Molecular docking is the most frequently used computational method for studying the interactions between organic molecules and biological macromolecules. In this context, docking allows predicting ...the preferred pose of a ligand inside a receptor binding site. However, the selection of the “best” solution is not a trivial task, despite the widely accepted selection criterion that the best pose corresponds to the best energy score. Here, several rigid-target docking methods were evaluated on the same dataset with respect to their ability to reproduce crystallographic binding orientations, to test if the best energy score is a reliable criterion for selecting the best solution. For this, two experiments were performed: (A) to reconstruct the ligand-receptor complex by performing docking of the ligand in its own crystal structure receptor (defined as self-docking), and (B) to reconstruct the ligand-receptor complex by performing docking of the ligand in a crystal structure receptor that contains other ligand (defined as cross-docking). Root-mean square deviation (RMSD) was used to evaluate how different the obtained docking orientation is from the corresponding co-crystallized pose of the same ligand molecule. We found that docking score function is capable of predicting crystallographic binding orientations, but the best ranked solution according to the docking energy is not always the pose that reproduces the experimental binding orientation. This happened when self-docking was achieved, but it was critical in cross-docking. Taking into account that docking is typically used with predictive purposes, during cross-docking experiments, our results indicate that the best energy score is not a reliable criterion to select the best solution in common docking applications. It is strongly recommended to choose the best docking solution according to the scoring function along with additional structural criteria described for analogue ligands to assure the selection of a correct docking solution.
Drug efficiency can be considerably boosted while adverse effects can be reduced by precisely monitoring the concentration of anti-cancer drugs. Thus, one of the most important parameters for human ...health is the monitoring and detection of anticancer drugs during chemotherapy treatment. Herein, a glassy carbon electrode (GCE) was modified by Pt- and Pd-incorporated ZnO nanoparticles-decorated single-wall carbon nanotubes (Pt–Pd–ZnO/SWCNTs) nanocomposites, and ds-DNA (Calf Thymus) that was a biological recognition element, and it was aimed to be utilized as an ultrasensitive and effective electroanalytical biosensor for idarubicin (IDR) monitoring. Various physicochemical characterization techniques including transmission electron microscopy (TEM), field-emission scanning electron microscopy (FE-SEM) with energy-dispersive X-ray spectroscopy (EDS) were used to investigate the morphology and structure of the Pt–Pd–ZnO/SWCNTs nanocomposite, which was produced via straightforward chemical precipitation combined with the one-pot method. The layer-by-layer modification technique was implemented to fabricate the ds-DNA/Pt–Pd–ZnO/SWCNTs/GCE to be further utilized as a voltammetric sensor for sensitive monitoring of idarubicin in biological fluids and pharmaceutical substances. The electroanalytical method implemented to detect idarubicin was based to detect the ds-DNA's guanine base signal on the surface of the modified electrode in the absence and presence of the anticancer drug. The results explicated that the developed biosensor performed well in determining idarubicin in concentrations ranging from 1.0 nM to 65 μM, with a detection limit of 0.8 nM. The idarubicin detection ability of the modified electrode in real samples was evaluated, and the recovery data was acquired in the range of 98.0% and 104.75%. In the final step, the preferential intercalative binding mode of idarubicin drug with ds-DNA was approved by molecular docking study. This study paves the way for engineering highly sensitive DNA biosensors to be employed in the monitoring of anticancer drugs by combining the benefits of nanocomposites and valuable information of a molecular docking study.
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•A novel DNA-based electrochemical biosensor was fabricated for sensing of idarubicin.•ds-DNA/Pt–Pd–ZnO/SWCNTs/GCE offered remarkable sensing activity for idarubicin.•The preferential intercalative binding mode was approved by molecular docking study.
Spike glycoprotein, a class I fusion protein harboring the surface of SARS-CoV-2 (SARS-CoV-2S), plays a seminal role in the viral infection starting from recognition of the host cell surface ...receptor, attachment to the fusion of the viral envelope with the host cells. Spike glycoprotein engages host Angiotensin-converting enzyme 2 (ACE2) receptors for entry into host cells, where the receptor recognition and attachment of spike glycoprotein to the ACE2 receptors is a prerequisite step and key determinant of the host cell and tissue tropism. Binding of spike glycoprotein to the ACE2 receptor triggers a cascade of structural transitions, including transition from a metastable pre-fusion to a post-fusion form, thereby allowing membrane fusion and internalization of the virus. From ancient times people have relied on naturally occurring substances like phytochemicals to fight against diseases and infection. Among these phytochemicals, flavonoids and non-flavonoids have been the active sources of different anti-microbial agents. We performed molecular docking studies using 10 potential naturally occurring compounds (flavonoids/non-flavonoids) against the SARS-CoV-2 spike protein and compared their affinity with an FDA approved repurposed drug hydroxychloroquine (HCQ). Further, our molecular dynamics (MD) simulation and energy landscape studies with fisetin, quercetin, and kamferol revealed that these molecules bind with the hACE2-S complex with low binding free energy. The study provided an indication that these molecules might have the potential to perturb the binding of hACE2-S complex. In addition, ADME analysis also suggested that these molecules consist of drug-likeness property, which may be further explored as anti-SARS-CoV-2 agents.
