Molecular docking as a popular tool in drug design, an in silico travel

Biological and molecular approaches of the degradation or decolorization potential of the hypersaline Lake Tuz Bacillus megaterium H2 isolate

The presence of synthetic dyes in water bodies and soil is one of the major issues affecting the global ecology, possibly impacting societal well-being adversely due to the colorants' recalcitrance and toxicity. Herein, the study spectrophotometrically monitored the ability of the Bacillus megaterium H2 azoreductase (AzrBmH2) to degrade four synthetic dyes, reactive blue 4, remazol brilliant red, thymol blue, and methyl red, followed by in-silico assessment using GROMACS. We found that the bacterium degraded as much as 60% of all four synthetic dyes at various tested concentrations. The genome analysis revealed five different azoreductase genes, which were then modeled into the AzrBmH21, AzrBmH22/3, and AzrBmH24/5 templates. The AzrBmH2-substrate complexes showed binding energies with all the dyes of between -10.6 to -6.9 kcal/mol and formed 4-6 hydrogen bonds with the predicted catalytic binding residues (His10, Glu 14, Ser 58, Met 99, Val 107, His 183, Asn184 and Gln 191). In contrast, the lowest binding energies were observed for the AzrBmH21-substrates (-10.6 to -7.9). Molecular dynamic simulations revealed that the AzrBmH21-substrate complexes were more stable (RMSD 0.2-0.25 nm, RMSF 0.05 - 0.3 nm) and implied strong bonding with the dyes. The Molecular Mechanics Poisson-Boltzmann Surface Area results also mirrored this outcome, showing the lowest azoreductase-dye binding energy in the order of AzrBmH21-RB4 (-78.18 ± 8.92 kcal/mol), AzrBmH21-RBR (-67.51 ± 7.74 kcal/mol), AzrBmH21-TB (-46.62 ± 5.23 kcal/mol) and AzrBmH21-MR (-40.78 ± 7.87 kcal/mol). In short, the study demonstrated the ability of the B. megaterium H2 to efficiently decolorize the above-said synthetic dyes, conveying the bacterium's promising use for large-scale dye remediation.Communicated by Ramaswamy H. Sarma.

Identification of Critical Amino Acid Residues of a Two-Component Sensor Protein for Signal Sensing in Porphyromonas gingivalis Fimbriation via Random Mutant Library Construction

Porphyromonas gingivalis (Pg) utilizes FimA fimbriae to colonize the gingival sulcus and evade the host immune system. The biogenesis of all FimA-related components is positively regulated by the FimS-FimR two-component system, making the FimS sensory protein an attractive target for preventing Pg infection. However, the specific environmental signal received by FimS remains unknown. We constructed random Pg mutant libraries to identify critical amino acid residues for signal sensing by FimS. Optimized error-prone polymerase chain reaction (PCR) was used to introduce a limited number of random mutations in the periplasmic-domain-coding sequence of fimS, and expression vectors carrying various mutants were generated by inverse PCR. More than 500 transformants were obtained from the fimS-knockout Pg strain using the Escherichia coli-Pg conjugal transfer system, whereas only ~100 transformants were obtained using electroporation. Four and six transformant strains showed increased and decreased fimA expression, respectively. Six strains had single amino acid substitutions in the periplasmic domain, indicating critical residues for signal sensing by FimS. This newly developed strategy should be generally applicable and contribute to molecular genetics studies of Pg, including the elucidation of structure-function relationships of proteins of interest.

Design and Evaluation of Nanoscale Materials with Programmed Responsivity towards Epigenetic Enzymes

Self-assembled materials capable of modulating their assembly properties in response to specific enzymes play a pivotal role in advancing 'intelligent' encapsulation platforms for biotechnological applications. Here, we introduce a previously unreported class of synthetic nanomaterials that programmatically interact with histone deacetylase (HDAC) as the triggering stimulus for disassembly. These nanomaterials consist of co-polypeptides comprising poly (acetyl L-lysine) and poly(ethylene glycol) blocks. Under neutral pH conditions, they self-assemble into particles. However, their stability is compromised upon exposure to HDACs, depending on enzyme concentration and exposure time. Our investigation, utilizing HDAC8 as the model enzyme, revealed that the primary mechanism behind disassembly involves a decrease in amphiphilicity within the block copolymer due to the deacetylation of lysine residues within the particles' hydrophobic domains. To elucidate the response mechanism, we encapsulated a fluorescent dye within these nanoparticles. Upon incubation with HDAC, the nanoparticle structure collapsed, leading to controlled release of the dye over time. Notably, this release was not triggered by denatured HDAC8, other proteolytic enzymes like trypsin, or the co-presence of HDAC8 and its inhibitor. We further demonstrated the biocompatibility and cellular effects of these materials and conducted a comprehensive computational study to unveil the possible interaction mechanism between enzymes and particles. By drawing parallels to the mechanism of naturally occurring histone proteins, this research represents a pioneering step toward developing functional materials capable of harnessing the activity of epigenetic enzymes such as HDACs.

Brasiliensic acid: in vitro cytotoxic and genotoxic, in vivo acute toxicity and in silico pharmacological prediction of a new promising molecule

Brasiliensic acid (Bras) is a chromanone isolated from Calophyllum brasiliense Cambèss. bark extracts with confirmed potential activity on gastric ulcer and Helicobacter pylori infection. This study aimed to investigate the in vitro and in vivo toxicity of Bras and molecular docking studies on its interactions with the H. pylori virulence factors and selected gastric cancer-related proteins. Cytotoxicity was evaluated by alamarBlue© assay, genotoxicity by micronucleus and comet assays, and on cell cycle by flow cytometry, using Chinese hamster epithelial ovary cells. Bras was not cytotoxic to CHO-K1 cells, and caused no chromosomal aberrations, nor altered DNA integrity. Furthermore, Bras inhibited damages to DNA by H2O2 at 1.16 µM. No cell cycle arrest was observed, but apoptosis accounted for 31.2% of the cell death observed in the CHO-K1 at 24 h incubation of the IC50. Oral acute toxicity by Hippocratic screening test in mice showed no relevant behavioral change/mortality seen up to 1,000 mg/kg. The molecular docking approach indicated potential interactions between Bras and the various targets for peptic ulcer and gastric cancer, notably CagA virulence factor of H. pylori and VEGFR-2. In conclusion, Bras is apparently safe and an optimization for Bras can be considered for gastric ulcer and cancer.Communicated by Ramaswamy H. Sarma.

In silico drug repurposing carvedilol and its metabolites against SARS-CoV-2 infection using molecular docking and molecular dynamic simulation approaches

The pandemic of coronavirus disease 2019 (COVID-19) caused by the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a significant impact on the economy and public health worldwide. Therapeutic options such as drugs and vaccines for this newly emerged disease are eagerly desired due to the high mortality. Using the U.S. Food and Drug Administration (FDA) approved drugs to treat a new disease or entirely different diseases, in terms of drug repurposing, minimizes the time and cost of drug development compared to the de novo design of a new drug. Drug repurposing also has some other advantages such as reducing safety evaluation to accelerate drug application on time. Carvedilol, a non-selective beta-adrenergic blocker originally designed to treat high blood pressure and manage heart disease, has been shown to impact SARS-CoV-2 infection in clinical observation and basic studies. Here, we applied computer-aided approaches to investigate the possibility of repurposing carvedilol to combat SARS-CoV-2 infection. The molecular mechanisms and potential molecular targets of carvedilol were identified by evaluating the interactions of carvedilol with viral proteins. Additionally, the binding affinities of in vivo metabolites of carvedilol with selected targets were evaluated. The docking scores for carvedilol and its metabolites with RdRp were - 10.0 kcal/mol, - 9.8 kcal/mol (1-hydroxyl carvedilol), - 9.7 kcal/mol (3-hydroxyl carvedilol), - 9.8 kcal/mol (4-hydroxyl carvedilol), - 9.7 kcal/mol (5-hydroxyl carvedilol), - 10.0 kcal/mol (8-hydroxyl carvedilol), and - 10.1 kcal/mol (O-desmethyl carvedilol), respectively. Using the molecular dynamics simulation (100 ns) method, we further confirmed the stability of formed complexes of RNA-dependent RNA polymerase (RdRp) and carvedilol or its metabolites. Finally, the drug-target interaction mechanisms that contribute to the complex were investigated. Overall, this study provides the molecular targets and mechanisms of carvedilol and its metabolites as repurposed drugs to fight against SARS-CoV-2 infection.

