Molecular Architect: A User-Friendly Workflow for Virtual Screening

Targeting the Pseudomonas aeruginosa quorum sensing system to inhibit virulence factors and eradicate biofilm formation using AHL-analogue phytochemicals

Quorum sensing plays a major role in the expression of virulence and development of biofilm in the human pathogen Pseudomonas aeruginosa. Natural compounds are well-known for their antibacterial characteristics by blocking various metabolic pathways. The goal of this study is to find natural compounds that mimic AHL (Acyl homoserine lactone) and suppress virulence in P. aeruginosa, which is triggered by quorum sensing-dependent pathways as an alternative drug development strategy. To support this rationale, functional network analysis and in silico investigations were carried out to find natural AHL analogues, followed by molecular docking studies. Out of the 16 top-hit AHL analogues derived from phytochemicals, seven ligands were found to bind to the quorum sensing activator proteins. Cassialactone, an AHL analogue, exhibited the highest binding affinity for RhlI, RhlR, and PqsE of P. aeruginosa, with a docking score of -9.4, -8.9, and -8.7 kcal/mol, respectively. 2(5H)-Furanone, a well-known inhibitor, was also docked to compare the docking score and intermolecular interactions between the ligand and the target protein. Furthermore, molecular dynamics simulations and binding free energy calculations were performed to determine the stability of the docked complexes. Additionally, the ADME properties of the analogues were also analyzed to evaluate the pharmacological parameters. Functional network analysis further showed that the interconnectedness of proteins such as RhlI, RhlR, LasI, and PqsE with the virulence and biofilm phenotype of the pathogen could offer potential as a therapeutic target.Communicated by Ramaswamy H. Sarma.

Understanding the biodegradation pathways of azo dyes by immobilized white-rot fungus, Trametes hirsuta D7, using UPLC-PDA-FTICR MS supported by in silico simulations and toxicity assessment

No biodegradation methods are absolute in the treatment of all textile dyes, which leads to structure-dependent degradation. In this study, biodegradation of three azo dyes, reactive black 5 (RB5), acid blue 113 (AB113), and acid orange 7 (AO7), was investigated using an immobilized fungus, Trametes hirsuta D7. The degraded metabolites were identified using UPLC-PDA-FTICR MS and the biodegradation pathway followed was proposed. RB5 (92%) and AB113 (97%) were effectively degraded, whereas only 30% of AO7 was degraded. Molecular docking simulations were performed to determine the reason behind the poor degradation of AO7. Weak binding affinity, deficiency in H-bonding interactions, and the absence of interactions between the azo (-NN-) group and active residues of the model laccase enzyme were responsible for the low degradation efficiency of AO7. Furthermore, cytotoxicity and genotoxicity assays confirmed that the fungus-treated dye produced non-toxic metabolites. The observations of this study will be useful for understanding and further improving enzymatic dye biodegradation.

In vitro and in silico assessment of new beta amino ketones with antiplasmodial activity

BACKGROUND

Based on the current need for new drugs against malaria, our study evaluated eight beta amino ketones in silico and in vitro for potential antimalarial activity.

METHODS

Using the Brazilian Malaria Molecular Targets (BraMMT) and OCTOPUS® software programs, the pattern of interactions of beta-amino ketones was described against different proteins of P. falciparum and screened to evaluate their physicochemical properties. The in vitro antiplasmodial activities of the compounds were evaluated using a SYBR Green-based assay. In parallel, in vitro cytotoxic data were obtained using the MTT assay.

RESULTS

Among the eight compounds, compound 1 was the most active and selective against P. falciparum (IC50 = 0.98 µM; SI > 60). Six targets were identified in BraMMT that interact with compounds exhibiting a stronger binding energy than the crystallographic ligand: P. falciparum triophosphate phosphoglycolate complex (1LYX), P. falciparum reductase (2OK8), PfPK7 (2PML), P. falciparum glutaredoxin (4N0Z), PfATP6, and PfHT.

