PrankWeb: a web server for ligand binding site prediction and visualization

Peptidomics and molecular dynamics on bioactive peptides produced and characterized from the fermented whey of "Panchali" sheep of West India

The study assessed the peptide production by using potent Lactiplantibacillus plantarum KGL3A (MG722814) culture to ferment the sheep milk for evaluation of α-glucosidase inhibition, ACE inhibition, α-amylase inhibition, & inhibiting lipase activities. The maximal ACE inhibitory, α-amylase, α-glucosidase, & lipase inhibiting actions were 71.69 %, 71.32 %, 67.14 %, and 64.15 %, respectively, at 37 °C after 48 h. Proteolytic activity was tested at various incubation times & inoculation rates to maximise the conditions for growth and the greatest action (9.38 mg/mL) was reported at 2.5 % rate of inoculation after incubation of 48 h. The anti-diabetic as well as ACE inhibitory properties of less than 3 kDa were maximum in contrast to >3 kDa, <10 kDa, and > 10 kDa cut-off fractions. Further, when LPS stimulation is applied to RAW 267.4 macrophage cells, the overabundance generation of IL-6, IL-1β, NO, and TNF-α is greatly reduced by using KGL3A to ferment sheep milk. 2D gel electrophoresis & SDS-PAGE were utilized in relation to protein purifications. Maximum numbers of sheep milk's fermented protein bands were present, about 10 to 124 kDa by SDS-PAGE, and 38 spots of protein were discovered using 2D gel chromatography. Ultra-filtered fractions water soluble extracts (WSEs) were employed in RP-HPLC to differentiate between various peptide fractions. The peptide sequences produced were matched using the databases of AHTPDB and BIOPEP to match hypertensive peptides & antidiabetic peptides, respectively. Furthermore, the discovered peptide sequences from the fermenting sheep milk was studied due to their penchant for binding against the active locations of human bile salt activated lipase (hBAL); human maltase-glucoamylase (hMGA); human pancreatic alpha-amylase (hPAM); & human angiotensin-converting enzyme (hACE) through molecular docking.

Binding of Selected Ligands to Human Protein Disulfide Isomerase and Microsomal Triglyceride Transfer Protein Complex and the Associated Conformational Changes: A Computational Molecular Modelling Study

Human protein disulfide isomerase (PDI) is a multifunctional protein, and also serves as the β subunit of the human microsomal triglyceride transfer protein (MTP) complex, a lipid transfer machinery. Dysfunction of the MTP complex is associated with certain disease conditions such as abetalipoproteinemia and cardiovascular diseases. It is known that the functions of PDI or the MTP complex can be regulated by the binding of a small-molecule ligand to either of these two proteins. In the present study, the conformational changes of the MTP complex upon the binding of three selected small-molecule ligands (17β-estradiol, lomitapide and a phospholipid) are investigated based on the available biochemical and structural information by using the protein-ligand docking method and molecular dynamics (MD) simulation. The ligand-binding sites, the binding poses and binding strengths, the key binding site residues, and the ligand binding-induced conformational changes in the MTP complex are analyzed based on the MD trajectories. The open-to-closed or closed-to-open transitions of PDI is found to occur in both reduced and oxidized states of PDI and also independent of the presence or absence of small-molecule ligands. It is predicted that lomitapide and 1,2-diacyl-sn-glycero-3-phosphocholine (a phospholipid) can bind inside the lipid-binding pocket in the MTP complex with high affinities, whereas 17β-estradiol interacts with the lipid-binding pocket in addition to its binding to the interface region of the MTP complex. Additionally, lomitapide can bind to the b' domain of PDI as reported earlier for E2. Key residues for the ligand-binding interactions are identified in this study. It will be of interest to further explore whether the binding of small molecules can facilitate the conformational transitions of PDI in the future. The molecular and structural insights gained from the present work are of value for understanding some of the important biological functions of PDI and the MTP complex.

Carbohydrate-active enzyme-catalyzed stereoselective glycosylation of complex natural product glycosides

Natural products and their derivatives are precious resources with extensive applications in various industrial fields. Enzymatic glycosylation is an efficient approach for chemical structure diversification and biological activity alternation of natural products. Herein, we reported a stereoselective glycosylation of complex natural product glycosides catalyzed by two carbohydrate-active enzymes (CAZys). ASP OleD, a mutant of glycosyltransferase OleD from Streptomyces antibioticus, catalyzed an explicit β-1,x-linkage glycosylation of the OH group of the glycosyl moiety of the representative plant-derived complex natural product glycosides, protodioscin (1) and epimedin C (2), producing two complex glycoside derivatives. The glycoside hydrolase Δ27ThCGT, a truncated cyclodextrin glucanotransferase from Thermoanaerobacter sp., exhibited a definite α-1,x-linkage glycosylation of the OH group of the glycosyl moiety of the glycosides 1, 2, and astragaloside IV (3), generating four complex glycoside derivatives. The chemical structures and absolute configurations of these enzymatic glycosylation products were determined by analysis of their HRMS and NMR data. The present study expands the enzymatic glycosylation diversification of complex glycosides catalyzed by the CAZys.

Multifunctional Dual Enzyme-Responsive Nanostructured Lipid Carriers for Targeting and Enhancing the Treatment of Bacterial Infections

Bacterial infections pose an increasingly worrisome threat to the health of humankind, with antibiotic resistance contributing significantly to this burden. With current conventional antibiotics perpetuating the problem, and a paucity in developing antibiotics, drug delivery systems incorporating nanotechnology appear promising. As such, a dual enzyme-responsive multifunctional nanostructured lipid carrier (NLC) incorporating farnesol (FAN) and triglycerol monostearate (TGMS), was conceptualized for the codelivery of vancomycin (VCM) and antimicrobial peptide (AMP) to enhance the antibacterial activity of VCM. In silico studies and Microscale Thermophoresis demonstrated the strong binding relationships between the NLC constituents and two enzymes that exist in higher concentrations during host infection, namely lipase and a matrix metalloproteinase (MMP). The formulated nanosystem, VCM-AMP-TF-NLCs, had a particle size, polydispersity index, zeta potential, and entrapment efficiency of 149.00 ± 2.97 nm, 0.07 ± 0.01, -5.51 ± 1.21 mV, and 86.20% ± 1.47%, respectively. The NLCs, which showed stability, and biocompatibility, also demonstrated lipase- and MMP-responsiveness. The in vitro antibacterial studies revealed 2-fold and 8-fold reductions in the minimum inhibitory concentration for the NLCs compared to bare VCM, against methicillin-resistant Staphylococcal aureus (MRSA) and Escherichia coli, respectively. Furthermore, in vivo studies revealed that tissues treated with the VCM-AMP-TF-NLCs displayed significantly reduced bacterial burdens (up to 8.73-fold) and less histopathological cellular injury, edema, and necrosis compared to the tissues treated with bare VCM alone. The results support the superiority of the VCM-AMP-TF-NLCs as a multifunctional dual enzyme-responsive NLC compared to bare VCM.

Extracellular domain of TREM2 possess two distinct ligand recognition sites: Insights from machine-learning guided docking and all-atoms molecular dynamics simulations

The myeloid-specific triggering receptors expressed on myeloid cells 2 (TREM2) is a group of class I receptors expressed in brain microglia plays a decisive role in neurodegenerative diseases such as Alzheimer's disease (AD) and Nasu Hakola disease (NHD). The extracellular domain (ECD) of TREM2 interacts with a wide-range of ligands, yet the molecular mechanism underlying recognition of such ligands to this class I receptor remains underexplored. Herein, we undertook a systematic investigation for exploring the mode of ligand recognition in immunoglobulin-like ectodomain by employing both knowledge-based and machine-learning guided molecular docking approach followed by the state-of-the-art all atoms molecular dynamics (MD) simulations. Besides the known binding site formed by complementarity-determining regions (CDR) 1 and CDR2 loops, which enables the binding of different anionic ligands, our study identifies the presence of second binding site formed by β-strands towards the C-terminal end. We observe a dense network of hydrophobic contacts formed between the explored ligands and CDR loops and β-strands, specifically CDR1, CDR2, β-strand C', loop connecting β-strand D and E, and loop connecting β-strand E and F. Ligand binding in immunoglobulin-like ectodomain increases the conformational flexibility of CDR2 loop, thus most frequently observed pathogenic variants i.e. R47H and R62H in TREM2 may affect the development and progression of AD. Our knowledge-based and machine-learning guided docking and physics-based simulations study unveils deep insights into the endogenous ligand recognition by the positive surface ligand binding site and distant core site pave the way for exploration of other small molecules towards development of novel therapeutics against Alzheimer's disease.

Therapeutic potential inhibitor for dipeptidyl peptidase IV in diabetic type 2: in silico approaches

Diabetes mellitus (DM) is a metabolic disease marked by an excessive rise in blood sugar (glucose) levels caused by a partial or total absence of insulin production, combined with alterations in the metabolism of proteins, lipids, and carbohydrates. The International Diabetes Federation estimates that 425 million individuals globally had diabetes in 2017 which will be 629 million by 2045. Several medications are used to treat DM, but they have limitations and side effects including weight gain, nausea, vomiting, and damage to blood vessels and kidneys. Therefore, it is essential to identify anti-diabetic drugs that have less or no side effects. Hence, the current study employed in silico approaches to discover new DPP-IV inhibitors that might be associated with diabetes. Thirty-four (34) co-crystalized DPP-IV enzymes were found from the protein data bank and the co-crystal ligands were docked into the active-site 6B1E protein to find out the hit compounds. From the docking results, we found two hit compounds (5T4E and 4J3J) which were used to find out the analogs from the experimental drug database using the DrugRep software. According to the results, twenty (20) analogs were found from the experimental drug database with the similarity score of ≥ 0.790 and docked once again into the active site of the DPP-IV (PDB ID: 6B1E) enzyme. Interestingly, DB02226 showed the best binding affinity (-10.3 kcal/mol) and prime MM/GBSA (-68.73 kcal/mol) compared to the reference drug (co-crystal ligand; -7.4 kcal/mol and -47.49 kcal/mol, respectively). Additionally, DB02226 has shown excellent reactivity, efficacy, and structural stability in the binding region of target proteins in studies using MD simulation, MM/GBSA, DFT, and MESP analysis. These findings can be utilized to support further in vitro, in vivo, pre-clinical and clinical research rather than definitively confirming anti-diabetic effectiveness.

