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Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design and discovery. Further, complex and big data from genomics, proteomics, microarray data, and clinical trials also impose an obstacle in the drug discovery pipeline. Artificial intelligence and machine learning technology play a crucial role in drug discovery and development. In other words, artificial neural networks and deep learning algorithms have modernized the area. Machine learning and deep learning algorithms have been implemented in several drug discovery processes such as peptide synthesis, structure-based virtual screening, ligand-based virtual screening, toxicity prediction, drug monitoring and release, pharmacophore modeling, quantitative structure–activity relationship, drug repositioning, polypharmacology, and physiochemical activity. Evidence from the past strengthens the implementation of artificial intelligence and deep learning in this field. Moreover, novel data mining, curation, and management techniques provided critical support to recently developed modeling algorithms. In summary, artificial intelligence and deep learning advancements provide an excellent opportunity for rational drug design and discovery process, which will eventually impact mankind. Graphic abstractThe primary concern associated with drug design and development is time consumption and production cost. Further, inefficiency, inaccurate target delivery, and inappropriate dosage are other hurdles that inhibit the process of drug delivery and development. With advancements in technology, computer-aided drug design integrating artificial intelligence algorithms can eliminate the challenges and hurdles of traditional drug design and development. Artificial intelligence is referred to as superset comprising machine learning, whereas machine learning comprises supervised learning, unsupervised learning, and reinforcement learning. Further, deep learning, a subset of machine learning, has been extensively implemented in drug design and development. The artificial neural network, deep neural network, support vector machines, classification and regression, generative adversarial networks, symbolic learning, and meta-learning are examples of the algorithms applied to the drug design and discovery process. Artificial intelligence has been applied to different areas of drug design and development process, such as from peptide synthesis to molecule design, virtual screening to molecular docking, quantitative structure–activity relationship to drug repositioning, protein misfolding to protein–protein interactions, and molecular pathway identification to polypharmacology. Artificial intelligence principles have been applied to the classification of active and inactive, monitoring drug release, pre-clinical and clinical development, primary and secondary drug screening, biomarker development, pharmaceutical manufacturing, bioactivity identification and physiochemical properties, prediction of toxicity, and identification of mode of action.

Non-cellular secretory components, including chemokines, cytokines, and growth factors in the tumor microenvironment, are often dysregulated, impacting tumorigenesis in Glioblastoma multiforme (GBM) microenvironment, where the prognostic significance of the current treatment remains unsatisfactory. Recent studies have demonstrated the potential of post-translational modifications (PTM) and their respective enzymes, such as acetylation and ubiquitination in GBM etiology through modulating signaling events. However, the relationship between non-cellular secretory components and post-translational modifications will create a research void in GBM therapeutics. Therefore, we aim to bridge the gap between non-cellular secretory components and PTM modifications through machine learning and computational biology approaches. Herein, we highlighted the importance of BMP1, CTSB, LOX, LOXL1, PLOD1, MMP9, SERPINE1, and SERPING1 in GBM etiology. Further, we demonstrated the positive relationship between the E2 conjugating enzymes (Ube2E1, Ube2H, Ube2J2, Ube2C, Ube2J2, and Ube2S), E3 ligases (VHL and GNB2L1) and substrate (HIF1A). Additionally, we reported the novel HAT1-induced acetylation sites of Ube2S (K211) and Ube2H (K8, K52). Structural and functional characterization of Ube2S (8) and Ube2H (1) have identified their association with protein kinases. Lastly, our results found a putative therapeutic axis HAT1-Ube2S(K211)-GNB2L1-HIF1A and potential predictive biomarkers (CTSB, HAT1, Ube2H, VHL, and GNB2L1) that play a critical role in GBM pathogenesis.

