Mechanism of Actions of Dexamethasone against COVID-19 predicted by Alpha Shape Analysis of Binding Sites

Background: COVID-19 emerged in late 2019 and became a pandemic disease with severe mortality and morbidity. No specific remedy exists at present, but some drugs, such as Dexamethasone, have shown clinical benefits against the causative agent, the SARS-CoV-2 virus. Objective: To analyze the binding affinity between drugs and an SARS-CoV-2 protein through geometrical methods and to study the theoretical effectiveness of Dexamethasone as a potential treatment for COVID-19. Method: The binding affinity of Dexamethasone to the target SARS-CoV-2 protein was compared with those of different inhibitors. Drug molecules were docked to the SARS-CoV-2 main protease, and the system was simulated by molecular dynamics, allowing alpha shape analysis to extract geometrical features, such as the matching rates of atoms, solid angles, and the distances between atoms at interfaces. Binding affinities between drugs and the main protease were assessed by these geometrical data and the free energy of binding. Results: The behaviour of Dexamethasone was similar to other inhibitors. The efficacy of Dexamethasone as a treatment may be due to it being a glucocorticoid and its properties as a potent inhibitor. Conclusion: This study revealed the mechanism of action of Dexamethasone and provided a geometrical method to distinguish among potential drugs for the treatment of COVID-19.

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Allergen fragrance molecules: a potential relief for COVID-19

BMC Complementary Medicine and Therapies ◽

10.1186/s12906-021-03214-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Aslı Deniz Aydın ◽

Faruk Altınel ◽

Hüseyin Erdoğmuş ◽

Çağdaş Devrim Son

Keyword(s):

Binding Affinity ◽

Docking Studies ◽

Binding Energies ◽

Binding Affinities ◽

Flexible Docking ◽

Potential Relief ◽

Docking Simulations ◽

Molegro Virtual Docker ◽

Drug Molecules ◽

Docking Protocol

Abstract Background The latest coronavirus SARS-CoV-2, discovered in China and rapidly spread Worldwide. COVID-19 affected millions of people and killed hundreds of thousands worldwide. There are many ongoing studies investigating drug(s) suitable for preventing and/or treating this pandemic; however, there are no specific drugs or vaccines available to treat or prevent SARS-CoV-2 as of today. Methods Fifty-eight fragrance materials, which are classified as allergen fragrance molecules, were selected and used in this study. Docking simulations were carried out using four functional proteins; the Covid19 Main Protase (MPro), Receptor binding domain (RBD) of spike protein, Nucleocapsid, and host Bromodomain protein (BRD2), as target macromolecules. Three different software, AutoDock, AutoDock Vina (Vina), and Molegro Virtual Docker (MVD), running a total of four different docking protocol with optimized energy functions were used. Results were compared with the five molecules reported in the literature as potential drugs against COVID-19. Virtual screening was carried out using Vina, molecules satisfying our cut-off (− 6.5 kcal/mol) binding affinity was confirmed by MVD. Selected molecules were analyzed using the flexible docking protocol of Vina and AutoDock default settings. Results Ten out of 58 allergen fragrance molecules were selected for further docking studies. MPro and BRD2 are potential targets for the tested allergen fragrance molecules, while RBD and Nucleocapsid showed weak binding energies. According to AutoDock results, three molecules, Benzyl Cinnamate, Dihydroambrettolide, and Galaxolide, had good binding affinities to BRD2. While Dihydroambrettolide and Galaxolide showed the potential to bind to MPro, Sclareol and Vertofix had the best calculated binding affinities to this target. When the flexible docking results analyzed, all the molecules tested had better calculated binding affinities as expected. Benzyl Benzoate and Benzyl Salicylate showed good binding affinities to BRD2. In the case of MPro, Sclareol had the lowest binding affinity among all the tested allergen fragrance molecules. Conclusion Allergen fragrance molecules are readily available, cost-efficient, and shown to be safe for human use. Results showed that several of these molecules had comparable binding affinities as the potential drug molecules reported in the literature to target proteins. Thus, these allergen molecules at correct doses could have significant health benefits.

