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Therapeutic intervention in cyclin-dependent kinase-like 5 (CDKL5) deficiency disorders (CDDs) has remained a concern over the years. Recent advances into the mechanistic interplay of signalling pathways has revealed the role of deficient tropomyosin receptor kinase B (TrkB)/phospholipase C γ1 signalling cascade in CDD. Novel findings showed that in vivo administration of a TrkB agonist, 7,8-dihydroxyflavone (7,8-DHF), resulted in a remarkable reversal in the molecular pathologic mechanisms underlying CDD. Owing to this discovery, this study aimed to identify more potent TrkB agonists than 7,8-DHF that could serve as alternatives or combinatorial drugs towards effective management of CDD. Using pharmacophore modelling and multiple database screening, we identified 691 compounds with identical pharmacophore features with 7,8-DHF. Virtual screening of these ligands resulted in identification of at least 6 compounds with better binding affinities than 7,8-DHF. The in silico pharmacokinetic and ADMET studies of the compounds also indicated better drug-like qualities than those of 7,8-DHF. Postdocking analyses and molecular dynamics simulations of the best hits, 6-hydroxy-10-(2-oxo-1-azatricyclo[7.3.1.05,13]trideca-3,5(13),6,8-tetraen-3-yl)-8-oxa-13,14,16-triazatetracyclo[7.7.0.02,7.011,15]hexadeca-1,3,6,9,11,15-hexaen-5-one (PubChem: 91637738) and 6-hydroxy-10-(8-methyl-2-oxo-1H-quinolin-3-yl)-8-oxa-13,14,16-triazatetracyclo[7.7.0.02,7.011,15]hexadeca-1,3,6,9,11,15-hexaen-5-one (PubChem ID: 91641310), revealed unique ligand interactions, validating the docking findings. We hereby recommend experimental validation of the best hits in CDKL5 knock out models before consideration as drugs in CDD management.

Hepatic encephalopathy (HE) is a set of complex neurological complications that arise from advanced liver disease. The precise molecular and cellular mechanism of HE is not fully understood. Differentially expressed genes (DEGs) from microarray technologies are powerful approaches to obtain new insight into the pathophysiology of HE. We analyzed microarray data sets of cirrhotic patients with HE from Gene Expression Omnibus to identify DEGs in postmortem cerebral tissues. Consequently, we uploaded significant DEGs into the STRING to specify protein-protein interactions. Cytoscape was used to reconstruct the genetic network and identify hub genes. Target genes were uploaded to different databases to perform comprehensive enrichment analysis and repurpose new therapeutic options for HE. A total of 457 DEGs were identified in 2 data sets totally from 12 cirrhotic patients with HE compared with 12 healthy subjects. We found that 274 genes were upregulated and 183 genes were downregulated. Network analyses on significant DEGs indicated 12 hub genes associated with HE. Enrichment analysis identified fatty acid beta-oxidation, cerebral organic acidurias, and regulation of actin cytoskeleton as main involved pathways associated with upregulated genes; serotonin receptor 2 and ELK-SRF/GATA4 signaling, GPCRs, class A rhodopsin-like, and p38 MAPK signaling pathway were related to downregulated genes. Finally, we predicted 39 probable effective drugs/agents for HE. This study not only confirms main important involved mechanisms of HE but also reveals some yet unknown activated molecular and cellular pathways in human HE. In addition, new targets were identified that could be of value in the future study of HE.

Plasmodium falciparum Apicomplexan Apetala 2 Invasion (PfAP2-I) transcription factor (TF) is a protein that regulates the expression of a subset of gene families involved in P. falciparum red blood cell (RBC) invasion. Inhibiting PfAP2-I TF with small molecules represents a potential new antimalarial therapeutic target to combat drug resistance, which this study aims to achieve. The 3D model structure of PfAP2-I was predicted ab initio using ROBETTA prediction tool and was validated using Save server 6.0 and MolProbity. Computed Atlas of Surface Topography of proteins (CASTp) 3.0 was used to predict the active sites of the PfAP2-I modeled structure. Pharmacophore modeling of the control ligand and PfAP2-I modeled structure was carried out using the Pharmit server to obtain several compounds used for molecular docking analysis. Molecular docking and postdocking studies were conducted using AutoDock vina and Discovery studio. The designed ligands' toxicity predictions and in silico drug-likeness were performed using the SwissADME predictor and OSIRIS Property Explorer. The modeled protein structure from the ROBETTA showed a validation result of 96.827 for ERRAT, 90.2% of the amino acid residues in the most favored region for the Ramachandran plot, and MolProbity score of 1.30 in the 98th percentile. Five (5) best hit compounds from molecular docking analysis were selected based on their binding affinity (between -8.9 and -11.7 Kcal/mol) to the active site of PfAP2-I and were considered for postdocking studies. For the absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, compound MCULE-7146940834 had the highest drug score (0.63) and drug-likeness (6.76). MCULE-7146940834 maintained a stable conformation within the flexible protein's active site during simulation. The good, estimated binding energies, drug-likeness, drug score, and molecular dynamics simulation interaction observed for MCULE-7146940834 against PfAP2-I show that MCULE-7146940834 can be considered a lead candidate for PfAP2-I inhibition. Experimental validations should be carried out to ascertain the efficacy of these predicted best hit compounds.

