B-cell receptor (BCR) signals play a critical role in the pathogenesis of chronic lymphocytic leukemia (CLL), but their role in regulating CLL cell proliferation has still not been firmly established. Unlike normal B cells, CLL cells do not proliferate in vitro upon engagement of the BCR, suggesting that CLL cell proliferation is regulated by other signals from the microenvironment, such as those provided by Toll-like receptors or T cells. Here, we report that BCR engagement of human and murine CLL cells induces several positive regulators of the cell cycle, but simultaneously induces the negative regulators CDKN1A, CDKN2A, and CDKN2B, which block cell-cycle progression. We further show that introduction of genetic lesions that downregulate these cell-cycle inhibitors, such as inactivating lesions in CDKN2A, CDKN2B, and the CDKN1A regulator TP53, leads to more aggressive disease in a murine in vivo CLL model and spontaneous proliferation in vitro that is BCR dependent but independent of costimulatory signals. Importantly, inactivating lesions in CDKN2A, CDKN2B, and TP53 frequently co-occur in Richter syndrome (RS), and BCR stimulation of human RS cells with such lesions is sufficient to induce proliferation. We also show that tumor cells with combined TP53 and CDKN2A/2B abnormalities remain sensitive to BCR-inhibitor treatment and are synergistically sensitive to the combination of a BCR and cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor both in vitro and in vivo. These data provide evidence that BCR signals are directly involved in driving CLL cell proliferation and reveal a novel mechanism of Richter transformation.

The enormous quantity of publicly available active chemical ligand and biological receptor data knowledge allows scientists to retreat several open questions by the analysis and systematic integration of these complex unique data. Systems biology plays a crucial role through the constructive alignment of bio-physiochemical monitoring of gene, protein along with metabolites from the complex data. Further, it integrates information within the data and responses (metabolic and signaling pathway) which lead to the formulation of computational models for the elucidation of structure and function of the molecular determinant. The system biology methods utilize big complex high throughput data for the identification of the whole drug target and for the mechanism of action to lead compound characterization. Nowadays, the system biology is one of the most popular approaches to characterize proteinligand interaction on a large scale and is vital to address a complex mode of the drug action to clinical indications. The network of protein-ligand interactions also reveals the correlation between molecular functions of the cell with their physiological processes which help to design safe and effective ligands for drug development. Here, we review recent attempts to apply system biology-based approaches with large-scale network analyses to predict novel interactions of ligand and targets. We also deliver an essential step involved in the discovery and development of such multi‐target drugs by identifying the group of proteins targeted by a particular ligand, leading to innovation in therapeutic research.

Alzheimer’s disease (AD), the most common type of dementia in older people, causes neurological problems associated with memory and thinking. The key enzymes involved in Alzheimer’s disease pathways are acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). Because of this, there is a lot of interest in finding new AChE inhibitors. Among compounds that are not alkaloids, flavonoids have stood out as good candidates. The apple fruit, Malus domestica (Rosaceae), is second only to cranberries regarding total phenolic compound concentration. Computational tools and biological databases were used to investigate enzymes and natural compounds. Molecular docking techniques were used to analyze the interactions of natural compounds of the apple with enzymes involved in the central nervous system (CNS), acetylcholinesterase, and butyrylcholinesterase, followed by binding affinity calculations using the AutoDock tool. The molecular docking results revealed that CID: 107905 exhibited the best interactions with AChE, with a binding affinity of −12.2 kcal/mol, and CID: 163103561 showed the highest binding affinity with BuChE, i.e., −11.2 kcal/mol. Importantly, it was observed that amino acid residue Trp286 of AChE was involved in hydrogen bond formation, Van Der Walls interactions, and Pi–Sigma/Pi–Pi interactions in the studied complexes. Moreover, the results of the Molecular Dynamics Simulation (MDS) analysis indicated interaction stability. This study shows that CID: 12000657 could be used as an AChE inhibitor and CID: 135398658 as a BuChE inhibitor to treat Alzheimer’s disease and other neurological disorders.

Deficiency of necessary macronutrients, i.e. Potassium (K), Magnesium (Mg), Nitrogen (N), Phosphorus (P), and Sulfate (S) in the soil leads to a reduction in plant growth and yield, which is a result of changes in expression level of various genes. This study was performed to identify the differentially expressed genes and its associated metabolic pathways occurred in soil grown wheat root samples excavated from the control and treated fields. To identify the difference in gene expression levels due to deficiency of the said nutrients, a transcriptomic, meta-analysis was performed on array expression profile data. A set of 435 statistically significant probes encoding 398 Nutrient Deficiency Response Genes (NRGs) responding at-least one nutrients deficiency (ND) were identified. Out of them 55 NRGs were found to response to minimum two ND. Singular Enrichment Analysis (SEA) predicts ontological based classifications and functional analysis of NRGs in different cellular/molecular pathways involved in root development and growth. Functional annotation and reaction mechanism of differentially expressed genes, proteins/enzymes in the different metabolic pathway through MapMan analysis were explored. Further the meta-analysis was performed to revels the active involvement each NRGs in distinct tissues and their comparative potential expression analysis in different stress conditions. The study results in exploring the role of major acting candidate genes such as Non-specific serine/threonine protein kinase, Xyloglucan endotransglucosylase/hydrolase, Peroxides, Glycerophosphoryl diester phosphodiesterase, S-adenosylmethionine decarboxylase proenzyme, Dehydrin family proteins, Transcription factors, Membrane Proteins, Metal binding proteins, Photosystem proteins, Transporter and Transferase associated in different metabolic pathways. Finally, the differences of transcriptional responses in the soil-grown root of T. aestivum cv. and in-vitro grown model plants under nutrients deficiency were summarized.