Docking Tools Research Articles

Aptamer-based electrochemical biosensor with S protein binding affinity for COVID-19 detection: Integrating computational design with experimental validation of S protein binding affinity

Aptamer-based biosensors capable of rapid one-step detection of viruses provide new capabilities for large-scale detection of COVID-19. Here we report a combined aptamer-based electrochemical and computational approach to characterize the interaction between a 60 base single stranded (ss)DNA aptamer and the viral S protein using molecular docking and bioinformatics tools. To construct the biosensor, the DNA aptamer was immobilized to the surface of a gold nanoparticles (AuNPs) modified electrode and methylene blue (MB) was used as redox indicator. Based on thermodynamic calculations for the aptamer sequence as well as several runs in APBS (Adaptive Poisson-Boltzmann Equation), we found that S protein GLN104-ASP115 pocket is the candidate for DNA 30–39(GGGAGTGGTT) sequence interaction. In the presence of S-protein, the target induced conformational changes in the aptamer’s structure, generating an increase in the MB redox signal, with a linear range between 10 pM to 6 nM and a limit of detection of 91.1 pM using differential pulse voltammetry (DPV). The aptasensor was investigated in spiked human saliva and serum samples, demonstrating performance in both media. This study demonstrates the potential of the MB-labeled electrochemical aptasensor for direct one-step detection of viral proteins, COVID-19 and potentially other viral agents.

Single domain antibodies specific for HER2 dimerization domain effectively disrupts HER2 dimerization

Dimer-dependent phosphorylation of HER2 receptor is a key event for the signal transduction of HER family of receptors which correlates with tumor invasion and metastasis. New generation of therapies based on dimerization domain inhibition using monoclonal or fragment antibodies was introduced. A potent method for manufacturing antibodies and antibody fragments is the phage display antibody library method. A recombinant phage was generated using the phage display method from synthetic dAb library. Subtractive biopanning was performed on sepharose 4b resin. Evaluation of success of subtractive biopanning was confirmed by the PCR fingerprinting after the fourth round of biopanning. The fourth round of biopanning results in the isolation of several dimerization domain reactive clones based on the polyclonal phage ELISA results. Monoclonal phage cell ELISA was used to select the positive clones with the highest affinity, and they were subsequently employed for functional tests. Cell-ELISA, MTT assay and dimerization inhibition test revealed that the reactivity and specificity of the selected monoclonal phage to dimerization domain of HER2. Further, Annexin V/PI staining and gene expression analysis showed that increased apoptosis rates. Also, in silico binding of the selected clones to conformational structure of HER2 was applied, using protein–protein docking tool of the ICM-Pro software, and showed sdAbs were specifically interacted with dimerization domain of the receptor. In conclusion, we have identified a single domain targeting HER2 dimerization, which represents a promising therapeutic and diagnostic candidate for HER2-positive cancers. Purified sdAb needs to more research to evaluate it both in vivo and in vitro via functional tests to determine if it can be applied for treatment and diagnostics.

ViTScore: a novel three-dimensional Vision Transformer method for accurate prediction of protein-ligand docking poses.

Protein-ligand interactions (PLIs) are essential for cellular activities and drug discovery, and due to the complexity and high cost of experimental methods, there is a great demand for computational approaches, such as protein-ligand docking, to decipher PLI patterns. One of the most challenging aspects of protein-ligand docking is to identify near-native conformations from a set of poses, but traditional scoring functions still have limited accuracy. Therefore, new scoring methods are urgently needed for methodological and/or practical implications. We present a novel deep learning-based scoring function for ranking protein-ligand docking poses based on Vision Transformer (ViT), named ViTScore. To recognize near-native poses from a set of poses, ViTScore voxelizes the protein-ligand interactional pocket into a 3D grid labeled by the occupancy contribution of atoms in different physicochemical classes. This allows ViTScore to capture the subtle differences between spatially and energetically favorable near-native poses and unfavorable non-native poses without needing extra information. After that, ViTScore will output the prediction of the root mean square deviation (rmsd) of a docking pose with reference to the native binding pose. ViTScore is extensively evaluated on diverse test sets including PDBbind2019 and CASF2016, and obtains significant improvements over existing methods in terms of RMSE, R and docking power. Moreover, the results demonstrate that ViTScore is a promising scoring function for protein-ligand docking, and it can be used to accurately identify near-native poses from a set of poses. Furthermore, the results suggest that ViTScore is a powerful tool for protein-ligand docking, and it can be used to accurately identify near-native poses from a set of poses. Additionally, ViTScore can be used to identify potential drug targets and to design new drugs with improved efficacy and safety.