Unlocking therapeutic potential of trigonelline through molecular docking as a promising approach for treating diverse neurological disorders

Neurological disorders pose significant challenges in terms of treatment options, necessitating the exploration of novel therapeutic approaches. Trigonelline, a naturally occurring alkaloid found in various plants, has emerged as a potential treatment option. It has also been reported that trigonelline is involved in several pathways like; Oxidative Stress and Antioxidant, Inflammatory, Neuroprotection and Neurotrophic, Mitochondrial Function and Energy Metabolism. This study aims to investigate the therapeutic potential of trigonelline for diverse neurological disorders using a molecular docking approach. Molecular docking simulations were performed to predict the binding affinity and interaction between trigonelline and target proteins implicated in neurological disorders. The structural requirements for effective binding were also explored. The molecular docking results revealed strong binding interactions and favorable binding affinities between trigonelline and the target proteins involved in diverse neurological disorders like Alzheimer's disease, Parkinson's disease, epilepsy, and depression etc. The predicted binding modes provided insights into the key molecular interactions governing the ligand-protein complexes. The findings suggest that trigonelline holds promise as a therapeutic approach for several neurological disorders. The molecular docking approach employed in this study provides a valuable tool for rational drug design and optimization of trigonelline-based compounds. Further experimental validation and preclinical studies are warranted to confirm the efficacy and safety of trigonelline as a potential treatment option, paving the way for the development of more effective and targeted therapies for neurological disorders.

Integrated Molecular Modeling and Machine Learning for Drug Design

Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on molecular mechanics optimized geometries. Meanwhile, we discuss remaining challenges and promising directions for further development and use a retrospective example of FDA approved kinase inhibitor Erlotinib to demonstrate the use of these newly developed computational tools.

Phytochemicals of Cocculus hirsutus deciphered SARS-CoV-2 inhibition by targeting main proteases in molecular docking, simulation, and pharmacological analyses

The COVID-19 pandemic is spreading rapidly due to the outbreak of novel coronavirus SARS-CoV-2 across the globe. Anti-COVID-19 drugs are urgently required in this situation. In this regard, the discovery of promising new anti-COVID-19 moieties is expected from traditional medicine. The study is aimed to discover phytochemicals of Cocculus hirsutus having anti-COVID-19 activity via inhibiting main proteases of SARS-CoV-2. Main proteases (Mpro) of SARS-CoV-2 serve as a protuberant target for anti-COVID-19 drug discovery because it is a key enzyme of coronaviruses and has a pivotal role in mediating viral replication and transcription that makes it an attractive drug target. Recent studies indicated the utility of C. hirsutus in the treatment of viral disorders like Dengue. Phytochemicals from C. hirsutus were docked against SARS-CoV-2 main proteases (6LU7, 5R7Y, 5R7Z, 5R80, 5R81, 5R82) using the PyRx virtual screen tool and discovery studio visualizer. Further, molecular dynamics simulations were performed (for 100 ns) to see conformational stability for all complexes. Pharmacokinetic properties and drug-likeness prediction of selected C. hirsutus phytoconstituents were also performed. Betulin, coclaurine, and quinic acid of C. hirsutus were found promising with significant binding affinity to SARS-CoV-2 Mpro in comparison to control. They have shown stable interactions with the amino acid residues present on the active site of most of the SARS-CoV-2 Mpro and were found as promising anti-COVID-19 candidates. These compounds could be potential leads for the development of target-specific anti-COVID-19 therapeutics while ethnomedicinal uses of this herb could further needed for its detailed antiviral therapeutic exploration.Communicated by Ramaswamy H. Sarma.

Improvement of binding pose prediction of the MR1 covalent ligands by inclusion of simple pharmacophore constraints and structural waters in the docking process

The major histocompatibility complex (MHC) class I-related molecule, MR1, is a key component of the immune system, presenting antigens to T-cell receptors (TCRs) and modulating the immune response against various antigens. MR1 possesses a compact ligand-binding pocket despite its ability to interact with ligands that can have either agonistic or antagonistic effects on the immune system. Agonistic ligands can stimulate the immune response, while antagonistic ligands do not elicit an immune response. In most cases, ligand binding to MR1 is mediated through a covalent bond with Lys43. However, recent studies have suggested that a variety of small molecules can interact with the MR1-binding site. In this study, we have used several approaches to improve the binding pose prediction of covalent ligands to MR1, including docking in mutated receptors, and imposing simple pharmacophore constraints and structural water molecules. The careful assignment of pharmacophore constraints and inclusion of structural water molecules in the challenging docking process of covalent docking improved the binding pose prediction and virtual screening performance. In a retrospective virtual screening, the proposed approach exhibited EF1% and EF2% values of 7.4 and 5.5, respectively. Conversely, when using the mutated receptor, both EF1% and EF2% were recorded as 0 for the conventional docking method. The performance of the pharmacophore constraints was also evaluated on other covalent docking cases, and compared to previously reported results for common covalent docking methods. The proposed approach achieved an average RMSD of 2.55, while AutoDock4, CovDock, FITTED, GOLD, ICM-Pro, and MOE exhibited average RMSD values of 3.0, 2.93, 3.04, 4.93, 2.44, and 3.36, respectively. Our results demonstrate that the inclusion of simple pharmacophore constraints and structural waters can improve the prediction of binding poses of covalent ligands to MR1, which can aid in the discovery of novel immunotherapeutic agents.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03694-w.

Screening of Potential Inhibitors Targeting the Main Protease Structure of SARS-CoV-2 via Molecular Docking, and Approach with Molecular Dynamics, RMSD, RMSF, H-Bond, SASA and MMGBSA

Severe Acute Respiratory Syndrome caused by a coronavirus is a recent viral infection. There is no scientific evidence or clinical trials to indicate that possible therapies have demonstrated results in suspected or confirmed patients. This work aims to perform a virtual screening of 1430 ligands through molecular docking and to evaluate the possible inhibitory capacity of these drugs about the M^pro protease of Covid-19. The selected drugs were registered with the FDA and available in the virtual drug library, widely used by the population. The simulation was performed using the MolAiCalD algorithm, with a Lamarckian genetic model (GA) combined with energy estimation based on rigid and flexible conformation grids. In addition, molecular dynamics studies were also performed to verify the stability of the receptor-ligand complexes formed through analyses of RMSD, RMSF, H-Bond, SASA, and MMGBSA. Compared to the binding energy of the synthetic redocking coupling (-6.8 kcal/mol/RMSD of 1.34 Å), which was considerably higher, it was then decided to analyze the parameters of only three ligands: ergotamine (-9.9 kcal/mol/RMSD of 2.0 Å), dihydroergotamine (-9.8 kcal/mol/RMSD of 1.46 Å) and olysio (-9.5 kcal/mol/RMSD of 1.5 Å). It can be stated that ergotamine showed the best interactions with the M^pro protease of Covid-19 in the in silico study, showing itself as a promising candidate for treating Covid-19.

Next-Generation Adjuvants: Applying Engineering Methods to Create and Evaluate Novel Immunological Responses

Adjuvants are a critical component of vaccines. Adjuvants typically target receptors that activate innate immune signaling pathways. Historically, adjuvant development has been laborious and slow, but has begun to accelerate over the past decade. Current adjuvant development consists of screening for an activating molecule, formulating lead molecules with an antigen, and testing this combination in an animal model. There are very few adjuvants approved for use in vaccines, however, as new candidates often fail due to poor clinical efficacy, intolerable side effects, or formulation limitations. Here, we consider new approaches using tools from engineering to improve next-generation adjuvant discovery and development. These approaches will create new immunological outcomes that will be evaluated with novel diagnostic tools. Potential improved immunological outcomes include reduced vaccine reactogenicity, tunable adaptive responses, and enhanced adjuvant delivery. Evaluations of these outcomes can leverage computational approaches to interpret "big data" obtained from experimentation. Applying engineering concepts and solutions will provide alternative perspectives, further accelerating the field of adjuvant discovery.

Harnessing and bioprospecting botanical-based herbal medicines against potential drug targets for COVID-19: a review coupled molecular docking studies

Since the end of February 2020, the world has come to a standstill due to the virus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). Since then, the global scientific community has explored various remedies and treatments against this virus, including natural products that have always been a choice because of their many benefits. Various known phytochemicals are well documented for their antiviral properties. Research is being carried out to discover new natural plant products or existing ones as a treatment measure for this disease. The three important targets in this regard are-papain like protease (PLpro), spike protein, and 3 chymotrypsin like proteases (3CLpro). Various docking studies are also being elucidated to identify the phytochemicals that modulate crucial proteins of the virus. The paper is simultaneously a comprehensive review that covers recent advances in the domain of the effect of various botanically derived natural products as an alternative treatment approach against Coronavirus Disease 2019 (COVID-19). Furthermore, the docking analyses revealed that rutin (inhibitor of the major protease of SARS-CoV-2), gallocatechin (e.g., interacting with 03 hydrogen bonds with a spike-like protein), lycorine (showing the best binding affinity with amino acids GLN498, THR500 and GLY446 of the spike-like protein), and quercetrin (inhabiting at its residues ASP216, PHE219, and ILE259) are promising inhibitors of SARS‑CoV‑2.Communicated by Ramaswamy H. Sarma.