The Miraculous Asian Fruit Baccaurea motleyana Müll. Arg. (Rambai): Exploring the Phyto-Pharmacological Potentials of Fruit Peel Through GC-MS/MS, In Vitro, In Vivo, and In Silico Approaches

Baccaurea motleyana Müll. Arg. (Rambai), an Asian fruit belonging to the Phyllanthaceae family, is cultivated throughout Southeast Asia and has been traditionally utilized in folk medicine to address eye discomfort, digestive issues, insomnia, and fevers. This study of the peel employed four Kupchan fractions (PSF, DSF, ESF, and ASF) obtained from the methanol extract of the peel of B. motleyana for in vitro assessments, including antioxidant cytotoxicity and antimicrobial activities. The crude methanol extract was also used for in vivo evaluations, focusing on antidiarrheal and antidepressant effects, complemented by phytochemical screening and analysis using GC-MS/MS. The investigation of B. motleyana methanol peel extract identified 20 phytochemicals, with primary constituents, including phenol, 3,5-bis(1,1-dimethylethyl) (26.14%) and 1-heptadec-1-ynyl-cyclohexanol (23.12%). The extract exhibited potent antioxidant activity (IC50: 9.43 µg/mL) and cytotoxicity (LC50: 6.01 µg/mL). The most significant antidiarrheal effect was observed at a dosage of 400 mg/kg. Molecular docking studies revealed that compounds, such as C9, C2, and C19, displayed noteworthy binding affinities against glutathione reductase (-6.3 kcal/mol), urease oxidase (-6 kcal/mol), and monoamine oxidase A (-6.5 kcal/mol) receptors. In summary, our study demonstrates that fruits, like Rambai, could serve as a promising source for therapeutics and drug development in Asian countries.

Repurposing FDA-Approved Drugs Against Potential Drug Targets Involved in Brain Inflammation Contributing to Alzheimer's Disease

Alzheimer's disease is a neurodegenerative disease that continues to have a rising number of cases. While extensive research has been conducted in the last few decades, only a few drugs have been approved by the FDA for treatment, and even fewer aim to be curative rather than manage symptoms. There remains an urgent need for understanding disease pathogenesis, as well as identifying new targets for further drug discovery. Alzheimer's disease (AD) is known to stem from a build-up of amyloid beta (Aβ) plaques as well as tangles of tau proteins. Furthermore, inflammation in the brain is known to arise from the degeneration of tissue and the build-up of insoluble material. Therefore, there is a potential link between the pathology of AD and inflammation in the brain, especially as the disease progresses to later stages where neuronal death and degeneration levels are higher. Proteins that are relevant to both brain inflammation and AD thus make ideal potential targets for therapeutics; however, the proteins need to be evaluated to determine which targets would be ideal for potential drug therapeutic treatments, or 'druggable'. Druggability analysis was conducted using two structure-based methods (i.e., Drug-Like Density analysis and SiteMap), as well as a sequence-based approach, SPIDER. The most druggable targets were then evaluated using single-nuclei sequencing data for their clinical relevance to inflammation in AD. For each of the top five targets, small molecule docking was used to evaluate which FDA approved drugs were able to bind with the chosen proteins. The top targets included DRD2 (inhibits adenylyl cyclase activity), C9 (binds with C5B8 to form the membrane attack complex), C4b (binds with C2a to form C3 convertase), C5AR1 (GPCR that binds C5a), and GABA-A-R (GPCR involved in inhibiting neurotransmission). Each target had multiple potential inhibitors from the FDA-approved drug list with decent binding infinities. Among these inhibitors, two drugs were found as top inhibitors for more than one protein target. They are C15H14N2O2 and v316 (Paracetamol), used to treat pain/inflammation originally for cataracts and relieve headaches/fever, respectively. These results provide the groundwork for further experimental investigation or clinical trials.

Plausible Action of N-(3,4-Dimethoxy-Phenyl)-6,7-Dimethoxyquinazoline-4-Amine (TKM01) as an Armor Against Alzheimer's Disease: In Silico and In Vivo Insights

Alzheimer's disease (AD) affects millions of people and has limited treatment options, thus making it a global health concern. Amyloid β (Aβ), a disrupted cholinergic system with high acetylcholinesterase (AChE), oxidative stress (OS), reduced antioxidants, and neuroinflammation are key factors influencing AD progression. Prior research has shown that AChE can interact with Aβ and increase its accumulation and neurotoxicity, so targeting AChEs and Aβ could be a potential therapeutic approach for AD treatment. It has been known that nonsteroidal anti-inflammatory drugs (NSAIDs) can inhibit Aβ accumulation. Previously, TKM01, a derivative of 4-anilinoquinazoline, has demonstrated inhibitory effects against GSK-3β-a regulator in AD progression. The current research included molecular docking studies of NSAIDs and TKM01 with Aβ and AChEs as targets. TKM01 exhibited a higher binding affinity with Aβ among all tested compounds. Molecular dynamic (MD) simulations confirmed the stability of the protein-TKM01 complexes. TKM01 also exhibited favorable drug-likeness properties, and no hepatoxicity was visualized in comparison with other compounds. Further, in vitro assay showed an inhibitory action of TKM01 (50-1200 µg/mL) on AChEs. In the in vivo studies on zebrafish larvae brains, we found that TKM01 (120 and 240 µg/mL) reduced the levels of AChEs and lipid peroxidation (LPO) and increased antioxidant superoxide dismutase (SOD) and catalase (CAT) in AlCl3(80 µM)-induced AD-like model. Additionally, TKM01 treatment was found to decrease pro-inflammatory cytokines TNF-α, IL-1β, and IL-6. The current study demonstrates that TKM01 can be used to treat AD. Nonetheless, experimental validation is needed to reveal the cellular, sub-cellular, and molecular mechanisms and possible implications at a clinical stage.

Unveiling the Therapeutic Potentials of Water Hyacinth (Eichhornia crassipes (Mart.) Solms) Flower against Oxidative Stress, Inflammation and Depressive Disorders: GC-MS/MS, In Vitro, In Vivo and In Silico Approaches

Water hyacinth (Eichhornia crassipes (Mart.) Solms) is a highly invasive aquatic weed native to the Amazonia basin, known for its rapid propagation, adaptability, and utilization in traditional medicine. The study aims to unveil the therapeutic potential of water hyacinth flowers methanolic extract (EC CME) and its four kupchan fractions (EC PESF, EC DCMSF, EC EASF, EC ASF) through diversified chemical-pharmacological approaches. GC-MS/MS of EC-CME uncovered a rich tapestry of 72 phytochemical components. In vitro DPPH scavenging assay and total phenolic content determination assay deciphered promising antioxidant assays with remarkably low IC50 values of 0.353 and 0.485 μg/mL, respectively for EC-ESF and EC-ASF. Besides, different in vivo tests, including tail emersion, acetic acid-induced writhing, and thiopental-induced sleeping test of EC-CME, yielded a remarkable 8.61±0.29 min of tail immersion time compared to the control's 2.05±0.11 min at the highest dose (600 mg/kg). The best % inhibition of writhing was recorded as 47.96 % accrued in 400 mg/kg dose, indicating robust pain-relieving properties. The onset and duration of sleep are significantly ameliorated for EC-CME, unveiling its antidepressant potential. Besides, molecular docking studies along with ADME/T analysis also validated the wet lab findings as well as their safety, efficacy, and drug-likeliness profile. Finally, this work can be an essential hint for utilizing aquatic weeds in drug development research.

Asoprisnil as a Novel Ligand Interacting with Stress-Associated Glucocorticoid Receptor

Background/objective: The glucocorticoid receptor (GR) is critical in regulating cortisol production during stress. This makes it a key target for treating conditions associated with hypothalamic-pituitary-adrenal (HPA) axis dysregulation, such as mental disorders. This study explores novel ligands beyond mifepristone for their potential to modulate GR with improved efficacy and safety. By investigating these interactions, we seek to identify new pharmacotherapeutic options for stress-related mental illness. Methods: The ligands asoprisnil, campestanol, and stellasterol were selected based on structural similarities to mifepristone (reference ligand) and evaluated for pharmacological and ADME (absorption, distribution, metabolism, and excretion) properties using the SwissADME database. Molecular docking with AutoDock 4.2.6 and molecular dynamics simulations were performed to investigate ligand-protein interactions with the human glucocorticoid receptor, and binding free energies were calculated using MMPBSA. Results: Pharmacokinetic analysis revealed that asoprisnil exhibited high gastrointestinal absorption and obeyed Lipinski's rule, while mifepristone crossed the blood-brain barrier. Toxicological predictions showed that mifepristone was active for neurotoxicity and immunotoxicity, while asoprisnil, campestanol, and stellasterol displayed lower toxicity profiles. Asoprisnil demonstrated the highest stability in molecular dynamics simulations, with the highest negative binding energy of -62.35 kcal/mol, when compared to mifepristone, campestanol, and stellasterol, with binding energies of -57.08 kcal/mol, -49.99 kcal/mol, and -46.69 kcal/mol, respectively. Conclusion: This makes asoprisnil a potentially favourable therapeutic candidate compared to mifepristone. However, further validation of asoprisnil's interaction, efficacy, and safety in stress-related mental disorders through experimental studies and clinical trials is needed.