COMPARATIVE EVALUATION OF PROTEIN AND LIGAND-BASED DOCKING PROTOCOLS THROUGH PROTEIN PHOSPHATASE SLINGSHOT HOMOLOG 2 COMPLEX

A molecular docking study is used to investigate the interactions between the two molecules. These interactions may be covalent, hydrogen, or Van der Waals forces. Various web-based and stand-alone tools have been discovered for molecular docking analysis. In this study, we performed a comparison between web-based and stand-alone docking tools to evaluate the accuracy. Five web-based tools i) Dockthor, ii) Patchdock, iii) RPBA Web, iv) Swissdock, v) Patinum and two stand-alone tools1) Autodock Vina & 2) Hex were selected for the evaluation of the tool`s accuracy in term of best conformations with minimum binding energies. Protein phosphatase Slingshot homolog 2, SSH2 (PDBID: 2NT2) and four of its related proteins were used as the key proteins in this study. Ligands and Proteins interacting with SSH2 in the Novel signalling pathway were investigated through above mentioned tools.

Computational investigation on the effect of the peptidomimetic inhibitors (NPT100-18A and NPT200-11) on the α-synuclein and lipid membrane interactions

Parkinson’s disease (PD) is associated with α-synuclein (α-Syn), a presynaptic protein that binds to cell membranes. The molecular pathophysiology of PD most likely begins with the binding of α-Syn to membranes. Recently, two peptidomimetic inhibitors (NPT100-18A and NPT200-11) were identified to potentially interact with α-Syn and affect the interaction of α-Syn with the membrane. In this study, the effect of the two peptidomimetic inhibitors on the α-Syn-membrane interaction was demonstrated. DFT calculations were performed for optimization of the two inhibitors, and the nucleophilicity (N) and electrophilicity (ω) of NPT100-18A and NPT200-11 were calculated to be 3.90 and 3.86 (N); 1.06 and 1.04 (ω), respectively. Using the docking tool (CB-dock2), the two α-Syn-peptidomimetic inhibitor complexes (α-Syn-NPT100-18A and α-Syn-NPT200-11) have been prepared. Then all-atom molecular dynamics (MD) simulation was carried out on the α-Syn (control), α-Syn-NPT100-18A and α-Syn-NPT200-11 complex systems in presence of DOPE: DOPS: DOPC (5:3:2) lipid bilayer. From the conformational dynamics analysis, the 3-D structure of α-Syn was found to be stable, and the helices present in the regions (1–37) and (45–95) of α-Syn were found to be retained in the presence of the two peptidomimetic inhibitors. The electron density profile analysis revealed the binding modes of NAC and C-terminal region of α-Syn (in the presence of NPT200-11 inhibitor) with lipid membrane are in the close vicinity from the lipid bilayer centre. Our findings in this study on α-Syn-membrane interactions may be useful for developing a new therapeutic approach for treating PD and other neurodegenerative disorders. Communicated by Ramaswamy H. Sarma

MEGADOCK-on-Colab: an easy-to-use protein–protein docking tool on Google Colaboratory

MotivationSince the advent of ColabFold, numerous software packages have been provided with Google Colaboratory-compatible ipynb files, allowing users to effortlessly test and reproduce results without the need for local installation or configuration. MEGADOCK, a protein–protein docking tool, is particularly well-suited for Google Colaboratory due to its lightweight computations and GPU acceleration capabilities. To increase accessibility and promote widespread use, it is crucial to provide a computing environment compatible with Google Colaboratory.ResultsIn this study, we report the development of a Google Colaboratory environment for running our protein–protein docking software, MEGADOCK. We provide a comprehensive ipynb file, including the compilation of MEGADOCK with the FFTW library installation on Colaboratory, the introduction of related tools using PyPI/apt, and the execution and visualization of docking structures. This streamlined environment enables users to visualize docking structures with just one click. The code is available under a CC-BY NC 4.0 license from https://github.com/ohuelab/MEGADOCK-on-Colab.

