Methods of protein structure comparison

Computational assessment of chemicals from Morinda citrifolia as potential inhibitors of B-Raf kinase in hepatocellular carcinoma treatment

Hepatocellular carcinoma (HCC) is a tumour pathology that lacks specific treatment and is predominantly resistant to chemotherapy. The inhibitory activity of Morinda citrifolia, an evergreen tree commonly called Noni, against various carcinomas especially HCC is widely acclaimed. This study was to assess the phytochemical constituents of the plant for inhibitory activity against B-Raf kinase (3C4C) in order to design drugs for HCC treatment. Molecular docking, pharmacophore modelling, induced-fit docking, molecular dynamics (MD) simulations and ADMET predictions were the computational techniques employed in this study to detect potential inhibitors of B-Raf kinase from 135 compounds of Morinda citrifolia. Soranjidiol, Thiamine, Lucidin, 2-Methyl-1,3,5-Trihydroxyanthraquinone and Rubiadin were the five top-scoring compounds ranging from -8.39 to -8.22 kcal/mol, however, the standard ligand, PLX4720, scored -11.26 kcal/mol. The five compounds, like PLX4720 demonstrated hydrogen bond interactions with active site amino acid residues such as GLN 530, CYS 532 and ASP 594. The main energy contributor to the interactions between the compounds and B-Raf kinase were pi-stacking, hydrogen bond, van der Waals and covalent energy. Better docking scores obtained in the induced-fit docking further validates the inhibitory potential of the Soranjidiol against the flexible protein. In MD simulations, Soranjidiol revealed good stability in the active site of the protein since significant conformational changes were not evident. These five compounds, unlike the standard compound, demonstrated adequate druglike properties and good safety profiles. Therefore, further studies should be undertaken so as to develop them into drugs against HCC.Communicated by Ramaswamy H. Sarma.

Holanamine, a Steroidal Alkaloid from the Bark of Holarrhena pubescens Wall. ex G. Don Inhibits the Growth of Leishmania donovani by Targeting DNA Topoisomerase 1B

Leishmaniasis is a group of neglected tropical diseases (NTDs) caused by about 20 species of obligate intracellular protozoan parasites of the genus Leishmania, which occurs in cutaneous, mucocutaneous, and visceral forms. Many researchers have sought to utilize natural products for novel and effective treatments to combat many infectious diseases, including leishmaniasis. Holarrhena pubescens Wall. ex G. Don (Apocynaceae) bark is a rich source of bioactive steroidal alkaloids. The total alkaloidal extract (IC₅₀ 6.12 ± 0.117 μg/mL), and the isolated alkaloid, holanamine, showed significant antileishmanial activity (IC₅₀ 2.66 ± 0.112 μM against AG83 and 3.80 ± 0.126 μM against BHU-575) against the Leishmania donovani parasite, better than miltefosine (IC₅₀ 19.61 ± 0.093 μM against AG83 and 23.20 ± 0.094 μM against BHU-575). Holanamine inhibited the L. donovani topoisomerase 1B (LdToP1B) in a non-competitive manner (IC₅₀ 2.81 ± 0.105 μM), indicating that it interacts with the free enzyme and enzyme-DNA complex without inhibiting human topoisomerase. Hydrogen bonding and hydrophobic interactions of holanamine with the N-terminal and hinge region of the large subunit of LTop1B is responsible for its potent antileishmanial activity, as shown by docking studies. Treatment with holanamine causes apoptotic-like cell death by generating cellular and mitochondrial reactive oxygen species, disrupting the mitochondrial membrane potential and inducing ultrastructural alterations in the promastigotes. Holanamine effectively clears intracellular amastigotes but minimally affects host macrophages with no significant cytotoxicity in HEK 293 and L929 cell lines. Thus, our studies show that holanamine can further be used to develop effective antileishmanial agents against evolving drug-resistant parasites.

AlteQ: a new complementarity principle-centered method for the evaluation of docking poses

Molecular docking is the most popular and widely used method for identifying novel molecules against a target of interest. However, docking procedures and their validation are still under intense development. In the present investigation, we evaluate a quantum free-orbital AlteQ method for evaluating docking complexes generated by taking EGFR complexes as an example. The AlteQ method calculates the electron density using Slater's type atomic contributions in the interspace between the receptor and the ligand. Since the interactions are determined by the overlap of electron clouds, they follow the complementarity principle, and an equation can be obtained that describes these interactions. The AlteQ method evaluates the quality of the interaction between the receptor and the ligand, how complementary the interactions are, and due to this, it is used to reject less realistic structures obtained by docking methods. Here, three different equations were used to determine the quality of the interactions in experimental complexes and docked complexes obtained using AutoDock Vina and AutoDock 4.2.6.Communicated by Ramaswamy H. Sarma.

Structure-Based Identification of Natural-Product-Derived Compounds with Potential to Inhibit HIV-1 Entry

Broadly neutralizing antibodies (bNAbs) are potent in neutralizing a wide range of HIV strains. VRC01 is a CD4-binding-site (CD4-bs) class of bNAbs that binds to the conserved CD4-binding region of HIV-1 envelope (env) protein. Natural products that mimic VRC01 bNAbs by interacting with the conserved CD4-binding regions may serve as a new generation of HIV-1 entry inhibitors by being broadly reactive and potently neutralizing. This study aimed to identify compounds that mimic VRC01 by interacting with the CD4-bs of HIV-1 gp120 and thereby inhibiting viral entry into target cells. Libraries of purchasable natural products were virtually screened against clade A/E recombinant 93TH057 (PDB: 3NGB) and clade B (PDB ID: 3J70) HIV-1 env protein. Protein-ligand interaction profiling from molecular docking and dynamics simulations showed that the compounds had intermolecular hydrogen and hydrophobic interactions with conserved amino acid residues on the CD4-binding site of recombinant clade A/E and clade B HIV-1 gp120. Four potential lead compounds, NP-005114, NP-008297, NP-007422, and NP-007382, were used for cell-based antiviral infectivity inhibition assay using clade B (HXB2) env pseudotype virus (PV). The four compounds inhibited the entry of HIV HXB2 pseudotype viruses into target cells at 50% inhibitory concentrations (IC₅₀) of 15.2 µM (9.7 µg/mL), 10.1 µM (7.5 µg/mL), 16.2 µM (12.7 µg/mL), and 21.6 µM (12.9 µg/mL), respectively. The interaction of these compounds with critical residues of the CD4-binding site of more than one clade of HIV gp120 and inhibition of HIV-1 entry into the target cell demonstrate the possibility of a new class of HIV entry inhibitors.

Design, synthesis, anti-acetylcholinesterase evaluation and molecular modelling studies of novel coumarin-chalcone hybrids

The major enzyme responsible for the hydrolytic breakdown of the neurotransmitter acetylcholine (ACh) is acetylcholinesterase (AChE). Acetylcholinesterase inhibitors (AChEIs) are the most prescribed class of medications for the treatment of Alzheimer's disease (AD) and dementia. The limitations of available therapy, like side effects, drug tolerance, and inefficacy in halting disease progression, drive the need for better, more efficacious, and safer drugs. In this study, a series of fourteen novel chalcone-coumarin derivatives (8a-n) were designed, synthesized and characterized by spectral techniques like FT-IR, NMR, and HR-MS. Subsequently, the synthesized compounds were tested for their ability to inhibit acetylcholinesterase (AChE) activity by Ellman's method. All tested compounds showed AChE inhibition with IC50 value ranging from 0.201 ± 0.008 to 1.047 ± 0.043 μM. Hybrid 8d having chloro substitution on ring-B of the chalcone scaffold showed relatively better potency, with IC50 value of 0.201 ± 0.008 μM compared to other members of the series. The reference drug, galantamine, exhibited an IC50 at 1.142 ± 0.027 μM. Computational studies revealed that designed compounds bind to the peripheral anionic site (PAS), the catalytic active site (CAS), and the mid-gorge site of AChE. Putative binding modes, ligand-enzyme interactions, and stability of the best active compound are studied using molecular docking, followed by molecular dynamics (MD) simulations. The cytotoxicity of the synthesised derivatives was determined using the MTT test at three concentrations (100 g/mL, 500 g/mL, and 1 mg/mL). None of the chemicals had a significant effect on the body at the highest dose of 1 mg/mL.Communicated by Ramaswamy H. Sarma.

