A pharmacoinformatic approach on Cannabinoid receptor 2 (CB2) and different small molecules: Homology modelling,molecular docking,MD simulations,drug designing and ADME analysis

CB2 receptor belongs to the family of G-protein coupled receptors (GPCRs), which extensively controls a range of pointer transduction. CB2 plays an essential role in the immune system. It also associates in the pathology of different ailment conditions. In this scenario, the synthetic drugs are inducing side effects to the human beings after the drug use. Therefore, this study is seeking novel alternate drug molecules with least side effects than conventional drugs. The alternative drug molecules were chosen from the natural sources. These molecules were selected from cyanobacteria with the help of earlier research findings. The target and ligand molecules were obtained from recognized databases. The bioactive molecules are selected from various cyanobacterial species, which are selected by their biological and pharmacological properties, after, which we incorporated to the crucial findings such as homology modelling, molecular docking, MD simulations along with absorption, distribution, metabolism, and excretion (ADME) analysis. Initially, the homology modelling was performed to frame the target from unknown sequences of CB2, which revealed 44% of similarities and 66% of identities with the A2A receptor. Subsequently, the CB2 protein molecule has docked with already known and prepared bioactive molecules, agonists and antagonist complex. In the present study, the agonists (5) and antagonist (1) were also taken for comparing the results with natural molecules. At the end of the docking analysis, the cyanobacterial molecules and an antagonist TNC-201 are revealed better docking scores with well binding contacts than the agonists. Especially, the usneoidone shows better results than other cyanobacterial molecules, and it is very close docking scores with that of TCN-201. Therefore, the usneoidone has incorporated to MD simulation with Cannabinoid receptors 2 (CB2). In MD simulations, the complex (CB2 and usneoidone) reveals better stability in 30 ns. Based on the computational outcome, we concluded that usneoidone is an effectual and appropriate drug candidate for activating CB2 receptors and it will be serving as a better component for the complications of CB2. Moreover, these computational approaches can be motivated to discover novel drug candidates in the pharmacological and healthcare sectors.     

FIPSDock: A new molecular docking technique driven by fully informed swarm optimization algorithm

The accurate prediction of protein–ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein–ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross‐docking experiments of 74 protein–ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland‐crossdock‐set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross‐docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm‐based algorithms in dealing with highly flexible docking problems. © 2012 Wiley Periodicals, Inc.     

Discovery of potentially biased agonists of mu-opioid receptor (MOR) through molecular docking,pharmacophore modeling,and MD simulation

Opioids are well known for their potent analgesic efficacy and severe side effects. Studies have shown that analgesic effects are mediated by the downstream G-protein-dependent pathway of the μ-opioid receptor (MOR), and another β-arrestin-dependent pathway mediates side effects such as respiratory depression, constipation and tolerance etc. TRV130 is a biased ligand for G-protein-dependent pathway, which has high analgesia and has fewer side effects than morphine. In this study, the structure similarity search was performed on the IBSSC database using Oliceridine (TRV130) and PZM21 as templates. The 3D structure-based pharmacophore model was built and combined molecular docking prediction mode was selected to filter out small molecules, Finally, based on affinity prediction, four candidate molecules were obtained. Molecular dynamics simulations explored the detailed interaction mechanism of proteins with small molecules under dynamics. These results suggest that these candidate molecules are potential MOR agonists.     

A molecular docking and dynamics study to screen phytochemicals that target mutant thymidine phosphorylase for colon cancer therapy

Thymidine phosphorylase (TYPH) is an enzyme involved in pyrimidine catabolism and its mutation is associated with chemoresistance of colon cancer to 5-fluorouracil (5-FU) treatment. Here we have analysed the most destabilized mutation of TYPH protein at glycosyltransferase domain where isoleucine alter to alanine at position 214(I214A) that linked to the onset of colon cancer. This study aims to conduct virtual screening of phytochemicals to find novel compounds against mutated TYPH protein. The in silico study aimed to predict the physicochemical properties of phytochemicals and their binding performance with mutated TYPH compared to 5-FU. From the screened phytochemicals, berbamine showed the best binding affinity (?7.2 kcal/mol) with mutant TYPH protein as compared to 5-FU. For further confirmations, the dynamics properties of native, mutant, and docked complex of I214A mutant with berbamine systems were studied through molecular dynamics simulations with a trajectory of 100ns. From root mean square fluctuation, radius of gyration, number of hydrogen bonds, principal component analysis, and free energy landscape, we predicted that the I214A mutant lost its compactness, however, on complex formation with berbamine it gained its compactness. MM/PBSA and molecular docking studies confirmed that berbamine could show potential inhibitory effects against the mutant model of TYPH. Our finding may open the door for its experimental validation and may take as a potential therapeutic against colon cancer treatment in near future.     