Background Reduced levels of endothelial progenitor cells (EPCs) counts have been reported in diabetic mellitus (DM) patients and other diabetes-related disorder. EPCs are a circulating, bone marrow-derived cell population that appears to participate in vasculogenesis, angiogenesis and damage repair. These EPC may revert the damage caused in diabetic condition. We aim to identify several existing drugs and signaling molecule, which could alleviate or improve the diabetes condition via mobilizing and increasing EPC number as well as function. Main body Accumulated evidence suggests that dysregulation of EPC phenotype and function may be attributed to several signaling molecules and cytokines in DM patients. Hyperglycemia alone, through the overproduction of reactive oxygen species (ROS) via eNOS and NOX, can induce changes in gene expression and cellular behavior in diabetes. Furthermore, reports suggest that EPC telomere shortening via increased oxidative DNA damage may play an important role in the pathogenesis of coronary artery disease in diabetic patients. In this review, different type of EPC derived from different sources has been discussed along with cell-surface marker. The reduced number and immobilized EPC in diabetic condition have been mobilized for the therapeutic purpose via use of existing, and novel drugs have been discussed. Hence, evidence list of all types of drugs that have been reported to target the same pathway which affect EPC number and function in diabetes has been reviewed. Additionally, we highlight that proteins are critical in diabetes via polymorphism and inhibitor studies. Ultimately, a lucid pictorial explanation of diabetic and normal patient signaling pathways of the collected data have been presented in order to understand the complex signaling mystery underlying in the diseased and normal condition. Conclusion Finally, we conclude on eNOS-metformin-HSp90 signaling and its remedial effect for controlling the EPC to improve the diabetic condition for delaying diabetes-related complication. Altogether, the review gives a holistic overview about the elaborate therapeutic effect of EPC regulated by novel and existing drugs in diabetes and diabetes-related disorder.

Polyhydroxyalkanoates (PHAs) are biodegradable polymers that can be produced from lignocellulosic biomass by microorganisms. Cheap and readily available raw material, such as corn stover waste, has the potential to lessen the cost of PHA synthesis. In this research study, corn stover is pretreated with NaOH under conditions optimized for high cellulose and low lignin with central composite design (CCD) followed by characterization using Fourier-transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA), and scanning electron microscopy (SEM). Design expert software performed further optimization of alkali pretreated corn stover for high total reducing sugar (TRS) enhancement using CCD using response surface methodology (RSM). The optimized condition by RSM produced a TRS yield of 707.19 mg/g. Fermentation using corn stover hydrolysate by Pseudomonas putida MTCC 2475 gave mcl-PHA detected through g as c hromatography – t andem m ass s pectrometry (GC-MS/MS) and characterization of the PHA film by differential scanning calorimetry (DSC), FTIR, and nuclear magnetic resonance (NMR). Thus, this research paper focuses on using agriculture (stubble) waste as an alternative feedstock for PHA production.

The bidirectional communication between the gut and brain or gut-brain axis is regulated by several gut microbes and microbial derived metabolites, such as short-chain fatty acids, trimethylamine N-oxide, and lipopolysaccharides. The Gut microbiota (GM) produce neuroactives, specifically neurotransmitters that modulates local and central neuronal brain functions. An imbalance between intestinal commensals and pathobionts leads to a disruption in the gut microbiota or dysbiosis, which affects intestinal barrier integrity and gut-immune and neuroimmune systems. Currently, fecal microbiota transplantation (FMT) is recommended for the treatment of recurrent Clostridioides difficile infection. FMT elicits its action by ameliorating inflammatory responses through the restoration of microbial composition and functionality. Thus, FMT may be a potential therapeutic option in suppressing neuroinflammation in post-stroke conditions and other neurological disorders involving the neuroimmune axis. Specifically, FMT protects against ischemic injury by decreasing IL-17, IFN-γ, Bax, and increasing Bcl-2 expression. Interestingly, FMT improves cognitive function by lowering amyloid-β accumulation and upregulating synaptic marker (PSD-95, synapsin-1) expression in Alzheimer’s disease. In Parkinson’s disease, FMT was shown to inhibit the expression of TLR4 and NF-κB. In this review article, we have summarized the potential sources and methods of administration of FMT and its impact on neuroimmune and cognitive functions. We also provide a comprehensive update on the beneficial effects of FMT in various neurological disorders by undertaking a detailed interrogation of the preclinical and clinical published literature.