Probe-Free Identification of RNA Virus Variants with Point Mutations by Surface-Enhanced Raman Spectroscopy

As observed in the COVID-19 pandemic, RNA viruses continue to rapidly evolve through mutations. In the absence of effective therapeutics, early detection of new severely pathogenic viruses and quarantine of infected people are critical for reducing the spread of the viral infections. However, conventional detection methods require a substantial amount of time to develop probes specific to new viruses, thereby impeding immediate response to the emergence of viral pathogens. In this study, we identified multiple types of viruses by obtaining the spectral fingerprint of their surface proteins with probe-free surface-enhanced Raman scattering (SERS). In addition, the SERS-based method can remarkably distinguish influenza virus variants with several surface protein point mutations from their parental strain. Principal component analysis (PCA) of the SERS spectra systematically captured the key Raman bands to distinguish the variants. Our results show that the combination of SERS and PCA can be a promising tool for rapid detection of newly emerging mutant viruses without a virus-specific probe.

Deep generative modeling for volume reconstruction in cryo-electron microscopy

Advances in cryo-electron microscopy (cryo-EM) for high-resolution imaging of biomolecules in solution have provided new challenges and opportunities for algorithm development for 3D reconstruction. Next-generation volume reconstruction algorithms that combine generative modelling with end-to-end unsupervised deep learning techniques have shown promise, but many technical and theoretical hurdles remain, especially when applied to experimental cryo-EM images. In light of the proliferation of such methods, we propose here a critical review of recent advances in the field of deep generative modelling for cryo-EM reconstruction. The present review aims to (i) provide a unified statistical framework using terminology familiar to machine learning researchers with no specific background in cryo-EM, (ii) review the current methods in this framework, and (iii) outline outstanding bottlenecks and avenues for improvements in the field.

In silico prediction suggests inhibitory effect of halogenated boroxine on human catalase and carbonic anhydrase

Background

This research work included bioinformatics modeling of the dipotassium-trioxohydroxytetrafluorotriborate-halogenated boroxine molecule, as well as simulation and prediction of structural interactions between the halogenated boroxine molecule, human carbonic anhydrase, and human catalase structures. Using computational methods, we tried to confirm the inhibitory effect of halogenated boroxine on the active sites of these previously mentioned enzymes. The three-dimensional crystal structures of human catalase (PDB ID: 1DGB) and human carbonic anhydrase (PDB ID: 6FE2) were retrieved from RCSB Protein Data Bank and the protein preparation was performed using AutoDock Tools. ACD/ChemSketch and ChemDoodle were used for creating the three-dimensional structure of halogenated boroxine. Molecular docking was performed using AutoDock Vina, while the results were visualized using PyMOL.

Results

Results obtained in this research are showing evidence that there are interactions between the halogenated boroxine molecule and both previously mentioned proteins (human carbonic anhydrase and human catalase) in their active sites, which led us to the conclusion that the inhibitory function of halogenated boroxine has been confirmed.

Conclusion

These findings could be an important step in determining the exact mechanisms of inhibitory activity and will hopefully serve in further research purposes of complex pharmacogenomics studies.

Molecular Dynamics Simulations to Decipher the Role of Phosphorylation of SARS-CoV-2 Nonstructural Proteins (nsps) in Viral Replication

Protein phosphorylation is a post-translational modification that enables various cellular activities and plays essential roles in protein interactions. Phosphorylation is an important process for the replication of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To shed more light on the effects of phosphorylation, we used an ensemble of neural networks to predict potential kinases that might phosphorylate SARS-CoV-2 nonstructural proteins (nsps) and molecular dynamics (MD) simulations to investigate the effects of phosphorylation on nsps structure, which could be a potential inhibitory target to attenuate viral replication. Eight target candidate sites were found as top-ranked phosphorylation sites of SARS-CoV-2. During the process of molecular dynamics (MD) simulation, the root-mean-square deviation (RMSD) analysis was used to measure conformational changes in each nsps. Root-mean-square fluctuation (RMSF) was employed to measure the fluctuation in each residue of 36 systems considered, allowing us to evaluate the most flexible regions. These analysis shows that there are significant structural deviations in the residues namely nsp1 THR 72, nsp2 THR 73, nsp3 SER 64, nsp4 SER 81, nsp4 SER 455, nsp5 SER284, nsp6 THR 238, and nsp16 SER 132. The identified list of residues suggests how phosphorylation affects SARS-CoV-2 nsps function and stability. This research also suggests that kinase inhibitors could be a possible component for evaluating drug binding studies, which are crucial in therapeutic discovery research.

Molecular engineering and activity improvement of acetylcholinesterase inhibitors: Insights from 3D-QSAR, docking, and molecular dynamics simulation studies

The carbamate molecule rivastigmine was found to possess promising anti-acetylcholinesterase activity, enabling to target and occupy choline binding sites, and as a result, widely used to improve the treatment of Alzheimer's disease (AD). Higher dose of rivastigmine indicates rapid onset but more adverse effects, such as the large fluctuations in plasma concentration level and frequent incidence of gastrointestinal side effect. To solve the dilemma, we developed a three-dimensional quantitative structure-activity relationship (3D-QSAR), docking and molecular dynamics (MD) simulation strategy to construct a dismountable nanoplatform of inhibitor engineering, verification and application for improving the inhibitory activity per unit concentration. With the aid of 3D-QSAR method, we constructed a model by using 25 molecules reported, and verified well the rationality of these QSAR models by non-cross validation coefficient (r² = 0.902). Docking and MD results show that rivastigmine, as a control, does target exactly the binding sites of acetylcholinesterase, those already observed experimentally, in turn, confirming the reliability of the present 3D-QSAR results. The method suggests that groups with electron-donating chemical property can improve the inhibitory activity, and screens out two novel inhibitors L-1 and L-2 with more activity from database (about 8000 compounds). Moreover, L-1 and L-2 not only target exactly the same binding sites of acetylcholinesterase as the rivastigmine does, but also hold stronger binding energy, showing a more powerful inhibitory ability. More broadly, this work showcases an approach in the engineering of carbamate inhibitors to enhance their inhibitory activity using electron-donating groups, which simplifies the design process of complex bioactive molecules.

Comparative Studies of Palmatine with Metformin and Glimepiride on the Modulation of Insulin Dependent Signaling Pathway In Vitro, In Vivo & Ex Vivo

(1) Insulin resistance, a symptom of type 2 diabetes mellitus (T2DM), is caused by the inactivation of the insulin signaling pathway, which includes IRS-PI3K-IRS-1-PKC-AKT2 and GLUT4. Metformin (biguanide) and glimepiride (sulfonylurea) are both drugs that are derivatives of urea, and they are widely used as first-line drugs for the treatment of type 2 diabetes mellitus. Palmatine has been previously reported to possess antidiabetic and antioxidant properties. (2) The current study compared palmatine to metformin and glimepiride in a type 2 diabetes model for ADME and insulin resistance via the PI3K/Akt/GLUT4 signaling pathway: in vitro, in vivo, ex vivo, and in silico molecular docking. (3) Methods: Differentiated L6 skeletal muscle cells and soleus muscle tissue were incubated in standard tissue culture media supplemented with high insulin and high glucose as a cellular model of insulin resistance, whilst streptozotocin (STZ)-induced Sprague Dawley rats were used as the diabetic model. The cells/tissue/animals were treated with palmatine, while glimepiride and metformin were used as standard drugs. The differential gene expression of PI3K, IRS-1, PKC-α, AKT2, and GLUT4 was evaluated using qPCR. (4) Results: The results revealed that the genes IRS-PI3K-IRS-1-PKC-AKT2 were significantly down-regulated, whilst PKC-α was upregulated significantly in both insulin-resistant cells and tissue animals. Interestingly, palmatine-treated cells/tissue/animals were able to reverse these effects. (5) Conclusions: Palmatine appears to have rejuvenated the impaired insulin signaling pathway through upregulation of the gene expression of IRS-1, PI3K, AKT2, and GLUT4 and downregulation of PKC-expression, according to in vitro, in vivo, and ex vivo studies.

Bio-Computational Evaluation of Compounds of Bacopa Monnieri as a Potential Treatment for Schizophrenia

Schizophrenia is a horrible mental disorder characterized by distorted perceptions of reality. Investigations have not identified a single etiology for schizophrenia, and there are multiple hypotheses based on various aspects of the disease. There is no specific treatment for schizophrenia. Hence, we have tried to investigate the updated information stored in the genetic databases related to genes that could be responsible for schizophrenia and other related neuronal disorders. After implementing combined computational methodology, such as protein-protein interaction analysis led by system biology approach, in silico docking analysis was performed to explore the 3D binding pattern of Bacopa monnieri natural compounds while interacting with STXBP1. The best-identified compound was CID:5319292 based on −10.3 kcal/mol binding energy. Further, selected complexes were dynamically evaluated by MDS methods, and the output reveals that the STXBP1-CID:5281800 complex showed the lowest RMSD value, i.e., between 0.3 and 0.4 nm. Hence, identified compounds could be used to develop and treat neuronal disorders after in vivo/in vitro testing.