Exploring the potential of fluoro-flavonoid derivatives as anti-lung cancer agents: DFT,molecular docking,and molecular dynamics techniques

The present investigation utilized in silico methodologies to explore the diverse pharmacological activities, toxicity profiles, and chemical reactivity of a series of fluoro-flavonoid compounds ( 1 – 14 ), which are secondary metabolites of plants known for their broad range of biological effects. A comprehensive strategy is utilized, incorporating methods such as prediction of activity spectra for substances (PASS) prediction, absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessments, and density functional theory (B3LYP) calculations using three basis sets: 6-31G(d,p), 6-311G(d,p), and 6-311++G(d,p). Furthermore, the study employed molecular docking technique to identify target proteins, including HER2 (7JXH), EGFR (4UV7), FPPS (1YQ7), HPGDS (1V40), DCK (1P60), and KEAP1 on Nrf2 (1X2J), for the investigated compounds, with cianidanol and genistein serving as reference drugs for the docking process. The investigated fluoro-flavonoid compounds exhibited significantly greater binding affinities (ranging from −8.3 to −10.6 kcal mol⁻¹) toward HER2, HPGDS, and KEAP1 compared to the reference drugs, cianidanol and genistein, which displayed binding affinities ranging from −8.4 to −9.4 kcal mol⁻¹. Furthermore, molecular dynamics simulations were conducted to assess the stability of the protein-ligand interaction, using the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), Radius of gyration (Rg) parameters and principle component analysis (PCA). Among the tested fluoro-flavonoid analogs, analog 11 showed a RMSD value of .15 nm with the HER2 protein target, indicating a stable interaction. Based on in silico results, it appears that the fluoro-flavonoid compound 11 has the potential to serve as a targeted anti-lung cancer drug. However, additional in vivo and in vitro studies are necessary to confirm this hypothesis.     

Response surface methodology in drug design: A case study on docking analysis of a potent antifungal fluconazole

Molecular docking is a valuable in silico technique for discovery/design of bioactive compounds. A current challenge within docking simulations is the incorporation of receptor flexibility. A useful strategy toward solving such problem would be the docking of a typical ligand into the multiple conformations of the target. In this study, a multifactor response surface model was constructed to estimate the AutoDock based binding free energy of fluconazole within multiple conformations of 14α-demethylase (CYP51) (cross docking) as a validated antifungal target. On the basis of developed models, individual and interactive effects of important experimental parameters on cross docking of fluconazole were elucidated. For this purpose, a set of high-resolution holo crystallographic structures from CYP51 of human pathogen Trypanosoma cruzi were retrieved to statistically model the binding mode and affinity of fluconazole. The changes of AutoDock binding free energy for the complexes of CYP51-fluconazole were elucidated with the simultaneous variations of six independent variables including grid size, grid spacing, number of genetic algorithm (GA) runs, maximum number of energy evaluations, torsion degrees for ligand and quaternion degrees for ligand. It was revealed that grid spacing (distance between adjacent grid points) and maximum number of energy evaluations were two significant model terms. It was also revealed that grid size, torsion degrees for ligand and quaternion degrees for ligand had insignificant effects on estimated binding energy while the effect of GA runs was non-significant. The interactive effect of “torsion degrees for ligand” with number of GA runs was found to be the significant factor. Other important interactive effects were the interaction of “number of GA runs” with “grid spacing” and “number of energy evaluations” with “grid size”. Furthermore; results of modeling studies within several CYP51 conformations exhibited that “number of GA runs” and “number of energy evaluations” were less sensitive to varied target conformations.     

