Akt signaling pathway. Interestingly, bone mineralization function and calcium signaling pathway were enriched in the cross-talk genes. Additionally, FGFR2, FGF1, and FGFR might be the potential targets for TNIK affecting the effects of risperidone. Conclusion: The study indicated that risperidone primarily influences functions and/or pathways associated with bone metabolism, potentially contributing to the adverse effect of osteoporosis. Our study may offer a novel perspective on investigating the mechanisms underlying the adverse effects of risperidone.

RESUMEN

The use of prior knowledge in the machine learning framework has been considered a potential tool to handle the curse of dimensionality in genetic and genomics data. Although random forest (RF) represents a flexible non-parametric approach with several advantages, it can provide poor accuracy in high-dimensional settings, mainly in scenarios with small sample sizes. We propose a knowledge-slanted RF that integrates biological networks as prior knowledge into the model to improve its performance and explainability, exemplifying its use for selecting and identifying relevant genes. knowledge-slanted RF is a combination of two stages. First, prior knowledge represented by graphs is translated by running a random walk with restart algorithm to determine the relevance of each gene based on its connection and localization on a protein-protein interaction network. Then, each relevance is used to modify the selection probability to draw a gene as a candidate split-feature in the conventional RF. Experiments in simulated datasets with very small sample sizes ( n ≤ 30 ) comparing knowledge-slanted RF against conventional RF and logistic lasso regression, suggest an improved precision in outcome prediction compared to the other methods. The knowledge-slanted RF was completed with the introduction of a modified version of the Boruta feature selection algorithm. Finally, knowledge-slanted RF identified more relevant biological genes, offering a higher level of explainability for users than conventional RF. These findings were corroborated in one real case to identify relevant genes to calcific aortic valve stenosis.