Molecular modelling and structure-activity relationship of a natural derivative of o-hydroxybenzoate as a potent inhibitor of dual NSP3 and NSP12 of SARS-CoV-2: in silico study

The nsp3 macrodomain and nsp12 (RdRp) enzymes are strongly implicated in the virulent regulation of the host immune response and viral replication of SARS-CoV-2, making them plausible therapeutic targets for mitigating infectivity. Remdesivir remains the only FDA-approved small-molecule inhibitor of the nsp12 in clinical conditions while none has been approved yet for the nsp3 macrodomain. In this study, 69,067 natural compounds from the IBScreen database were screened for efficacious potentials with mechanistic multitarget-directed inhibitory pharmacology against the dual targets using in silico approaches. Standard and extra precision (SP and XP) Maestro glide docking analyses were employed to evaluate their inhibitory interactions against the enzymes. Four compounds, STOCK1N-45901, 03804, 83408, 08377 consistently showed high XP scores against the respective targets and interacted strongly with pharmacologically essential amino acid and RNA residues, in better terms than the standard, co-crystallized inhibitors, GS-441524 and remdesivir. Further assessments through the predictions of ADMET and mutagenicity distinguished STOCK1N-45901, a natural derivative of o-hydroxybenzoate as the most promising candidate. The ligand maintained a good conformational and thermodynamic stability in complex with the enzymes throughout the trajectories of 100 ns molecular dynamics, indicated by RMSD, RMSF and radius of gyration plots. Its binding free energy, MM-GBSA was recorded as -54.24 and -31.77 kcal/mol against the respective enzyme, while its structure-activity relationships confer high probabilities as active antiviral, anti-inflammatory, antiinfection, antitussive and peroxidase inhibitor. The IBScreen database natural product, STOCK1N-45901 (2,3,4,5,6-pentahydroxyhexyl o-hydroxybenzoate) is thus recommended as a potent inhibitor of dual nsp3 and nsp12 of SARS-CoV-2 for further study. Communicated by Ramaswamy H. Sarma.

Naphthoquinones biflorin and bis-biflorin (Capraria biflora) as possible inhibitors of the fungus Candida auris polymerase: molecular docking, molecular dynamics, MM/GBSA calculations and in silico drug-likeness study

A new worldwide concern has emerged with the recent emergence of infections caused by Candida auris. This reflects its comparative ease of transmission, substantial mortality, and the increasing level of resistance seen in the three major classes of antifungal drugs. Efforts to create a better design for structure-based drugs that described numerous modifications and the search for secondary metabolic structures derived from plant species are likely to reduce the virulence of several fungal pathogens. In this context, the present work aimed to evaluate in silico two naphthoquinones isolated from the roots of Capraria biflora, biflorin, and its dimmer, bis-biflorin, as potential inhibitors of Candida auris polymerase. Based on the simulation performed with the two naphthoquinones, biflorin and bis-biflorin, it can be stated that bis-biflorin showed the best interactions with Candida auris polymerase. Still, biflorin also demonstrated favorable coupling energy. Predictive pharmacokinetic assays suggest that biflorin has high oral bioavailability and more excellent metabolic stability compared to the bis-biflorin analogue. constituting a promising pharmacological tool.Communicated by Ramaswamy H. Sarma.

Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review

BACKGROUND

Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body.

METHODS

This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review.

RESULTS

Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes.

CONCLUSION

Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.

Accuracy and precision of binding free energy prediction for a tacrine related lead inhibitor of acetylcholinesterase with an arsenal of supercomputerized molecular modelling methods: a comparative study

Nowadays, advanced computational chemistry methods offer various strategies for revealing prospective hit structures in drug development essentially through accurate binding free energy predictions. After the era of molecular docking and quantitative structure-activity relationships, much interest has been lately oriented to perturbed molecular dynamic approaches like replica exchange with solute tempering and free energy perturbation (REST/FEP) and the potential of the mean force with adaptive biasing and accelerated weight histograms (PMF/AWH). Both of these receptor-based techniques can exploit exascale CPU&GPU supercomputers to achieve high throughput performance. In this fundamental study, we have compared the predictive power of a panel of supercomputerized molecular modelling methods to distinguish the major binding modes and the corresponding binding free energies of a promising tacrine related potential antialzheimerics in human acetylcholinesterase. The binding free energies were estimated using flexible molecular docking, molecular mechanics/generalized Born surface area/Poisson-Boltzmann surface area (MM/GBSA/PBSA), transmutation REST/FEP with 12 x 5 ns/λ windows, annihilation FEP with 20 x 5 ns/λ steps, PMF with weight histogram analysis method (WHAM) and 40 x 5 ns samples, and PMF/AWH with 10 x 100 ns replicas. Confrontation of the classical approaches such as canonical molecular dynamics and molecular docking with alchemical calculations and steered molecular dynamics enabled us to show how large errors in ΔG predictions can be expected if these in silico methods are employed in the elucidation of a common case of enzyme inhibition.Communicated by Ramaswamy H. Sarma.

Development of Peptide-based Metallo-β-lactamase Inhibitors as a New Strategy to Combat Antimicrobial Resistance: A Mini-review

Global dissemination of antimicrobial resistance (AMR) not only poses a significant threat to human health, food security, and social development but also results in millions of deaths each year. In Gram-negative bacteria, the primary mechanism of resistance to β-lactam antibiotics is the production of β-lactamases, one of which is carbapenem-hydrolyzing β-lactamases known as carbapenemases. As a general scheme, these enzymes are divided into Ambler class A, B, C, and D based on their protein sequence homology. Class B β-lactamases are also known as metallo-β-lactamases (MBLs). The incidence of recovery of bacteria expressing metallo-β- lactamases (MBLs) has increased dramatically in recent years, almost reaching a pandemic proportion. MBLs can be further divided into three subclasses (B1, B2, and B3) based on the homology of protein sequences as well as the differences in zinc coordination. The development of inhibitors is one effective strategy to suppress the activities of MBLs and restore the activity of β-lactam antibiotics. Although thousands of MBL inhibitors have been reported, none have been approved for clinical use. This review describes the clinical application potential of peptide-based drugs that exhibit inhibitory activity against MBLs identified in past decades. In this report, peptide-based inhibitors of MBLs are divided into several groups based on the mode of action, highlighting compounds of promising properties that are suitable for further advancement. We discuss how traditional computational tools, such as in silico screening and molecular docking, along with new methods, such as deep learning and machine learning, enable a more accurate and efficient design of peptide-based inhibitors of MBLs.

Discovery of Novel HIV Protease Inhibitors Using Modern Computational Techniques

The human immunodeficiency virus type 1 (HIV-1) has continued to be a global concern. With the new HIV incidence, the emergence of multi-drug resistance and the untoward side effects of currently used anti-HIV drugs, there is an urgent need to discover more efficient anti-HIV drugs. Modern computational tools have played vital roles in facilitating the drug discovery process. This research focuses on a pharmacophore-based similarity search to screen 111,566,735 unique compounds in the PubChem database to discover novel HIV-1 protease inhibitors (PIs). We used an in silico approach involving a 3D-similarity search, physicochemical and ADMET evaluations, HIV protease-inhibitor prediction (IC50/percent inhibition), rigid receptor-molecular docking studies, binding free energy calculations and molecular dynamics (MD) simulations. The 10 FDA-approved HIV PIs (saquinavir, lopinavir, ritonavir, amprenavir, fosamprenavir, atazanavir, nelfinavir, darunavir, tipranavir and indinavir) were used as reference. The in silico analysis revealed that fourteen out of the twenty-eight selected optimized hit molecules were within the acceptable range of all the parameters investigated. The hit molecules demonstrated significant binding affinity to the HIV protease (PR) when compared to the reference drugs. The important amino acid residues involved in hydrogen bonding and п-п stacked interactions include ASP25, GLY27, ASP29, ASP30 and ILE50. These interactions help to stabilize the optimized hit molecules in the active binding site of the HIV-1 PR (PDB ID: 2Q5K). HPS/002 and HPS/004 have been found to be most promising in terms of IC50/percent inhibition (90.15%) of HIV-1 PR, in addition to their drug metabolism and safety profile. These hit candidates should be investigated further as possible HIV-1 PIs with improved efficacy and low toxicity through in vitro experiments and clinical trial investigations.