CONCLUSIONS

The physicochemical properties of compound 1 were compatible with the set of criteria established by the Lipinski rule and demonstrated its potential as a drug prototype for antiplasmodial activity.

Synthesis, Electrochemical Studies, Molecular Docking, and Biological Evaluation as an Antimicrobial Agent of 5-Amino-6-cyano-3-hydroxybenzo[c]coumarin Using Ni-Cu-Al-CO3 Hydrotalcite as a Catalyst

New insights via a multicomponent cyclocondensation reaction of 2-hydroxy benzaldehyde acetoacetic ester and malononitrile were attained under efficient conditions. A detailed mechanistic study exhibits that the reaction via multicomponent, one-pot, two-step incooperating three-components' reactants under nominal conditions efficiently synthesizes the intermediates in shorter than reported time along with the formation of a novel compound [5-amino-6-cyano-3-hydroxybenzo[c]coumarin] in the presence of Ni-Cu-Al-CO₃ hydrotalcite as a heterogeneous catalyst. Hydrotalcite functions as an efficient and versatile catalyst as it is safe, easy to work up, and recyclable many times under ambient conditions, and the reaction time is shorter. The aforementioned conditions make these solid basic heterogeneous catalysts environmentally friendly. The product yield obtained was 89%. The product was characterized using FTIR, LCMS, and NMR. Electrochemical studies were also carried out to check the reduction and oxidation behavior. The synthesized product showed antimicrobial activity. Antimicrobial activity against human pathogens, viz, S. Aureus, P. Aeruginosa, and P. Bulgaria, was studied by using the agar well diffusion method. The molecular docking studies of 5-amino-6-cyano-3-hydroxybenzo[c]coumarin exhibit its suitable attachment at the active center of the type IIA topoisomerases and gyrase enzymes which suggest its potential antibacterial activity when compared using ciprofloxacin drug as the control.

Evaluation of Docking Machine Learning and Molecular Dynamics Methodologies for DNA-Ligand Systems

DNA is a molecular target for the treatment of several diseases, including cancer, but there are few docking methodologies exploring the interactions between nucleic acids with DNA intercalating agents. Different docking methodologies, such as AutoDock Vina, DOCK 6, and Consensus, implemented into Molecular Architect (MolAr), were evaluated for their ability to analyze those interactions, considering visual inspection, redocking, and ROC curve. Ligands were refined by Parametric Method 7 (PM7), and ligands and decoys were docked into the minor DNA groove (PDB code: 1VZK). As a result, the area under the ROC curve (AUC-ROC) was 0.98, 0.88, and 0.99 for AutoDock Vina, DOCK 6, and Consensus methodologies, respectively. In addition, we proposed a machine learning model to determine the experimental ∆T_m value, which found a 0.84 R² score. Finally, the selected ligands mono imidazole lexitropsin (42), netropsin (45), and N,N′-(1H-pyrrole-2,5-diyldi-4,1-phenylene)dibenzenecarboximidamide (51) were submitted to Molecular Dynamic Simulations (MD) through NAMD software to evaluate their equilibrium binding pose into the groove. In conclusion, the use of MolAr improves the docking results obtained with other methodologies, is a suitable methodology to use in the DNA system and was proven to be a valuable tool to estimate the ∆T_m experimental values of DNA intercalating agents.