PacDOCK: A Web Server for Positional Distance-Based and Interaction-Based Analysis of Docking Results

Molecular docking is a key method for structure-based drug design used to predict the conformations assumed by small drug-like ligands when bound to their target. However, the evaluation of molecular docking studies can be hampered by the lack of a free and easy to use platform for the complete analysis of results obtained by the principal docking programs. To this aim, we developed PacDOCK, a freely available and user-friendly web server that comprises a collection of tools for positional distance-based and interaction-based analysis of docking results, which can be provided in several file formats. PacDOCK allows a complete analysis of molecular docking results through root mean square deviation (RMSD) calculation, molecular visualization, and cluster analysis of docked poses. The RMSD calculation compares docked structures with a reference structure, also when atoms are randomly labelled, and their conformational and positional differences can be visualised. In addition, it is possible to visualise a ligand into the target binding pocket and investigate the key receptor–ligand interactions. Moreover, PacDOCK enables the clustering of docking results by identifying a restrained number of clusters from many docked poses. We believe that PacDOCK will contribute to facilitating the analysis of docking results to improve the efficiency of computer-aided drug design.

Identification of doxorubicin as a potential therapeutic against SARS-CoV-2 (COVID-19) protease: a molecular docking and dynamics simulation studies

After one year, the COVID-19 pandemic caused by SARS-CoV-2 is still the largest concern for the scientific community. Of the many recognized drug targets of SARS-CoV-2, the main protease is one of the most important target due to its function in viral replication. We conducted an in silico study with repurposing drugs of antibiotics class against virus protease and peptidase using AutoDock tool. The following significant binding energy interaction was observed with protease (PDB: 6LU7) like piperacillin -7.25; tobramycin -9.20 and doxorubicin (Doxo) -10.04 kcal/mol and with peptidase (PDB: 2GTB) piperacillin -7.08; tobramycin -8.54 and Doxo -9.89 kcal/mol. Furthermore, the interaction and stability behavior of the Doxo-protease and Doxo-peptidase complexes were analyzed for a 100-nanosecond (ns) time. Calculated RMSD values observed using molecular dynamics simulation (MDS) were found to be 0.15-0.25 nm, RMSF calculation per residues showed a value near 0.2 nm and Rg values remained approximately 2.25 nm. MM-PBSA analysis of total binding energy calculation of Doxo-protease and Doxo-peptidase complexes are found to be -148.692 and -105.367 kJ/mol, respectively. Moreover, amino acid residue ASP-197 showed the lowest contribution binding energy i.e. -18.1185 kJ/mol, and amino acid residue ASP-187 showed -17.0267 kJ/mol contribution energy. Thus, significant docking interaction and stable dynamicity of Doxo-protease complex with time was suggested that Doxo could be a choice to inhibit potentially the viral proteases that could prevent the entry inside the host cell to control the COVID-19 disease. Communicated by Ramaswamy H. Sarma.

Combined nanometric and phylogenetic analysis of unique endocytic compartments in Giardia lamblia sheds light on the evolution of endocytosis in Metamonada

Background

Giardia lamblia, a parasitic protist of the Metamonada supergroup, has evolved one of the most diverged endocytic compartment systems investigated so far. Peripheral endocytic compartments, currently known as peripheral vesicles or vacuoles (PVs), perform bulk uptake of fluid phase material which is then digested and sorted either to the cell cytosol or back to the extracellular space.

Results

Here, we present a quantitative morphological characterization of these organelles using volumetric electron microscopy and super-resolution microscopy (SRM). We defined a morphological classification for the heterogenous population of PVs and performed a comparative analysis of PVs and endosome-like organelles in representatives of phylogenetically related taxa, Spironucleus spp. and Tritrichomonas foetus. To investigate the as-yet insufficiently understood connection between PVs and clathrin assemblies in G. lamblia, we further performed an in-depth search for two key elements of the endocytic machinery, clathrin heavy chain (CHC) and clathrin light chain (CLC), across different lineages in Metamonada. Our data point to the loss of a bona fide CLC in the last Fornicata common ancestor (LFCA) with the emergence of a protein analogous to CLC (GlACLC) in the Giardia genus. Finally, the location of clathrin in the various compartments was quantified.

Conclusions

Taken together, this provides the first comprehensive nanometric view of Giardia’s endocytic system architecture and sheds light on the evolution of GlACLC analogues in the Fornicata supergroup and, specific to Giardia, as a possible adaptation to the formation and maintenance of stable clathrin assemblies at PVs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01402-3.

Multiprotein Inhibitory Effect of Dietary Polyphenol Rutin from Whole Green Jackfruit Flour Targeting Different Stages of Diabetes Mellitus: Defining a Bio-Computational Stratagem

The anti-diabetic potential of whole unripe jackfruit (peel with pulp, flake, and seed) was investigated using inhibitory assays for α-glucosidase, α-amylase, aldose reductase, and glycation at multiple stages. Using activity-guided repeated fractionation on a silica gel column chromatography, dietary flavonoid rutin with potent antihyperglycemic activity was extracted from the methanol extract of whole jackfruit flour (MJ). Rutin was found to inhibit both α-glucosidase (IC50: 7.86 µg/mL) and α-amylase (IC50: 22.00 µg/mL) in a competitive manner of inhibition with low Ki values. In addition, in vitro glycation experiments revealed that rutin prevented each stage of protein glycation as well as the production of intermediate molecules. Furthermore, rutin significantly inhibited aldose reductase (IC50: 2.75 µg/mL) in a non-competitive manner. During in silico studies, molecular docking and molecular dynamics simulation studies have suggested that rutin has a high binding affinity for the enzymes studied, which could explain its inhibitory effects. Rutin interacted with the key residues of the target enzymes’ inhibitor binding sites. Compared to the controls used, rutin had a higher binding efficiency as well as stability in the inhibitor binding pocket of the target enzymes. According to our findings, the presence of rutin is more likely to be associated with the potential of MJ in antihyperglycemic activity via inhibition of α-glucosidase and in anti-diabetic action via inhibition of the polyol pathway and protein glycation. The bio-computational study indicates rutin as a potential lead inhibitor of all the target enzymes used and could be used as an effective anti-diabetic drug in the near future.

Iterative Landmark-Based Umbrella Sampling (ILBUS) Protocol for Sampling of Conformational Space of Biomolecules

Computer simulations of biomolecules such as molecular dynamics often suffer from insufficient sampling. Due to limited computational resources, insufficient sampling prevents obtaining proper equilibrium distributions of observed properties. To deal with this problem, we proposed a simulation protocol for efficient resampling of collected off-equilibrium trajectories. These trajectories are utilized for the initial mapping of the conformational space, which is later properly resampled by the introduced Iterative Landmark-Based Umbrella Sampling (ILBUS) method. Reconstruction of static equilibrium properties is achieved by the multistate Bennett acceptance ratio (MBAR) method, which enables efficient use of simulated data. The ILBUS protocol is geometry-based and does not demand any additional collective variable or a dimensional-reduction technique. The only requirement is a set of suitably spaced reference conformations, which serve as landmarks in the mapped conformational space. Additionally, the ILBUS protocol encompasses an iterative process that optimizes the force constant used in the umbrella sampling simulation. Such tuning is an inherent feature of the protocol and does not need to be performed by the user in advance. Furthermore, even the simulations with suboptimal force constants can be used in estimates by MBAR. We demonstrate the feasibility and the performance of this approach in the study of the conformational landscape of the alanine dipeptide, met-enkephalin, and adenylate kinase.

Multispectral and Molecular Docking Studies Reveal Potential Effectiveness of Antidepressant Fluoxetine by Forming π-Acceptor Complexes

Poor mood, lack of pleasure, reduced focus, remorse, unpleasant thoughts, and sleep difficulties are all symptoms of depression. The only approved treatment for children and adolescents with major depressive disorder (MDD) is fluoxetine hydrochloride (FXN), a serotonin selective reuptake inhibitor antidepressant. MDD is the most common cause of disability worldwide. In the present research, picric acid (PA); dinitrobenzene; p-nitro benzoic acid; 2,6-dichloroquinone-4-chloroimide; 2,6-dibromoquinone-4-chloroimide; and 7,7′,8,8′-tetracyanoquinodimethane were used to make 1:1 FXN charge-transfer compounds in solid and liquid forms. The isolated complexes were then characterized by elemental analysis, conductivity, infrared, Raman, and ¹H-NMR spectra, thermogravimetric analysis, scanning electron microscopy, and X-ray powder diffraction. Additionally, a molecular docking investigation was conducted on the donor moiety using FXN alone and the resulting charge transfer complex [(FXN)(PA)] as an acceptor to examine the interactions against two protein receptors (serotonin or dopamine). Interestingly, the [(FXN)(PA)] complex binds to both serotonin and dopamine more effectively than the FXN drug alone. Furthermore, [(FXN)(PA)]–serotonin had a greater binding energy than [FXN]–serotonin. Theoretical data were also generated by density functional theory simulations, which aided the molecular geometry investigation and could be beneficial to researchers in the future.