Polyhydroxyalkanoates are a class of biodegradable, biocompatible polymers composed of polyesters of R-hydroxyalkanoic acids and deposited intracellularly by a variety of microorganisms which have potential to serve as alternative to commercial plastic. Bioplastics are gaining attention due to sustainability, biodegradability, biocompatibility, and lower carbon footprint. Nevertheless, the commercialization of PHA is predominantly hindered by the elevated production expenses arising primarily from the use of a pure sugar substrate. Our study has established a feasible method for bioplastic formation applying Pseudomonas putida MTCC 2475 and Solanum tuberosum periderm as a carbon source. To optimize the sugar yield response surface methodology was used, which released 69.34% ± 0.25% reducing sugar. PHA production experiments were performed in hydrolysate containing media as well as commercial sugar containing mineral salt media. After 48 h of fermentation of using this sugar, a biomass concentration of 2.19 gL −1 , with a PHA production of 0.60 gL −1 (28.71% ± 0.55%) was obtained which was comparatively similar with synthetic media (2.56 gL −1 cell dry weight and 29.97% ± 0.45% PHA). Furthermore, the monomers of PHA produced by hydrolysate were characterized using Gas chromatography-mass spectrometry, Fourier transform infrared spectroscopy, differential scanning calorimetry, and nuclear magnetic resonance. This investigation has identified three distinct monomers of medium-chain PHAs, namely, methyl 3-Hydroxydodecanoate, 3-Hydroxytetradecanoate, and Hexadecanoic acid 3-Hydroxy methyl esters. Hence this study concludes a sustainable production of bioplastics from S. tuberosum periderm waste.

The cell cycle is the sequence of events orchestrated by a complex network of cell cycle proteins. Unlike normal cells, mature neurons subsist in a quiescent state of the cell cycle, and aberrant cell cycle activation triggers neuronal death accompanied by neurodegeneration. The periodicity of cell cycle events is choreographed by various mechanisms, including DNA damage repair, oxidative stress, neurotrophin activity, and ubiquitin-mediated degradation. Given the relevance of cell cycle processes in cancer and neurodegeneration, this review delineates the overlapping cell cycle events, signaling pathways, and mechanisms associated with cell cycle aberrations in cancer and the major neurodegenerative disorders. We suggest that dysregulation of some common fundamental signaling processes triggers anomalous cell cycle activation in cancer cells and neurons. We discussed the possible use of cell cycle inhibitors for neurodegenerative disorders and described the associated challenges. We propose that a greater understanding of the common mechanisms driving cell cycle aberrations in cancer and neurodegenerative disorders will open a new avenue for the development of repurposed drugs. Graphical Abstract Cell cycle activation and cell cycle re-entry are the two critical cellular phenomena associated with cancer and neurodegeneration, respectively. Various regulatory proteins, such as cyclin-dependent kinases (CDKs), cyclins, and checkpoint kinases, control the cell cycle dynamics at different phases. Further, the integrity of cell cycle is controlled by different mechanisms like DNA damage response, oxidative stress, neurotrophin activity, and the ubiquitin–proteasome system (UPS), the alterations which play an essential role in the pathogenesis of both cancer and neurodegenerative disorders. Pharmacological targeting of important cell cycle regulatory molecules like the application of CDK inhibitors, PARP inhibitors, checkpoint kinase inhibitors, and microtubule inhibitors holds great promise for treating various human cancers and can be repurposed for different neurodegenerative disorders.