Theoretical insights into the effect of halogenated substituent on the electronic structure and spectroscopic properties of the favipiravir tautomeric forms and its implications for the treatment of COVID-19

In this study, we systematically investigated the electronic structure, spectroscopic (nuclear magnetic resonance, infrared, Raman, electron ionization mass spectrometry, UV-Vis, circular dichroism, and emission) properties, and tautomerism of halogenated favipiravir compounds (fluorine, chlorine, and bromine) from a computational perspective. Additionally, the effects of hydration on the proton transfer mechanism of the tautomeric forms of the halogenated favipiravir compounds are discussed. Our results suggest that spectroscopic properties allow for the elucidation of such tautomeric forms. As is well-known, the favipiravir compound has excellent antiviral properties and hence was recently tested for the treatment of new coronavirus (SARS-CoV-2). Through in silico modeling, in the current study, we evaluate the role of such tautomeric forms in order to consider the effect of drug-metabolism in the inhibition process of the main protease (Mpro) and RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 virus. According to the molecular docking, all halogenated compounds presented a better interaction energy than the co-crystallized active ligand (-3.5 kcal mol-1) in the viral RdRp, in both wild-type (-6.3 to -6.5 kcal mol-1) and variant (-5.4 to -5.6 kcal mol-1) models. The variant analyzed for RdRp (Y176C) decreases the affinity of the keto form of the compounds in the active site, and prevented the ligands from interacting with RNA. These findings clearly indicated that all these compounds are promising as drug candidates for this molecular target.

Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.

Effect of drug metabolism in the treatment of SARS-CoV-2 from an entirely computational perspective

Understanding the effects of metabolism on the rational design of novel and more effective drugs is still a considerable challenge. To the best of our knowledge, there are no entirely computational strategies that make it possible to predict these effects. From this perspective, the development of such methodologies could contribute to significantly reduce the side effects of medicines, leading to the emergence of more effective and safer drugs. Thereby, in this study, our strategy is based on simulating the electron ionization mass spectrometry (EI-MS) fragmentation of the drug molecules and combined with molecular docking and ADMET models in two different situations. In the first model, the drug is docked without considering the possible metabolic effects. In the second model, each of the intermediates from the EI-MS results is docked, and metabolism occurs before the drug accesses the biological target. As a proof of concept, in this work, we investigate the main antiviral drugs used in clinical research to treat COVID-19. As a result, our strategy made it possible to assess the biological activity and toxicity of all potential by-products. We believed that our findings provide new chemical insights that can benefit the rational development of novel drugs in the future.

Synthesis, docking, machine learning and antiproliferative activity of the 6-ferrocene/heterocycle-2-aminopyrimidine and 5-ferrocene-1H-Pyrazole derivatives obtained by microwave-assisted Atwal reaction as potential anticancer agents

A simple and fast methodology under microwave irradiation for the synthesis of 2-aminopyrimidine and pyrazole derivatives using Atwal reaction is reported. After the optimization of the reaction conditions, eight 2-aminolpyrimidines containing ferrocene and heterocycles and three ferrocene pyrazoles were synthesized from the respective chalcones in good yields. Eight compounds had their structure determined by X-ray diffraction. The molecular hybrid 6a-h and 9a-c were tested on four cancer cell lines - HCT116, PC3, HL60 and SNB19 - where four pyrimidine 6a, 6f-h and one pyrazole 9c derivatives show promising antiproliferative activity. In addition, docking simulation and machine learning methods were carried out to explain the biological activity achieved by the synthetized compounds.

Computational Screening of Potential Inhibitors of Desulfobacter postgatei for Pyrite Scale Prevention in Oil and Gas Wells