Pharmacoinformatic study of inhibitory potentials of selected flavonoids against papain-like protease and 3-chymotrypsin-like protease of SARS-CoV-2

Background

Inhibition of papain-like protease (PLpro) and 3-chymotrypsin-like protease (3CLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is projected to terminate its replication. Hence, these proteases represent viable therapeutic targets.

Methods

Sixty-one flavonoids with reported activities against other RNA viruses were selected and docked in PLpro and 3CLpro. Flavonoids with better binding energies compared to reference inhibitors (lopinavir and ritonavir) in their interaction with PLpro and 3CLpro were selected for drug-likeness and ADMET analysis. The best representative flavonoid for each protease from the ADMET filtering analysis was subjected to molecular dynamics simulations (MDS) and clustering analysis of the trajectory files.

Results

Licorice, ugonin M, procyanidin, silymarin, and gallocatechin gallate had better binding energies (-11.8, -10.1, -9.8, -9.7 and -9.6 kcal/mol respectively) with PLpro compared to lopinavir and ritonavir (-9.1 and -8.5 kcal/mol respectively). Also, isonymphaeol B, baicalin, abyssinone II, tomentin A, and apigetrin had better binding energies (-8.7, -8.3, -8.2, -8.1, and -8.1 kcal/mol respectively) with 3CLpro compared to lopinavir and ritonavir (-7.3 and -7.1 kcal/mol respectively). These flavonoids interacted with the proteases via hydrogen and non-hydrogen bonding. Of these flavonoids, silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics in silico. These two flavonoids exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run.

Conclusion

Silymarin and isonymphaeol B are proposed for further studies as compounds with potential activities against SARS-CoV-2.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40816-022-00347-y.

• Flavonoids displayed varying affinities for PLpro and 3CLpro of SARS-CoV-2

• They interacted via hydrogen and non-hydrogen bonds; nine and twenty-seven flavonoids had better binding affinities for PLpro and 3CLpro respectively than lopinavir and ritonavir

• Silymarin and isonymphaeol B demonstrated most favourable combination of attributes in terms of binding energies, compliance with Lipinski rule for drug-likeness and favourable pharmacokinetics.

• Silymarin and isonymphaeol B exhibited appreciable degree of structural stability, maintaining strong interaction with residues in the different representative clusters selected during the MDS run.

Attempting to Increase the Effectiveness of the Antidepressant Trazodone Hydrochloride Drug Using π-Acceptors

Major depressive disorder is a prevalent mood illness that is mildly heritable. Cases with the highest familial risk had recurrence and onset at a young age. Trazodone hydrochloride is an antidepressant medicine that affects the chemical messengers in the brain known as neurotransmitters, which include acetylcholine, norepinephrine, dopamine, and serotonin. In the present research, in solid and liquid phases, the 1:1 charge-transfer complexes between trazodone hydrochloride (TZD) and six different π-acceptors were synthesized and investigated using different microscopic techniques. The relation of dative ion pairs [TZD+, A-], where A is the acceptor, was inferred via intermolecular charge-transfer complexes. Additionally, a molecular docking examination was utilized to compare the interactions of protein receptors (serotonin-6BQH) with the TZD alone or in combination with the six distinct acceptor charge-transfer complexes. To refine the docking results acquired from AutoDock Vina and to better examine the molecular mechanisms of receptor-ligand interactions, a 100 ns run of molecular dynamics simulation was used. All the results obtained in this study prove that the 2,6-dichloroquinone-4-chloroimide (DCQ)/TZD complex interacts with serotonin receptors more efficiently than reactant donor TZD only and that [(TZD)(DCQ)]-serotonin has the highest binding energy value of all π-acceptor complexes.

Identification of New Drug Target in Staphylococcus lugdunensis by Subtractive Genomics Analysis and Their Inhibitors through Molecular Docking and Molecular Dynamic Simulation Studies

Staphylococcus lugdunensis is a coagulase-negative, Gram-positive, and human pathogenic bacteria. S. lugdunensis is the causative agent of diseases, such as native and prosthetic valve endocarditis, meningitis, septic arthritis, skin abscesses, brain abscess, breast abscesses, spondylodiscitis, post-surgical wound infections, bacteremia, and peritonitis. S. lugdunensis displays resistance to beta-lactam antibiotics due to the production of beta-lactamases. This study aimed to identify potential novel essential, human non-homologous, and non-gut flora drug targets in the S. lugdunensis strain N920143, and to evaluate the potential inhibitors of drug targets. The method was concerned with a homology search between the host and the pathogen proteome. Various tools, including the DEG (database of essential genes) for the essentiality of proteins, the KEGG for pathways analysis, CELLO V.2.5 for cellular localization prediction, and the drug bank database for predicting the druggability potential of proteins, were used. Furthermore, a similarity search with gut flora proteins was performed. A DNA-binding response-regulator protein was identified as a novel drug target against the N920143 strain of S. lugdunensis. The three-dimensional structure of the drug target was modelled and validated with the help of online tools. Furthermore, ten thousand drug-like compounds were retrieved from the ZINC15 database. The molecular docking approach for the DNA-binding response-regulator protein identified ZINC000020192004 and ZINC000020530348 as the most favorable compounds to interact with the active site residues of the drug target. These two compounds were subjected to an MD simulation study. Our analysis revealed that the identified compounds revealed more stable behavior when bound to the drug target DNA-binding response-regulator protein than the apostate.

Early Stages of Misfolding of PAP248-286 at two different pH values: An Insight from Molecular Dynamics Simulations

PAP248-286 peptides, which are highly abundant in human semen, aggregate and form amyloid fibrils that enhance HIV infection. Previous experimental studies have shown that the infection-promoting activity of PAP248-286 begins to increase well before amyloid formation takes place and that pH plays a key role in the enhancement of PAP248-286-related infection. Hence, understanding the early stages of misfolding of the PAP2482-86 peptide is crucial. To this end, we have performed 60 independent MD simulations for a total of 24 µs at two different pH values (4.2 and 7.2). Our data shows that early stages of misfolding of the PAP248-286 peptide is a multistage process and that the first step of the process is a transition from an “I-shaped” structure to a “U-shaped” structure. We further observed that the structure of PAP248-286 at the two different pH values shows significantly different features. At pH 4.2, the peptide has less intra-molecular H-bonds and a reduced α-helical content than at pH 7.2. Moreover, differences in intra-peptide residues contacts are also observed at the two pH values. Finally, free energy landscape analysis shows that there are more local minima in the energy surface of the peptide at pH 7.2 than at pH 4.2. Overall, the present study elucidates the early stages of misfolding of the PAP248-286 peptide at the atomic level, thus possibly opening new avenues in structure-based drug discovery against HIV infection.

Cheminformatics Identification of Phenolics as Modulators of Penicillin-Binding Protein 2a of Staphylococcus aureus: A Structure–Activity-Relationship-Based Study

The acquisition of penicillin-binding protein (PBP) 2a in resistant strains of Staphylococcus aureus allows for the continuous production of cell walls even after the inactivation of intrinsic PBPs. Thus, the discovery of novel therapeutics with enhanced modulatory activity on PBP2a is crucial, and plant secondary metabolites, such as phenolics, have found relevance in this regard. In this study, using computational techniques, phenolics were screened against the active site of PBP2a, and the ability of the lead phenolics to modulate PBP2a’s active and allosteric sites was studied. The top-five phenolics (leads) identified through structure–activity-based screening, pharmacokinetics and synthetic feasibility evaluations were subjected to molecular dynamics simulations. Except for propan-2-one at the active site, the leads had a higher binding free energy at both the active and allosteric sites of PBP2a than amoxicillin. The leads, while promoting the thermodynamic stability of PBP2a, showed a more promising affinity at the allosteric site than the active site, with silicristin (−25.61 kcal/mol) and epicatechin gallate (−47.65 kcal/mol) having the best affinity at the active and allosteric sites, respectively. Interestingly, the modulation of Tyr446, the active site gatekeeper residue in PBP2a, was noted to correlate with the affinity of the leads at the allosteric site. Overall, these observations point to the leads’ ability to inhibit PBP2a, either directly or through allosteric modulation with conventional drugs. Further confirmatory in vitro studies on the leads are underway.