Combining molecular docking and molecular dynamics studies for modelling Staphylococcus aureus MurD inhibitory activity

The ATP-dependent bacterial MurD enzyme catalyses the formation of the peptide bond between cytoplasmic intermediate UDP-N-acetylmuramoyl-L-alanine and D-glutamic acid. This is essential for bacterial cell wall peptidoglycan synthesis in both Gram-positive and Gram-negative bacteria. MurD is recognized as an important target for the development of new antibacterial agents. In the present study we prepared the 3D-stucture of the catalytic pocket of the Staphylococcus aureus MurD enzyme by homology modelling. Extra-precision docking, binding free energy calculation by the MM–GBSA approach and a 40 ns molecular dynamics (MD) simulation of 2-thioxothiazolidin-4-one based inhibitor $1 was carried out to elucidate its inhibition potential for the S. aureus MurD enzyme. Molecular docking results showed that Lys19, Gly147, Tyr148, Lys328, Thr330 and Phe431 residues are responsible for the inhibitor–protein complex stabilization. Binding free energy calculation revealed electrostatic solvation and van der Waals energy components as major contributors for the inhibitor binding. The inhibitor-modelled S. aureus protein complex had a stable conformation in response to the atomic flexibility and interaction, when subjected to MD simulation at 40 ns in aqueous solution. We designed some molecules as potent inhibitors of S. aureus MurD, and to validate the stability of the designed molecule D1-modelled protein complex we performed a 20 ns MD simulation. Results obtained from this study can be utilized for the design of potent S. aureus MurD inhibitors.     

Synthesis and molecular docking study of novel COVID-19 inhibitors

In 2020, the world tried to combat the corona virus (COVID-19) pandemic. A proven treatment method specific to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is still not found. In this study, seven new antiviral compounds were designed for COVID-19 treatment. The ability of these compounds to inhibit COVID-19’s RNA processing was calculated by the molecular docking study. It has been observed that the compounds can have high binding affinities especially against NSP12 (between -9.06 and -8.00 kcal/mol). The molecular dynamics simulation of NSP12-ZG 7 complex proved the stability of interaction. The synthesis of two most active molecules was performed by one-pot reaction and characterized by FT-IR, ¹H-NMR, ¹³C-NMR, and mass spectroscopy. The compounds presented with their synthesis are inhibitory core structures against SARS-CoV-2 infection.     

FWAVina: A novel optimization algorithm for protein-ligand docking based on the fireworks algorithm

Protein-ligand docking is an essential process that has accelerated drug discovery. How to accurately and effectively optimize the predominant position and orientation of ligands in the binding pocket of a target protein is a major challenge. This paper proposed a novel ligand binding pose search method called FWAVina based on the fireworks algorithm, which combined the fireworks algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon local search method adopted in AutoDock Vina to address the pose search problem in docking. The FWA was used as a global optimizer to rapidly search promising poses, and the Broyden-Fletcher-Goldfarb-Shannon method was incorporated into FWAVina to perform an exact local search. FWAVina was developed and tested on the PDBbind and DUD-E datasets. The docking performance of FWAVina was compared with the original Vina program. The results showed that FWAVina achieves a remarkable execution time reduction of more than 50 % than Vina without compromising the prediction accuracies in the docking and virtual screening experiments. In addition, the increase in the number of ligand rotatable bonds has almost no effect on the efficiency of FWAVina. The higher accuracy, faster convergence and improved stability make the FWAVina method a better choice of docking tool for computer-aided drug design. The source code is available at https://github.com/eddyblue/FWAVina/.     

1,2,3-Triazole tethered acetophenones: Synthesis,bioevaluation and molecular docking study

A small focused library of eighteen new 1,2,3-triazole tethered acetophenones has been efficiently prepared via click chemistry approach and evaluated for their antifungal and antioxidant activity. The antifungal activity was evaluated against five human pathogenic fungal strains: Candida albicans, Fusarium oxysporum, Aspergillus flavus, Aspergillus niger, and Cryptococcus neoformans. Among the synthesized compounds, 9c, 9i, and 9p found to be more potent antifungal agents that the reference standard. These 1,2,3-triazole based derivatives were also evaluated for antioxidant activity, and compound 9h was found to be the most potent antioxidant as compared to the standard drug. Furthermore, molecular docking study of the newly synthesized compounds was performed and results showed good binding mode in the active site of fungal C. albicans enzyme P450 cytochrome lanosterol 14a-demethylase. Moreover, the synthesized compounds were also analyzed for ADME properties and showed potential as good oral drug candidates.     

