Silico Modelling Research Articles

An In Silico Modelling Approach to Predict Hemodynamic Outcomes in Diabetic and Hypertensive Kidney Disease

Early diagnosis of kidney disease remains an unmet clinical challenge, preventing timely and effective intervention. Diabetes and hypertension are two main causes of kidney disease, can often appear together, and can only be distinguished by invasive biopsy. In this study, we developed a modelling approach to simulate blood velocity, volumetric flow rate, and pressure wave propagation in arterial networks of ageing, diabetic, and hypertensive virtual populations. The model was validated by comparing our predictions for pressure, volumetric flow rate and waveform-derived indexes with in vivo data on ageing populations from the literature. The model simulated the effects of kidney disease, and was calibrated to align quantitatively with in vivo data on diabetic and hypertensive nephropathy from the literature. Our study identified some potential biomarkers extracted from renal blood flow rate and flow pulsatility. For typical patient age groups, resistive index values were 0.69 (SD 0.05) and 0.74 (SD 0.02) in the early and severe stages of diabetic nephropathy, respectively. Similar trends were observed in the same stages of hypertensive nephropathy, with a range from 0.65 (SD 0.07) to 0.73 (SD 0.05), respectively. Mean renal blood flow rate through a single diseased kidney ranged from 329 (SD 40, early) to 317 (SD 38, severe) ml/min in diabetic nephropathy and 443 (SD 54, early) to 388 (SD 47, severe) ml/min in hypertensive nephropathy, showing potential as a biomarker for early diagnosis of kidney disease. This modelling approach demonstrated its potential application in informing biomarker identification and facilitating the setup of clinical trials.

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.

Investigation of the Role of Osteoporotic Vertebra Degeneration on the Stability of the Lumbar Spine: In Silico Modelling under Compressive Loading.

An evaluation of the impact of osteoporosis on loss of spinal stability, with or without intervertebral disc degeneration, using computational analysis is presented. The research also investigates the correlation between osteoporosis and intervertebral disc degeneration. Three-dimensional finite element models of human lumbar spine segments were used to assess the influence of osteoporosis on spinal stability. Five different models of age-related degeneration were created using various material properties for trabecular bone and intervertebral discs. Calculation results indicate that in a spine with osteoporosis, the deformation of the intervertebral discs can increase by more than 30% when compared to a healthy spine. Thus, intervertebral disc deformation depends not only on the degree of degeneration of the discs themselves, but their deformation is also influenced by the degree of osteoporosis of the vertebrae. Additionally, the load-bearing capacity of the spine can decrease by up to 30% with osteoporosis, regardless of the degree of intervertebral disc deformation. In conclusion, osteoporosis can contribute to intervertebral disc degeneration.

Fus-SMO: Kinetics, Biochemical Characterisation and In Silico Modelling of a Chimeric Styrene Monooxygenase Demonstrating Quantitative Coupling Efficiency.

The styrene monooxygenase, a two-component enzymatic system for styrene epoxidation, was characterised through the study of Fus-SMO - a chimera resulting from the fusion of StyA and StyB using a flexible linker. Notably, it remains debated whether the transfer of FADH2 from StyB to StyA occurs through diffusion, channeling, or a combination of both. Fus-SMO was identified as a trimer with one bound FAD molecule. In silico modelling revealed a well-distanced arrangement (45-50 Å) facilitated by the flexible linker's loopy structure. Pre-steady-state kinetics elucidated the FADox reduction intricacies (kred=110 s-1 for bound FADox), identifying free FADox binding as the rate-determining step. The aerobic oxidation of FADH2 (kox=90 s-1) and subsequent decomposition to FADox and H2O2 demonstrated StyA's protective effect on the bound hydroperoxoflavin (kdec=0.2 s-1) compared to free cofactor (kdec=1.8 s-1). At varied styrene concentrations, kox for FADH2 ranged from 80 to 120 s-1. Studies on NADH consumption vs. styrene epoxidation revealed Fus-SMO's ability to achieve quantitative coupling efficiency in solution, surpassing natural two-component SMOs. The results suggest that Fus-SMO exhibits enhanced FADH2 channelling between subunits. This work contributes to comprehending FADH2 transfer mechanisms in SMO and illustrates how protein fusion can elevate catalytic efficiency for biocatalytic applications.

Ecotoxicological Evaluation of Bisphenol A and Alternatives: A Comprehensive In Silico Modelling Approach.