Reproductive traits are affected by many factors, including ovarian function, hormones, and genetics. Genetic polymorphisms of candidate genes are associated with reproductive traits. Several candidate genes are associated with economic traits, including the follistatin (FST) gene. Thus, this study aimed to evaluate whether the genetic variations in the FST gene are associated with the reproductive traits in Awassi ewes. The genomic DNA was extracted from 109 twin ewes and 123 single-progeny ewes. Therefore, 4 sequence fragments from the FST gene were amplified using polymerase chain reaction (PCR) (exon 2/240, exon 3/268, exon 4/254, and exon 5/266 bp, respectively). For a 254 bp amplicon, 3 genotypes were identified: CC, CG, and GG. Sequencing revealed a novel mutation in CG genotypes c.100C > G. The statistical analysis of c.100C > G showed an association with reproductive characteristics. Ewes carrying the c.100C > G had significantly (P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing compared with CG and CC genotypes. Logistic regression analysis confirmed that the c.100C > G single-nucleotide polymorphism (SNP) is responsible for decreasing litter size. According to these results, the variant c.100C > G negatively affects the traits of interest and is associated with lower reproductive traits in Awassi sheep. As a result of this study, ewes carrying the c.100C > G SNP have lower litter size and are less prolific.

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Several genes influence sheep's reproductive performance, among them the paired-like homeodomain transcription factor 2 (PITX2) gene. Thus, this study aimed to examine whether the variability within the PITX2 gene is associated with the reproductive performance of Awassi ewes. A total of 123 single-progeny ewes and 109 twin ewes were used to extract genomic DNA. An amplicon of 4 sequence fragments from exons 2, 4, 5 (upstream portion), and 5 (downstream portion) of the PITX2 gene was generated by polymerase chain reaction (PCR), 228, 304, 381, and 382 bp, respectively. Three genotypes of 382 bp amplicons were identified: CC, CT, and TT. Sequence analysis revealed a novel mutation in the CT genotype 319C > T. Statistical analysis revealed that single-nucleotide polymorphism (SNP) 319C > T was associated with reproductive performance. Single-nucleotide polymorphism 319C > T-carrying ewes had significantly (P ⩽ .01) lower litter sizes, twinning rates, lambing rates, and more days to lambing than those carrying CT and CC genotypes. Based on a logistic regression analysis, it was confirmed that the 319C > T SNP decreased litter size. Ewes with TT genotype produced fewer lambs than ewes with CT and CC genotypes. According to these results, the variant 319C> T SNP negatively affects the reproductive performance of Awassi sheep. Ewes carrying the 319C > T SNP have a lower litter size and are less prolific than those without the SNP.

Aim: Antibiotics treat various diseases by targeting microorganisms by killing them or reducing their multiplication rate. New Delhi Metallo-beta-lactamase-1 (NDM-1) is produced by bacteria possessing the resistance gene blaNDM-1, the enzyme that makes bacteria resistant to beta-lactams. Bacteriophages, especially Lactococcus, have shown their ability to break down lactams. Hence, the current study computationally evaluated the binding potential of Lactococcus bacteriophages with NDM using Molecular docking and dynamics.

Methods: Modelling of NDM I-TASSER for Main tail protein gp19 OS=Lactococcus phage LL-H or Lactobacillus delbrueckii subsp. lactis after downloading from UNIPROT ID- Q38344. Cluspro tool helps in Understanding cellular function and organization with protein-protein interactions. MD simulations(19) typically compute atom movements over time. Simulations were used to predict the ligand binding status in the physiological environment.

Results: The best binding affinity score was found -1040.6 Kcal/mol compared to other docking scores. MD simulations show in RMSD values for target remains within 1.0 Angstrom, which is acceptable. The ligand-protein fit to receptor protein RMSD values of 2.752 fluctuates within 1.5 Angstrom after equilibration.

Conclusions: Lactococcus bacteriophages showed a strong affinity to the NDM. Hence, this hypothesis, supported by evidence from a computational approach, will solve this life-threatening superbug problem.