Macrophage-Targeted Punicalagin Nanoengineering to Alleviate Methotrexate-Induced Neutropenia: A Molecular Docking,DFT, and MD Simulation Analysis

Punicalagin is the most bioactive pomegranate polyphenol with high antioxidant and free-radical scavenging activity and can potentially cure different ailments related to the cardiovascular system. The current research work was envisioned to predict the targeting efficiency of punicalagin (PG) nanoparticles to the macrophages, more specifically to bone marrow macrophages. For this, we selected mannose-decorated PLGA-punicalagin nanoparticles (Mn-PLGA-PG), and before formulating this nanocarrier in laboratory settings, we predicted the targeting efficiency of this nanocarrier by in silico analysis. The analysis proceeded with macrophage mannose receptors to be acquainted with the binding affinity and punicalagin-based nanocarrier interactions with this receptor. In silico docking studies of macrophage mannose receptors and punicalagin showed binding interactions on its surface. PG interacted with hydrogen bonds to the charged residue ASP668 and GLY666 and polar residue GLN760 of the Mn receptor. Mannose with a docking score of −5.811 Kcal/mol interacted with four hydrogen bonds and the mannose receptor of macrophage, and in PLGA, it showed a −4.334 Kcal/mol docking score. Further, the analysis proceeded with density functional theory analysis (DFT) and HOMO–LUMO analysis, followed by an extensive 100 ns molecular dynamics simulation to analyse the trajectories showing the slightest deviation and fluctuation. While analysing the ligand and protein interaction, a wonderful interaction was found among the atoms of the ligand and protein residues. This computational study confirms that this nanocarrier could be a promising lead molecule to regulate the incidence of drug-induced neutropenia. Furthermore, experimental validation is required before this can be stated with complete confidence or before human use.     

Grid‐based molecular footprint comparison method for docking and de novo design: Application to HIVgp41

Scoring functions are a critically important component of computer‐aided screening methods for the identification of lead compounds during early stages of drug discovery. Here, we present a new multigrid implementation of the footprint similarity (FPS) scoring function that was recently developed in our laboratory which has proven useful for identification of compounds which bind to a protein on a per‐residue basis in a way that resembles a known reference. The grid‐based FPS method is much faster than its Cartesian‐space counterpart, which makes it computationally tractable for on‐the‐fly docking, virtual screening, or de novo design. In this work, we establish that: (i) relatively few grids can be used to accurately approximate Cartesian space footprint similarity, (ii) the method yields improved success over the standard DOCK energy function for pose identification across a large test set of experimental co‐crystal structures, for crossdocking, and for database enrichment, and (iii) grid‐based FPS scoring can be used to tailor construction of new molecules to have specific properties, as demonstrated in a series of test cases targeting the viral protein HIVgp41. The method is available in the program DOCK6. © 2013 Wiley Periodicals, Inc.     

A structure-activity relationship study of catechol-O-methyltransferase inhibitors combining molecular docking and 3D QSAR methods

A panel of 92 catechol-O-methyltransferase (COMT) inhibitors was used to examine the molecular interactions affecting their biological activity. COMT inhibitors are used as therapeutic agents in the treatment of Parkinson's disease, but there are limitations in the currently marketed compounds due to adverse side effects. This study combined molecular docking methods with three-dimensional structure-activity relationships (3D QSAR) to analyse possible interactions between COMT and its inhibitors, and to incite the design of new inhibitors. Comparative molecular field analysis (CoMFA) and GRID/GOLPE models were made by using bioactive conformations from docking experiments, which yielded q2 values of 0.594 and 0.636, respectively. The docking results, the COMT X-ray structure, and the 3D QSAR models are in agreement with each other. The models suggest that an interaction between the inhibitor's catechol oxygens and the Mg2+ ion in the COMT active site is important. Both hydrogen bonding with Lys144, Asn170 and Glu199, and hydrophobic contacts with Trp38, Pro174 and Leu198 influence inhibitor binding. Docking suggests that a large R1 substituent of the catechol ring can form hydrophobic contacts with side chains of Val173, Leu198, Met201 and Val203 on the COMT surface. Our models propose that increasing steric volume of e.g. the diethylamine tail of entacapone is favourable for COMT inhibitory activity.     

DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases

In this paper we describe the search strategies developed for docking flexible molecules to macomolecular sites that are incorporated into the widely distributed DOCK software, version 4.0. The search strategies include incremental construction and random conformation search and utilize the existing Coulombic and Lennard-Jones grid-based scoring function. The incremental construction strategy is tested with a panel of 15 crystallographic testcases, created from 12 unique complexes whose ligands vary in size and flexibility. For all testcases, at least one docked position is generated within 2 Å of the crystallographic position. For 7 of 15 testcases, the top scoring position is also within 2 Å of the crystallographic position. The algorithm is fast enough to successfully dock a few testcases within seconds and most within 100 s. The incremental construction and the random search strategy are evaluated as database docking techniques with a database of 51 molecules docked to two of the crystallographic testcases. Incremental construction outperforms random search and is fast enough to reliably rank the database of compounds within 15 s per molecule on an SGI R10000 cpu.     