Bisphenol A (BPA), a compound widely used in industrial applications, has raised concerns due to its environmental impact. As a key component in the manufacture of polycarbonate plastics and epoxy resins used in many consumer products, concerns about potential harm to human health and the environment are unavoidable. This study seeks to address these concerns by evaluating a range of potential BPA alternatives, focusing on their ecotoxicological properties. The research examines 76 bisphenols, including BPA derivatives, using a variety of in silico ecotoxicological models, although it should be noted that these models were not developed exclusively for this particular class of compounds. Consequently, interpretations should be made with caution. The results of this study highlight specific compounds of potential environmental concern and underscore the need to develop more specific models for BPA alternatives that will allow for more accurate and reliable assessment.

In Silico Modelling to Assess the Electrical and Thermal Disturbance Provoked by a Metal Intracoronary Stent during Epicardial Pulsed Electric Field Ablation.

Background: Pulsed Electric Field (PEF) ablation has been recently proposed to ablate cardiac ganglionic plexi (GP) aimed to treat atrial fibrillation. The effect of metal intracoronary stents in the vicinity of the ablation electrode has not been yet assessed. Methods: A 2D numerical model was developed accounting for the different tissues involved in PEF ablation with an irrigated ablation device. A coronary artery (with and without a metal intracoronary stent) was considered near the ablation source (0.25 and 1 mm separation). The 1000 V/cm threshold was used to estimate the ‘PEF-zone’. Results: The presence of the coronary artery (with or without stent) distorts the E-field distribution, creating hot spots (higher E-field values) in the front and rear of the artery, and cold spots (lower E-field values) on the sides of the artery. The value of the E-field inside the coronary artery is very low (~200 V/cm), and almost zero with a metal stent. Despite this distortion, the PEF-zone contour is almost identical with and without artery/stent, remaining almost completely confined within the fat layer in any case. The mentioned hot spots of E-field translate into a moderate temperature increase (<48 °C) in the area between the artery and electrode. These thermal side effects are similar for pulse intervals of 10 and 100 μs. Conclusions: The presence of a metal intracoronary stent near the ablation device during PEF ablation simply ‘amplifies’ the E-field distortion already caused by the presence of the vessel. This distortion may involve moderate heating (<48 °C) in the tissue between the artery and ablation electrode without associated thermal damage.

Assessing Clinical Potential of Old Antibiotics against Severe Infections by Multi-Drug-Resistant Gram-Negative Bacteria Using In Silico Modelling.

In the light of increasing antimicrobial resistance among gram-negative bacteria and the lack of new more potent antimicrobial agents, new strategies have been explored. Old antibiotics, such as colistin, temocillin, fosfomycin, mecillinam, nitrofurantoin, minocycline, and chloramphenicol, have attracted the attention since they often exhibit in vitro activity against multi-drug-resistant (MDR) gram-negative bacteria, such as Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. The current review provides a summary of the in vitro activity, pharmacokinetics and PK/PD characteristics of old antibiotics. In silico modelling was then performed using Monte Carlo simulation in order to combine all preclinical data with human pharmacokinetics and determine the probability of target (1-log kill in thigh/lung infection animal models) attainment (PTA) of different dosing regimens. The potential of clinical efficacy of a drug against severe infections by MDR gram-negative bacteria was considered when PTA was >95% at the epidemiological cutoff values of corresponding species. In vitro potent activity against MDR gram-negative pathogens has been shown for colistin, polymyxin B, temocillin (against E. coli and K. pneumoniae), fosfomycin (against E. coli), mecillinam (against E. coli), minocycline (against E. coli, K. pneumoniae, A. baumannii), and chloramphenicol (against E. coli) with ECOFF or MIC90 ≤ 16 mg/L. When preclinical PK/PD targets were combined with human pharmacokinetics, Monte Carlo analysis showed that among the old antibiotics analyzed, there is clinical potential for polymyxin B against E. coli, K. pneumoniae, and A. baumannii; for temocillin against K. pneumoniae and E. coli; for fosfomycin against E. coli and K. pneumoniae; and for mecillinam against E. coli. Clinical studies are needed to verify the potential of those antibiotics to effectively treat infections by multi-drug resistant gram-negative bacteria.

In Silico Modelling of Aortic Strain and Strain Rate in Aortic Coarctation Treated with Stent Angioplasty with Comparison to Clinical Cohorts

In Silico Modelling of Aortic Strain and Strain Rate in Aortic Coarctation Treated with Stent Angioplasty with Comparison to Clinical Cohorts

Ultrasound Assisted Synthesis and In Silico Modelling of 1,2,4-Triazole Coupled Acetamide Derivatives of 2-(4-Isobutyl phenyl)propanoic acid as Potential Anticancer Agents.