Binding of MAP3773c Protein of Mycobacterium avium subsp. paratuberculosis in the Mouse Ferroportin1 Coding Region

Mycobacterium avium subsp. paratuberculosis (MAP) is known to cause paratuberculosis. One notable protein, MAP3773c, plays a critical role in iron metabolism as a transcription factor. This study aims to investigate the binding affinity of MAP3773c to the chromatin of the Ferroportin1 (FPN1) gene in murine macrophage J774 A.1. We conducted a sequence alignment to identify potential interaction sites for MAP3773c. Following this, we used in silico analysis to predict binding interactions, complemented by electrophoretic mobility shift assay (EMSA) to confirm in vitro binding of MAP3773c. The map3773c gene was cloned into the pcDNA3.1 vector, with subsequent expression analysis carried out via Western blotting and real-time PCR. Chromatin immunoprecipitation (CHiP) assays were performed on transfected macrophages to confirm binding in the native chromatin context. Our in silico and in vitro analysis indicated that MAP3773c interacts with two binding motifs within the FPN1 coding region. The ChiP results provided additional validation, demonstrating the binding of MAP3773c to the FPN1 chromatin through successful amplification of the associated chromatin fragment via PCR. Our study demonstrated that MAP3773c binds to FPN1 and provides insight into the role of MAP3773c and its effect on host iron transport.

Tiliroside protects against diabetic nephropathy in streptozotocin-induced diabetes rats by attenuating oxidative stress and inflammation

BACKGROUND

Diabetic nephropathy (DN), affecting half of diabetic patients and contributing significantly to end-stage kidney disease, poses a substantial medical challenge requiring dialysis or transplantation. The nuanced onset and clinical progression of kidney disease in diabetes involve consistent renal function decline and persistent albuminuria.

AIM

To investigate Tiliroside's (Til) protective effect against diabetic nephropathy (DN) in rats under diabetic conditions.

METHODS

Five groups of six rats each were included in this study: Rats treated with DMSO by intraperitoneal injection as controls, those treated with STZ by intraperitoneal injection, those treated with STZ + Til (25 mg/kg body weight [bwt]) or Til (50 mg/kg bwt), and those treated with anti-diabetic medication glibenclamide (600 μg/kg bwt). Biochemical markers, fasting blood glucose, food intake, kidney weight, antioxidant enzymes, inflammatory and fibrotic markers, and renal injury were monitored in different groups. Molecular docking analysis was performed to identify the interactions between Til and its targeted biomarkers.

RESULTS

Til significantly reduced biochemical markers, fasting blood glucose, food intake, and kidney weight and elevated antioxidant enzymes in diabetic rats. It also mitigated inflammatory and fibrotic markers, lessened renal injury, and displayed inhibitory potential against crucial markers associated with DN as demonstrated by molecular docking analysis.

CONCLUSION

These findings suggest Til's potential as a therapeutic agent for DN treatment, highlighting its promise for future drug development.

Comparative evaluation of methods for the prediction of protein-ligand binding sites

The accurate identification of protein-ligand binding sites is of critical importance in understanding and modulating protein function. Accordingly, ligand binding site prediction has remained a research focus for over three decades with over 50 methods developed and a change of paradigm from geometry-based to machine learning. In this work, we collate 13 ligand binding site predictors, spanning 30 years, focusing on the latest machine learning-based methods such as VN-EGNN, IF-SitePred, GrASP, PUResNet, and DeepPocket and compare them to the established P2Rank, PRANK and fpocket and earlier methods like PocketFinder, Ligsite and Surfnet. We benchmark the methods against the human subset of our new curated reference dataset, LIGYSIS. LIGYSIS is a comprehensive protein-ligand complex dataset comprising 30,000 proteins with bound ligands which aggregates biologically relevant unique protein-ligand interfaces across biological units of multiple structures from the same protein. LIGYSIS is an improvement for testing methods over earlier datasets like sc-PDB, PDBbind, binding MOAD, COACH420 and HOLO4K which either include 1:1 protein-ligand complexes or consider asymmetric units. Re-scoring of fpocket predictions by PRANK and DeepPocket display the highest recall (60%) whilst IF-SitePred presents the lowest recall (39%). We demonstrate the detrimental effect that redundant prediction of binding sites has on performance as well as the beneficial impact of stronger pocket scoring schemes, with improvements up to 14% in recall (IF-SitePred) and 30% in precision (Surfnet). Finally, we propose top-N+2 recall as the universal benchmark metric for ligand binding site prediction and urge authors to share not only the source code of their methods, but also of their benchmark.Scientific contributionsThis study conducts the largest benchmark of ligand binding site prediction methods to date, comparing 13 original methods and 15 variants using 10 informative metrics. The LIGYSIS dataset is introduced, which aggregates biologically relevant protein-ligand interfaces across multiple structures of the same protein. The study highlights the detrimental effect of redundant binding site prediction and demonstrates significant improvement in recall and precision through stronger scoring schemes. Finally, top-N+2 recall is proposed as a universal benchmark metric for ligand binding site prediction, with a recommendation for open-source sharing of both methods and benchmarks.

Possibility of re-purposing antifungal drugs posaconazole & isavuconazole against promastigote form of Leishmania major

Background & objectives The emergence of drug resistance in leishmaniasis has remained a concern. Even new drugs have been found to be less effective within a few years of their use. Coupled with their related side effects and cost-effectiveness, this has prompted the search for alternative therapeutic options. In this study, the Computer Aided Drug Design (CADD) approach was used to repurpose already existing drugs against Leishmania major. The enzyme lanosterol 14-alpha demethylase (CYP51), in L. major, was chosen as the drug target since it is a key enzyme involved in synthesizing ergosterol, a crucial component of the cell membrane. Methods A library of 1615 FDA-approved drugs was virtually screened and docked with modeled CYP51 at its predicted binding site. The drugs with high scores and high affinity were subjected to Molecular Dynamics (MD) simulations for 100 ns. Finally, the compounds were tested in vitro using an MTT [3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide] assay against the promastigotes of L. major. Results Computational screening of FDA-approved drugs identified posaconazole and isavuconazole as promising candidates, as both drugs target the CYP51 enzyme in fungi. Molecular dynamics (MD) simulations demonstrated that both drugs form stable complexes with the target enzyme. In vitro studies of posaconazole and isavuconazole against promastigotes of L. major demonstrated significant efficacy, with IC50 values of 2.062±0.89 µg/ml and 1.202±0.47 µg/ml, respectively. Interpretation & conclusions The study showed that the existing FDA-approved drugs posaconazole and isavuconazole can successfully be repurposed for treating L. major by targeting the CYP51 enzyme, demonstrating significant efficacy against promastigotes.

sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms

BACKGROUND

Bacterial small regulatory RNA (sRNA) plays a crucial role in cell metabolism and could be used as a new potential drug target in the treatment of pathogen-induced disease. However, experimental methods for identifying sRNAs still require a large investment of human and material resources.

METHODS

In this study, we propose a novel sRNA prediction model called sRNAdeep based on the DistilBERT feature extraction and TextCNN methods. The sRNA and non-sRNA sequences of bacteria were considered as sentences and then fed into a composite model consisting of deep learning models to evaluate classification performance.

RESULTS

By filtering sRNAs from BSRD database, we obtained a validation dataset comprised of 2438 positive and 4730 negative samples. The benchmark experiments showed that sRNAdeep displayed better performance in the various indexes compared to previous sRNA prediction tools. By applying our tool to Mycobacterium tuberculosis (MTB) genome, we have identified 21 sRNAs within the intergenic and intron regions. A set of 272 targeted genes regulated by these sRNAs were also captured in MTB. The coding proteins of two genes (lysX and icd1) are implicated in drug response, with significant active sites related to drug resistance mechanisms of MTB.

CONCLUSION

In conclusion, our newly developed sRNAdeep can help researchers identify bacterial sRNAs more precisely and can be freely available from https://github.com/pyajagod/sRNAdeep.git .

Network analysis and molecular modeling studies of pinocembrin a bioactive phytochemical of Dodonaea viscosa against Parkinson's disease

Parkinson's disease, a neurodegenerative disorder, is quickly progressing and accounts for 15% of dementia cases. Parkinson's disease is the second most frequent form of neuronal degeneration after Alzheimer's, with an average age of 55 years for individuals exhibiting neuropsychiatric and physiological symptoms. Due to the effectiveness, low toxicity, and low side effects, bioactive compounds from plants have received increased attention recently as therapeutic drugs. In the current study, effective anti-neurodegenerative phytochemicals from Dodonaea viscosa were screened using in silico methods and have been proposed to be further investigated for the treatment of Parkinson's disease. The structures of twenty bioactive chemicals were screened and graph theoretical network analysis revealed alpha-synuclein as a potent therapeutic target. Based on docking scores, an effective bioactive molecule was selected, and its energy values, electrostatic potential surface and drug-like qualities were examined using molecular orbitals, pharmacokinetics and toxicity studies. Pinocembrin was found as a superior binder based on molecular docking as it demonstrated stronger binding with - 10.2 kcal/mol. An investigation using Ramachandran plot validated the protein-ligand complex secondary structure's stability. Pinocembrin, a bioactive phytochemical from Dodonaea viscosa, may be a viable lead molecule that may be developed as a candidate medicine for anti-neurodegenerative therapy against Parkinson's disease.