Evaluation of immune evasion in SARS-CoV-2 Delta and Omicron variants

Emerging SARS-CoV-2 variants with higher transmissibility and immune escape remain a persistent threat across the globe. This is evident from the recent outbreaks of the Delta (B.1.617.2) and Omicron variants. These variants have originated from different continents and spread across the globe. In this study, we explored the genomic and structural basis of these variants for their lineage defining mutations of the spike protein through computational analysis, protein modeling, and molecular dynamic (MD) simulations. We further experimentally validated the importance of these deletion mutants for their immune escape using a pseudovirus-based neutralization assay, and an antibody (4A8) that binds directly to the spike protein's NTD. Delta variant with the deletion and mutations in the NTD revealed a better rigidity and reduced flexibility as compared to the wild-type spike protein (Wuhan isolate). Furthermore, computational studies of 4A8 monoclonal antibody (mAb) revealed a reduced binding of Delta variant compared to the wild-type strain. Similarly, the MD simulation data and virus neutralization assays revealed that the Omicron also exhibits immune escape, as antigenic beta-sheets appear to be disrupted. The results of the present study demonstrate the higher possibility of immune escape and thereby achieved better fitness advantages by the Delta and Omicron variants, which warrants further demonstrations through experimental evidences. Our study, based on in-silico computational modelling, simulations, and pseudovirus-based neutralization assay, highlighted and identified the probable mechanism through which the Delta and Omicron variants are more pathogenically evolved with higher transmissibility as compared to the wild-type strain.

Functional Characterization of Recombinant Endo-Levanase (LevBk) from Bacillus koreensis HL12 on Short-Chain Levan-Type Fructooligosaccharides Production

Levan-type fructooligosaccharides (L-FOSs) are a prominent class of non-digestible oligosaccharides with potential as nutritional prebiotics. Endo-levanase, which randomly hydrolyzes β-(2,6)-linkages in fructans, is a promising enzyme for short-chain FOS production. In this work, a recombinant levanase (LevBk) from Bacillus koreensis strain HL12 was characterized. Soluble LevBk protein was produced in Escherichia coli BL21(DE3) system at 40 mg/L of culture medium. Based on sequence and structural analysis, LevBk was classified as a member of endo-levanase in GH32 family containing N-terminal substrate binding pocket and C-terminal β-sandwich domains. LevBk optimally worked at 45 °C, pH 6.0 with the specific activity of 2.43 U/mg. Based on enzymatic hydrolysis, short-chain L-FOSs with degree of polymerization (DP) of 2-4 were produced from hydrolysis of timothy grass levan under optimal conditions for 9-24 h. With its ability to produce L-FOSs with specific chain lengths, LevBk could be attractively applied for converting of levan containing material to high value-added sweetener in the biorefinery industry.

The Flexible, Extended Coil of the PDZ-Binding Motif of the Three Deadly Human Coronavirus E Proteins Plays a Role in Pathogenicity

The less virulent human (h) coronaviruses (CoVs) 229E, NL63, OC43, and HKU1 cause mild, self-limiting respiratory tract infections, while the more virulent SARS-CoV-1, MERS-CoV, and SARS-CoV-2 have caused severe outbreaks. The CoV envelope (E) protein, an important contributor to the pathogenesis of severe hCoV infections, may provide insight into this disparate severity of the disease. We, therefore, generated full-length E protein models for SARS-CoV-1 and -2, MERS-CoV, HCoV-229E, and HCoV-NL63 and docked C-terminal peptides of each model to the PDZ domain of the human PALS1 protein. The PDZ-binding motif (PBM) of the SARS-CoV-1 and -2 and MERS-CoV models adopted a more flexible, extended coil, while the HCoV-229E and HCoV-NL63 models adopted a less flexible alpha helix. All the E peptides docked to PALS1 occupied the same binding site and the more virulent hCoV E peptides generally interacted more stably with PALS1 than the less virulent ones. We hypothesize that the increased flexibility of the PBM in the more virulent hCoVs facilitates more stable binding to various host proteins, thereby contributing to more severe disease. This is the first paper to model full-length 3D structures for both the more virulent and less virulent hCoV E proteins, providing novel insights for possible drug and/or vaccine development.

Insighting the Therapeutic Potential of Fifty (50) Shogaol Derivatives Against Mpro of SARS-CoV-2

SARS-CoV-2, which causes COVID-19 disease, has proven to be a disastrous pandemic due to its contagious nature. This study has been planned to theoretically explore some antidotes against this virus from natural compounds. A total of 150 compounds from the shogaol class and shogaol derivatives (SDs) have been screened whereas 50 among those, which obeyed Lipinski’s Rule of Five (Ro5), have further been investigated using molecular docking techniques. Furthermore, reference antiviral drug chloroquine (ChQ) and Co-Crystallized inhibitor have also been studied against Mpro of SARS-CoV-2 for comparing the potential of our docked ligands. Surprisingly, 78% of our docked ligands have shown binding energies and inhibition constants lower than ChQ and all ligands showed these values lower than an inhibitor. We further visualized the nature of intermolecular interactions for the best docked six ligands, which have shown higher binding affinities. We have also assessed ADMET properties for three ligands that displayed visually the best intermolecular interactions. Quantum analysis of three selected ligands L4, L5, and L9 has proved their reactivity and kinetic stability. Moreover, molecular dynamic simulations over 60[Formula: see text]ns have been run for free Mpro and its selected three ligand-protein complexes for evaluating conformational stability and residual flexibility of docked complexes. Furthermore, 100[Formula: see text]ns the MD simulations have been performed for two ligand complexes L4, L5 (with negative binding free energy), and inhibitor. Available parameters suggest stable complexes for our ligands and could be active drugs against SARS-CoV-2 in near future.

Snowflake: A deep learning-based human leukocyte antigen matching algorithm considering allele-specific surface accessibility

Histocompatibility in solid-organ transplantation has a strong impact on long-term graft survival. Although recent advances in matching of both B-cell epitopes and T-cell epitopes have improved understanding of allorecognition, the immunogenic determinants are still not fully understood. We hypothesized that HLA solvent accessibility is allele-specific, thus supporting refinement of HLA B-cell epitope prediction. We developed a computational pipeline named Snowflake to calculate solvent accessibility of HLA Class I proteins for deposited HLA crystal structures, supplemented by constructed HLA structures through the AlphaFold protein folding predictor and peptide binding predictions of the APE-Gen docking framework. This dataset trained a four-layer long short-term memory bidirectional recurrent neural network, which in turn inferred solvent accessibility of all known HLA Class I proteins. We extracted 676 HLA Class-I experimental structures from the Protein Data Bank and supplemented it by 37 Class-I alleles for which structures were predicted. For each of the predicted structures, 10 known binding peptides as reported by the Immune Epitope DataBase were rendered into the binding groove. Although HLA Class I proteins predominantly are folded similarly, we found higher variation in root mean square difference of solvent accessibility between experimental structures of different HLAs compared to structures with identical amino acid sequence, suggesting HLA’s solvent accessible surface is protein specific. Hence, residues may be surface-accessible on e.g. HLA-A*02:01, but not on HLA-A*01:01. Mapping these data to antibody-verified epitopes as defined by the HLA Epitope Registry reveals patterns of (1) consistently accessible residues, (2) only subsets of an epitope’s residues being consistently accessible and (3) varying surface accessibility of residues of epitopes. Our data suggest B-cell epitope definitions can be refined by considering allele-specific solvent-accessibility, rather than aggregating HLA protein surface maps by HLA class or locus. To support studies on epitope analyses in organ transplantation, the calculation of donor-allele-specific solvent-accessible amino acid mismatches was implemented as a cloud-based web service.