The activation of the Wnt signaling pathway is implicated in a neuroprotective mechanism against the Alzheimer disease. When this pathway is blocked, it activates GSK3 beta, leading to tau hyperphosphorylation and the apoptosis of neurons. Dickkopf-related protein 1 (DKK1) is a protein that competes with the Wnt ligand for the low-density lipoprotein receptor-related protein 6 (LRP6) receptor's binding, interrupting the Wnt-induced Fzd-Wnt-LRP6 complex. This counteracts Wnt's neuroprotective effect and contributes to the progression of the Alzheimer disease. The aim of this study was to use in silico approach to develop new agents that can combat the Alzheimer disease by targeting the interaction between DKK1 and LRP6. To achieve this, we conducted a virtual screening (Vsw) of the Asinex-CNS database library (n = 54 513) compounds against a generated grid in LRP6 protein. From this screening, we selected 6 compounds based on their docking score and performed molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations on the selected ligands. Next, we evaluated the Absorption, Distribution, Metabolism, and Excretion (ADME) results of the 6 screened compounds using the Quick prop module of Schrödinger. We then employed several computational techniques, including PCA (Principal Component Analysis), DCCM (Dynamic Cross-Correlation Map), molecular dynamics simulation, and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA)-based negative binding free energy (BFE) calculation, to further analyze the compounds. Our extensive computational analysis resulted in the identification of 3 potential hits, LAS 29757582, LAS 29984441, and LAS 29757942. These compounds were found to block the interaction of DKK1 with LRP6 (A and B interface) protein, and their potential as therapeutic agents was supported by negative BFE calculation. Therefore, these compounds show potential as possible therapeutic agents for treating the Alzheimer disease through targeting the interaction between DKK1 and LRP6.

Tumor microenvironment is characterized by the occurrence of significant changes due to disrupted signaling pathways that affect a broad spectrum of cellular activities such as proliferation, differentiation, signaling, invasiveness, migration, and apoptosis. Similarly, a downregulated suppressor of cytokine signaling 3 (SOCS3) promotes increased JAK/STAT function due to aberrant cytokine signaling, which results in increased cell proliferation, differentiation, and migration. Multiple carcinomas including breast cancer, prostate cancer, hepatocellular carcinoma, pancreatic cancer, and colorectal cancer involve the disruption of SOCS3 expression due to microRNA overexpression. MicroRNAs are small, conserved, and non-coding RNA molecules that regulate gene expression through post-transcriptional inhibition and mRNA destabilization. The aim of this study was to identify putative microRNAs that interact with SOCS3 and downregulate its expression. In this study, miRWalk, TargetScan, and miRDB were used to identify microRNAs that interact with SOCS3, whereas RNA22 was utilized to identify the binding sites of 238 significant microRNAs. The tertiary structures of shortlisted microRNAs and SOCS3 regions were predicted through MC Sym and RNAComposer, respectively. For molecular docking, HDOCK was used, which predicted 80 microRNA-messengerRNA complexes and the interactions of the top 5 shortlisted complexes were assessed. The complexes were shortlisted on the basis of least binding affinity score and maximum confidence score. This study identifies the interactions of known (miR-203a-5p) and novel (miR-6756-5p, miR-6732-5p, miR-1203, miR-6887-5p) microRNAs with SOCS3 regions due to their maximum interactions. Identifying the interactions of these microRNAs with SOCS3 will significantly advance the understanding of oncomiRs (miRNAs that are associated with cancer development) in tumor development due to their influence on SOCS3 expression. These insights will assist in future studies to understand the significance of miRNA-SOCS3-associated tumor development and progression.

Drug-resistant tuberculosis (TB), which results mainly from the selection of naturally resistant strains of Mycobacterium tuberculosis (MTB) due to mismanaged treatment, poses a severe challenge to the global control of TB. Therefore, screening novel and unique drug targets against this pathogen is urgently needed. The metabolic pathways of Homo sapiens and MTB were compared using the Kyoto Encyclopedia of Genes and Genomes tool, and further, the proteins that are involved in the metabolic pathways of MTB were subtracted and proceeded to protein-protein interaction network analysis, subcellular localization, drug ability testing, and gene ontology. The study aims to identify enzymes for the unique pathways for further screening to determine the feasibility of the therapeutic targets. The qualitative characteristics of 28 proteins identified as drug target candidates were studied. The results showed that 12 were cytoplasmic, 2 were extracellular, 12 were transmembrane, and 3 were unknown. Furthermore, druggability analysis revealed 14 druggable proteins, of which 12 were novel and responsible for MTB peptidoglycan and lysine biosynthesis. The novel targets obtained in this study are used to develop antimicrobial treatments against pathogenic bacteria. Future studies should further shed light on the clinical implementation to identify antimicrobial therapies against MTB.