SARS-CoV-2 uses Spike glycoprotein to control the host's anaerobic metabolism by inhibiting LDHB

The SARS-CoV-2 pandemic, responsible for approximately 7 million deaths worldwide, highlights the urgent need to understand the molecular mechanisms of the virus in order to prevent future outbreaks. The Spike glycoprotein of SARS-CoV-2, which is critical for viral entry through its interaction with ACE2 and other host cell receptors, has been a focus of this study. The present research goes beyond receptor recognition to explore Spike's influence on cellular metabolism. AP-MS interactome analysis revealed an interaction between the Spike S1 domain and lactate dehydrogenase B (LDHB), which was further confirmed by co-immunoprecipitation and immunofluorescence, indicating colocalisation in cells expressing the S1 domain. The study showed that Spike inhibits the catalytic activity of LDHB, leading to increased lactate levels in HEK-293T cells overexpressing the S1 subunit. In the hypothesised mechanism, Spike deprives LDHB of NAD+, facilitating a metabolic switch from aerobic to anaerobic energy production during infection. The Spike-NAD+ interacting region was characterised and mainly involves the W436 within the RDB domain. This novel hypothesis suggests that the Spike protein may play a broader role in altering host cell metabolism, thereby contributing to the pathophysiology of viral infection.

In silico evidence of bitopertin's broad interactions within the SLC6 transporter family

The Glycine Transporter Type 1 (GlyT1) significantly impacts central nervous system functions, influencing glycinergic and glutamatergic neurotransmission. Bitopertin, the first GlyT1 inhibitor in clinical trials, was developed for schizophrenia treatment but showed limited efficacy. Despite this, bitopertin's repositioning could advance treating various pathologies. This study aims to understand bitopertin's mechanism of action using computational methods, exploring off-target effects, and providing a comprehensive pharmacological profile. Similarity Ensemble Approach (SEA) and SwissTargetPrediction initially predicted targets, followed by molecular modeling on SWISS-MODEL and GalaxyWeb servers. Binding sites were identified using PrankWeb, and molecular docking was performed with DockThor and GOLD software. Molecular dynamics analyses were conducted on the Visual Dynamics platform. Reverse screening on SEA and SwissTargetPrediction identified GlyT1 (SLC6A9), GlyT2 (SLC6A5), PROT (SLC6A7), and DAT (SLC6A3) as potential bitopertin targets. Homology modeling on SwissModel generated high-resolution models, optimized further on GalaxyWeb. PrankWeb identified similar binding sites in GlyT1, GlyT2, PROT, and DAT, indicating potential interaction. Docking studies suggested bitopertin's interaction with GlyT1 and proximity to GlyT2 and PROT. Molecular dynamics confirmed docking results, highlighting bitopertin's target stability beyond GlyT1. The study concludes that bitopertin potentially interacts with multiple SLC6 family targets, indicating a broader pharmacological property.

Pharmacoinformatics-based identification of phytochemicals from Solanum torvum Swartz. fruits as potential inhibitors for MAPK14 protein

Plants and phytocompounds gained more attention because of their unrivalled variety of chemical diversity. In this view, the present study was executed to predict the anticancer potential of Solanum torvum Swartz. fruits derived phytocompounds against one of the breast cancer target proteins (MAPK14, PDB ID: 5ETA, resolution: 2.80 Å) through pharmacoinformatics-based screening and molecular dynamics simulation tools. Initially, a graph theoretical network approach was used to visualize the genes, enzymes, and proteins involved in the signalling pathway of breast cancer and identify the significant target protein (MAPK14). A total of thirty-three active compounds were selected from S. torvum sw. through the IMPPAT database, and their structures were drawn by Chemsketch software. The drug-like behaviours of the compounds were assessed through pharmacokinetics and physicochemical characterization studies. Five compounds, namely chlorogenin (-10.90 kcal × mol-1), corosolic acid (-10.80 kcal × mol-1), solaspigenin (-10.80 kcal × mol-1), paniculogenin (-10.70 kcal × mol-1), spirostane-3,6-dione (-10.70 kcal × mol-1) exhibited top binding score against MAPK14, these are higher than that of the standard drug (Doxorubicin) (-8.60 kcal × mol-1). Additionally, the five top-binding compounds revealed better drug-likeness traits and the lowest toxicity profiles. MD simulation studies confirmed the stability of the top five scored compounds with the MAPK14 binding pockets. According to these findings, the selected five compounds might be used as significant MAPK14 inhibitors and can be used as new medicines for the treatment of breast cancer.Communicated by Ramaswamy H. Sarma.

Chemico-pharmacological evaluations of the dwarf elephant ear (Colocasia affinis Schott) plant metabolites and extracts: health benefits from vegetable source

Introduction: Colocasia affinis Schott (Family: Araceae), found in the Asian region, is a traditional root vegetable consumed by the locals and well-known as Dwarf Elephant Ear. Methods: For the pharmacological exploration of this root vegetable, four kupchan fractions (i.e. HSF, DCMSF, EASF, and AQSF) from ethanolic extract of C. affinis were employed to in vitro i.e. antioxidant, cytotoxicity, and antimicrobial and in vivo i.e. antidiarrheal and analgesic assays, followed by phytochemical screening and GC-MS protocol. Result and Discussion: In the antioxidant assay, the AQSF showed promising potential with an IC50 value of 29.4 μg/mL and additionally, it exhibited the greatest overall phenolic content, measuring 57.23 mg GAE/gm. of extract among other fractions. The AQSF also revealed promising cytotoxic activity in brine shrimp lethality assay with an LC50 value of 1.36 μg/mL. Both AQSF and EASF exhibited substantial antimicrobial efficacy against both gram-positive and gram-negative bacteria as well as various fungus species with a remarkable zone of inhibitions compared to standards. Whereas, during both the castor oil-induced antidiarrheal and acetic acid-induced writhing assay, the DCMSF at 400 mg/kg dose exhibited the highest 51.16% reduction of diarrhea and 52.33% reduction of writhing. Phytochemical screening revealed several chemical groups while GC-MS study of different fractions of dwarf elephant ear ethanolic extract revealed 48 different bioactive phytochemicals in total. Several targets such as KAS, DHFR for anti-microbial activities, GLR, URO for antioxidant activities, EGFR, BCL-2 for cytotoxicity, KOR, DOR for antidiarrheal activities and COX-2, TNF-α for analgesic activities are considered for molecular docking against identified phytocompounds and standards along with ADME/T studies to ascertain their safety, efficacy and drug likeliness profiles. Conclusion: To recapitulate, our study revealed that vegetables such as dwarf elephant ear can be considered as a prospective source of therapeutics and drug development besides their nutritive food values.

Isoliquiritigenin: a potential drug candidate for the management of erectile dysfunction

OBJECTIVE

This study aimed to assess the erectogenic properties of isoliquiritigenin taking sildenafil (SDF) as the standard.

METHODS

The binding affinity of isoliquiritigenin (ISL) with the erectile marker proteins (endothelial nitric oxide synthase [eNOS] and enzyme phosphodiesterase type 5 [PDE5]) was investigated using Autodock Vina, which was validated using molecular dynamics simulation. Furthermore, the effect of ISL on the eNOS and PDE5 messenger ribonucleic acid (mRNA) expression and the sexual behavior of mice was investigated, along with the assessment of the pharmacokinetics of ISL.

KEY FINDINGS

The results revealed that the binding affinity of ISL-eNOS/PDE5 and SDF-eNOS/PDE5 was in the range of -7.5 to -8.6 kcal/mol. The ISL-eNOS/PDE5 complexes remained stable throughout the 100 ns simulation period. Root mean square deviation, Rg, SASA, hydrogen, and hydrophobic interactions were similar between ISL-eNOS/PDE5 and SDF-eNOS/PDE5. Analysis of mRNA expressions in paroxetine (PRX)-induced ED mice showed that the co-administration of PRX with ISL reduced PDE5 and increased eNOS mRNA expression, similar to the co-administered group (PRX+SDF). The sexual behavior study revealed that the results of PRX+ISL were better than those of the PRX+SDF group. Pharmacokinetic evaluation further demonstrated that ISL possesses drug-like properties.

CONCLUSIONS

The results showed that ISL is equally potent as SDF in terms of binding affinity, specific pharmacological properties, and modulating sexual behavior.

Virtual screening, molecular dynamics and density functional theory on pain inhibitors against TRPV1 associating inflammatory conditions

Transient receptor potential vanilloid 1 protein (TRPV1) is expressed widely in skin and sensory neurons that contribute to pain/heat sensation in the human system. TRPV1 gene polymorphisms are susceptible to multiple diseases and it is considered a therapeutic target for various inflammatory conditions. Among the TRPV1 variants, rs8065080 (1911 A > G) plays a vital role in painful osteoarthritis and migraine. The presence of rs8065080 polymorphism may render drug efficacy. This study aimed to identify better antagonists against wild-type and variant TRPV1 that may help in the relief of pain/inflammation. We constructed suitable TRPV1 protein structures for wild-type and rs8065080 variant through a homology modelling approach. A total of 3363 anti-inflammatory compounds with high chemical diversity and good drug-like properties were collected and screened against the generated structures. Molecular docking showed that nobilamide B had the highest binding affinity (-5.83 kcal/mol) towards the wild-type. Whereas, isoquinoline analogue displayed highest binding potency with the variant TRPV1 (-11.65 kcal/mol). Besides those, C18H15F3N4O showed affinity towards both wild-type (-5.53 kcal/mol) and variant TRPV1 (-9.75 kcal/mol). Then, molecular dynamic simulation revealed stable conformation in wild-type and variant TRPV1 upon binding of nobilmaide B, isoquinoline analogue and C18H15F3N4O. Additionally, density functional theory (DFT) using B3LYP hybrid function showed high chemical reactiveness of nobilamie B, isoquinoline analogue and C18H15F3N4O. Overall, our systematic investigations provide, C18H15F3N4O could be a potential analgesic inhibiting both wild-type and variant TRPV1 against inflammatory conditions.