Studies on the binding of curcumin and glycyrrhetinic acid to human serum albumin by multi-spectroscopic methods and molecular docking approaches

Human serum albumin (HSA) is the most prevalent and important carrier in plasma, and its interaction with drugs may have a significant effect on the efficacy of drugs. Curcumin (CU) and glycyrrhizic acid (GA) are excellent potential anti-cancer candidates, and studies have shown that the combined application of them can significantly enhance the anti-cancer effect. In order to investigate the interaction of binary systems (HSA-CU/GA) and ternary systems (HSA-CU-GA), we employed spectroscopic methods to study the interaction mechanism and binding affinity, and carried out molecular docking with docking tools. The fluorescence quenching spectrum showed that CU and GA all had fluorescence quenching effects on HSA, and the quenching mechanism were static quenching. The binding sites of CU and GA to HSA were both in site I, and the main force were van der Waals forces and hydrogen bonds. The presence of GA enhanced the affinity between CU and HSA, increased the bioavailability of CU and its stability in plasma. The circular dichroism (CD) and three-dimensional fluorescence experiments showed that CU and GA dramatically altered the conformation of HSA, and GA could enhance the influence of CU on the conformation of HSA. This study aimed at exploring the binding properties of CU/GA to HSA, and providing important theoretical support for their combined use.

Fagopyrum tataricum (L.) Gaertn interacts with Gsk-3β/Nrf-2 signalling to protect neurotoxicity in a zebrafish model

Ethnopharmacological relevanceFagopyrum tataricum (L.) Gaertn is used as a folk medicine in many Asian countries due to its anti-inflammatory, antioxidant, and several other health-promoting properties. It is also prescribed to improve neurocognitive functions and alleviate inflammatory conditions. Aim of the studyOxidative stress and neuroinflammation plays a crucial role in neurodegenerative conditions. Hence, based on the ethnomedical claims and available literature, the present study investigated neuroprotective efficacy of a seed extract (ft-ext) of Fagopyrum tataricum against acrylamide (ACR)-induced neurotoxicity. Materials and methodsThe phytochemical characterization of ft-ext was performed by a high-performance liquid chromatography method. Molecular interactions of the identified compounds of ft-ext were studied using an in-silico docking tool. An in-vitro protein denaturation assay was done to check anti-inflammatory activity. The 5 days’ post-fertilized zebrafish larvae were exposed to 1 mM and 2.5 mM ACR with or without ft-ext for 72 h to study its neuroprotective efficacy. Real-time polymerase chain reaction and western blotting studies were performed to analyse the oxidative stress-related gene and protein expressions respectively. ResultsThe extract showed the presence of chlorogenic acid, rutin, caffeic acid, vitexin, syringic acid, quercetin, p-coumaric acid, kaempferol, and ferulic acid. In-vitro protein denaturation assay of ft-ext showed a potent anti-inflammatory effect. The ft-ext improved ACR-mediated locomotor deficit and reduced overall mortality in the larvae. The brain lipid peroxidation and protein carbonylation results revealed an elevated level of oxidative stress in the ACR-treated group, which was reduced in ft-ext-treated larvae. The extract treatment increased the expression of nrf2, gpx, and hmox1a, while simultaneously downregulated trxr2 levels in the brain of larvae exposed to ACR. The treatment also showed inactivation of Gsk-3β, thus maintaining a normal pool of Nrf2 and β-catenin. Molecular docking of identified compounds of ft-ext showed possible hydrogen and hydrophobic interactions with Gsk-3β. ConclusionThe ft-ext prevents ACR-mediated neurotoxicity by suppressing Gsk-3β mediated oxidative stress.

Insights into molecular docking: A comprehensive view

Molecular docking software is mainly used in drug development. Molecular docking offers a wide range of useful techniques for the creation and analysis of pharmaceuticals. Before now, predicting the target for a receptor was extremely challenging however, docking the target protein with a ligand is a straightforward and dependable procedure presently and binding affinity is designed. To see a molecule's three-dimensional structure, a variety of docking tools have been created. The docking score can also be examined using a variety of computational techniques. This review mainly emphases on the core idea of molecular docking, as well as its major uses and many kinds of interaction, Basics requirements for molecular docking, Molecular Approach, Application, and Software available for the Docking of molecules.

Analysis of the Chemical Composition and Evaluation of the Antioxidant, Antimicrobial, Anticoagulant, and Antidiabetic Properties of Pistacia lentiscus from Boulemane as a Natural Nutraceutical Preservative.