The development of an economical method for the synthesis of biologically active compounds was the major goal of this research. In the present study, we have reported the ultrasound-radiation-assisted synthesis of a series of novel N-substituted 1,2,4-triazole-2-thiol derivatives. The target compounds 6a-f were efficiently synthesized in significant yields (75-89%) by coupling 1,2,4-triazole of 2-(4-isobutylphenyl) propanoic acid 1 with different electrophiles using ultrasound radiation under different temperatures. The sonication process accelerated the rate of the reaction as well as yielded all derivatives compared to conventional methods. All derivatives were confirmed by spectroscopic (FTIR, 1HNMR, 13CNMR, HRMS) and physiochemical methods. All derivatives were further screened for their anticancer effects against the HepG2 cell line. Compound 6d containing two electron-donating methyl moieties demonstrated the most significant anti-proliferative activity with an IC50 value of 13.004 µg/mL, while compound 6e showed the lowest potency with an IC50 value of 28.399 µg/mL. The order of anticancer activity was found to be: 6d &gt; 6b &gt; 6f &gt; 6a &gt; 6c &gt; 6e, respectively. The in silico modelling of all derivatives was performed against five different protein targets and the results were consistent with the biological activities. Ligand 6d showed the best binding affinity with the Protein Kinase B (Akt) pocket with the lowest ∆G value of -176.152 kcal/mol. Compound 6d has been identified as a promising candidate for treatment of liver cancer.

Efficiency of Natural Deep Eutectic Solvents to Extract Phenolic Compounds from Agrimonia eupatoria: Experimental Study and In Silico Modelling.

To replace common organic solvents that present inherent toxicity and have high volatility and to improve the extraction efficiency, a range of natural deep eutectic solvents (NADESs) were evaluated for the extraction of phenolic compounds from Agrimonia eupatoria. Screening of NADES efficiency was carried out based on the total phenolic and flavonoid content and radical-scavenging activity, determined by spectrophotometry, as well as phenolic compounds quantified, obtained using ultra-high-performance liquid chromatography with a diode array detector and a triple-quadrupole mass spectrometer. Increased extraction efficiency when compared with organic solvent was achieved using NADES mixtures choline chloride (ChCl):urea 1:2 and choline chloride:glycerol 1:1. Flavonol glycosides were the most abundant compounds in all extracts. The COSMO-RS model provided insights into the most important intermolecular interactions that drive the extraction process. Moreover, it could explain the extraction efficiency of flavonol glycosides using ChCl:glycerol NADES. The current article offers experimental evidence and mechanistic insights for the selection of optimal NADES to extract bioactive components from Agrimonia eupatoria.

Phytochemical Analysis, Antioxidant, Antimicrobial, and Anti-Swarming Properties of Hibiscus sabdariffa L. Calyx Extracts: In Vitro and In Silico Modelling Approaches.

The aim of this study was to investigate the phytochemical composition of dried Roselle calyx (Hibiscus sabdariffa L.) using both ethanolic and aqueous extracts. We report the antimicrobial activities against a wide range of bacteria, yeast, and fungi. The antioxidant activities were tested using 2,2-diphenyl-1-picrylhydrazyl (DPPH), hydroxyl, and 2–2′-azinobis-(3-ethylbenzthiazoline-6-sulfonic acid) radical scavenging assays. We report also for the first time the effect of the swarming motility in Pseudomonas aeruginosa PAO1. Our results showed that the tested two extracts were a rich source of phenols, flavonoids, and tannins with different degrees. Additionally, eleven phytoconstituents were identified by LC/MS technique (Hibiscus acid: 3-caffeoylquinic acid, 5-caffeoylquinic acid, 5-feruloylquinic acid, cyanidin 3-o-glucoside, myricetin, quercetin 7-o-rutinoside, quercetin 3-o-glucoside, delphinidin 3-o-sambubioside, and kaempferol 3-o-p-coumaroyl-glucoside). Also, it was shown that the calyx extract can scavenge 86% of the DPPH radical, while the rate of 53% and 23% of inhibition of the DPPH was obtained only at the concentration of 125 and 50 µg/mL, and a small inhibition was made at a concentration of 5 μg/mL. Roselle extracts inhibited the growth of the selected microorganisms at low concentrations, while higher concentrations are needed to completely kill them. However, no activity against CVB-3 was recorded for both extracts. In addition, the obtained extracts reduced the swarming motility of P. aeruginosa at 2.5 mg/ml. The docking simulation showed acceptable binding affinities (up to −9.6 kcal/mol) and interaction with key residues of 1JIJ, 2QZW, and 2UVO. The obtained results highlighted the potential use of Roselle extract as a source of phytoconstituents with promising antimicrobial, antioxidant, and anti-quorum sensing activities.