Identification of new correctors for traffic-defective ABCB4 variants by a high-content screening approach

ABCB4 is located at the canalicular membrane of hepatocytes and is responsible for the secretion of phosphatidylcholine into bile. Genetic variations of this transporter are correlated with rare cholestatic liver diseases, the most severe being progressive familial intrahepatic cholestasis type 3 (PFIC3). PFIC3 patients most often require liver transplantation. In this context of unmet medical need, we developed a high-content screening approach to identify small molecules able to correct ABCB4 molecular defects. Intracellularly-retained variants of ABCB4 were expressed in cell models and their maturation, cellular localization and function were analyzed after treatment with the molecules identified by high-content screening. In total, six hits were identified by high-content screening. Three of them were able to correct the maturation and canalicular localization of two distinct intracellularly-retained ABCB4 variants; one molecule was able to significantly restore the function of two ABCB4 variants. In addition, in silico molecular docking calculations suggest that the identified hits may interact with wild type ABCB4 residues involved in ATP binding/hydrolysis. Our results pave the way for their optimization in order to provide new drug candidates as potential alternative to liver transplantation for patients with severe forms of ABCB4-related diseases, including PFIC3.

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming

Organophosphates constitute a major class of pesticides widely employed in agriculture to manage insect pests. Their toxicity is attributed to their ability to inhibit the functioning of acetylcholinesterase (AChE), an essential enzyme for normal nerve transmission. Organophosphates, especially chlorpyrifos, have been a key component of the integrated pest management (IPM) in onions, effectively controlling onion maggot Delia antiqua, a severe pest of onions. However, the growing concerns over the use of this insecticide on human health and the environment compelled the need for an alternative organophosphate and a potential microbial agent for bioremediation to mitigate organophosphate pesticide pollution. In the present study, chloropyrifos along with five other organophosphate insecticides, phosmet, primiphos-methyl, isofenphos, iodofenphos and tribuphos, were screened against the target protein AChE of D. antiqua using molecular modeling and docking techniques. The results revealed that iodofenphos showed the best interaction, while tribuphos had the lowest interaction with the AChE based on comparative binding energy values. Further, protein-protein interaction analysis conducted using the STRING database and Cytoscap software revealed that AChE is linked with a network of 10 different proteins, suggesting that the function of AChE is disrupted through interaction with insecticides, potentially leading to disruption within the network of associated proteins. Additionally, an in silico study was conducted to predict the binding efficiency of two organophosphate degrading enzymes, organophosphohydrolase (OpdA) from Agrobacterium radiobacter and Trichoderma harzianum paraoxonase 1 like (ThPON1-like) protein from Trichoderma harzianum, with the selected insecticides. The analysis revealed their potential to degrade the pesticides, offering a promising alternative before going for cumbersome onsite remediation.

The global distribution of the macrolide esterase EstX from the alpha/beta hydrolase superfamily

Macrolide antibiotics, pivotal in clinical therapeutics, are confronting resistance challenges mediated by enzymes like macrolide esterases, which are classified into Ere-type and the less studied Est-type. In this study, we provide the biochemical confirmation of EstX, an Est-type macrolide esterase that initially identified as unknown protein in the 1980s. EstX is capable of hydrolyzing four 16-membered ring macrolides, encompassing both veterinary (tylosin, tidipirosin, and tilmicosin) and human-use (leucomycin A5) antibiotics. It uses typical catalytic triad (Asp233-His261-Ser102) from alpha/beta hydrolase superfamily for ester bond hydrolysis. Further genomic context analysis suggests that the dissemination of estX is likely facilitated by mobile genetic elements such as integrons and transposons. The global distribution study indicates that bacteria harboring the estX gene, predominantly pathogenic species like Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae, are prevalent in 74 countries across 6 continents. Additionally, the emergence timeline of the estX gene suggests its proliferation may be linked to the overuse of macrolide antibiotics. The widespread prevalence and dissemination of Est-type macrolide esterase highlight an urgent need for enhanced monitoring and in-depth research, underlining its significance as an escalating public health issue.

Antibiotic discovery with artificial intelligence for the treatment of Acinetobacter baumannii infections

Global challenges presented by multidrug-resistant Acinetobacter baumannii infections have stimulated the development of new treatment strategies. We reported that outer membrane protein W (OmpW) is a potential therapeutic target in A. baumannii. Here, a library of 11,648 natural compounds was subjected to a primary screening using quantitative structure-activity relationship (QSAR) models generated from a ChEMBL data set with >7,000 compounds with their reported minimal inhibitory concentration (MIC) values against A. baumannii followed by a structure-based virtual screening against OmpW. In silico pharmacokinetic evaluation was conducted to assess the drug-likeness of these compounds. The ten highest-ranking compounds were found to bind with an energy score ranging from -7.8 to -7.0 kcal/mol where most of them belonged to curcuminoids. To validate these findings, one lead compound exhibiting promising binding stability as well as favorable pharmacokinetics properties, namely demethoxycurcumin, was tested against a panel of A. baumannii strains to determine its antibacterial activity using microdilution and time-kill curve assays. To validate whether the compound binds to the selected target, an OmpW-deficient mutant was studied and compared with the wild type. Our results demonstrate that demethoxycurcumin in monotherapy and in combination with colistin is active against all A. baumannii strains. Finally, the compound was found to significantly reduce the A. baumannii interaction with host cells, suggesting its anti-virulence properties. Collectively, this study demonstrates machine learning as a promising strategy for the discovery of curcuminoids as antimicrobial agents for combating A. baumannii infections.

IMPORTANCE

Acinetobacter baumannii presents a severe global health threat, with alarming levels of antimicrobial resistance rates resulting in significant morbidity and mortality in the USA, ranging from 26% to 68%, as reported by the Centers for Disease Control and Prevention (CDC). To address this threat, novel strategies beyond traditional antibiotics are imperative. Computational approaches, such as QSAR models leverage molecular structures to predict biological effects, expediting drug discovery. We identified OmpW as a potential therapeutic target in A. baumannii and screened 11,648 natural compounds. We employed QSAR models from a ChEMBL bioactivity data set and conducted structure-based virtual screening against OmpW. Demethoxycurcumin, a lead compound, exhibited promising antibacterial activity against A. baumannii, including multidrug-resistant strains. Additionally, demethoxycurcumin demonstrated anti-virulence properties by reducing A. baumannii interaction with host cells. The findings highlight the potential of artificial intelligence in discovering curcuminoids as effective antimicrobial agents against A. baumannii infections, offering a promising strategy to address antibiotic resistance.

Identification and Evaluation of Olive Phenolics in the Context of Amine Oxidase Enzyme Inhibition and Depression: In Silico Modelling and In Vitro Validation

The Mediterranean diet well known for its beneficial health effects, including mood enhancement, is characterised by the relatively high consumption of extra virgin olive oil (EVOO), which is rich in bioactive phenolic compounds. Over 200 phenolic compounds have been associated with Olea europaea, and of these, only a relatively small fraction have been characterised. Utilising the OliveNetTM library, phenolic compounds were investigated as potential inhibitors of the epigenetic modifier lysine-specific demethylase 1 (LSD1). Furthermore, the compounds were screened for inhibition of the structurally similar monoamine oxidases (MAOs) which are directly implicated in the pathophysiology of depression. Molecular docking highlighted that olive phenolics interact with the active site of LSD1 and MAOs. Protein-peptide docking was also performed to evaluate the interaction of the histone H3 peptide with LSD1, in the presence of ligands bound to the substrate-binding cavity. To validate the in silico studies, the inhibitory activity of phenolic compounds was compared to the clinically approved inhibitor tranylcypromine. Our findings indicate that olive phenolics inhibit LSD1 and the MAOs in vitro. Using a cell culture model system with corticosteroid-stimulated human BJ fibroblast cells, the results demonstrate the attenuation of dexamethasone- and hydrocortisone-induced MAO activity by phenolic compounds. The findings were further corroborated using human embryonic stem cell (hESC)-derived neurons stimulated with all-trans retinoic acid. Overall, the results indicate the inhibition of flavin adenine dinucleotide (FAD)-dependent amine oxidases by olive phenolics. More generally, our findings further support at least a partial mechanism accounting for the antidepressant effects associated with EVOO and the Mediterranean diet.

Gene identification, expression analysis, and molecular docking of SAT and OASTL in the metabolic pathway of selenium in Cardamine hupingshanensis

KEY MESSAGE

Identification of selenium stress-responsive expression and molecular docking of serine acetyltransferase (SAT) and O-acetyl serine (thiol) lyase (OASTL) in Cardamine hupingshanensis. A complex coupled with serine acetyltransferase (SAT) and O-acetyl serine (thiol) lyase (OASTL) is the key enzyme that catalyzes selenocysteine (Sec) synthesis in plants. The functions of SAT and OASTL genes were identified in some plants, but it is still unclear whether SAT and OASTL are involved in the selenium metabolic pathway in Cardamine hupingshanensis. In this study, genome-wide identification and comparative analysis of ChSATs and ChOASTLs were performed. The eight ChSAT genes were divided into three branches, and the thirteen ChOASTL genes were divided into four branches by phylogenetic analysis and sequence alignment, indicating the evolutionary conservation of the gene structure and its association with other plant species. qRT-PCR analysis showed that the ChSAT and ChOASTL genes were differentially expressed in different tissues under various selenium levels, suggesting their important roles in Sec synthesis. The ChSAT1;2 and ChOASTLA1;2 were silenced by the VIGS system to investigate their involvement in selenium metabolites in C. hupingshanensis. The findings contribute to understanding the gene functions of ChSATs and ChOASTLs in the selenium stress and provide a reference for further exploration of the selenium metabolic pathway in plants.