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Allergen Fragrance Molecules: A Potential Relief for COVID-19

10.21203/rs.3.rs-57251/v1 ◽

2020 ◽

Author(s):

Aslı Deniz Aydın ◽

Faruk Altınel ◽

Hüseyin Erdoğmuş ◽

Cagdas Devrim Son

Keyword(s):

Binding Affinity ◽

Docking Studies ◽

Binding Energies ◽

Binding Affinities ◽

Flexible Docking ◽

Potential Relief ◽

Docking Simulations ◽

Molegro Virtual Docker ◽

Drug Molecules ◽

Docking Protocol

Abstract Background: The latest coronavirus SARS-CoV-2, discovered in China and rapidly spread Worldwide. COVID-19 affected millions of people and killed hundreds of thousands worldwide. There are many ongoing studies investigating drug(s) suitable for preventing and/or treating this pandemic; however, there are no specific drugs or vaccines available to treat or prevent SARS-CoV-2 as of today.Methods: 58 fragrance materials, which are classified as allergen fragrance molecules, were selected and used in this study. Docking simulations were carried out using four functional proteins; the Covid19 Main Protase (Mpro), Receptor binding domain (RBD) of spike protein, Nucleocapsid, and host Bromodomain protein (BRD2), as target macromolecules. Three different software, AutoDock, AutoDock Vina (Vina), and Molegro Virtual Docker (MVD), running a total of four different docking protocol with optimized energy functions were used. Results were compared with the five molecules reported in the literature as potential drugs against COVID-19. Virtual screening was carried out using Vina, molecules satisfying our cut-off (-6.5 kcal/mol) binding affinity was confirmed by MVD. Selected molecules were analyzed using the flexible docking protocol of Vina and AutoDock default settings. Results: Ten out of 58 allergen fragrance molecules were selected for further docking studies. Mpro and BRD2 are potential targets for the tested allergen fragrance molecules, while RBD and Nucleocapsid showed weak binding energies. According to AutoDock results, three molecules, Benzyl Cinnamate, Dihydroambrettolide, and Galaxolide, had good binding affinities to BRD2. While Dihydroambrettolide and Galaxolide showed the potential to bind to Mpro, Sclareol and Vertofix had the best calculated binding affinities to this target. When the flexible docking results analyzed, all the molecules tested had better calculated binding affinities as expected. Benzyl Benzoate and Benzyl Salicylate showed good binding affinities to BRD2. In the case of Mpro, Sclareol had the lowest binding affinity among all the tested allergen fragrance molecules. Conclusion: Allergen fragrance molecules are readily available, cost-efficient, and shown to be safe for human use. Results showed that several of these molecules had comparable binding affinities as the potential drug molecules reported in the literature to target proteins. Thus, these allergen molecules at correct doses could have significant health benefits.

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Identification of Pharmacophoric Features and Novel Compounds for Inhibition of SARS-Cov-2 Main Protease

10.20944/preprints202004.0329.v1 ◽

2020 ◽

Author(s):

Priti Jain ◽

Rupesh Dorik ◽

Munendra Jain

Keyword(s):

Crystal Structure ◽

Phylogenetic Analysis ◽

Nucleotide Sequence ◽

Binding Affinity ◽

High Mortality ◽

Sequence Similarity ◽

Mortality And Morbidity ◽

Future Design ◽

Main Protease ◽

Approved Drugs

A big race for the search for novel lead has begun due to the emergence of COVID-19 across the globe. More than 6,00,000 cases of afflicted patients worldwide has been reported till date with high mortality and morbidity. At present no approved drugs are known for COVID-19. Phylogenetic analysis present strong nucleotide sequence similarity of around 80% with SARS-CoV. Therefore, the drugs used for treating SARS-CoV and MERS are being used for SARS-CoV-2 also. Recently, the crystal structure of COVID-19 is reported and hence, we have used this tom predict the binding affinity with SARS-CoV-2-main protease and prepared a pharmacophore that may be used for future design of novel inhibitors.

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Drug Repurposing Studies Targeting SARS-nCoV2: An Ensemble Docking Approach on Drug Target 3C-like Protease (3CLpro)

10.26434/chemrxiv.12228831 ◽

2020 ◽

Author(s):

Shruti Koulgi ◽

Vinod Jani ◽

Mallikarjunachari Uppuladinne ◽

Uddhavesh Sonavane ◽

Asheet Kumar Nath ◽

...