In Silico Modelling, Regulation of Cell Viability and Anti Atherosclerotic Effect in Macrophage by Decaffeinated Coffee and Green Tea Extract

In Silico Modelling, Regulation of Cell Viability and Anti Atherosclerotic Effect in Macrophage by Decaffeinated Coffee and Green Tea Extract

Sea Anemones Responding to Sex Hormones, Oxybenzone, and Benzyl Butyl Phthalate: Transcriptional Profiling and in Silico Modelling Provide Clues to Decipher Endocrine Disruption in Cnidarians.

Endocrine disruption is suspected in cnidarians, but questions remain how occurs. Steroid sex hormones are detected in corals and sea anemones even though these animals do not have estrogen receptors and their repertoire of steroidogenic enzymes appears to be incomplete. Pathways associated with sex hormone biosynthesis and sterol signaling are an understudied area in cnidarian biology. The objective of this study was to identify a suite of genes that can be linked to exposure of endocrine disruptors. Exaiptasia diaphana were exposed to nominal 20ppb concentrations of estradiol (E2), testosterone (T), cholesterol, oxybenzone (BP-3), or benzyl butyl phthalate (BBP) for 4 h. Eleven genes of interest (GOIs) were chosen from a previously generated EST library. The GOIs are 17β-hydroxysteroid dehydrogenases type 14 (17β HSD14) and type 12 (17β HSD12), Niemann-Pick C type 2 (NPC2), Equistatin (EI), Complement component C3 (C3), Cathepsin L (CTSL), Patched domain-containing protein 3 (PTCH3), Smoothened (SMO), Desert Hedgehog (DHH), Zinc finger protein GLI2 (GLI2), and Vitellogenin (VTG). These GOIs were selected because of functional associations with steroid hormone biosynthesis; cholesterol binding/transport; immunity; phagocytosis; or Hedgehog signaling. Quantitative Real-Time PCR quantified expression of GOIs. In silico modelling utilized protein structures from Protein Data Bank as well as creating protein structures with SWISS-MODEL. Results show transcription of steroidogenic enzymes, and cholesterol binding/transport proteins have similar transcription profiles for E2, T, and cholesterol treatments, but different profiles when BP-3 or BBP is present. C3 expression can differentiate between exposures to BP-3 versus BBP as well as exposure to cholesterol versus sex hormones. In silico modelling revealed all ligands (E2, T, cholesterol, BBP, and BP-3) have favorable binding affinities with 17β HSD14, 17β HSD12, NPC2, SMO, and PTCH proteins. VTG expression was down-regulated in the sterol treatments but up-regulated in BP-3 and BBP treatments. In summary, these eleven GOIs collectively generate unique transcriptional profiles capable of discriminating between the five chemical exposures used in this investigation. This suite of GOIs are candidate biomarkers for detecting transcriptional changes in steroidogenesis, gametogenesis, sterol transport, and Hedgehog signaling. Detection of disruptions in these pathways offers new insight into endocrine disruption in cnidarians.

The Molecular Dynamics Effects of Rutin on CDKS 2, 4 and 6: In Silico Modelling and Molecular Dynamics

Objectives: This simulated study has mechanistically evaluated the molecular dynamics effects of rutin on CDKs 2, 4, and 6 in cell cycling. Methods: Protein Data Bank (http://www.rcsb.org) was used to obtain the PDB file of CDK 2, 4, and 6. After simulation of CDKs in Gromacs software, AutoDock 4.2 was used to run 200 stages of molecular docking of CDKs in the presence of the rutin. CDK 2, 4, and 6 were simulated in the presence of rutin after docking. Results: Rutin had the highest tendency to bind the CDK-2 and CDK-6 via binding 16 and 18 residues in the binding site with hydrogen and hydrophobic bonds (respectively). Also, they had the highest amount of binding energy released. Rutin decreased total energy in CDKs and reduced the radius of gyration in CDK-2 and CDK-6 after docking. The secondary coil structure increased in CDK-2 and decreased in CDK-4 and 6. Conclusion: Conformational changes in CDK2 and 6 via rutin can inhibit the activity of these proteins and subsequently arrest the cell cycle in phases G1, S, and G2, which can lead the damaged cell to cell repair or Apoptosis. Keywords: Apoptosis, cell arresting, rutin, molecular dynamic, simulation