Autophagy and apoptosis are two crucial self-destructive processes that maintain cellular homeostasis, which are characterized by their morphology and regulated through signal transduction mechanisms. These pathways determine the fate of cellular organelle and protein involved in human health and disease such as neurodegeneration, cancer, and cardiovascular disease. Cell death pathways share common molecular mechanisms, such as mitochondrial dysfunction, oxidative stress, calcium ion concentration, reactive oxygen species, and endoplasmic reticulum stress. Some key signaling molecules such as p53 and VEGF mediated angiogenic pathway exhibit cellular and molecular responses resulting in the triggering of apoptotic and autophagic pathways. Herein, based on previous studies, we describe the intricate relation between cell death pathways through their common genes and the role of various stress-causing agents. Further, extensive research on autophagy and apoptotic machinery excavates the implementation of selective biomarkers, for instance, mTOR, Bcl-2, BH3 family members, caspases, AMPK, PI3K/Akt/GSK3β, and p38/JNK/MAPK, in the pathogenesis and progression of neurodegenerative diseases. This molecular phenomenon will lead to the discovery of possible therapeutic biomolecules as a pharmacological intervention that are involved in the modulation of apoptosis and autophagy pathways. Moreover, we describe the potential role of micro-RNAs, long non-coding RNAs, and biomolecules as therapeutic agents that regulate cell death machinery to treat neurodegenerative diseases.Mounting evidence demonstrated that under stress conditions, such as calcium efflux, endoplasmic reticulum stress, the ubiquitin–proteasome system, and oxidative stress intermediate molecules, namely p53 and VEGF, activate and cause cell death. Further, activation of p53 and VEGF cause alteration in gene expression and dysregulated signaling pathways through the involvement of signaling molecules, namely mTOR, Bcl-2, BH3, AMPK, MAPK, JNK, and PI3K/Akt, and caspases. Alteration in gene expression and signaling cascades cause neurotoxicity and misfolded protein aggregates, which are characteristics features of neurodegenerative diseases. Excessive neurotoxicity and misfolded protein aggregates lead to neuronal cell death by activating death pathways like autophagy and apoptosis. However, autophagy has a dual role in the apoptosis pathways, i.e., activation and inhibition of the apoptosis signaling. Further, micro-RNAs and LncRNAs act as pharmacological regulators of autophagy and apoptosis cascade, whereas, natural compounds and chemical compounds act as pharmacological inhibitors that rescue neuronal cell death through inhibition of apoptosis and autophagic cell death.

The present study investigated the effects of alloying and nano-reinforcement on the mechanical properties (microhardness, tensile strength, and compressive strength) of Mg-based alloys and composites. Pure Mg, Mg-3Sn alloy, and Mg-3Sn + 0.2 GNP alloy-nanocomposite were synthesized by powder metallurgy followed by hot extrusion. The microstructural characteristics of the bulk extruded samples were explored using X-ray diffraction, field-emission scanning electron microscopy, and optical microscopy and their mechanical properties were compared. The microhardness, tensile strength, and compressive strength of the Mg-3Sn alloy improved when compared to those of monolithic Mg sample and further improvements were displayed by Mg-3Sn + 0.2 GNP alloy-nanocomposite. No significant change in the compressive strain to failure was observed in both the alloy and the alloy-nanocomposite with respect to that of the pure Mg sample. However, an enhanced tensile strain to failure was displayed by both the alloy and the alloy-nanocomposite.

Polymers of hydroxy alkanoates (PHA), also known as biodegradable, biocompatible plastic, are potential alternatives to petrochemical-based plastics. PHA is synthesized by microbes in their cytoplasm in the form of inclusion bodies in stress conditions such as nitrogen, oxygen, and phosphorus with excessive amounts of carbon. Sugar extracted from potato peel in the form of hydrolysate was employed as a carbon source for PHA production after acidic hydrolysis. The acid hydrolysis conditions are optimized for dilute acid concentrations and temperatures. The highest sugar-yielding condition (2% 15 min at 121 ℃) was used for submerged fermentation for PHA production by Bacillus circulans MTCC 8167. Fourier transform infrared spectroscopy, nuclear magnetic resonance, and differential scanning calorimetry were used for polymer characterization. Gas chromatography coupled with mass spectrometry confirmed the monomers such as hexadecenoic acid 3-hydroxy, methyl esters, pentadecanoic acid 14 methyl esters, and tetradecanoic acid 12- methyl esters. Crotonic acid assay was used for quantification of PHA and it was found highest (0.232 ± 0.04 g/L) at 37 °C and 36 h of incubation. Hence, potato peel waste could be a potential feedstock for waste to valuable production. Graphical Abstract