Synthesis of Novel N-Methylmorpholine-Substituted Benzimidazolium Salts as Potential α-Glucosidase Inhibitors

The α-glucosidase enzyme, located in the brush border of the small intestine, is responsible for overall glycemic control in the body. It hydrolyses the 1,4-linkage in the carbohydrates to form blood-absorbable monosaccharides that ultimately increase the blood glucose level. α-Glucosidase inhibitors (AGIs) can reduce hydrolytic activity and help to control type 2 diabetes. Aiming to achieve this, a novel series of 1-benzyl-3-((2-substitutedphenyl)amino)-2-oxoethyl)-2-(morpholinomethyl)-1H-benzimidazol-3-ium chloride was synthesized and screened for its α-glucosidase inhibitory potential. Compounds 5d, 5f, 5g, 5h and 5k exhibited better α-glucosidase inhibitions compared to the standard drug (acarbose IC50 = 58.8 ± 0.012 µM) with IC50 values of 15 ± 0.030, 19 ± 0.060, 25 ± 0.106, 21 ± 0.07 and 26 ± 0.035 µM, respectively. Furthermore, the molecular docking studies explored the mechanism of enzyme inhibitions by different 1,2,3-trisubstituted benzimidazolium salts via significant ligand–receptor interactions.

A Second Life for MAP, a Model Amphipathic Peptide

Cell-penetrating peptides (CPP) have been shown to be efficient in the transport of cargoes into the cells, namely siRNA and DNA, proteins and peptides, and in some cases, small therapeutics. These peptides have emerged as a solution to increase drug concentrations in different tissues and various cell types, therefore having a relevant therapeutic relevance which led to clinical trials. One of them, MAP, is a model amphipathic peptide with an α-helical conformation and both hydrophilic and hydrophobic residues in opposite sides of the helix. It is composed of a mixture of alanines, leucines, and lysines (KLALKLALKALKAALKLA). The CPP MAP has the ability to translocate oligonucleotides, peptides and small proteins. However, taking advantage of its unique properties, in recent years innovative concepts were developed, such as in silico studies of modelling with receptors, coupling and repurposing drugs in the central nervous system and oncology, or involving the construction of dual-drug delivery systems using nanoparticles. In addition to designs of MAP-linked vehicles and strategies to achieve highly effective yet less toxic chemotherapy, this review will be focused on unique molecular structure and how it determines its cellular activity, and also intends to address the most recent and frankly motivating issues for the future.

Protein-Ligand Docking in the Machine-Learning Era

Molecular docking plays a significant role in early-stage drug discovery, from structure-based virtual screening (VS) to hit-to-lead optimization, and its capability and predictive power is critically dependent on the protein-ligand scoring function. In this review, we give a broad overview of recent scoring function development, as well as the docking-based applications in drug discovery. We outline the strategies and resources available for structure-based VS and discuss the assessment and development of classical and machine learning protein-ligand scoring functions. In particular, we highlight the recent progress of machine learning scoring function ranging from descriptor-based models to deep learning approaches. We also discuss the general workflow and docking protocols of structure-based VS, such as structure preparation, binding site detection, docking strategies, and post-docking filter/re-scoring, as well as a case study on the large-scale docking-based VS test on the LIT-PCBA data set.

The Current Perspectives in Clinical Research: Computer-Assisted Drug Designing, Ethics, and Good Clinical Practice

In the era of emerging microbial and non-communicable diseases and re-emerging microbial infections, the medical fraternity and the public are plagued by under-preparedness. It is evident by the severity of the Coronavirus disease (COVID-19) pandemic that novel microbial diseases are a challenge and are challenging to control. This is mainly attributed to the lack of complete knowledge of the novel microbe’s biology and pathogenesis and the unavailability of therapeutic drugs and vaccines to treat and control the disease. Clinical research is the only answer utilizing which can handle most of these circumstances. In this review, we highlight the importance of computer-assisted drug designing (CADD) and the aspects of molecular docking, molecular superimposition, 3D-pharmacophore technology, ethics, and good clinical practice (GCP) for the development of therapeutic drugs, devices, and vaccines.

Phytochemical profile, antioxidant, antiproliferative, and enzyme inhibition-docking analyses of Salvia ekimiana Celep & Doğan

Salvia ekimiana Celep & Doğan is an endemic species of Turkey. To our knowledge, the number of studies on biological activities and phytochemical profiling of this plant is quite limited. Therefore, this study aimed to analyze its activities and phytochemical content in detail. The qualitative-quantitative compositions were determined via spectrophotometric and chromatographic (LC-MS/MS and HPLC) techniques. 1,1-Diphenyl-2-picrylhydrazyl radical (DPPH^•) and 2,2'-Azino-bis 3-ethylbenzothiazoline-6-sulfonic acid (ABTS^•+) radical scavenging and ascorbate-iron (III)-catalyzed phospholipid peroxidation experiments were performed to measure antioxidant capacity. Hyaluronidase, collagenase, and elastase enzyme inhibition tests were determined in vitro using a spectrophotometer. Antiproliferative activity was evaluated in human lung cancer (A549) and human breast cancer (MCF7) cells. The murine fibroblast (L929) cell line was used as a normal control cell. While the subextract rich in phenolic compounds was n-butanol extract, rosmarinic acid was defined as the main secondary metabolite. The highest antioxidant activity observed for the n-butanol subextract included the following: DPPH^• EC50: 0.08±0.00 mg/mL, TEAC/ABTS: 2.19±0.09 mmol/L Trolox, MDA EC50: 0.42±0.03 mg/mL. The methanolic extract, the ethyl acetate, and n-butanol subextracts displayed significant inhibitory activity on collagenase, while the other subextracts did not show any inhibitory activity on hyaluronidase and elastase. Due to strong interactions with their active sites, molecular docking showed luteolin 7-glucuronide, apigenin 7-glucuronide, and luteolin 5-glucoside had the highest binding affinity with target enzymes. The chloroform subextract showed significant cytotoxicity in all cell lines. These novel results revealed that S. ekimiana has strong antioxidant, collagenase enzyme inhibitory, and cytotoxic potential.

Phloroglucinol and Its Derivatives: Antimicrobial Properties toward Microbial Pathogens

Phloroglucinol (PG) is a natural product isolated from plants, algae, and microorganisms. Aside from that, the number of PG derivatives has expanded due to the discovery of their potential biological roles. Aside from its diverse biological activities, PG and its derivatives have been widely utilized to treat microbial infections caused by bacteria, fungus, and viruses. The rapid emergence of antimicrobial-resistant microbial infections necessitates the chemical synthesis of numerous PG derivatives in order to meet the growing demand for drugs. This review focuses on the use of PG and its derivatives to control microbial infection and the underlying mechanism of action. Furthermore, as future perspectives, some of the various alternative strategies, such as the use of PG and its derivatives in conjugation, nanoformulation, antibiotic combination, and encapsulation, have been thoroughly discussed. This review will enable the researcher to investigate the possible antibacterial properties of PG and its derivatives, either free or in the form of various formulations.

Metronidazole, acyclovir and tetrahydrobiopterin may be promising to treat COVID-19 patients, through interaction with interleukin-12

COVID-19 patients have shown overexpressed serum levels of several pro-inflammatory cytokines, leading to a high mortality rate due to numerous complications. Also, previous studies demonstrated that the metronidazole (MTZ) administration reduced pro-inflammatory cytokines and improved the treatment outcomes for inflammatory disorders. However, the effect and mechanism of action of MTZ on cytokines have not been studied yet. Thus, the current study aimed to identify anti-cytokine therapeutics for the treatment of COVID-19 patients with cytokine storm. The interaction of MTZ with key cytokines was investigated using molecular docking studies. MTZ-analogues, and its structurally similar FDA-approved drugs were also virtually screened against interleukin-12 (IL-12). Moreover, their mechanism of inhibition regarding IL-12 binding to IL-12 receptor was investigated by measuring the change in volume and area. IL-12-metronidazole complex is found to be more stable than all other cytokines under study. Our study also revealed that the active sites of IL-12 are inhibited from binding to its target, IL-12 receptor, by modifying the position of the methyl and hydroxyl functional groups in MTZ. Three MTZ analogues, metronidazole phosphate, metronidazole benzoate, 1-[1-(2-Hydroxyethyl)-5-nitroimidazol-2-yl]-N-methylmethanimine-oxide, and two FDA-approved drugs acyclovir (ACV), and tetrahydrobiopterin (THB) were also found to prevent binding of IL-12 to IL-12 receptor similar to MTZ by changing the surface and volume of IL-12 upon IL-12-drug/ligand complex formation. According to the RMSD results, after 100 ns MD simulations of human IL-12-MTZ/ACV/THB drug complexes, it was also observed that each complex was swinging within a few Å compared to their corresponding docking poses, indicating that the docking poses were reliable. The current study demonstrates that three FDA-approved drugs, namely, metronidazole, acyclovir and tetrahydrobiopterin, are potential repurposable treatment options for overexpressed serum cytokines found in COVID-19 patients. Similar approach is also useful to develop therapeutics against other human disorders.