Synthesis and Cytotoxicity Evaluation of DNA-Interactive β-Carboline Indolyl-3-Glyoxamide Derivatives: Topo-II Inhibition and in Silico Modelling Studies

Synthesis and Cytotoxicity Evaluation of DNA-Interactive β-Carboline Indolyl-3-Glyoxamide Derivatives: Topo-II Inhibition and in Silico Modelling Studies

QPoweredCompound2DeNovoDrugPropMax – a novel programmatic tool incorporating deep learning and in silico methods for automated in silico bio-activity discovery for any compound of interest

Network data is composed of nodes and edges. Successful application of machine learning/deep learning algorithms on network data to make node classification and link prediction have been shown in the area of social networks through which highly customized suggestions are offered to social network users. Similarly one can attempt the use of machine learning/deep learning algorithms on biological network data to generate predictions of scientific usefulness. In the presented work, compound-drug target interaction network data set from bindingDB has been used to train deep learning neural network and a multi class classification has been implemented to classify PubChem compound queried by the user into class labels of PBD IDs. This way target interaction prediction for PubChem compounds is carried out using deep learning. The user is required to input the PubChem Compound ID (CID) of the compound the user wishes to gain information about its predicted biological activity and the tool outputs the RCSB PDB IDs of the predicted drug target interaction for the input CID. Further the tool also optimizes the compound of interest of the user toward drug likeness properties through a deep learning based structure optimization protocol. The tool also incorporates a feature to perform automated In Silico modelling to find the interaction between the compounds and the predicted drug targets to uncover their protein-ligand interaction profiles. The program is hosted, supported and maintained at the following GitHub repository. https://github.com/bengeof/Compound2DeNovoDrugPropMax. Anticipating the use of quantum computing and quantum machine learning in drug discovery we use the Penny-lane interface to quantum hardware to turn classical Keras layers used in our machine/deep learning models into a quantum layer and introduce quantum layers into classical models to produce a quantum-classical machine/deep learning hybrid model of our tool and the code corresponding to the same is provided below. https://github.com/bengeof/QPoweredCompound2DeNovoDrugPropMax. HIGHLIGHTS Deep learning based network pharmacology approach to predict the bio-activity of compounds. Further optimization of the compound toward drug like properties using deep learning techniques. Automated in silico modeling and interaction profiling of deep learning predicted target protein-ligand interaction. Communicated by Ramaswamy H. Sarma

A Study of the Antibacterial Activities and the Mode of Action of L-Methionine and L-Cystine Based Surfactants and their Interaction with Bovine Serum Albumin Using Fluorescence Spectroscopy and in Silico Modelling

Surfactants are versatile excipients that are commonly employed in diverse pharmaceutical formulations given their broad range of antimicrobial activities. Sulfur-based amino acid surfactants are promising candidates as substitutes for conventional antibacterial agents in light of the current antibiotic resistance crisis. Dodecyl esters of the free amine (SURF1), cationic ester hydrochloride (SURF2), and quaternary ammonium (QUAT3) derivatives of methionine, and the Gemini diester of cystine (GEM4) were synthesized and evaluated for antibacterial activity against Gram-positive and Gram-negative pathogens. All surfactants displayed moderate to high antibacterial activities, particularly on Gram-positive bacteria, with QUAT3 showing the highest activity. Among Gram-negative bacteria, QUAT3, GEM4, and SURF2 were mostly active towards K. pneumoniae with minimum inhibitory concentrations (MIC) ranging from 0.004 to 0.441 mM. QUAT3 and GEM4 displayed a bacteriostatic behavior similar to that of tetracycline, as assessed by broth macrodilution assays. Fluorescence binding studies with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) revealed that the antibacterial activities could be attributed to a combination of electrostatic and hydrophobic interactions. Bovine serum albumin (BSA) fluorescence and molecular docking studies indicated that SURF1 and QUAT3 interact mainly via van der Waals' forces and hydrogen bonding while SURF2 binds through hydrophobic interactions. QUAT3, which displays broad-spectrum activity, has the potential to combat drug-resistant bacteria.