Sulfate-reducing bacteria (SRB), such as Desulfobacter postgatei are found in oil wells. However, they lead to the release of hydrogen sulfide. This in turn leads to the iron sulfide scale formation (pyrite). ATP sulfurylase is an enzyme present in SRB, which catalyzes the formation of adenylyl sulfate (APS) and inorganic pyrophosphatase (PPi) from ATP and sulfate. This reaction is the first among many in hydrogen sulfide production by D. postgatei . Consensus scoring using molecular docking and machine learning was used to identify three potential inhibitors of ATP sulfurylase from a database of about 40 million compounds. These selected hits ((S,E)-1-(4-methoxyphenyl)-3-(9-((m-tolylimino)methyl)-9,10-dihydroanthracen-9-yl)pyrrolidine-2,5-dione; methyl 2-[[(1S)-5-cyano-2-imino-1-(4-phenylthiazol-2-yl)-3-azaspiro[5.5]undec-4-en-4-yl]sulfanyl]acetate; and (4S)-4-(3-chloro-4-hydroxy-phenyl)-1-(6-hydroxypyridazin-3-yl)-3-methyl-4,5-dihydropyrazolo[3,4-b]pyridin-6-ol), known as A, B, and C, respectively) all had good binding affinities with ATP sulfurylase and were further analyzed for their toxicological properties. Compound A had the highest docking score. However, based on the physicochemical and toxicological properties, only compound C was predicted to be both safe and effective as a potential inhibitor of ATP sulfurylase, hence the preferred choice. The molecular interactions of compound C revealed favorable interactions with the following residues: LEU213, ASP308, ARG307, TRP347, LEU224, GLN212, MET211, and HIS309.

Docking Paradigm in Drug Design

Docking is in demand for the rational computer aided structure based drug design. A review of docking methods and programs is presented. Different types of docking programs are described. They include docking of non-covalent small ligands, protein-protein docking, supercomputer docking, quantum docking, the new generation of docking programs and the application of docking for covalent inhibitors discovery. Taking into account the threat of COVID-19, we present here a short review of docking applications to the discovery of inhibitors of SARS-CoV and SARS-CoV-2 target proteins, including our own result of the search for inhibitors of SARS-CoV-2 main protease using docking and quantum chemical post-processing. The conclusion is made that docking is extremely important in the fight against COVID-19 during the process of development of antivirus drugs having a direct action on SARS-CoV-2 target proteins.

Computational evidence for nitro derivatives of quinoline and quinoline N-oxide as low-cost alternative for the treatment of SARS-CoV-2 infection

A new and more aggressive strain of coronavirus, known as SARS-CoV-2, which is highly contagious, has rapidly spread across the planet within a short period of time. Due to its high transmission rate and the significant time–space between infection and manifestation of symptoms, the WHO recently declared this a pandemic. Because of the exponentially growing number of new cases of both infections and deaths, development of new therapeutic options to help fight this pandemic is urgently needed. The target molecules of this study were the nitro derivatives of quinoline and quinoline N-oxide. Computational design at the DFT level, docking studies, and molecular dynamics methods as a well-reasoned strategy will aid in elucidating the fundamental physicochemical properties and molecular functions of a diversity of compounds, directly accelerating the process of discovering new drugs. In this study, we discovered isomers based on the nitro derivatives of quinoline and quinoline N-oxide, which are biologically active compounds and may be low-cost alternatives for the treatment of infections induced by SARS-CoV-2.

Dehydrobufotenin extracted from the Amazonian toad Rhinella marina (Anura: Bufonidae) as a prototype molecule for the development of antiplasmodial drugs

Background:

The resistance against antimalarial drugs represents a global challenge in the fight and control of malaria. The Brazilian biodiversity can be an important tool for research and development of new medicinal products. In this context, toxinology is a multidisciplinary approach on the development of new drugs, including the isolation, purification, and evaluation of the pharmacological activities of natural toxins. The present study aimed to evaluate the cytotoxicity, as well as the antimalarial activity in silico and in vitro of four compounds isolated from Rhinella marina venom as potential oral drug prototypes.

Methods:

Four compounds were challenged against 35 target proteins from P. falciparum and screened to evaluate their physicochemical properties using docking assay in Brazilian Malaria Molecular Targets (BraMMT) software and in silico assay in OCTOPUS® software. The in vitro antimalarial activity of the compounds against the 3D7 Plasmodium falciparum clones were assessed using the SYBR Green I based assay (IC₅₀). For the cytotoxic tests, the LD₅₀ was determined in human pulmonary fibroblast cell line using the [3(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] (MTT) assay.