Antidiabetic Potential of Volatile Cinnamon Oil: A Review and Exploration of Mechanisms Using In Silico Molecular Docking Simulations

Cinnamon has been used as a flavoring and medicinal agent for centuries. Much research has focused on cinnamon bark powder, which contains antioxidants, flavonoids, carotenoids, vitamins, minerals, fiber, and small amounts of essential oil. However, isolated and concentrated cinnamon essential oil may also have important medicinal qualities, particularly in antidiabetic therapy. Some of the most common essential oil constituents identified in the literature include cinnamaldehyde, eugenol, and beta-caryophyllene. Due to their high concentration in cinnamon essential oil, these constituents are hypothesized to have the most significant physiological activity. Here, we present a brief review of literature on cinnamon oil and its constituents as they relate to glucose metabolism and diabetic pathogenesis. We also present molecular docking simulations of these cinnamon essential oil constituents (cinnamaldehyde, eugenol, beta-caryophyllene) that suggest interaction with several key enzymes in glucometabolic pathways.

Identification of Cyclic Sulfonamides with an N-Arylacetamide Group as α-Glucosidase and α-Amylase Inhibitors: Biological Evaluation and Molecular Modeling

Diabetes mellitus (DM), a complicated metabolic disorder, is due to insensitivity to insulin function or reduction in insulin secretion, which results in postprandial hyperglycemia. α-Glucosidase inhibitors (AGIs) and α-amylase inhibitors (AAIs) block the function of digestive enzymes, which delays the carbohydrate hydrolysis process and ultimately helps to control the postprandial hyperglycemia. Diversified 2-(3-(3-methoxybenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)-N-arylacetamides were synthesized and evaluated for their in vitro inhibitory potential against α-glucosidase and α-amylase enzymes. The compounds with chloro, bromo and methyl substituents demonstrated good inhibition of α-glucosidase enzymes having IC₅₀ values in the range of 25.88–46.25 μM, which are less than the standard drug, acarbose (IC₅₀ = 58.8 μM). Similarly, some derivatives having chloro, bromo and nitro substituents were observed potent inhibitors of α-amylase enzyme, with IC₅₀ values of 7.52 to 15.06 μM, lower than acarbose (IC₅₀ = 17.0 μM). In addition, the most potent compound, N-(4-bromophenyl)-2-(4-hydroxy-3-(3-methoxybenzoyl)-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)acetamide (12i), was found to be a non-competitive and competitive inhibitor of α-glucosidase and α-amylase enzymes, respectively, during kinetic studies. The molecular docking studies provided the binding modes of active compounds and the molecular dynamics simulation studies of compound 12i in complex with α-amylase also showed that the compound is binding in a fashion similar to that predicted by molecular docking studies.

Computer-Aided Drug Design (CADD) to De-Orphanize Marine Molecules: Finding Potential Therapeutic Agents for Neurodegenerative and Cardiovascular Diseases

Computer-aided drug design (CADD) techniques allow the identification of compounds capable of modulating protein functions in pathogenesis-related pathways, which is a promising line on drug discovery. Marine natural products (MNPs) are considered a rich source of bioactive compounds, as the oceans are home to much of the planet's biodiversity. Biodiversity is directly related to chemodiversity, which can inspire new drug discoveries. Therefore, natural products (NPs) in general, and MNPs in particular, have been used for decades as a source of inspiration for the design of new drugs. However, NPs present both opportunities and challenges. These difficulties can be technical, such as the need to dive or trawl to collect the organisms possessing the compounds, or biological, due to their particular marine habitats and the fact that they can be uncultivable in the laboratory. For all these difficulties, the contributions of CADD can play a very relevant role in simplifying their study, since, for example, no biological sample is needed to carry out an in-silico analysis. Therefore, the amount of natural product that needs to be used in the entire preclinical and clinical study is significantly reduced. Here, we exemplify how this combination between CADD and MNPs can help unlock their therapeutic potential. In this study, using a set of marine invertebrate molecules, we elucidate their possible molecular targets and associated therapeutic potential, establishing a pipeline that can be replicated in future studies.

Structure-based protein-ligand interaction fingerprints for binding affinity prediction

Binding affinity prediction (BAP) using protein–ligand complex structures is crucial to computer-aided drug design, but remains a challenging problem. To achieve efficient and accurate BAP, machine-learning scoring functions (SFs) based on a wide range of descriptors have been developed. Among those descriptors, protein–ligand interaction fingerprints (IFPs) are competitive due to their simple representations, elaborate profiles of key interactions and easy collaborations with machine-learning algorithms. In this paper, we have adopted a building-block-based taxonomy to review a broad range of IFP models, and compared representative IFP-based SFs in target-specific and generic scoring tasks. Atom-pair-counts-based and substructure-based IFPs show great potential in these tasks.

Molecular Docking Analysis of Ficus religiosa Active Compound with Anti-Inflammatory Activity by Targeting Tumour Necrosis Factor Alpha and Vascular Endothelial Growth Factor Receptor in Diabetic Wound Healing

BACKGROUND: Diabetes mellitus contributes to the delayed healing of wounds causes disturbance of inflammatory cytokine. Tumour necrosis factor alpha (TNF-alpha) and Vascular Endothelial Growth Factor Receptor (VEGFR) both have a role in the persistent inflammation associated with diabetic wounds. Ficus religiosa has developed a reputation as a traditional wound healer among some java people in Indonesia. AIM: Our study aims to discover the molecular interaction between the active constituents of F. religiosa with TNF-alpha and VEGFR. MATERIALS AND METHODS: This research was conducted in computerized molecular docking using Protein database, Pymol, Discovery studio, and Pyrex software. A thorough literature search was conducted to identify the potential compound and molecular target for diabetic wounds. Analysis of its anti-inflammatory properties was also carried out using a passonline webserver. Pharmacokinetic analysis was performed using the Lipinski Rule of Five websites and the PreADMET website. RESULTS: Each of the study’s active compounds has a good pharmacokinetic profile. The predictions of the compound’s structure indicate that it has a strong anti-inflammatory impact. Lupenyl acetate and Lanosterol bind more strongly to the TNF-alpha than the natural ligand, but Piperine binds more strongly to VEGFR. CONCLUSIONS: Lupenyl acetate, Lanosterol, and Piperine compounds have anti-inflammatory effects through inhibition of TNF-alpha and VEGFR. In addition, this compound has potential to become a drug because it has good pharmacokinetics. Future studies are required to determine the effectiveness and toxicity of Lupenyl acetate, Lanosterol, and Piperine as potential treatment in diabetic wounds.

Antidepressant-like effect of dehydrozingerone from Zingiber officinale by elevating monoamines in brain: in silico and in vivo studies

BACKGROUND

Dehydrozingerone (DHZ) is an active ingredient of Zingiber officinale and structural half analogue of curcumin. In the present study, DHZ was evaluated for monoamine oxidase (MAO) inhibitory activity in silico and antidepressant activity in vivo.

METHOD

The binding affinity of DHZ with MAO-A (PDB ID: 2Z5Y) was assessed using Schrodinger's Maestro followed by free energy calculation, pharmacokinetic property prediction using Qikprop and Molecular dynamics simulation using Desmond. In vivo antidepressant activity of DHZ was evaluated on C57 BL/6 male mice using Escilatopram as the standard antidepressant. Open field test (OFT), forced swimming test (FST) and tail suspension test (TST) were used to evaluate the antidepressant effect of the drugs on days 1 and 7. Following the behavioural study, neurotransmitters (noradrenaline, dopamine and serotonin) were estimated using liquid chromatography-mass spectrometry.

RESULTS

DHZ demonstrated a greater binding affinity for the MAO-A enzyme compared to moclobemide in silico. Immobility in TST and FST were significantly (p < 0.05) reduced in vivo with 100mg/kg DHZ as compared to respective controls. DHZ treatment was more effective 1 h post treatment compared to vehicle control. A significant increase in levels of neurotransmitters was observed in mice brain homogenate in response to DHZ treatment, reassuring its antidepressant-like potential.

CONCLUSION

DHZ demonstrated MAO-A inhibition in silico, and the increased neurotransmitter levels in the brain in vivo were associated with an antidepressant-like effect.