Molecular docking and molecular dynamic simulations of apoptosis proteins with potential anticancer compounds present in Clinacanthus nutans extract using gas chromatography-mass spectrometry

Clinacanthus nutans is a medicinal plant recognised for its anticancer properties. We previously discovered that the C. nutans extract had the most potent inhibitory effect on MCF7 breast cancer cell and significantly induced apoptosis. However, there is a scarcity of studies demonstrating the molecular interactions of C. nutans-derived chemical compounds associated with apoptosis-related proteins. Therefore, the objective of this study was to determine the potential chemical compounds found in the C. nutans extract and examine their interactions with the targeted apoptotic proteins using molecular docking and molecular dynamic simulations. To address this objective, the compounds found in the SF2 extract of C. nutans were analysed using Gas Chromatography-Mass Spectrometry (GC-MS). The molecular interaction of the compounds with the targeted apoptotic proteins were determined using molecular docking and molecular dynamic simulations. GC-MS analysis revealed a total of 32 compounds in the SF2 extract. Molecular docking analysis showed that compound β-amyrenol had the highest binding affinity for MDM2-P53 (-7.26 kcal/mol), BCL2 (-11.14 kcal/mol), MCL1-BAX (-6.42 kcal/mol), MCL1-BID (-6.91 kcal/mol), and caspase-9 (-12.54 kcal/mol), whereas campesterol had the highest binding affinity for caspase-8 (-10.11 kcal/mol) and caspase-3 (-10.14 kcal/mol). These selected compounds were subjected to molecular dynamic simulation at 310 K for 100 ns. The results showed that the selected protein-ligand conformation complexes were stable, compact, and did not alter much when compared to the protein references. The findings indicate that β-amyrenol and campesterol are potentially significant compounds that might provide insight into the molecular interactions of the compounds with the apoptosis-related proteins.Communicated by Ramaswamy H. Sarma.

A ricin-based peptide BRIP from Hordeum vulgare inhibits Mpro of SARS-CoV-2

COVID-19 pandemic caused by SARS-CoV-2 led to the research aiming to find the inhibitors of this virus. Towards this world problem, an attempt was made to identify SARS-CoV-2 main protease (M^pro) inhibitory peptides from ricin domains. The ricin-based peptide from barley (BRIP) was able to inhibit M^pro in vitro with an IC₅₀ of 0.52 nM. Its low and no cytotoxicity upto 50 µM suggested its therapeutic potential against SARS-CoV-2. The most favorable binding site on M^pro was identified by molecular docking and steered molecular dynamics (MD) simulations. The M^pro-BRIP interactions were further investigated by evaluating the trajectories for microsecond timescale MD simulations. The structural parameters of M^pro-BRIP complex were stable, and the presence of oppositely charged surfaces on the binding interface of BRIP and M^pro complex further contributed to the overall stability of the protein-peptide complex. Among the components of thermodynamic binding free energy, Van der Waals and electrostatic contributions were most favorable for complex formation. Our findings provide novel insight into the area of inhibitor development against COVID-19.

Exploring the Binding Interaction of Active Compound of Pineapple against Foodborne Bacteria and Novel Coronavirus (SARS-CoV-2) Based on Molecular Docking and Simulation Studies

Natural resources, particularly plants and microbes, are an excellent source of bioactive molecules. Bromelain, a complex enzyme mixture found in pineapples, has numerous pharmacological applications. In a search for therapeutic molecules, we conducted an in silico study on natural phyto-constituent bromelain, targeting pathogenic bacteria and viral proteases. Docking studies revealed that bromelain strongly bound to food-borne bacterial pathogens and SARS-CoV-2 virus targets, with a high binding energy of −9.37 kcal/mol. The binding interaction was mediated by the involvement of hydrogen bonds, and some hydrophobic interactions stabilized the complex and molecular dynamics. Simulation studies also indicated the stable binding between bromelain and SARS-CoV-2 protease as well as with bacterial targets which are essential for DNA and protein synthesis and are required to maintain the integrity of membranous proteins. From this in silico study, it is also concluded that bromelain could be an effective molecule to control foodborne pathogen toxicity and COVID-19. So, eating pineapple during an infection could help to interfere with the pathogen attaching and help prevent the virus from getting into the host cell. Further, research on the bromelain molecule could be helpful for the management of COVID-19 disease as well as other bacterial-mediated diseases. Thus, the antibacterial and anti-SARS-CoV-2 virus inhibitory potentials of bromelain could be helpful in the management of viral infections and subsequent bacterial infections in COVID-19 patients.

Evaluation of apigenin-based biflavonoid derivatives as potential therapeutic agents against viral protease (3CLpro) of SARS-CoV-2 via molecular docking, molecular dynamics and quantum mechanics studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent of the pandemic COVID-19 disease that affects human respiratory function. Despite the scientific progression made in the development of the vaccine, there is an urgent need for the discovery of antiviral drugs for better performance at different stages of SARS-CoV-2 reproduction. The main protease (Mpro or 3CLpro) plays a pivotal role in the life cycle of the virus, making it an attractive target for the development of antiviral agents effective against the new strains of coronaviruses (CoVs). In this study, a series of apigenin-based natural biflavonoid derivatives as potential inhibitors of coronaviruses 3CLpro was investigated by in silico approaches. For this purpose, the molecular docking was performed to analyze the interaction of the natural biflavonoids with SARS-Cov-2 main protease and for further investigation, docking to the 3CLpro of SARS-CoV and MERS-CoV. Based on docking scores and comparison with the reference inhibitors (ritonavir and lopinavir), more than half of the biflavonoids had strong interactions with the residues of the binding pocket of the coronaviruses 3CLpro and exhibited better binding affinities toward the main protease than ritonavir and lopinavir. The top biflavonoids were further explored through molecular dynamics simulation, binding free energy calculation and residual energy contributions estimated by the MM-PBSA. Also, drug likeness property investigation by Swiss ADME tools and density functional theory (DFT) calculations were performed. The results confirmed that the 3CLpro-amentoflavone, 3CLpro-bilobetin, 3CLpro-ginkgetin, and 3CLpro-sotetsuflavone complexes possess a large amount of dynamic properties such as high stability, significant binding energy and fewer conformation fluctuations. Also, the pharmacokinetics and drug-likeness studies and HOMO-LUMO and DFT descriptor values indicated a promising result of the selected natural biflavonoids. Overall findings indicate that the apigenin-based biflavonoids may inhibit COVID-19 by significant interactions in the binding pocket and those results can pave the way in drug discovery although the effectiveness of these bioactive compounds should be further validated by in-vitro and in-vivo investigations. Communicated by Ramaswamy H. Sarma.

Interaction of Bioactive Compounds of Moringa oleifera Leaves with SARS-CoV-2 Proteins to Combat COVID-19 Pathogenesis: a Phytochemical and In Silico Analysis

Novel SARS-CoV-2 claimed a large number of human lives. The main proteins for viral entry into host cells are SARS-CoV-2 spike glycoprotein (PDB ID: 6VYB) and spike receptor-binding domain bound with ACE2 (spike RBD-ACE2; PDB ID: 6M0J). Currently, specific therapies are lacking globally. This study was designed to investigate the bioactive components from Moringa oleifera leaf (MOL) extract by gas chromatography-mass spectroscopy (GC–MS) and their binding interactions with spike glycoprotein and spike RBD-ACE2 protein through computational analysis. GC–MS-based analysis unveiled the presence of thirty-seven bioactive components in MOL extract, viz. polyphenols, fatty acids, terpenes/triterpenes, phytosterols/steroids, and aliphatic hydrocarbons. These bioactive phytoconstituents showed potential binding with SARS-CoV-2 spike glycoprotein and spike RBD-ACE2 protein through the AutoDock 4.2 tool. Further by using AutoDock 4.2 and AutoDock Vina, the top sixteen hits (binding energy ≥  − 6.0 kcal/mol) were selected, and these might be considered as active biomolecules. Moreover, molecular dynamics simulation was determined by the Desmond module. Interestingly two biomolecules, namely β-tocopherol with spike glycoprotein and β-sitosterol with spike RBD-ACE2, displayed the best interacting complexes and low deviations during 100-ns simulation, implying their strong stability and compactness. Remarkably, both β-tocopherol and β-sitosterol also showed the drug- likeness with no predicted toxicity. In conclusion, these findings suggested that both compounds β-tocopherol and β-sitosterol may be developed as anti-SARS-CoV-2 drugs. The current findings of in silico approach need to be optimized using in vitro and clinical studies to prove the effectiveness of phytomolecules against SARS-CoV-2.