Results:

All compounds presented a ligand-receptor interaction with ten Plasmodium falciparum-related protein targets, as well as antimalarial activity against chloroquine resistant strain (IC₅₀ = 3.44 μM to 19.11 μM). Three of them (dehydrobufotenine, marinobufagin, and bufalin) showed adequate conditions for oral drug prototypes, with satisfactory prediction of absorption, permeability, and absence of toxicity. In the cell viability assay, only dehydrobufotenin was selective for the parasite.

Conclusions:

Dehydrobufotenin revealed to be a potential oral drug prototype presenting adequate antimalarial activity and absence of cytotoxicity, therefore should be subjected to further studies.

Potential Inhibitors of Fascin From A Database of Marine Natural Products: A Virtual Screening and Molecular Dynamics Study

Marine nature products are unique compounds that are produced by the marine environment including plants, animals, and microorganisms. The wide diversity of marine natural products have great potential and are versatile in terms of drug discovery. In this paper, we use state-of-the-art computational methods to discover inhibitors from marine natural products to block the function of Fascin, an overexpressed protein in various cancers. First, virtual screening (pharmacophore model and molecular docking) was carried out based on a marine natural products database (12015 molecules) and provided eighteen molecules that could potentially inhibit the function of Fascin. Next, molecular mechanics generalized Born surface area (MM/GBSA) calculations were conducted and indicated that four molecules have higher binding affinities than the inhibitor NP-G2-029, which was validated experimentally. ADMET analyses of pharmacokinetics demonstrated that one of the four molecules does not match the criterion. Finally, ligand Gaussian accelerated molecular dynamics (LiGaMD) simulations were carried out to validate the three inhibitors binding to Fascin stably. In addition, dynamic interactions between protein and ligands were analyzed systematically. Our study will accelerate the development of the cancer drugs targeting Fascin.

Ligand and structure-based virtual screening applied to the SARS-CoV-2 main protease: an in silico repurposing study

Aim: The identification of drugs for the coronavirus disease-19 pandemic remains urgent. In this manner, drug repurposing is a suitable strategy, saving resources and time normally spent during regular drug discovery frameworks. Essential for viral replication, the main protease has been explored as a promising target for the drug discovery process. Materials & methods: Our virtual screening pipeline relies on the known 3D properties of noncovalent ligands and features of crystalized complexes, applying consensus analyses in each step. Results: Two oral (bedaquiline and glibenclamide) and one buccal drug (miconazole) presented 3D similarity to known ligands, reasonable predicted binding modes and micromolar predicted binding affinity values. Conclusion: We identified three approved drugs as promising inhibitors of the main viral protease and suggested design insights for future studies for development of novel selective inhibitors.

Uncovering New Drug Properties in Target-Based Drug-Drug Similarity Networks

Despite recent advances in bioinformatics, systems biology, and machine learning, the accurate prediction of drug properties remains an open problem. Indeed, because the biological environment is a complex system, the traditional approach—based on knowledge about the chemical structures—can not fully explain the nature of interactions between drugs and biological targets. Consequently, in this paper, we propose an unsupervised machine learning approach that uses the information we know about drug–target interactions to infer drug properties. To this end, we define drug similarity based on drug–target interactions and build a weighted Drug–Drug Similarity Network according to the drug–drug similarity relationships. Using an energy-model network layout, we generate drug communities associated with specific, dominant drug properties. DrugBank confirms the properties of 59.52% of the drugs in these communities, and 26.98% are existing drug repositioning hints we reconstruct with our DDSN approach. The remaining 13.49% of the drugs seem not to match the dominant pharmacologic property; thus, we consider them potential drug repurposing hints. The resources required to test all these repurposing hints are considerable. Therefore we introduce a mechanism of prioritization based on the betweenness/degree node centrality. Using betweenness/degree as an indicator of drug repurposing potential, we select Azelaic acid and Meprobamate as a possible antineoplastic and antifungal, respectively. Finally, we use a test procedure based on molecular docking to analyze Azelaic acid and Meprobamate’s repurposing.