Pistacia lentiscus L. has traditionally been employed as a diuretic and stimulant in the treatment of hypertension. Our interest centered on analyzing the chemical profile of the plant's leaves and its in vitro, in vivo, and in silico antioxidant, antimicrobial, anticoagulant, and antidiabetic effects in order to valorize this species and prepare new high-value products that can be used in the agro-food and pharmaceutical industries. When this species' essential oil was hydrodistilled and subjected to GC-MS analysis, the results showed that the principal components were germacrene D (17.54%), spathulenol (17.38%), bicyclogermacrene (12.52%), and terpinen-4-ol (9.95%). The extraction of phenolic compounds was carried out by decoction and Soxhlet. The determination of total polyphenols, flavonoids, and tannins of aqueous and organic extracts by spectrophotometric methods demonstrated the richness of this species in phenolic compounds. Chromatographic analysis by HPLC/UV-ESI-MS of the aqueous extract of P. lentiscus revealed the presence of 3,5-di-O-galloyl quinic acid, gallic acid, and 3,4,5-tri-O-galloyl quinic acid specific to this species. The study of antioxidant activity by three methods (DPPH, FRAP, and Total Antioxidant Capacity) revealed that P. lentiscus is a very promising source of natural antioxidants. The antimicrobial activity of the essential oil and aqueous extract (E0) was studied by microdilution on the microplate. The results revealed the effectiveness of the aqueous extract compared to the essential oil against Gram-negative bacteria (K. pneumoniae, A. baumannii, E. aerogenes, E. cloacae, P. fluorescence, Salmonella sp., Shigella sp., and Y. enterolitica) and candidoses (C. krusei and C. albicans). The measurements of prothrombin time (PT) and activated partial thromboplastin time (aPTT) of the aqueous extract (E0) can significantly prolong these tests from concentrations of 2.875 and 5.750 mg/mL, respectively. The antihyperglycemic effect of the aqueous extract (E0) showed a strong in vitro inhibitory activity of α-amylase and α-glucosidase compared to acarbose. Thus, it significantly inhibited postprandial hyperglycemia in Wistar albino rats. The in-silico study of the major compounds of the essential oil and extract (E0) carried out using PASS, SwissADME, pkCSM, and molecular docking tools confirmed our in vitro and in vivo results. The studied compounds showed a strong ability to be absorbed by the gastrointestinal tract and to passively diffuse through the blood-brain barrier, a similarity to drugs, and water solubility. Molecular docking experiments deduced the probable mode of action of the identified compounds on their respective target proteins, such as NADPH oxidase, thrombin, α-amylase, and α-glucosidase. Furthermore, given the demonstrated antioxidant, antimicrobial, anticoagulant, and antidiabetic effects, we can affirm the richness of P. lentiscus in bioactive molecules and its use in traditional medicine as a source of preservative agent.

Investigation of target genes and potential mechanisms related to compound Xiao-ai-fei honey ointment based on network pharmacology and bioinformatics analysis.

Compound Xiao-ai-fei honey ointment (CXHO) is an anticancer preparation with a long history in Uyghur folk medicine in China and has been used for the treatment of gastric cancer (GC) in Xinjiang, China. Nevertheless, the mechanism of its anticancer effect remains to be investigated. Bioactive ingredients of CXHO were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Target genes of ingredients were acquired via the PubChem and Swiss target prediction database. Gene expression profiling of GC was obtained from GSE54129 in the GEO database and analyzed using the limma package in R. The hub genes associated with CXHO in GC were validated using the TIMER2.0 database, GEPIA2 database and Auto Dock tools. The effect of CXHO on migration of GC cells was detected by Transwell chamber assay and Wound healing assay. The effect of CXHO on expression levels of MMP2/MMP9 and NF-κb, PI3K/AKT signaling pathway was detected by Western blot assay. Forty-five bioactive ingredients and their 819 related genes were found. A total of 462 differentially expressed genes were identified between GC patients and healthy controls. Seventeen common target genes were identified as hub genes CXHO against GC. Among them, MMP2 and MMP9 were significantly associated with tumor immune infiltrates and had good binding affinity with effective ingredients. Moreover, we validated the mRNA and protein expression levels and prognostic value of MMP2 and MMP9 by different databases. In addition, Kyoto encyclopedia of genes and genomes and gene ontology analyses showed that the 17 common target genes were mainly involved in steroid hormone biosynthesis and cancer-related pathways. Experimental results showed that CXHO inhibited migration of GC cells and down regulated the expression levels of MMP2/MMP9, NF-κb. In addition, CXHO can inhibited PI3K/AKT signaling pathway. We identified and experimental validated 2 pivotal target genes of CXHO against GC and preliminarily analyzed the potential mechanisms by which CXHO inhibits the development of GC. All these findings support CXHO as a promising drug for the treatment of GC.