Reconstruction of Avian Reovirus History and Dispersal Patterns: A Phylodynamic Study

Avian reovirus (ARV) infection can cause significant losses to the poultry industry. Disease control has traditionally been attempted mainly through vaccination. However, the increase in clinical outbreaks in the last decades demonstrated the poor effectiveness of current vaccination approaches. The present study reconstructs the evolution and molecular epidemiology of different ARV genotypes using a phylodynamic approach, benefiting from a collection of more than one thousand sigma C (σC) sequences sampled over time at a worldwide level. ARVs' origin was estimated to occur several centuries ago, largely predating the first clinical reports. The origins of all genotypes were inferred at least one century ago, and their emergence and rise reflect the intensification of the poultry industry. The introduction of vaccinations had only limited and transitory effects on viral circulation and further expansion was observed, particularly after the 1990s, likely because of the limited immunity and the suboptimal and patchy vaccination application. In parallel, strong selective pressures acted with different strengths and directionalities among genotypes, leading to the emergence of new variants. While preventing the spread of new variants with different phenotypic features would be pivotal, a phylogeographic analysis revealed an intricate network of viral migrations occurring even over long distances and reflecting well-established socio-economic relationships.

Human Plasma Butyrylcholinesterase Hydrolyzes Atropine: Kinetic and Molecular Modeling Studies

The participation of butyrylcholinesterase (BChE) in the degradation of atropine has been recurrently addressed for more than 70 years. However, no conclusive answer has been provided for the human enzyme so far. In the present work, a steady-state kinetic analysis performed by spectrophotometry showed that highly purified human plasma BChE tetramer slowly hydrolyzes atropine at pH 7.0 and 25 °C. The affinity of atropine for the enzyme is weak, and the observed kinetic rates versus the atropine concentration was of the first order: the maximum atropine concentration in essays was much less than Km. Thus, the bimolecular rate constant was found to be kcat/Km = 7.7 × 104 M-1 min-1. Rough estimates of catalytic parameters provided slow kcat < 40 min-1 and high Km = 0.3-3.3 mM. Then, using a specific organophosphoryl agent, echothiophate, the time-dependent irreversible inhibition profiles of BChE for hydrolysis of atropine and the standard substrate butyrylthiocholine (BTC) were investigated. This established that both substrates are hydrolyzed at the same site, i.e., S198, as for all substrates of this enzyme. Lastly, molecular docking provided evidence that both atropine isomers bind to the active center of BChE. However, free energy perturbations yielded by the Bennett Acceptance Ratio method suggest that the L-atropine isomer is the most reactive enantiomer. In conclusion, the results provided evidence that plasma BChE slowly hydrolyzes atropine but should have no significant role in its metabolism under current conditions of medical use and even under administration of the highest possible doses of this antimuscarinic drug.

Graph Attention Site Prediction (GrASP): Identifying Druggable Binding Sites Using Graph Neural Networks with Attention

Identifying and discovering druggable protein binding sites is an important early step in computer-aided drug discovery, but it remains a difficult task where most campaigns rely on a priori knowledge of binding sites from experiments. Here, we present a binding site prediction method called Graph Attention Site Prediction (GrASP) and re-evaluate assumptions in nearly every step in the site prediction workflow from data set preparation to model evaluation. GrASP is able to achieve state-of-the-art performance at recovering binding sites in PDB structures while maintaining a high degree of precision which will minimize wasted computation in downstream tasks such as docking and free energy perturbation.

Searching for new plastic-degrading enzymes from the plastisphere of alpine soils using a metagenomic mining approach

Plastic materials, including microplastics, accumulate in all types of ecosystems, even in remote and cold environments such as the European Alps. This pollution poses a risk for the environment and humans and needs to be addressed. Using shotgun DNA metagenomics of soils collected in the eastern Swiss Alps at about 3,000 m a.s.l., we identified genes and their proteins that potentially can degrade plastics. We screened the metagenomes of the plastisphere and the bulk soil with a differential abundance analysis, conducted similarity-based screening with specific databases dedicated to putative plastic-degrading genes, and selected those genes with a high probability of signal peptides for extracellular export and a high confidence for functional domains. This procedure resulted in a final list of nine candidate genes. The lengths of the predicted proteins were between 425 and 845 amino acids, and the predicted genera producing these proteins belonged mainly to Caballeronia and Bradyrhizobium. We applied functional validation, using heterologous expression followed by enzymatic assays of the supernatant. Five of the nine proteins tested showed significantly increased activities when we used an esterase assay, and one of these five proteins from candidate genes, a hydrolase-type esterase, clearly had the highest activity, by more than double. We performed the fluorescence assays for plastic degradation of the plastic types BI-OPL and ecovio® only with proteins from the five candidate genes that were positively active in the esterase assay, but like the negative controls, these did not show any significantly increased activity. In contrast, the activity of the positive control, which contained a PLA-degrading gene insert known from the literature, was more than 20 times higher than that of the negative controls. These findings suggest that in silico screening followed by functional validation is suitable for finding new plastic-degrading enzymes. Although we only found one new esterase enzyme, our approach has the potential to be applied to any type of soil and to plastics in various ecosystems to search rapidly and efficiently for new plastic-degrading enzymes.

Computational Approach to Identify the Key Genes for Invasive Lobular Carcinoma (ILC) Diagnosis and Therapies

Invasive Lobular Carcinoma (ILC) is a common form of breast cancer that begins in milk-producing glands lobules and spreads to other parts of the breast. According to the American Cancer Society, about 10–15% of breast cancer cases are ILC. ILC risk rises with age. The number of deaths caused by this cancer each year can be decreased through early diagnosis and if accurate therapy is given. However, diagnosis of ILC is difficult due to its development pattern as it grows as single file strands and not as lumps. Treatments of ILC involve chemotherapy, hormonal therapy and radiation therapy. Drugs that are being used for ILC, are commonly used to treat all types of breast cancer and there are no specific drugs that target receptors of ILC are available. Microarray technology’s emergence helps in finding the differentially expressed genes (DEGs) in malignant cells. From the DEGs, highly interacting genes were identified using the online tool, string. Seven key genes were identified based on the interaction and they are FN1, CDKN2A, COL1A1, COL3A1, COL11A1, LEF1 and IL1B. Thus, the drugs targeting these biomarkers were identified by doing molecular docking using the tool Autodock and molecular dynamic (MD) simulation using the tool iMODs. The response of the identified drugs to the ILC cell line was compared with the control drugs by in silico pharmacogenomic analysis and it was found that the identified drugs have a good response to the ILC cell line.

Deciphering the Lexicon of Protein Targets: A Review on Multifaceted Drug Discovery in the Era of Artificial Intelligence

Understanding protein sequence and structure is essential for understanding protein-protein interactions (PPIs), which are essential for many biological processes and diseases. Targeting protein binding hot spots, which regulate signaling and growth, with rational drug design is promising. Rational drug design uses structural data and computational tools to study protein binding sites and protein interfaces to design inhibitors that can change these interactions, thereby potentially leading to therapeutic approaches. Artificial intelligence (AI), such as machine learning (ML) and deep learning (DL), has advanced drug discovery and design by providing computational resources and methods. Quantum chemistry is essential for drug reactivity, toxicology, drug screening, and quantitative structure-activity relationship (QSAR) properties. This review discusses the methodologies and challenges of identifying and characterizing hot spots and binding sites. It also explores the strategies and applications of artificial-intelligence-based rational drug design technologies that target proteins and protein-protein interaction (PPI) binding hot spots. It provides valuable insights for drug design with therapeutic implications. We have also demonstrated the pathological conditions of heat shock protein 27 (HSP27) and matrix metallopoproteinases (MMP2 and MMP9) and designed inhibitors of these proteins using the drug discovery paradigm in a case study on the discovery of drug molecules for cancer treatment. Additionally, the implications of benzothiazole derivatives for anticancer drug design and discovery are deliberated.

Targeting XGHPRT enzyme to manage Helicobacter pylori induced gastric cancer: A multi-pronged machine learning, artificial intelligence and biophysics-based study

Helicobacter pylori infects the stomach mucosa of over half of the global population and can lead to gastric cancer. This pathogen has demonstrated resistance to many frequently prescribed antibiotics, thereby underscoring the pressing need to identify novel therapeutic targets. The inhibition or disruption of nucleic acid biosynthesis constitutes a promising avenue for either restraining or eradicating bacterial proliferation. The synthesis of RNA and DNA precursors (6-oxopurine nucleoside monophosphates) is catalyzed by the XGHPRT enzyme. In this study, using machine learning, artificial intelligence and biophysics-based software, CHEMBRIDGE-10000196, CHEMBRIDGE-10000295, and CHEMBRIDGE-10000955 were predicted as promising binders to the XGHPRT with a binding score of -14.20, -13.64, and -12.08 kcal/mol, respectively, compared to a control guanosine-5'-monophosphate exhibiting a docking score of -10.52 kcal/mol. These agents formed strong interactions with Met33, Arg34, Ala57, Asp92, Ser93, and Gly94 at short distance. The docked complexes of the lead compounds exhibited stable dynamics during the simulation time with no global changes noticed. The docked complexes demonstrate a significantly stable MM-GBSA and MM-PBSA net binding energy of -60.1 and -61.18 kcal/mol for the CHEMBRIDGE-10000196 complex. The MM-GBSA net energy value of the CHEMBRIDGE-10000295 complex and the CHEMBRIDGE-10000955 complex is -71.17 and -65.29 kcal/mol, respectively. The CHEMBRIDGE-10000295 and CHEMBRIDGE-10000955 complexes displayed a net value of -71.91 and -63.49 kcal/mol, respectively, as per the MM-PBSA. The major driving intermolecular interactions for the docked complexes were found to be the electrostatic and van der Waals. The three filtered molecules hold potential for experimental evaluation of their potency against the XGHPRT enzyme.