Spectroscopic and Molecular Docking Studies of Cu(II), Ni(II), Co(II), and Mn(II) Complexes with Anticonvulsant Therapeutic Agent Gabapentin

New Cu(II), Ni(II), Co(II), and Mn(II) complexes of the gabapentin (Gpn) bidentate drug ligand were synthesized and studied using elemental analyses, melting temperatures, molar conductivity, UV–Vis, magnetic measurements, FTIR, and surface morphology (scanning (SEM) and transmission (TEM) electron microscopes).The gabapentin ligand was shown to form monobasic metal:ligand (1:1) stoichiometry complexes with the metal ions Cu(II), Ni(II), Co(II), and Mn(II). Molar conductance measurements in dimethyl-sulfoxide solvent with a concentration of 10⁻³ M correlated to a non-electrolytic character for all of the produced complexes. A deformed octahedral environment was proposed for all metal complexes. Through the nitrogen atom of the –NH₂ group and the oxygen atom of the carboxylate group, the Gpn drug chelated as a bidentate ligand toward the Mn²⁺, Co²⁺, Ni²⁺, and Cu²⁺ metal ions. This coordination behavior was validated by spectroscopic, magnetic, and electronic spectra using the formulas of the [M(Gpn)(H₂O)₃(Cl)]·nH₂O complexes (where n = 2–6).Transmission electron microscopy was used to examine the nanostructure of the produced gabapentin complexes. Molecular docking was utilized to investigate the comparative interaction between the Gpn drug and its four metal [Cu(II), Ni(II), Co(II), and Mn(II)] complexes as ligands using serotonin (6BQH) and dopamine (6CM4) receptors. AutoDock Vina results were further refined through molecular dynamics simulation, and molecular processes for receptor–ligand interactions were also studied. The B3LYP level of theory and LanL2DZ basis set was used for DFT (density functional theory) studies. The optimized geometries, along with the MEP map and HOMO → LUMO of the metal complexes, were studied.

Molecular modelling identification of phytocompounds from selected African botanicals as promising therapeutics against druggable human host cell targets of SARS-CoV-2

The coronavirus disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is highly pathogenic and transmissible. It is mediated by the binding of viral spike proteins to human cells via entry and replication processes involving human angiotensin converting enzyme-2 (hACE2), transmembrane serine protease (TMPRSS2) and cathepsin L (Cath L). The identification of novel therapeutics that can modulate viral entry or replication has been of research interest and would be germane in managing COVID-19 subjects. This study investigated the structure-activity relationship inhibitory potential of 99 phytocompounds from selected African botanicals with proven therapeutic benefits against respiratory diseases focusing on SARS-CoV-2's human cell proteins (hACE2, TMPRSS2, and Cathepsin L) as druggable targets using computational methods. Evaluation of the binding energies of the phytocompounds showed that two compounds, Abrusoside A (−63.393 kcal/mol) and Kaempferol-3-O-rutinoside (−58.939 kcal/mol) had stronger affinity for the exopeptidase site of hACE2 compared to the reference drug, MLN-4760 (−54.545 kcal/mol). The study further revealed that Verbascoside (−63.338 kcal/mol), Abrectorin (−37.880 kcal/mol), and Friedelin (−36.989 kcal/mol) are potential inhibitors of TMPRSS2 compared to Nafamostat (−36.186 kcal/mol), while Hemiphloin (−41.425 kcal/mol), Quercetin-3-O-rutinoside (−37.257 kcal/mol), and Myricetin-3-O-galactoside (−36.342 kcal/mol) are potential inhibitors of Cathepsin L relative to Bafilomycin A1 (−38.180 kcal/mol). The structural analysis suggests that these compounds do not compromise the structural integrity of the proteins, but rather stabilized and interacted well with the active site amino acid residues critical to inhibition of the respective proteins. Overall, the findings from this study are suggestive of the structural mechanism of inhibitory action of the identified leads against the proteins critical for SARS-CoV-2 to enter the human host cell. While the study has lent credence to the significant role the compounds could play in developing potent SARS-CoV-2 candidate drugs against COVID-19, further structural refinement, and modifications of the compounds for subsequent in vitro as well as preclinical and clinical evaluations are underway.

Benchmarking the ability of novel compounds to inhibit SARS-CoV-2 main protease using steered molecular dynamics simulations

BACKGROUND

The SARS-CoV-2 main protease (M^pro) is an attractive target in the COVID-19 drug development process. It catalyzes the polyprotein's translation from viral RNA and specifies a particular cleavage site. Due to the absence of identical cleavage specificity in human cell proteases, targeting M^pro with chemical compounds can obstruct the replication of the virus.

METHODS

To explore the potential binding mechanisms of 1,2,3-triazole scaffolds in comparison to co-crystallized inhibitors 11a and 11b towards M^pro, we herein utilized molecular dynamics and enhanced sampling simulation studies.

RESULTS AND CONCLUSION

All the 1,2,3-triazole scaffolds interacted with catalytic residues (Cys145 and His41) and binding pocket residues of M^pro involving Met165, Glu166, Ser144, Gln189, His163, and Met49. Furthermore, the adequate binding free energy and potential mean force of the topmost compound 3h was comparable to the experimental inhibitors 11a and 11b of M^pro. Overall, the current analysis could be beneficial in developing the SARS-CoV-2 M^pro potential inhibitors.

Essential Dynamics Ensemble Docking for Structure-Based GPCR Drug Discovery

The lack of biologically relevant protein structures can hinder rational design of small molecules to target G protein-coupled receptors (GPCRs). While ensemble docking using multiple models of the protein target is a promising technique for structure-based drug discovery, model clustering and selection still need further investigations to achieve both high accuracy and efficiency. In this work, we have developed an original ensemble docking approach, which identifies the most relevant conformations based on the essential dynamics of the protein pocket. This approach is applied to the study of small-molecule antagonists for the PAC1 receptor, a class B GPCR and a regulator of stress. As few as four representative PAC1 models are selected from simulations of a homology model and then used to screen three million compounds from the ZINC database and 23 experimentally validated compounds for PAC1 targeting. Our essential dynamics ensemble docking (EDED) approach can effectively reduce the number of false negatives in virtual screening and improve the accuracy to seek potent compounds. Given the cost and difficulties to determine membrane protein structures for all the relevant states, our methodology can be useful for future discovery of small molecules to target more other GPCRs, either with or without experimental structures.

Insighting isatin derivatives as potential antiviral agents against NSP3 of COVID-19

The world is now facing intolerable damage in all sectors of life because of the deadly COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2. The discovery and development of anti-SARS-CoV-2 drugs have become pragmatic in the time needed to fight against this pandemic. The non-structural protein 3 is essential for the replication of transcriptase complex (RTC) and may be regarded as a possible target against SARS-CoV-2. Here, we have used a comprehensive in silico technique to find potent drug molecules against the NSP3 receptor of SARS-CoV-2. Virtual screening of 150 Isatin derivatives taken from PubChem was performed based on their binding affinity estimated by docking simulations, resulting in the selection of 46 ligands having binding energy greater than -7.1 kcal/mol. Moreover, the molecular interactions of the nine best-docked ligands having a binding energy of ≥ -8.5 kcal/mol were analyzed. The molecular interactions showed that the three ligands (S5, S16, and S42) were stabilized by forming hydrogen bonds and other significant interactions. Molecular dynamic simulations were performed to mimic an in vitro protein-like aqueous environment and to check the stability of the best three ligands and NSP3 complexes in an aqueous environment. The binding energy of the S5, S16, and S42 systems obtained from the molecular mechanics Poisson-Boltzmann surface area also favor the system's stability. The MD and MM/PBSA results explore that S5, S16, and S42 are more stable and can be considered more potent drug candidates against COVID-19 disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11696-022-02298-7.

Cryo-EM structure of a type IV secretion system

Bacterial conjugation is the fundamental process of unidirectional transfer of DNAs, often plasmid DNAs, from a donor cell to a recipient cell¹. It is the primary means by which antibiotic resistance genes spread among bacterial populations^2,3. In Gram-negative bacteria, conjugation is mediated by a large transport apparatus—the conjugative type IV secretion system (T4SS)—produced by the donor cell and embedded in both its outer and inner membranes. The T4SS also elaborates a long extracellular filament—the conjugative pilus—that is essential for DNA transfer^4,5. Here we present a high-resolution cryo-electron microscopy (cryo-EM) structure of a 2.8 megadalton T4SS complex composed of 92 polypeptides representing 8 of the 10 essential T4SS components involved in pilus biogenesis. We added the two remaining components to the structural model using co-evolution analysis of protein interfaces, to enable the reconstitution of the entire system including the pilus. This structure describes the exceptionally large protein–protein interaction network required to assemble the many components that constitute a T4SS and provides insights on the unique mechanism by which they elaborate pili.

Cryo-electron microscopy structures of a 2.8 megadalton bacterial type IV secretion system encoded by the plasmid R388 and comprising 92 polypeptides provide insights into the stepwise mechanism of pilus assembly.