Phytochemical profiling, pharmacology prediction, and molecular docking study of Chromolaena odorata extract against multiple target proteins in wound healing

Introduction: Wounds have a significant influence on socioeconomic and the quality of life. Many attempts have been taken to produce advanced wound dressing to fulfill demands. The incorporation of natural therapeutics like medicinal plants in wound dressings is currently popular. However, several medications have failed to enter the market due to inadequate pharmacokinetics data. Computer-aided tools are now available as advanced drug discovery methods, which can be used to screen pharmaceuticals from phytochemicals found in various medicinal plants. This study aims to evaluate the phytoconstituents of Chromolaena odorata extract and its pharmacological potential as a wound-healing agent. Methods: Phytoconstituents from C. odorata were identified using qualitative screening methods and gas chromatography-mass spectrometry (GC-MS), and their mechanistic properties were assessed using molecular docking and SwissADME tools. Results: Current works revealed that the topmost phytoconstituents in C. odorata were phytol (49.83%), hexadecanoic acid ethyl ester (9.40%), linolenic acid (8.07%), and squalene (3.53%). Through SwissADME analysis, all four topmost compounds obeyed Lipinski’s Rule of 5. In silico molecular docking study of these top phytoconstituents against several protein targets involved in wound healing revealed that squalene had the highest binding affinity to GSK3-β (-6.8 kJ/ mol), MMP-9 (-7.4 kJ/mol), and COX-2 (-8.6 kJ/mol) as compared to other ligands (phytol, linolenic acid, and hexadecenoic acid ethyl ester). Conclusion: These findings suggest that the most prominent compound that contributes to C. odorata’s wound healing capacity is squalene and the incorporation of C. odorata in potential wound dressing formulation is justified.

ML-PLIC: a web platform for characterizing protein-ligand interactions and developing machine learning-based scoring functions.

Cracking the entangling code of protein-ligand interaction (PLI) is of great importance to structure-based drug design and discovery. Different physical and biochemical representations can be used to describe PLI such as energy terms and interaction fingerprints, which can be analyzed by machine learning (ML) algorithms to create ML-based scoring functions (MLSFs). Here, we propose the ML-based PLI capturer (ML-PLIC), a web platform that automatically characterizes PLI and generates MLSFs to identify the potential binders of a specific protein target through virtual screening (VS). ML-PLIC comprises five modules, including Docking for ligand docking, Descriptors for PLI generation, Modeling for MLSF training, Screening for VS and Pipeline for the integration of the aforementioned functions. We validated the MLSFs constructed by ML-PLIC in three benchmark datasets (Directory of Useful Decoys-Enhanced, Active as Decoys and TocoDecoy), demonstrating accuracy outperforming traditional docking tools and competitive performance to the deep learning-based SF, and provided a case study of the Serine/threonine-protein kinase WEE1 in which MLSFs were developed by using the ML-based VS pipeline in ML-PLIC. Underpinning the latest version of ML-PLIC is a powerful platform that incorporates physical and biological knowledge about PLI, leveraging PLI characterization and MLSF generation into the design of structure-based VS pipeline. The ML-PLIC web platform is now freely available at http://cadd.zju.edu.cn/plic/.

Identification of potential inhibitors of HER2 targeting breast cancer—a structure-based drug design approach

Breast cancer is one of the most prevalent and malignant cancers in women. Most breast cancer patients show overexpression of the HER2 protein. The current study focused on identifying potent inhibitors of HER2 using a structure-based drug design approach. Prefiltered compounds from the Drugbank and the ZINC database were docked on HER2 protein using the FlexX docking tool of LeadIT. The docking study identified the 12 best molecules that interacted strongly with the active site of HER2 and also fulfilled the ADMET parameters. The complexes of these compounds with HER2 were further subjected to molecular dynamics simulation using GROMACS 2021.4, followed by the end-state MMGBSA binding energy calculations. The RMSD analysis was conducted to study the conformational changes, which revealed stability throughout the 100 ns simulation period. The local flexibility and dynamics of the simulated ligand-protein complexes were studied using RMSF analysis. The values of the radius of gyration were computed to analyze the compactness of HER2. The MMGBSA analysis provided insights into the energetic aspects of the system. The compound DB15187 emerged as the most potent candidate, showing MMGBSA-computed binding energy of −63.60 ± 3.39 kcal/mol. The study could help develop targeted therapies for HER2-positive breast cancer. Communicated by Ramaswamy H. Sarma