β-Carboline alkaloids induce structural plasticity and inhibition of SARS-CoV-2 nsp3 macrodomain more potently than remdesivir metabolite GS-441524: computational approach

The nsp3 macrodomain is implicated in the viral replication, pathogenesis and host immune responses through the removal of ADP-ribosylation sites during infections of coronaviruses including the SARS-CoV-2. It has ever been modulated by macromolecules including the ADP-ribose until Ni and co-workers recently reported its inhibition and plasticity enhancement unprecedentedly by remdesivir metabolite, GS-441524, creating an opportunity for investigating other biodiverse small molecules such as β-Carboline (βC) alkaloids. In this study, 1497 βC analogues from the HiT2LEAD chemical database were screened, using computational approaches of Glide XP docking, molecular dynamics simulation and pk-CSM ADMET predictions. Selectively, βC ligands, 129, 584, 1303 and 1323 demonstrated higher binding affinities to the receptor, indicated by XP docking scores of -10.72, -10.01, -9.63 and -9.48 kcal/mol respectively than remdesivir and GS-441524 with -4.68 and -9.41 kcal/mol respectively. Consistently, their binding free energies were -36.07, -23.77, -24.07 and -17.76 kcal/mol respectively, while remdesivir and GS-441524 showed -21.22 and -24.20 kcal/mol respectively. Interestingly, the selected βC ligands displayed better stability and flexibility for enhancing the plasticity of the receptor than GS-441524, especially 129 and 1303. Their predicted ADMET parameters favour druggability and low expressions for toxicity. Thus, they are recommended as promising adjuvant/standalone anti-SARS-CoV-2 candidates for further study.Key words: SARS-CoV-2, nsp3 macrodomain, ADP-ribose, β-carboline, bioinformatics, drug design.

Emerging Need of Today: Significant Utilization of Various Databases and Softwares in Drug Design and Development

In drug discovery, in silico methods have become a very important part of the process. These approaches impact the entire development process by discovering and identifying new target proteins as well as designing potential ligands with a significant reduction of time and cost. Furthermore, in silico approaches are also preferred because of reduction in the experimental use of animals as; in vivo testing for safer drug design and repositioning of known drugs. Novel software-based discovery and development such as direct/indirect drug design, molecular modelling, docking, screening, drug-receptor interaction, and molecular simulation studies are very important tools for the predictions of ligand-target interaction pattern, pharmacodynamics as well as pharmacokinetic properties of ligands. On the other part, the computational approaches can be numerous, requiring interdisciplinary studies and the application of advanced computer technology to design effective and commercially feasible drugs. This review mainly focuses on the various databases and software used in drug design and development to speed up the process.

The glomerular filtration barrier: a structural target for novel kidney therapies

Loss of normal kidney function affects more than 10% of the population and contributes to morbidity and mortality. Kidney diseases are currently treated with immunosuppressive agents, antihypertensives and diuretics with partial but limited success. Most kidney disease is characterized by breakdown of the glomerular filtration barrier (GFB). Specialized podocyte cells maintain the GFB, and structure-function experiments and studies of intercellular communication between the podocytes and other GFB cells, combined with advances from genetics and genomics, have laid the groundwork for a new generation of therapies that directly intervene at the GFB. These include inhibitors of apolipoprotein L1 (APOL1), short transient receptor potential channels (TRPCs), soluble fms-like tyrosine kinase 1 (sFLT1; also known as soluble vascular endothelial growth factor receptor 1), roundabout homologue 2 (ROBO2), endothelin receptor A, soluble urokinase plasminogen activator surface receptor (suPAR) and substrate intermediates for coenzyme Q10 (CoQ₁₀). These molecular targets converge on two key components of GFB biology: mitochondrial function and the actin-myosin contractile machinery. This Review discusses therapies and developments focused on maintaining GFB integrity, and the emerging questions in this evolving field.

Isolation and Characterization of an Endophytic Fungus Colletotrichum coccodes Producing Tyrosol From Houttuynia cordata Thunb. Using ITS2 RNA Secondary Structure and Molecular Docking Study

An endophytic fungus isolated from healthy leaf tissues of Houttuynia cordata Thunb., an ethnomedicinal plant of North East India, showed a considerable amount of antimicrobial activity. The ethyl acetate extract of the fungal culture filtrates displayed promising antimicrobial activity against a panel of clinically significant pathogens including Candida albicans, Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa. Bioassay guided purification of the organic extract using column and thin layer chromatography yielded a pure homogenous compound which was identified using spectroscopic methods (essentially by ¹H NMR and MS) as tyrosol, a well-known phenylethanoid present in several natural sources. Besides, molecular docking studies against tyrosyl tRNA synthetases (TyrRS) of S. aureus (PDB ID: 1JIL) and E. coli (PDB ID: 1VBM), and CYP45014α-lanosterol demethylase (CYP51) of C. albicans (PDB ID: 5FSA) revealed tyrosol has a strong binding affinity with the enzyme active site residues. The fungus was identified as Colletotrichum sp. and characterized by its genomic ITS rDNA and ITS2 sequences. Phylogenetic analyses showed clustering of our isolate with Colletotrichum coccodes. Species of Colletotrichum are also reported to be plant pathogens. Therefore, to confirm the endophytic lifestyle of the isolate, ITS2 RNA secondary structure study was undertaken. The result indicated our isolate exhibited differences in the folding pattern as well as in motif structures when compared to those of pathogenic C. coccodes. The findings indicated that endophytic fungi harboring H. cordata could be explored as a potent source of antimicrobial agents.

Molecular docking study of bio-inhibitors extracted from marine macro-alga Ulva fasciata against hemolysin protein of luminescence disease-causing Vibrio harveyi

Shrimp grow-out and hatchery systems are being affected by bacterial disease particularly Vibrios. The use of chemotherapeutic agents in aquaculture practices has to lead to the development of resistance among aquatic bacteria. Thus, health management becomes of major importance in aquaculture. Under this situation, progressing bio-inhibitors from marine resources are most appropriate to be considered against pathogenic bacteria. Molecular docking is an appropriate tool in structural biology and computer-assisted drug design to predict and neutralize a target protein of known diseases. In this study, marine macro-alga Ulva fasciata was aimed at developing inhibitors against luminescence disease-causing pathogenic bacteria Vibrio harveyi. U. fasciata was collected from Thoothukudi, Tamil Nadu, India. Extract of U. fasciata was tested against growth and virulence factors of V. harveyi during Penaeus monodon larviculture. Further U. fasciata extract was subjected to GC-MS analysis to identify the biomolecules. The homology modeling of virulent protein, hemolysin of V. harveyi was designed in this study. Hence, it was aimed for molecular docking against the biomolecules identified from U. fasciata extract. During shrimp larviculture, the extract of U. fasciata (200 μg mL^-1) exhibited reduction on Cumulative Percentage of Mortality (32.40%) in postlarvae against challenge of V. harveyi infection. Biomolecule Methyl dehydroabietate had showed highest binding affinity among the compounds was evaluated in molecular docking study. Statistical analysis had revealed significant differences (p < 0.05) in trials. Therefore, it was proved that the bio-inhibitors from U. fasciata will be a better option for controlling luminescence disease-causing V. harveyi in shrimp grow-out practices.

Quinoline Antimalarials Increase the Antibacterial Activity of Ampicillin

Bacterial and malaria co-infections are common in malaria endemic countries and thus necessitate co-administration of antibiotics and antimalarials. There have long been anecdotal clinical reports of interactions between penicillins and antimalarial agents, but the nature and mechanisms of these interactions remain to be investigated. In this study, we employed antimicrobial interaction testing methods to study the effect of two antimalarials on the antibacterial activity of ampicillin in vitro. Paper strip diffusion, a modified disc diffusion and checkerboard methods were used to determine the nature of interactions between ampicillin and quinoline antimalarials, chloroquine and quinine, against Gram-positive and Gram-negative bacteria. The impact of antimalarials and ampicillin-antimalarial drug combinations on cell integrity of test bacteria were determined by measuring potassium release. The tested antimalarials did not show substantial antibacterial activity but quinine was bactericidal at high concentrations. Chloroquine and quinine increased ampicillin activity, with increasing concentrations extending the antibacterial’s inhibition zones by 2.7-4.4 mm and from 1.1 to over 60 mm, respectively. Observed interactions were largely additive with Fractional Inhibitory Concentration Indices of >0.5-1 for all ampicillin-antimalarial combinations. Quinine and, to a lesser extent, chloroquine increase the activity of ampicillin and potentially other β-lactams, which has implications for combined clinical use.