Fluorescence quenching and molecular docking study on the binding of four hydroxyanthraquinones to FTO

In this work, the binding of four hydroxyanthraquinones (HAQs) to fat mass and obesity-associated (FTO) protein has been studied using fluorescence, UV-vis absorption and circular dichroism spectroscopy as well as molecular docking analysis. Analysis of fluorescence data showed that the binding of HAQs to FTO occurred via a static quenching mechanism. Thermodynamic analysis and molecular docking results suggested that hydrophobic force played a major role in stabilising the HAQ-FTO complex. Circular dichroism spectra indicated that the secondary structure of FTO was changed by the addition of HAQs. Results also showed that emodin had the strongest quenching and binding ability among four HAQs.     

A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme

COVID-19 has affected millions of people. Although many drugs are in use to combat disease, there is not any sufficient treatment yet. Having critical role in propagation of the novel coronavirus (SARS-CoV-2) works Main Protease up into a significant drug target. We have performed a molecular docking study to define possible inhibitor candidates against SARS-CoV-2 Main Protease enzyme. Besides docking Remdesivir, Ribavirin, Chloroquine and 28 other antiviral inhibitors (totally 31 inhibitors) to Main Protease enzyme, we have also performed a molecular docking study of 2177 ligands, which are used against Main Protease for the first time by using molecular docking program Autodock4. All ligands were successfully docked into Main Protease enzyme binding site. Among all ligands, EY16 coded ligand which previously used as EBNA1-DNA binding blocker candidate showed the best score for Main Protease with a binding free energy of −10.83 ​kcal/mol which was also lower than re-docking score of N3 ligand (−10.72 ​kcal/mol) contained in crystal structure of Main Protease. After analyzing the docking modes and docking scores we have found that our ligands have better binding free energy values than the inhibitors in use of treatment. We believe that further studies such as molecular dynamics or Molecular Mechanic Poisson Boltzmann Surface Area studies can make contribution that is more exhaustive to the docking results.     

A novel urea derivative anticonvulsant: In vivo biological evaluation,radioreceptor analysis of GABAA receptors and molecular docking studies of enantiomers

It has been experimentally established that the original new generation anticonvulsant Galodif, N-[(3-chlorophenyl)-(phenyl)methyl]urea, allosterically modulates GABA_A receptor (GABA_AR). Binding of [³H]flunitrazepam and [³H]Ro5-4864 to the benzodiazepine (BZD) site of GABA_AR in the brain of Galodif-treated rats showes an increase in receptor affinity in Scatchard Plot for Ligand Receptor binding analysis. The results of molecular docking (Schrödinger program Glide) reveal that the enantiomers of Galodif are complementary to the BZD binding site of GABA_AR; binding energy of R-Galodif is lower than that of S-Galodif (scoring GScore being –11.14 and –10.7 kcal mol^–1, respectively); R-Galodif interacts with key amino acids at the α1γ2 interface: Tyr159, Tyr209, H101 Phe77 with high model fit – dG of insert: 7.41.     

Aspects of the mechanism of catalysis of glucose oxidase: A docking, molecular mechanics and quantum chemical study

The complex structure of glucose oxidase (GOX) with the substrate glucose was determined using a docking algorithm and subsequent molecular dynamics simulations. Semiempirical quantum chemical calculations were used to investigate the role of the enzyme and FAD co-enzyme in the catalytic oxidation of glucose. On the basis of a small active site model, substrate binding residues were determined and heats of formation were computed for the enzyme substrate complex and different potential products of the reductive half reaction. The influence of the protein environment on the active site model was estimated with a point charge model using a mixed QM/MM method. Solvent effects were estimated with a continuum model. Possible modes of action are presented in relation to experimental data and discussed with respect to related enzymes. The calculations indicate that the redox reaction of GOX differs from the corresponding reaction of free flavins as a consequence of the protein environment. One of the active site histidines is involved in substrate binding and stabilization of potential intermediates, whereas the second histidine is a proton acceptor. The former one, being conserved in a series of oxidoreductases, is also involved in the stabilization of a C4a-hydroperoxy dihydroflavin in the course of the oxidative half reaction.