Artificial intelligence channelizing protein-peptide interactions pipeline for host-parasite paradigm in IL-10 and IL-12 reciprocity by SHP-1

Identification of molecular targets in any cellular phenomena is a challenge and a path that one endeavors upon independently. We have identified a phosphatase SHP-1 as a point of intervention of IL-10 and IL-12 reciprocity in leishmaniasis. The therapeutic model that we have developed uniquely targets this protein but the pipeline in general can be used by the researchers for their unique targets. Naturally occurring peptides are well known for their biochemical participation in cellular functions hence we were motivated to use this uniqueness of physico-chemical properties of peptides conferred by amino acids through machine learning to channelize a mode of therapeutic exploration in infectious disease. Using computational approaches, we identified high order sequence conservation and similarity in SHP-1 sequence which was also evolutionarily conserved, complete structure of Mouse SHP-1 was predicted and validated, a unique motif of the same was identified against which library of synthetic peptides were designed and validated followed by screening the library by docking them with MuSHP-1 protein structure. Our findings showed 3 peptides had high binding affinity and in future can be validated using cell based and in vivo assays.

Crystal structure of human acetylcholinesterase in complex with tacrine: Implications for drug discovery

Alzheimer's disease (AD) is one of the most common, progressive neurodegenerative disorders affecting the aged populations. Though various disease pathologies have been suggested for AD, the impairment of the cholinergic system is one of the critical factors for the disease progression. Restoration of the cholinergic transmission through acetylcholinesterase (AChE) inhibitors is a promising disease modifying therapy. Being the first marketed drug for AD, tacrine reversibly inhibits AChE and thereby slows the breakdown of the chemical messenger acetylcholine (ACh) in the brain. However, the atomic level of interactions of tacrine towards human AChE (hAChE) is unknown for years. Hence, in the current study, we report the X-ray structure of hAChE-tacrine complex at 2.85 Å resolution. The conformational heterogeneity of tacrine within the electron density was addressed with the help of molecular mechanics assisted methods and the low-energy ligand configuration is reported, which provides a mechanistic explanation for the high binding affinity of tacrine towards AChE. Additionally, structural comparison of reported hAChE structures sheds light on the conformational selection and induced fit effects of various active site residues upon binding to different ligands and provides insight for future drug design campaigns against AD where AChE is a drug target.

Identification of dual active sites in Caenorhabditis elegans GANA-1 protein: an ortholog of the human α-GAL a and α-NAGA enzymes

Fabry disease (FD) is caused by a defective α-galactosidase A (α-GAL A) enzyme responsible for breaking down globotriaosylceramide (Gb₃). To develop affordable therapeutics, more effort is needed to obtain insights into the underlying mechanism of FD and understanding human α-GAL A structure and function in related animal models. We adopted C. elegans as a model to elucidate the sequence and 3D structure of its GANA-1 enzyme and compared it to human α-GAL A. We constructed GANA-1 3D structure by homology modelling and validated the quality of the predicted GANA-1 structure, followed by computational docking of human ligands. The GANA-1 protein shared sequence similarities up to 42.1% with the human α-GAL A in silico and had dual active sites. GANA-1 homology modelling showed that 11 out of 13 amino acids in the first active site of GANA-1 protein overlapped with the human α-GAL A active site, indicating the prospect for substrate cross-reaction. Computational molecular docking using human ligands like Gb₃ (first pocket)_, 4-nitrophenyl-α-D-galactopyranoside (second pocket), α-galactose (second pocket), and N-acetyl-D-galactosamine (second pocket) showed negative binding energy. This revealed that the ligands were able to bind within both GANA-1 active sites, mimicking the human α-GAL A and α-NAGA enzymes. We identified human compounds with adequate docking scores, predicting robust interactions with the GANA-1 active site. Our data suggested that the C. elegans GANA-1 enzyme may possess structural and functional similarities to human α-GAL A, including an intrinsic capability to metabolize Gb₃ deposits.Communicated by Ramaswamy H. Sarma.

COMBI: Artificial Intelligence for Computer-Based Forensic Analysis of Persons

During the prosecution process the primary objective is to prove criminal offences to the correct perpetrator to convict them with legal effect. However, in reality this may often be difficult to achieve. Suppose a suspect has been identified and is accused of a bank robbery. Due to the location of the crime, it can be assumed that there is sufficient image and video surveillance footage available, having recorded the perpetrator at the crime scene. Depending on the surveillance system used, there could be even high-resolution material available. In short, optimal conditions seem to be in place for further investigations, especially as far as the identification of the perpetrator and the collection of evidence of their participation in the crime are concerned. However, perpetrators usually act using some kind of concealment to hide their identity. In most cases, they disguise their faces and even their gait. Conventional investigation approaches and methods such as facial recognition and gait analysis then quickly reach their limits. For this reason, an approach based on anthropometric person-specific digital skeletons, so-called rigs, that is being researched by the COMBI research project is presented in this publication. Using these rigs, it should be possible to assign known identities, comparable to suspects, to unknown identities, comparable to perpetrators. The aim of the COMBI research project is to study the anthropometric pattern as a biometric identifier as well as to make it feasible for the standardised application in the taking of evidence by the police and prosecution. The approach is intended to present computer-aided opportunities for the identification of perpetrators that can support already established procedures.

Unique SMYD5 Structure Revealed by AlphaFold Correlates with Its Functional Divergence

SMYD5 belongs to a special class of protein lysine methyltransferases with an MYND (Myeloid-Nervy-DEAF1) domain inserted into a SET (Suppressor of variegation, Enhancer of Zeste, Trithorax) domain. Despite recent advances in its functional characterization, the lack of the crystal structure has hindered our understanding of the structure-and-function relationships of this most unique member of the SMYD protein family. Here, we demonstrate the reliability of using AlphaFold structures for understanding the structure and function of SMYD5 by comparing the AlphaFold structures to the known crystal structures of SMYD proteins, using an inter-residue distance maps-based metric. We found that the AlphaFold confidence scores are inversely associated with the refined B-factors and can serve as a structural indicator of conformational flexibility. We also found that the N-terminal sequence of SMYD5, predicted to be a mitochondrial targeting signal, contains a novel non-classical nuclear localization signal. This sequence is structurally flexible and does not have a well-defined conformation, which might facilitate its recognition for SMYD5’s cytonuclear transport. The structure of SMYD5 is unique in many aspects. The “crab”-like structure with a large negatively charged cleft provides a potential binding site for basic molecules such as protamines. The less positively charged MYND domain is associated with the undetectable DNA-binding ability. The most surprising feature is an incomplete target lysine access channel that lacks the evolutionarily conserved tri-aromatic arrangement, being associated with the low H3/H4 catalytic activity. This study expands our understanding of the SMYD protein family from a classical two-lobed structure to a structure of its own kind, being as a fundamental determinant of its functional divergence.

Designing of disruptor molecules to restrain the protein-protein interaction network of VANG1/SCRIB/NOS1AP using fragment-based drug discovery techniques

Governing protein-protein interaction networks are the cynosure of cell signaling and oncogenic networks. Multifarious processes when aligned with one another can result in a dysregulated output which can result in cancer progression. In the current research, one such network of proteins comprising VANG1/SCRIB/NOS1AP, which is responsible for cell migration, is targeted. The proteins are modeled using in-silico approaches, and the interaction is visualized utilizing protein-protein docking. Designing drugs for the convoluted protein network can serve as a challenging task that can be overcome by fragment-based drug designing, a recent game-changer in the computational drug discovery strategy for protein interaction networks. The model is exposed to the extraction of hotspots, also known as the restrained regions for small molecular hits. The hotspot regions are subjected to a library of generated fragments, which are then recombined and rejoined to develop small molecular disruptors of the macromolecular assemblage. Rapid screening methods using pharmacokinetic tools and 2D interaction studies resulted in four molecules that could serve the purpose of a disruptor. The final validation is executed by long-range simulations of 100 ns and exploring the stability of the complex using several parameters leading to the emergence of two novel molecules VNS003 and VNS005 that could be used as the disruptors of the protein assembly VANG1/SCRIB/NOS1AP. Also, the molecules were explored as single protein targets approbated via molecular docking and 100 ns molecular dynamics simulation. This concluded VNS003 as the most suitable inhibitor module capable of acting as a disruptor of a macromolecular assembly as well as acting on individual protein chains, thus leading to the primary hindrance in the formation of the protein interaction complex.

AlphaFold illuminates half of the dark human proteins

We investigate the use of confidence scores to evaluate the accuracy of a given AlphaFold (AF2) protein model for drug discovery. Prediction of accuracy is improved by not considering confidence scores below 80 due to the effects of disorder. On a set of recent crystal structures, 95% are likely to have accurate folds. Conformational discordance in the training set has a much more significant effect on accuracy than sequence divergence. We propose criteria for models and residues that are possibly useful for virtual screening. Based on these criteria, AF2 provides models for half of understudied (dark) human proteins and two-thirds of residues in those models.