Communicated by Ramaswamy H. Sarma
•The article describes the synthesis, characterization, molecular docking, and quantum computational studies of the novel compound.•Hirshfeld surface analysis, molecular electrostatic potential, ...molecular docking are studied in detail.•DFT calculations are performed to optimize the molecular geometry.•HOMO, LUMO frontier molecular orbitals are analyzed.•The compound was investigated as an inhibitor for SARS CoV-2 protease using in-silico molecular docking analysis.
The novel series of hydrazones carrying both pyrazole and triazole moiety were synthesized and characterized using single crystal X-ray diffraction studies. It is found that the compound crystallizes in the triclinic system in the space group P1̅. Hirshfeld analysis was carried out to visualize the noncovalent intermolecular interactions which are responsible for molecular packing in the crystal. Further, density functional theory (DFT) calculations were used to calculate optimized molecular structure, stability, and a few of the quantum chemical parameters. Derived results are in good agreement with the experimentally obtained results. Analysis of frontier molecular orbitals (HOMO and LUMO) and their energy gap of the optimized structure revealed that the compound is stable in the gaseous state. Molecular electron densities, and electrostatic potential maps provide the reactive site and charge distribution of triazole group. Quantum theory of atoms in molecules (QTAIM) and reduced density gradient (RDG) analysis were carried out to explore the weak interactions present in the molecule. In addition, the synthesized compound was investigated as an inhibitor for SARS CoV-2 protease using in-silico molecular docking analysis to understand the mode of binding. The docking results showed the good binding score with Mpro protease 6LU7. Further, molecular dynamics (MD) were carried out for the best hit docked complexes.
The main protease of SARS-CoV-2 is one of the important targets to design and develop antiviral drugs. In this study, we have selected 40 antiviral phytochemicals to find out the best candidates ...which can act as potent inhibitors against the main protease. Molecular docking is performed using AutoDock Vina and GOLD suite to determine the binding affinities and interactions between the phytochemicals and the main protease. The selected candidates strongly interact with the key Cys145 and His41 residues. To validate the docking interactions, 100 ns molecular dynamics (MD) simulations on the five top-ranked inhibitors including hypericin, cyanidin 3-glucoside, baicalin, glabridin, and α-ketoamide-11r are performed. Principal component analysis (PCA) on the MD simulation discloses that baicalin, cyanidin 3-glucoside, and α-ketoamide-11r have structural similarity with the apo-form of the main protease. These findings are also strongly supported by root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), and solvent accessible surface area (SASA) investigations. PCA is also used to find out the quantitative structure-activity relationship (QSAR) for pattern recognition of the best ligands. Multiple linear regression (MLR) of QSAR reveals the R
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value of 0.842 for the training set and 0.753 for the test set. Our proposed MLR model can predict the favorable binding energy compared with the binding energy detected from molecular docking. ADMET analysis demonstrates that these candidates appear to be safer inhibitors. Our comprehensive computational and statistical analysis show that these selected phytochemicals can be used as potential inhibitors against the SARS-CoV-2.
Communicated by Ramaswamy H. Sarma
As a marine antifouling biocide, 4,5-dichloro-2-n-octyl-4-isothiazolin-3-one (DCOIT) exhibited high toxicity to marine organisms. This study investigated the interaction between DCOIT and human serum ...albumin (HSA) using several spectroscopic techniques combined with computer prediction methods. The UV–vis absorption spectra, Stern-Volmer constant (KSV) and fluorescence resonance energy transfer (FRET) results indicated that DCOIT caused static quenching of HSA fluorescence. The ΔG°, ΔH° and ΔS° values were −31.03 ± 0.17 kJ·mol−1, −133.54 ± 0.88 kJ·mol−1 and −348.46 ± 2.86 J.mol−1·K−1, respectively, suggesting that van der Waals forces and hydrogen bonds governed the spontaneous formation of the complex. Synchronous fluorescence and circular dichroism (CD) spectroscopy observed the burial of Trp residues within HSA and the unfolding of HSA secondary structure induced by DCOIT. Three-dimensional (3D) fluorescence and Atomic Force Microscopy (AFM) further detected DCOIT-induced loosening of HSA peptide chain structure. Site displacement experiments indicated that DCOIT binding at site I of HSA. Computational predictions indicated that hydrophobic interactions were also essential in the complex. The increased RMSD, Rg, SASA, and RMSF confirmed that DCOIT weakened the stability and compactness of HSA, rendering residues more flexible. Lastly, esterase activity assays demonstrated that DCOIT inhibited esterase activity and interfered with the human detoxification process.