Synthesis and α-Glucosidase Inhibition Activity of 2-[3-(Benzoyl/4-bromobenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl]-N-arylacetamides: An In Silico and Biochemical Approach

Diabetes mellitus (DM) is a chronic disorder and has affected a large number of people worldwide. Insufficient insulin production causes an increase in blood glucose level that results in DM. To lower the blood glucose level, various drugs are employed that block the activity of the α-glucosidase enzyme, which is considered responsible for the breakdown of polysaccharides into monosaccharides leading to an increase in the intestinal blood glucose level. We have synthesized novel 2-(3-(benzoyl/4-bromobenzoyl)-4-hydroxy-1,1-dioxido-2H-benzo[e][1,2]thiazin-2-yl)-N-arylacetamides and have screened them for their in silico and in vitro α-glucosidase inhibition activity. The derivatives 11c, 12a, 12d, 12e, and 12g emerged as potent inhibitors of the α-glucosidase enzyme. These compounds exhibited good docking scores and excellent binding interactions with the selected residues (Asp203, Asp542, Asp327, His600, Arg526) during in silico screening. Similarly, these compounds also showed good in vitro α-glucosidase inhibitions with IC₅₀ values of 30.65, 18.25, 20.76, 35.14, and 24.24 μM, respectively, which were better than the standard drug, acarbose (IC₅₀ = 58.8 μM). Furthermore, a good agreement was observed between in silico and in vitro modes of study.

Noncovalent molecular interactions between antineoplastic drug gemcitabine and a carrier protein identified through spectroscopic and in silico methods

Herein we have studied the noncovalent molecular interactions between hen egg white lysozyme (HEWL) and the commonly employed antineoplastic drug gemcitabine through the cumulative implementation of spectroscopic techniques and in silico approaches. The formation of a complex between HEWL and gemcitabine was made evident by the differences between the UV-visible spectra of the protein and protein-gemcitabine complex. Fluorescence quenching of HEWL by gemcitabine was hardly detectable at room temperature, but it became prominent at higher temperatures. Very low values for the bimolecular quenching constant and the non-reciprocal dependence of quenching on temperature indicated that dynamic quenching was taking place. Analysis of experimental data indicated that the interaction was dominated by hydrophobic forces, while the results of a computational investigation suggested the concomitant contribution of hydrogen bonding. Gemcitabine binding induced modifications of the secondary structure of HEWL by slightly increasing the α-helical content of the protein. Finally, gemcitabine binding site was inferred to be located in HEWL big hydrophobic cavity.

Behavior of Chemokine Receptor 6 (CXCR6) in Complex with CXCL16 Soluble form Chemokine by Molecular Dynamic Simulations: General Protein‒Ligand Interaction Model and 3D-QSAR Studies of Synthetic Antagonists

The CXCR6‒CXCL16 axis is involved in several pathological processes, and its overexpression has been detected in different types of cancer, such as prostate, breast, ovary, and lung cancer, along with schwannomas, in which it promotes invasion and metastasis. Moreover, this axis is involved in atherosclerosis, type 1 diabetes, primary immune thrombocytopenia, vitiligo, and other autoimmune diseases, in which it is responsible for the infiltration of different immune system cells. The 3D structure of CXCR6 and CXCL16 has not been experimentally resolved; therefore, homology modeling and molecular dynamics simulations could be useful for the study of this signaling axis. In this work, a homology model of CXCR6 and a soluble form of CXCL16 (CXCR6‒CXCL16s) are reported to study the interactions between CXCR6 and CXCL16s through coarse-grained molecular dynamics (CG-MD) simulations. CG-MD simulations showed the two activation steps of CXCR6 through a decrease in the distance between the chemokine and the transmembrane region (TM) of CXCR6 and transmembrane rotational changes and polar interactions between transmembrane segments. The polar interactions between TM3, TM5, and TM6 are fundamental to functional conformation and the meta-active state of CXCR6. The interactions between D77-R280 and T243-TM7 could be related to the functional conformation of CXCR6; alternatively, the interaction between Q195-Q244 and N248 could be related to an inactive state due to the loss of this interaction, and an arginine cage broken in the presence of CXCL16s allows the meta-active state of CXCR6. A general protein‒ligand interaction supports the relevance of TM3‒TM5‒TM6 interactions, presenting three relevant pharmacophoric features: HAc (H-bond acceptor), HDn (H-bond donator), and Hph (hydrophobic), distributed around the space between extracellular loops (ECLs) and TMs. The HDn feature is close to TM3 and TM6; likewise, the HAc and Hph features are close to ECL1 and ECL2 and could block the rotation and interactions between TM3‒TM6 and the interactions of CXCL16s with the ECLs. Tridimensional quantitative structure-activity relationships (3D-QSAR) models show that the positive steric (VdW) and electrostatic fields coincide with the steric and positive electrostatic region of the exo-azabicyclo[3.3.1]nonane scaffold in the best pIC50 ligands. This substructure is close to the E274 residue and therefore relevant to the activity of CXCR6. These data could help with the design of new molecules that inhibit chemokine binding or antagonize the receptor based on the activation mechanism of CXCR6 and provoke a decrease in chemotaxis caused by the CXCR6‒CXCL16 axis.

<i>In silico </i>Identification of Peptide as Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Lung Cancer Treatment

BACKGROUND AND OBJECTIVE

Epidermal growth factor receptor (EGFR) is the biomarker for lung cancer in which the protein has the most active mutated genes in lung cancer patients. Peptides have pharmacological potential as drugs because of their bioactivity and accessibility. The research objective was to obtain peptide compounds drug candidates with good interaction and pharmacological properties that can act as an inhibitor for EGFR for lung cancer treatment by using in silico method.

MATERIALS AND METHODS

EGFR protein structure was obtained from Protein Data Bank and the peptide compounds were retrieved from PubChem. Optimization and energy minimization process were done to prepare the peptides for the simulation. Protein-Ligand Interaction Fingerprint (PLIF) was used to determine the pharmacophore features in the EGFR binding site. Both proteins and ligands underwent a virtual screening through rigid and flexible molecular docking simulation and the best ligands were subjected to a computational ADME-Tox properties prediction.

RESULTS

After screening through molecular docking simulation, nine best compounds were identified to have a good interaction with EGFR protein according to its binding energy and RMSD value. The compounds were identified to form hydrogen bond interactions with the macromolecule.

CONCLUSION

Two peptide compounds (PubChem ID: 20832941 and 9805315) have been predicted as the best ligands with desired pharmacological properties for the inhibition of EGFR tyrosine kinase.

FGDB: Database of follicle stimulating hormone glycans

Glycomics, the study of the entire complement of sugars of an organism has received significant attention in the recent past due to the advances made in high throughput mass spectrometry technologies. These analytical advancements have facilitated the characterization of glycans associated with the follicle-stimulating hormones (FSH), which play a central role in the human reproductive system both in males and females utilizing regulating gonadal (testicular and ovarian) functions. The irregularities in FSH activity are also directly linked with osteoporosis. The glycoanalytical studies have been tremendously helpful in understanding the biological roles of FSH. Subsequently, the increasing number of characterized FSH glycan structures and related glycoform data has thrown a challenge to the glycoinformatics community in terms of data organization, storage and access. Also, a user-friendly platform is needed for providing easy access to the database and performing integrated analysis using a high volume of experimental data to accelerate FSH-focused research. FSH Glycans DataBase (FGDB) serves as a comprehensive and unique repository of structures, features, and related information of glycans associated with FSH. Apart from providing multiple search options, the database also facilitates an integrated user-friendly interface to perform the glycan abundance and comparative analyses using experimental data. The automated integrated pipelines present the possible structures of glycans and variants of FSH based on the input data, and allow the user to perform various analyses. The potential application of FGDB will significantly help both glycoinformaticians as well as wet-lab researchers to stimulate the research in this area. FGDB web access: https://fgdb.unmc.edu/.

DFT investigation of atazanavir as potential inhibitor for 2019-nCoV coronavirus M protease

Atazanavir (ATZ) is an antiviral drug synthesized.ATZ is being investigated for potential application against the Coronavirus 2019-nCoV. To find candidate drugs for 2019-nCoV, we have carried out a computational study to screen for effective available drug ATZ which may work as an inhibitor for the Mpro of 2019-nCoV. In the present work, the first time the molecular structure of ATZ molecule has been studied using Density Functional Theory (CAMB3LYP/6-31G*) in solvent water. The electronic properties, atomic charges, MEP, NBO analysis, and excitation energies of ATZ have also been studied. The interaction of ATZ compound with the Coronavirus was performed by molecular docking studies.