Norfloxacin Loaded Lipid Polymer Hybrid Nanoparticles for Oral Administration: Fabrication, Characterization, In Silico Modelling and Toxicity Evaluation.

Norfloxacin (NOR), widely employed as an anti-bacterial drug, has poor oral bioavailability. Nano based drug delivery systems are widely used to overcome the existing oral bioavailability challenges. Lipid–Polymer Hybrid Nanoparticles (LPHNs) exhibit the distinctive advantages of both polymeric and liposomes nanoparticles, while excluding some of their disadvantages. In the current study, NOR loaded LPHNs were prepared, and were solid amorphous in nature, followed by in vitro and in vivo evaluation. The optimized process conditions resulted in LPHNs with the acceptable particle size 121.27 nm, Polydispersity Index (PDI) of 0.214 and zeta potential of −32 mv. The addition of a helper lipid, oleic acid, and polymers, ethyl cellulose, substantially increased the encapsulation efficiency (EE%) (65% to 97%). In vitro study showed a sustained drug release profile (75% within 12 h) for NOR LPHNs. The optimized NOR LPHNs showed a significant increase (p < 0.05) in bioavailability compared to the commercial product. From the acute toxicity study, the LD50 value was found to be greater than 1600 mg/kg. The molecular modelling studies substantiated the experimental results with the best combination of polymers and surfactants that produced highly stable LPHNs. Therefore, LPHNs proved to be a promising system for the delivery of NOR, as well as for other antibiotics and hydrophobic drugs.

Towards Novel 3-Aminopyrazinamide-Based Prolyl-tRNA Synthetase Inhibitors: In Silico Modelling, Thermal Shift Assay and Structural Studies.

Human cytosolic prolyl-tRNA synthetase (HcProRS) catalyses the formation of the prolyl-tRNAPro, playing an important role in protein synthesis. Inhibition of HcProRS activity has been shown to have potential benefits in the treatment of fibrosis, autoimmune diseases and cancer. Recently, potent pyrazinamide-based inhibitors were identified by a high-throughput screening (HTS) method, but no further elaboration was reported. The pyrazinamide core is a bioactive fragment found in numerous clinically validated drugs and has been subjected to various modifications. Therefore, we applied a virtual screening protocol to our in-house library of pyrazinamide-containing small molecules, searching for potential novel HcProRS inhibitors. We identified a series of 3-benzylaminopyrazine-2-carboxamide derivatives as positive hits. Five of them were confirmed by a thermal shift assay (TSA) with the best compounds 3b and 3c showing EC50 values of 3.77 and 7.34 µM, respectively, in the presence of 1 mM of proline (Pro) and 3.45 µM enzyme concentration. Co-crystal structures of HcProRS in complex with these compounds and Pro confirmed the initial docking studies and show how the Pro facilitates binding of the ligands that compete with ATP substrate. Modelling 3b into other human class II aminoacyl-tRNA synthetases (aaRSs) indicated that the subtle differences in the ATP binding site of these enzymes likely contribute to its potential selective binding of HcProRS. Taken together, this study successfully identified novel HcProRS binders from our anti-tuberculosis in-house compound library, displaying opportunities for repurposing old drug candidates for new applications such as therapeutics in HcProRS-related diseases.

Computational in Silico Modelling of Phytochemicals as a Potential Cure

Urinary tract infection (UTI) is one of the most severe public health problems affecting both sexes but females are more susceptible due to the differences in urogenital and reproductive anatomy, physiology and lifestyle. Due to multi?drug resistant strains and high recurrence rate, UTI has become a major socioeconomic burden. It was found that microbial infections including Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa and Proteus mirabilis species are the major causes of UTI with different signs and symptoms including painful urination or dysuria, haematuria, urinary urgency, burning micturition, frequent urination, nausea, and vomiting. Phytochemicals are effective to combat bacterial resistance with high efficacy, and easy availability with minimal or no side effects. For this reason, we present a docking?based screening using a quantum mechanical scoring of a library built from approved drugs and compounds that Curcumin, Anolignan B, Piperine, Carvacrol, Quercetin, Kaempferol, Citral, Allyl Isothiocyanate with Proteins with PDB id’s 2N50, 4C4V, 6H1X, 4UU4 could display antibacterial activity against UTI. Clearly, these compounds should be further evaluated in experimental assays and clinical trials to confirm their actual activity against the disease. We hope that these findings may contribute to the rational drug design against UTI.