A new human coronavirus (HCoV), which has been designated SARS-CoV-2, began spreading in December 2019 in Wuhan City, China causing pneumonia called COVID-19. The spread of SARS-CoV-2 has been faster ...than any other coronaviruses that have succeeded in crossing the animal-human barrier. There is concern that this new virus will spread around the world as did the previous two HCoVs—Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS)—each of which caused approximately 800 deaths in the years 2002 and 2012, respectively. Thus far, 11,268 deaths have been reported from the 258,842 confirmed infections in 168 countries.
In this study, the RNA-dependent RNA polymerase (RdRp) of the newly emerged coronavirus is modeled, validated, and then targeted using different anti-polymerase drugs currently on the market that have been approved for use against various viruses.
The results suggest the effectiveness of Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir as potent drugs against SARS-CoV-2 since they tightly bind to its RdRp. In addition, the results suggest guanosine derivative (IDX-184), Setrobuvir, and YAK as top seeds for antiviral treatments with high potential to fight the SARS-CoV-2 strain specifically.
The availability of FDA-approved anti-RdRp drugs can help treat patients and reduce the danger of the mysterious new viral infection COVID-19. The drugs mentioned above can tightly bind to the RdRp of the SARS-CoV-2 strain and thus may be used to treat the disease. No toxicity measurements are required for these drugs since they were previously tested prior to their approval by the FDA.
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•SARS-CoV-2 RdRp shares 97% sequence identity to SARS.•SARS-CoV-2 RdRp model is built to study different inhibitors.•Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir can bind tightly the RdRp of SARS-CoV-2.•Setrobuvir, YAK, and IDX-184 can be used as potent compounds against SARS-CoV-2 RdRp.
Toll-like receptor 4 (TLR4), a member of the Toll-like receptor (TLR) family, is involved in innate immunity and mediates inflammatory responses by recognizing lipopolysaccharide (LPS) or bacterial ...endotoxins. Hyperactivation of TLR4 triggers the production of various inflammatory factors, which are associated with the development of a variety of diseases, such as sepsis, endotoxemia, acute lung injury, rheumatoid arthritis, and cardiovascular diseases. And anti-inflammatory potential of TLR4 inhibitors have been validated. In this review, we discuss TLR4 inhibitors that can bind directly to TLR4 or the TLR4/MD2 complex, and provide a brief introduction to compounds that can downregulate the expression of TLR4. We focused on the possible modes by which the TLR4 inhibitors bind to the TLR4 or TLR4/MD2 complex. Three compounds targeting TLR4 have entered clinical trials, but unfortunately, two of them have been discontinued due to poor efficacy. Therefore, the discovery of effective small molecular compounds is the main research focus for TLR4 inhibitor design. In this review, by summarizing results from molecular dynamics simulation and molecular docking, we found that the Arg241 residue of TLR4 and the Tyr102, Ser120, and Lys122 residues of MD2 are involved in the binding of antagonistic ligands to the TLR4/MD2 complex; this is useful information for structure-based TLR4 inhibitor design.
Toll-like receptor 4 (TLR4) could mediate inflammatory response by triggering the production of various proinflammatorymediators, which are associated with sepsis, endotoxemia, acute lung injury, rheumatoid arthritis and cardiovascular diseases. In this review, we will discuss TLR4 inhibitors which can bind directly to TLR4 or TLR4/MD2 complex. We will focus on the possible binding modes of TLR4 inhibitors with TLR4 or TLR4/MD2 complex. Display omitted
•TLR4 inhibitors binding directly to TLR4 or TLR4/MD2 complex will be discussed.•A brief introduction of compounds downregulating the expression of TLR4.•Focusing on the binding modes of TLR4 inhibitors with TLR4 or TLR4/MD2 complex.
With the recent explosion of chemical libraries beyond a billion molecules, more efficient virtual screening approaches are needed. The Deep Docking (DD) platform enables up to 100-fold acceleration ...of structure-based virtual screening by docking only a subset of a chemical library, iteratively synchronized with a ligand-based prediction of the remaining docking scores. This method results in hundreds- to thousands-fold virtual hit enrichment (without significant loss of potential drug candidates) and hence enables the screening of billion molecule-sized chemical libraries without using extraordinary computational resources. Herein, we present and discuss the generalized DD protocol that has been proven successful in various computer-aided drug discovery (CADD) campaigns and can be applied in conjunction with any conventional docking program. The protocol encompasses eight consecutive stages: molecular library preparation, receptor preparation, random sampling of a library, ligand preparation, molecular docking, model training, model inference and the residual docking. The standard DD workflow enables iterative application of stages 3-7 with continuous augmentation of the training set, and the number of such iterations can be adjusted by the user. A predefined recall value allows for control of the percentage of top-scoring molecules that are retained by DD and can be adjusted to control the library size reduction. The procedure takes 1-2 weeks (depending on the available resources) and can be completely automated on computing clusters managed by job schedulers. This open-source protocol, at https://github.com/jamesgleave/DD_protocol , can be readily deployed by CADD researchers and can significantly accelerate the effective exploration of ultra-large portions of a chemical space.
Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The ...development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.
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