Understanding the Molecular Regulation of Serotonin Receptor 5-HTR1B-β-Arrestin1 Complex in Stress and Anxiety Disorders.

The serotonin receptor subtype 5-HTR1B is widely distributed in the brain with an important role in various behavioral implications including neurological conditions and psychiatric disorders. The neuromodulatory action of 5-HTR1B largely depends upon its arrestin mediated signaling pathway. In this study, we tried to investigate the role of unusually long intracellular loop3 (ICL3) region of the serotonin receptor 5-HTR1B in interaction with β-arrestin1 (Arr2) to compensate for the absence of the long cytoplasmic tail. Molecular modeling and docking tools were employed to obtain a suitable molecular conformation of the ICL3 region in complex with Arr2 which dictates the specific complex formation of 5-HTR1B with Arr2. This reveals the novel molecular mechanism of phosphorylated ICL3 mediated GPCR-arrestin interaction in the absence of the long cytoplasmic tail. The in-cell disulfide cross-linking experiments and molecular dynamics simulations of the complex further validate the model of 5-HTR1B-ICL3-Arr2 complex. Two serine residues (Ser281 and Ser295) within the 5-HTR1B-ICL3 region were found to be occupying the electropositive pocket of Arr2 in our model and might be crucial for phosphorylation and specific Arr2 binding. The alignment studies of these residues showed them to be conserved only across 5-HTR1B mammalian species. Thus, our studies were able to predict a molecular conformation of 5-HTR1B-Arr2 and identify the role of long ICL3 in the signaling process which might be crucial in designing targeted drugs (biased agonists) that promote GPCR-Arr2 signaling to deter the effects of stress and anxiety-like disorders.

Synthesis of New Organoselenium-Based Succinanilic and Maleanilic Derivatives and In Silico Studies as Possible SARS-CoV-2 Main Protease Inhibitors

Herein we report the synthesis of organic selenide-based maleanilic and succinanilic acids in good yields (up to 95%). Their structural identities were elucidated by spectroscopic techniques (e.g., IR, 1H- & 13C-NMR, and MS). The ADMET analysis, molecule electrostatic potential map, DFT, and frontier molecular orbital were used to study the organoselenium compounds’ pharmacokinetics, drug-likeness characteristics, geometries, and chemical and electronic properties. Moreover, a molecular docking tool was employed to investigate the organic selenides’ ability to inhibit the SARS-CoV-2 Mpro target (PDB: 7BFB). Within this context, organic selenides exhibited promising binding affinities to the SARS-CoV-2 Mpro receptor in the following order (12 > 11 > 10 > 9 > 7 > 8). Furthermore, molecular dynamics simulations were also carried out for 200 ns to evaluate the exact behavior of the most active compound (12) within the Mpro binding pocket of SARS-CoV-2 compared with its co-crystallized inhibitor (Co).

A New Tool to Study the Binding Behavior of Intrinsically Disordered Proteins.

Understanding the binding behavior and conformational dynamics of intrinsically disordered proteins (IDPs) is crucial for unraveling their regulatory roles in biological processes. However, their lack of stable 3D structures poses challenges for analysis. To address this, we propose an algorithm that explores IDP binding behavior with protein complexes by extracting topological and geometric features from the protein surface model. Our algorithm identifies a geometrically favorable binding pose for the IDP and plans a feasible trajectory to evaluate its transition to the docking position. We focus on IDPs from Homo sapiens and Mus-musculus, investigating their interaction with the Plasmodium falciparum (PF) pathogen associated with malaria-related deaths. We compare our algorithm with HawkDock and HDOCK docking tools for quantitative (computation time) and qualitative (binding affinity) measures. Our results indicated that our method outperformed the compared methods in computation performance and binding affinity in experimental conformations.