From Flora to Pharmaceuticals: 100 new additions to angiosperms of Gafargaon subdistrict in Bangladesh and unraveling antidiabetic drug candidates targeting DPP4 through in silico approach

Addition to the angiosperm flora provides essential insights into the biodiversity of a region, contributing to ecological understanding and conservation planning. Gafargaon subdistrict under Mymensingh district in Bangladesh represents a diverse population of angiosperms with a multifaceted ecosystem that demands re-evaluation of the existing angiosperm diversity of Gafargaon to update the status of angiosperm taxa and facilitate their conservation efforts. With this endeavor, a total of 100 angiosperm taxa belonging to 90 genera and 46 families were uncovered as additional occurrence in Gafargaon. The species in the area showcased a variety of life forms, including 63 herbs, 14 shrubs, 14 trees, and 9 climbers. Among the recorded taxa, Chamaecostus cuspidatus (Nees & Mart.) C.D. Specht & D.W. Stev. was selected for antidiabetic drug design endeavor based on citation frequency and ethnomedicinal evidence. A total of 41 phytochemicals of C. cuspidatus were screened virtually, targeting the Dipeptidyl peptidase 4 protein through structure-based drug design approach, which unveiled two lead compounds, such as Tigogenin (-9.0 kcal/mol) and Diosgenin (-8.5 kcal/mol). The lead candidates demonstrated favorable pharmacokinetic and pharmacodynamic properties with no major side effects. Molecular dynamics simulation revealed notable stability and structural compactness of the lead compounds. Principal component analysis and Gibbs free energy landscape further supported the results of molecular dynamics simulation. Molecular mechanics-based MM/GBSA approach unraveled higher free binding energies of Diosgenin (-47.36 kcal/mol) and Tigogenin (-46.70 kcal/mol) over Alogliptin (-46.32 kcal/mol). The outcome of the present investigation would enrich angiosperm flora of Gafargaon and shed light on the role of C. cuspidatus to develop novel antidiabetic therapeutics to combat diabetes.

In silico studies on the anti-acne potential of Garcinia mangostana xanthones and benzophenones

Garcinia mangostana fruits are used traditionally for inflammatory skin conditions, including acne. In this study, an in silico approach was employed to predict the interactions of G. mangostana xanthones and benzophenones with three proteins involved in the pathogenicity of acne, namely the human JNK1, Cutibacterium acnes KAS III and exo-β-1,4-mannosidase. Molecular docking analysis was performed using Autodock Vina. The highest docking scores and size-independent ligand efficiency values towards JNK1, C. acnes KAS III and exo-β-1,4-mannosidase were obtained for garcinoxanthone T, gentisein/2,4,6,3',5'-pentahydroxybenzophenone and mangostanaxanthone VI, respectively. To the best of our knowledge, this is the first report of the potential of xanthones and benzophenones to interact with C. acnes KAS III. Molecular dynamics simulations using GROMACS indicated that the JNK1-garcinoxanthone T complex had the highest stability of all ligand-protein complexes, with a high number of hydrogen bonds predicted to form between this ligand and its target. Petra/Osiris/Molinspiration (POM) analysis was also conducted to determine pharmacophore sites and predict the molecular properties of ligands influencing ADMET. All ligands, except for mangostanaxanthone VI, showed good membrane permeability. Garcinoxanthone T, gentisein and 2,4,6,3',5'-pentahydroxybenzophenone were identified as the most promising compounds to explore further, including in experimental studies, for their anti-acne potential.

XRCC1 Polymorphisms p.Arg194Trp, p.Arg280His, and p.Arg399Gln, Polycyclic Aromatic Hydrocarbons, and Infertility: A Case-Control and In Silico Study

XRCC1 is involved in repair of single-strand breaks generated by mutagenic exposure. Polymorphisms within XRCC1 affect its ability to efficiently repair DNA damage. Polycyclic aromatic hydrocarbons or PAHs are genotoxic compounds which form bulky DNA adducts that are linked with infertility. Few reports suggest combined role of XRCC1 polymorphisms and PAHs in infertility. Present study investigates association of three XRCC1 polymorphisms (p.Arg194Trp, p.Arg280His, p.Arg399Gln) with male and female infertility in a North-West Indian population using case-control approach. Additionally, in silico approach has been used to predict whether XRCC1 polymorphisms effect interaction of XRCC1 with different PAHs. For case-control study, XRCC1 polymorphisms were screened in peripheral blood samples of age- and gender-matched 201 infertile cases (♂-100, ♀-101) and 201 fertile controls (♂-100, ♀-101) using PCR-RFLP method. For in silico study, AutoDock v4.2.6 was used for molecular docking of B[a]P, BPDE-I, ( ±)-anti-BPDE, DB[a,l]P, 1-N, 2-N, 1-OHP, 2-OHF with XRCC1 and assess effect of XRCC1 polymorphisms on their interaction. In case-control study, statistical analysis showed association of XRCC1 p.Arg280His GA genotype (p = 0.027), A allele (p = 0.019) with reduced risk of male infertility. XRCC1 p.Arg399Gln AA genotype (p = 0.021), A allele (p = 0.014) were associated with reduced risk for female primary infertility. XRCC1 p.Arg194Trp T allele was associated with increased risk for female infertility (p = 0.035). In silico analysis showed XRCC1-PAH interaction with non-significant effect of XRCC1 polymorphisms on predicted binding. Therefore, present study concludes that XRCC1 polymorphism-modified risk for male and female infertility in North-West Indians without significant effect on predicted XRCC1-PAH interactions. This is the first report on XRCC1 in female infertility.

Whole genome identification, molecular docking and expression analysis of enzymes involved in the selenomethionine cycle in Cardamine hupingshanensis

BACKGROUND

The selenomethionine cycle (SeMTC) is a crucial pathway for the metabolism of selenium. The basic bioinformatics and functions of four enzymes involved in the cycle including S-adenosyl-methionine synthase (MAT), SAM-dependent methyltransferase (MTase), S-adenosyl-homocysteine hydrolase (SAHH) and methionine synthase (MTR), have been extensively reported in many eukaryotes. The identification and functional analyses of SeMTC genes/proteins in Cardamine hupingshanensis and their response to selenium stress have not yet been reported.

RESULTS

In this study, 45 genes involved in SeMTC were identified in the C. hupingshanensis genome. Phylogenetic analysis showed that seven genes from ChMAT were clustered into four branches, twenty-seven genes from ChCOMT were clustered into two branches, four genes from ChSAHH were clustered into two branches, and seven genes from ChMTR were clustered into three branches. These genes were resided on 16 chromosomes. Gene structure and homologous protein modeling analysis illustrated that proteins in the same family are relatively conserved and have similar functions. Molecular docking showed that the affinity of SeMTC enzymes for selenium metabolites was higher than that for sulfur metabolites. The key active site residues identified for ChMAT were Ala269 and Lys273, while Leu221/231 and Gly207/249 were determined as the crucial residues for ChCOMT. For ChSAHH, the essential active site residues were found to be Asn87, Asp139 and Thr206/207/208/325. Ile204, Ser111/329/377, Asp70/206/254, and His329/332/380 were identified as the critical active site residues for ChMTR. In addition, the results of the expression levels of four enzymes under selenium stress revealed that ChMAT3-1 genes were upregulated approximately 18-fold, ChCOMT9-1 was upregulated approximately 38.7-fold, ChSAHH1-2 was upregulated approximately 11.6-fold, and ChMTR3-2 genes were upregulated approximately 28-fold. These verified that SeMTC enzymes were involved in response to selenium stress to varying degrees.

CONCLUSIONS

The results of this research are instrumental for further functional investigation of SeMTC in C. hupingshanensis. This also lays a solid foundation for deeper investigations into the physiological and biochemical mechanisms underlying selenium metabolism in plants.

Unveiling Glucosinolate Diversity in Brassica Germplasm and In Silico Analysis for Determining Optimal Antioxidant Potential

This study explored the glucosinolate (GSL) content in Brassica plants and utilized in silico analysis approach to assess their antioxidant capabilities. GSLs, present abundantly in Brassica vegetables, offer potential health advantages, including antioxidant effects. Employing Ultra-Performance Liquid Chromatography (UPLC) coupled with tandem mass spectrometry (MS/MS), major GSLs were identified in 89 accessions from diverse species and subspecies. Statistical analysis and principal component analysis unveiled significant GSL variation and potential correlations among the Brassica germplasms. This study unveils the dominance of aliphatic GSLs over aromatic and indolyl compounds in all the accessions. Notably, Gluconapin (GNA) (33,049.23 µmol·kg-1 DW), Glucobrassicanapin (GBN) (9803.82 µmol·kg-1 DW), Progoitrin (PRO) (12,780.48 µmol·kg-1 DW) and Sinigrin (SIN) (14,872.93 µmol·kg-1 DW) were the most abundant compounds across the analyzed accessions. Moreover, in silico docking studies predicted promising antioxidant activity by evaluating the interactions of each GSL with antioxidant enzymes. Specifically, Sinigrin and Gluconapin exhibited a notably weaker influence on antioxidant enzymes. This provides key insights into the antioxidant potential of Brassica germplasm and highlights the importance of in silico analysis for evaluating bioactive properties. In general, the results of this study could be utilized in breeding programs to maximize GSL levels and antioxidant properties in Brassica crops and for developing functional foods with enhanced health benefits.