Anti-diabetic effect of the lupinalbin A compound isolated from Apios americana: In vitro analysis and molecular docking study

Dipeptidyl peptidase 4 (DPP4) and α-glucosidase inhibitors have been developed as anti-diabetic agents for the treatment of diabetes mellitus. In the present study, the anti-diabetic effects of the lupinalbin A compound isolated from Apios americana was investigated by measuring its inhibitory activity against DPP4 and α-glucosidase. To detect the inhibitory effect of lupinalbin A, DPP4 and α-glucosidase assays were performed in vitro. Molecular docking analysis was performed using AutoDock 4.2. The IC₅₀ values of lupinalbin A against DPP4 and α-glucosidase were 45.2 and 53.4 µM, respectively. Analysis of the enzyme kinetics revealed that lupinalbin A interacted with the active site of DPP4 in a competitive manner, with an inhibition constant (Ki) value of 35.1±2.0 µM, whereas the lupinalbin A interaction with α-glucosidase was non-competitive, with a Ki value of 45.0 µM. Molecular docking analysis revealed a binding pose between the DPP4 enzyme and lupinalbin A. Taken together, these data suggest lupinalbin A is more effective against DPP4 than α-glucosidase, with regard to its anti-diabetic effects.

Homology modeling, docking, molecular dynamics and in vitro studies to identify Rhipicephalus microplus acetylcholinesterase inhibitors

Rhipicephalus microplus is an important ectoparasite of cattle, causing considerable economical losses. Resistance to chemical acaricides has stimulated the search for new antiparasitic drugs, including natural products as an eco-friendly alternative of control. Flavonoids represent a class of natural compounds with many biological activities, such as enzyme inhibitors. Acetylcholinesterase is an essential enzyme for tick survival that stands out as an important target for the development of acaricides. This work aimed to predict this 3D structure by homology modeling and use the model to identify compound with inhibitory activity. The model of R. microplus AChE1 (RmAChE1) was constructed using MODELLER program. The optimization and molecular dynamic investigation were performed in GROMACS program. The model developed was used, by molecular docking, to evaluate the anticholinesterase activity of flavonoids (quercetin, rutin, diosmin, naringin and hesperidin) and an acaricide synthetic (eserine). Additionally, in vitro inhibition of AChE and larval immersion tests were performed. The model of RmAChE1 showed to be sterically and energetically acceptable. In molecular dynamics simulations, the 3D structure remains stable with Root Mean Square Deviation = 3.58 Å and Root Mean Square Fluctuation = 1.43 Å. In molecular docking analyses, only eserine and quercetin show affinity energy to the RmAChE (Gridscore: -52.17 and -39.44 kcal/mol, respectively). Among the flavonoids, quercetin exhibited the best in vitro inhibition of AChE activity (15.8%) and mortality of larvae tick (30.2%). The use of in silico and in vitro techniques has shown that quercetin showed promising anti-tick activity and structural requirements to interact with RmAChE1. Communicated by Ramaswamy H. Sarma.

Elucidation of S-Allylcysteine Role in Inducing Apoptosis by Inhibiting PD-L1 Expression in Human Lung Cancer Cells

AIM

The aim of this study is to explore the therapeutic potential of S-allylcysteine (SAC) organosulphur compound as a potent immune checkpoint inhibitor PD-L1.

BACKGROUND

Natural compounds have been showing tremendous anticancerous potential via suppressing the expression of genes involved in the development and progression of several carcinomas. This has further motivated us to explore the therapeutic potential of organosulphur compounds as potent immune checkpoint inhibitors.

OBJECTIVE

Our study was designed to elucidate the potential of S-allylcysteine (SAC) as significant PD-L1 (immune checkpoint) inhibitor in human lung cancer A549 cancer cell line by using both the in vitro and in silico approaches.

METHODS

Anticancerous effect of the SAC on lung cancer cells was determined by using the MTT cell viability. Apoptotic induction was confirmed by Hoechst staining, percent caspase-3 activity as well as gene expression analysis by real time PCR. Reactive Oxygen Species (ROS) was estimated by DCFDA method. Additionally, ligand-target protein interaction was analysed by molecular docking.

RESULT

Cell growth and proliferation was significantly reduced in SAC treated A549 cells in a concentration and time.dependent manner. The effect of SAC on apoptotic induction was analyzed by enhanced nuclear condensation, increased percent caspase-3 activity as well as modulation of apoptotic genes. Furthermore, SAC treatment also resulted in reduced expression of PD-L1 and HIF-1α. Additionally, in silico analysis also supported the in vitro findings by showing efficient docking with PD-L1 immune checkpoint target.

CONCLUSION

Therefore, our results clearly suggested that SAC could serve as a novel chemotherapeutic candidate for the treatment of lung cancer by inhibiting immune checkpoint target PD-L1 in human lung cancer cells. Additionally, our study also explained a novel molecular mechanism of its antitumor activity.

Antioxidant-Rich Woodfordia fruticosa Leaf Extract Alleviates Depressive-Like Behaviors and Impede Hyperglycemia

Dhaiphul (Woodfordia fruticosa) is a frequently demanded plant in South-East Asian regions for its diverse medicinal values. This study was proposed to examine antioxidant, antidiabetic, and antidepressant potentials of methanol extract of W. fruticosa leaves (MEWF) and its derived n-hexane (NHFMEWF) and ethyl acetate (EAFMEWF) fractions through in vitro, in vivo, and computational models. Among test samples, MEWF and EAFMEWF contained the highest phenolic content and showed maximal antioxidant activity in DPPH radical scavenging and ferric reducing power assays. In comparison, NHFMEWF possessed maximum flavonoid content and a significantly potent α-amylase inhibitory profile comparable with positive control acarbose. In animal models of depression (forced swimming and tail suspension test), EAFMEWF and NHFMEWF demonstrated a dose-dependent antidepressant-like effect; explicitly, the depressive-like behaviors significantly declined in EAFMEWF-treated dosing groups in contrast to the control group. In the computational analysis, previously isolated flavonoid compounds from Dhaiphul leaves manifested potent binding affinity against several key therapeutic target proteins of diabetes and depressive disorders including α-amylase, serotonin transporter, dopamine transporter, and neuronal nitric oxide synthase with varying pharmacokinetics and toxicity profiles. This research's outcomes may provide potential dietary supplements for mitigating hyperglycemia, cellular toxicity, and depressive disorder.

Gene set enrichment analysis of α-amylase and α-glucosidase inhibitors of Cassia glauca

Background

The present study aimed to evaluate in vitro α-amylase and α-glucosidase inhibitory activity of various extracts of Cassia glauca, predict the binding affinity of multiple phytoconstituents with both enzymes via in silico molecular docking and identify the probably modulated pathways by the lead hit.

Methods

Different extracts of Cassia glauca i.e. acetone, ethanol, and aqueous extracts were evaluated for α-amylase and α-glucosidase inhibitory activity using in vitro method in which starch and 4-Nitrophenyl β-D-glucopyranoside were used as substrate respectively. Similarly, the docking study was performed using autodock4 to predict the binding affinity of phytoconstituents with α-amylase and α-glucosidase. After docking, ten different poses were obtained for the ligand molecule. Among them, the pose of ligand molecule with the lowest binding energy was visualized in Discovery Studio 2019.

Results and conclusion

Among the multiple extracts, the aqueous extract showed the highest α-amylase (IC₅₀:652.10 ± 20.09) and α-glucosidase (IC₅₀:482.46 ± 8.70) inhibitory activity. Similarly, cassiaoccidentalin B was predicted to have the highest binding affinity with both enzymes. The potency of aqueous extract to inhibit α-amylase and α-glucosidase could be due to multiple water-soluble compounds like saponins, flavonoids, and glycosides.

Identification of DNA Methyltransferase-1 Inhibitor for Breast Cancer Therapy through Computational Fragment-Based Drug Design

Epimutation by DNA Methyltransferase 1 (DNMT1), an epigenetic regulator enzyme, may lead to the proliferation of breast cancer. In this report, 168,686 natural products from the PubChem database were screened and modified by in silico method to acquire the potential inhibitor of DNMT1. The initial screening of PubChem natural products using Lipinski's and Veber's rules of three and toxic properties have resulted in 2601 fragment candidates. Four fragments from pharmacophore-based molecular docking simulation were modified by utilizing FragFP and the Lipinski's and Veber's rules of five, and resulted in 51,200 ligands. The toxicological screening collected 13,563 ligands for a series of pharmacophore-based molecular docking simulations to sort out the modified ligands, which had the better binding activity and interactions to DNMT1 compared to the standards, SAH, SAM, and SFG. This step resulted in five ligand candidates, namely C-7756, C-5769, C-1723, C-2129, and C-2140. The ADME-Tox properties prediction showed that the selected ligands are generally better than standards in terms of druglikeness, GI absorption, and oral bioavailability. C-7756 exhibited a stronger affinity to DNMT1 as well as better ADME-Tox properties compared to the other ligands.