Sonochemical synthesis, docking studies and in vitro evaluation of imidazo-1,3-oxazinone derivatives as potential inhibitors of TNF-α

A series of imidazo-1,3-oxazinone derivatives was explored as new and prospective inhibitors of TNF-α. These compounds were synthesized via a direct, one-pot method involving the coupling of appropriate bromo compound with various terminal alkynes in the presence of (PPh3)4Pd, CuI and ZnCl2 in DMF under ultrasound. This sonochemical reaction proceeded via the sequential formation of CC (coupling) and then intramolecular CO bond (cyclization) in the same pot affording the imidazo-1,3-oxazinone derivatives in good yield. A thorough docking studies carried out using the TNF-α protein (PDB: 7JRA and 6 × 81) in silico primarily with the help of AutoDock and then JAMDA docking tool predicted 3j, 3l, 3m and 3o as potential hit molecules from the current series of compounds synthesized. The majority of the compounds interacted with the common interacting residues in the TNF-α trimer e.g. TYR135, TYR227, ILE231, LEU133, LEU233, LEU196 in case of 7JRA and TYR119, TYR59, LEU57, GLY121 in case of 6 × 81. When examined in vitro against TNF-α, the compound 3l, 3m and 3o (with 69–82% inhibition) emerged as the most active compounds in this series. It was observed that the compounds possessing the tricyclic fused ring generally showed better inhibition than that having the fused bicyclic ring as noted during the docking studies. From the viewpoint of SAR (Structure Activity Relationship) the effectiveness of the C-3 aryl group in case of benzoimidazo-1,3-oxazinones was found to be in the order C6H5 > C6H4Me-p > 2-pyridyl > C6H4OMe-p > C6H4Cl-p etc. In terms of IC50 values the compound 3l, 3m and 3o (IC50 ∼5.2–6.2 µM) did not show better activities than rolipram (IC50 ∼0.9 µM) but they appeared to be superior than thalidomide (IC50 ∼197.3 µM). Thus the outcome of docking studies, in vitro evaluation and in silico ADME predictions indicated further pharmacological interest of the preliminary hits identified.

Ce-ZSM-5: A highly capable catalyst for the construction of acridines in water and their computational study against DNA gyrase protein.

Cerium doped ZSM-5 (Ce-ZSM-5) as an environmentally benign and reusable catalyst for the construction of acridines in aqueous medium. This method produced corresponding acridines with good yields and shorter reaction times. Also avoids the use of hazardous solvents and involves a simple work-up process. The solid catalyst was prepared by doping Ce ions with ZSM-5 (Zeolite Socony Mobil-5) and confirmed by XRD, BET SA-PSD and SEM. The synthesised acridine derivatives were confirmed by 1H NMR, 13C NMR and FTIR spectroscopic data. The docking studies of the synthesised compounds are performed by the PyRx auto dock tool against DNA gyrase protein. The products 5a and 6d are found to be the best fit ligands against DNA gyrase protein.

Anti-SARS-CoV-2 invitro potential of castor oil plant (Ricinus communis) leaf extract: in-silico virtual evidence.

Ricinus communis L. is a medicinal plant that displays valuable pharmacological properties, including antioxidant, antimicrobial, analgesic, antibacterial, antiviral and anti-inflammatory properties. This study targeted to isolate and identify some constituents of R.communis leaves using ultra-performance liquid chromatography coupled with mass spectroscopy (UPLC-MS/MS) and different chromatographic techniques. In vitro anti-MERS and anti-SARS-CoV-2 activity for different fractions and for two pure isolated compounds, lupeol (RS) and ricinine (RS1) were evaluated using a plaque reduction assay with three different mechanisms and IC50 based on their cytotoxic concentration (CC50) from an MTT assay using Vero E6 cell line. Isolated phytoconstituents and remdesivir are assessed for in-silico anti-COVID-19 activity using molecular docking tools. The methylene chloride extract showed pronounced virucidal activity against SARS-CoV-2 (IC50=1.76 μg/ml). It was also shown that ricinine had superior potential activity against SARS-CoV-2, (IC50=2.5 μg/ml). Lupeol displayed the most potency against MERS, (IC50=5.28 μg/ml). Ricinine appeared to be the most biologically active compound. The study showed that R.communis and its isolated compounds have potential natural virucidal activity against SARS-COV-2; however, additional exploration is necessary and study for their invivo activity.