Machine Learning for Sequence and Structure-Based Protein-Ligand Interaction Prediction

Developing new drugs is too expensive and time -consuming. Accurately predicting the interaction between drugs and targets will likely change how the drug is discovered. Machine learning-based protein-ligand interaction prediction has demonstrated significant potential. In this paper, computational methods, focusing on sequence and structure to study protein-ligand interactions, are examined. Therefore, this paper starts by presenting an overview of the data sets applied in this area, as well as the various approaches applied for representing proteins and ligands. Then, sequence-based and structure-based classification criteria are subsequently utilized to categorize and summarize both the classical machine learning models and deep learning models employed in protein-ligand interaction studies. Moreover, the evaluation methods and interpretability of these models are proposed. Furthermore, delving into the diverse applications of protein-ligand interaction models in drug research is presented. Lastly, the current challenges and future directions in this field are addressed.

Insights of phytoremediation mechanisms for viruses based on in-vitro, in-vivo and in-silico assessments of selected herbal plants

Waterborne pathogenic viruses present unrelenting challenges to the global health and wastewater treatment industry. Phytoremediation offers promising solutions for wastewater treatment through plant-based technologies. This study investigated antiviral mechanisms in-vivo using bacteriophages MS2 and T4 as surrogates for effective herbs screened in-vitro from three embryophytes (Ocimum basilicum, Mentha sp., Plectranthus amboinicus), two macrophytes (Eichhornia crassipes, Pistia stratiotes) and a perennial grass (Cyperus rotundas). In-silico virtual screening predicted antiviral phytochemicals for further antiviral potency assessment. Results suggested in-vitro antiviral activities of embryophytes and macrophytes were higher (43-62%) than grass (21-26%). O. basilicum (OB, 57-62%) and P. stratiotes (PS, 59-60%) exhibited the highest antiviral activities. In-vivo tests showed notable virus reduction (>60%) in culture solution, attributed to rhizofiltration (66-74%) and phytoinactivation/phytodegradation (63-84%). In-silico analysis identified rutin as a primary antiviral phytochemical for MS2 (-9.7 kcal/mol) and T4 (-10.9 kcal/mol), correlating with dose-response inactivation (∼58-62%). In-vivo tests suggested additional phytocompounds may contribute to viral inactivation, presenting new opportunities for herb-based wastewater treatment solutions. Consequently, this study not only demonstrates the antiviral capabilities of OB and PS but also introduces an innovative approach for addressing viral contaminants in water.

Chemico-pharmacological evaluation of the methanolic leaf extract of Catharanthus ovalis: GC-MS/MS, in vivo, in vitro, and in silico approaches

Introduction: Natural plant-based medicines have gained popularity recently as a major source of inventive, risk-free, and more potent secondary bioactive compounds with medicinal potential. Catharanthus ovalis is a perennial shrub containing various indole alkaloids cultivated extensively for local medical purposes. Methods: This research is conducted to identify the phytocompounds present in the leaves of C. ovalis and its central and peripheral analgesic, thrombolytic, and membrane-stabilizing activities through tail immersion, acetic acid-induced writhing, human blood clot lysis, and erythrocyte lysis by heat and hypotonic solution methods, respectively. Results and discussion: A total of 39 compounds were identified using GC-MS/MS techniques, including hexadecanoic acid, methyl ester (56.749%), methyl stearate (29.782%), carvacrol and its TBDMS derivative (12.586%), and 9-octadecenoic acid, methyl ester, (E)-] (9.297%) presented in high quantity. The highest tail immersion latency was observed for the 600 mg/kg extract of C. ovalis crude extract. Both 400 and 600 mg/kg doses of C. ovalis crude extract exhibited prominent peripheral analgesic activity. The maximum thrombolytic effect was observed by DCM soluble fraction extract by inhibiting 54.87% of the clot. However, the aqueous-soluble fraction of this extract manifested an excellent membrane-stabilizing effect by showing 73.98% and 87.51% hemolysis against heat- and hypotonic-induced hemolysis, respectively. Some of the compounds were identified as active agents against different receptors related to these diseases, which supported the findings of in vitro and in vivo tests. Conclusion: Further investigation needs to be conducted to specify and identify the exact mechanism of action of these compounds.

Phyto-pharmacological evaluation and characterization of the methanolic extract of the Baccaurea motleyana Müll. Arg. seed: promising insights into its therapeutic uses

Introduction: Plants and their extracts have been integral to the development of medicinal treatments throughout history, offering a vast array of compounds for innovative therapies. Baccaurea motleyana Müll. Arg., commonly known as Rambai, is an evergreen tree with economic importance in the Old-World Tropics. Method: The study investigates its phytochemical composition through Gas Chromatography-Mass Spectrometry (GC-MS) and evaluates its pharmacological properties, including antidiabetic, antidiarrheal, antimicrobial, and antidepressant effects. Result and Discussion: The GC-MS analysis revealed 15 bioactive compounds in the methanol extract, with Phenol, 3,5-bis(1,1-dimethylethyl)-, Methyl stearate, and Hexadecanoic acid, methyl ester being the predominant ones. The cytotoxicity assay demonstrated significant activity in the ethyl acetate fraction. Antimicrobial assays indicated mild to moderate antibacterial activity. In vivo studies on mice revealed significant hypoglycemic, antidiarrheal, and antidepressant properties. Molecular docking studies against EGFR, DHFR, GLUT-3, KOR, and MOA identified promising compounds with potential therapeutic effects. The identified compounds exhibited favorable ADME/T properties, emphasizing their potential for drug development. The study underscores the promising therapeutic potential of Baccaurea motleyana, showcasing its diverse bioactive compounds with significant medicinal properties. Conclusion: These findings lay the groundwork for future research, emphasizing the exploration of B. motleyana as a source of natural remedies for addressing prevalent health conditions.

Enhanced Antioxidant and Neuroprotective Properties of Pterostilbene (Resveratrol Derivative) in Amorphous Solid Dispersions

In this study, amorphous solid dispersions (ASDs) of pterostilbene (PTR) with polyvinylpyrrolidone polymers (PVP K30 and VA64) were prepared through milling, affirming the amorphous dispersion of PTR via X-ray powder diffraction (XRPD) and differential scanning calorimetry (DSC). Subsequent analysis of DSC thermograms, augmented using mathematical equations such as the Gordon-Taylor and Couchman-Karasz equations, facilitated the determination of predicted values for glass transition (Tg), PTR's miscibility with PVP, and the strength of PTR's interaction with the polymers. Fourier-transform infrared (FTIR) analysis validated interactions maintaining PTR's amorphous state and identified involved functional groups, namely, the 4'-OH and/or -CH groups of PTR and the C=O group of PVP. The study culminated in evaluating the impact of amorphization on water solubility, the release profile in pH 6.8, and in vitro permeability (PAMPA-GIT and BBB methods). In addition, it was determined how improving water solubility affects the increase in antioxidant (ABTS, DPPH, CUPRAC, and FRAP assays) and neuroprotective (inhibition of cholinesterases: AChE and BChE) properties. The apparent solubility of the pure PTR was ~4.0 µg·mL-1 and showed no activity in the considered assays. For obtained ASDs (PTR-PVP30/PTR-PVPVA64, respectively) improvements in apparent solubility (410.8 and 383.2 µg·mL-1), release profile, permeability, antioxidant properties (ABTS: IC50 = 52.37/52.99 μg·mL-1, DPPH: IC50 = 163.43/173.96 μg·mL-1, CUPRAC: IC0.5 = 122.27/129.59 μg·mL-1, FRAP: IC0.5 = 95.69/98.57 μg·mL-1), and neuroprotective effects (AChE: 39.1%/36.2%, BChE: 76.9%/73.2%) were confirmed.

Therapeutic targeting Tudor domains in leukemia via CRISPR-Scan Assisted Drug Discovery

Epigenetic dysregulation has been reported in multiple cancers including leukemias. Nonetheless, the roles of the epigenetic reader Tudor domains in leukemia progression and therapy remain unexplored. Here, we conducted a Tudor domain-focused CRISPR screen and identified SGF29, a component of SAGA/ATAC acetyltransferase complexes, as a crucial factor for H3K9 acetylation, ribosomal gene expression, and leukemogenesis. To facilitate drug development, we integrated the CRISPR tiling scan with compound docking and molecular dynamics simulation, presenting a generally applicable strategy called CRISPR-Scan Assisted Drug Discovery (CRISPR-SADD). Using this approach, we identified a lead inhibitor that selectively targets SGF29's Tudor domain and demonstrates efficacy against leukemia. Furthermore, we propose that the structural genetics approach used in our study can be widely applied to diverse fields for de novo drug discovery.

Discovery of 2,3-Diaminoindole Derivatives as a Novel Class of NOD Antagonists

NOD1 and NOD2 are members of the pattern recognition receptors involved in the innate immune response. Overactivation of NOD1 is implicated in inflammatory disorders, multiple sclerosis, and cancer cell metastases. NOD1 antagonists would represent valuable pharmacological tools to gain further insight into protein roles, potentially leading to new therapeutic strategies. We herein report the expansion of the chemical space of NOD1 antagonists via a multicomponent synthetic approach affording a novel chemotype, namely, 2,3-diaminoindoles. These efforts resulted in compound 37, endowed with low micromolar affinity toward NOD1. Importantly, a proof-of-evidence of direct binding to NOD1 of Noditinib-1 and derivative 37 is provided here for the first time. Additionally, the combination of computational studies and NMR-based displacement assays enabled the characterization of the binding modality of 37 to NOD1, thus providing key unprecedented knowledge for the design of potent and selective NOD1 antagonists.