Keyword(s):

Drug Repurposing ◽

Drug Binding ◽

Ensemble Docking ◽

Drug Molecules ◽

Drug Binding Site ◽

Main Protease ◽

Docking Approach ◽

Novel Coronavirus ◽

Markov State Modeling ◽

Viral Polyprotein

The COVID-19 pandemic has been responsible for several deaths worldwide. The causative agent behind this disease is the Severe Acute Respiratory Syndrome – novel Coronavirus 2 (SARS-nCoV2). SARS-nCoV2 belongs to the category of RNA viruses. The main protease, responsible for the cleavage of the viral polyprotein is considered as one of the hot targets for treating COVID-19. Earlier reports suggest the use of HIV anti-viral drugs for targeting the main protease of SARS-CoV, which caused SARS in the year 2002-03. Hence, drug repurposing approach may prove to be useful in targeting the main protease of SARS-nCoV2. The high-resolution crystal structure of 3CLpro (main protease) of SARS-nCoV2 (PDB ID: 6LU7) was used as the target. The Food and Drug Administration (FDA) approved and SWEETLEAD database of drug molecules were screened. The apo form of the main protease was simulated for a cumulative of 150 ns and 10 μs open source simulation data was used, to obtain conformations for ensemble docking. The representative structures for docking were selected using RMSD-based clustering and Markov State Modeling analysis. This ensemble docking approach for main protease helped in exploring the conformational variation in the drug binding site of the main protease leading to efficient binding of more relevant drug molecules. The drugs obtained as best hits from the ensemble docking possessed anti-bacterial and anti-viral properties. Small molecules with these properties may prove to be useful to treat symptoms exhibited in COVID-19. This in-silico ensemble docking approach would support identification of potential candidates for repurposing against COVID-19.

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Discovery of Some Antiviral Natural products to fight against Novel Corona Virus (SARS-CoV-2) using Insilico approach

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323666200902135928 ◽

2020 ◽

Vol 23 ◽

Author(s):

Ashish Shah ◽

Vaishali Patel ◽

Bhumika Parmar

Keyword(s):

Binding Affinity ◽

Protein S ◽

Docking Studies ◽

Spike Protein ◽

Enveloped Viruses ◽

Bioactivity Prediction ◽

Corona Virus ◽

Main Protease ◽

Antiviral Activities ◽

Deadly Disease

Background: Novel Corona virus is a type of enveloped viruses with a single stranded RNA enclosing helical nucleocapsid. The envelope consists of spikes on the surface which are made up of proteins through which virus enters into human cells. Until now there is no specific drug or vaccine available to treat COVID-19 infection. In this scenario, reposting of drug or active molecules may provide rapid solution to fight against this deadly disease. Objective: We had selected 30 phytoconstituents from the different plants which are reported for antiviral activities against corona virus (CoVs) and performed insilico screening to find out phytoconstituents which have potency to inhibit specific target of novel corona virus. Methods: We had perform molecular docking studies on three different proteins of novel corona virus namely COVID-19 main protease (3CL pro), papain-like protease (PL pro) and spike protein (S) attached to ACE2 binding domain. The screening of the phytoconstituents on the basis of binding affinity compared to standard drugs. The validations of screened compounds were done using ADMET and bioactivity prediction. Results: We had screened five compounds biscoclaurine, norreticuline, amentoflavone, licoricidin and myricetin using insilico approach. All compounds found safe in insilico toxicity studies. Bioactivity prediction reviles that these all compounds may act through protease or enzyme inhibition. Results of compound biscoclaurine norreticuline were more interesting as this biscoclaurine had higher binding affinity for the target 3CLpro and PLpro targets and norreticuline had higher binding affinity for the target PLpro and Spike protein. Conclusion: Our study concludes that these compounds could be further explored rapidly as it may have potential to fight against COVID-19.

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SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors

Journal of Cheminformatics ◽

10.1186/s13321-021-00507-1 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Surendra Kumar ◽

Mi-hyun Kim

Keyword(s):

Ligand Binding ◽

Binding Affinity ◽

Scoring Functions ◽

Binding Affinities ◽

Ligand Interaction ◽

Fingerprint Pattern ◽

Comparable Performance ◽

Direct Interpretation ◽

Benchmark Datasets ◽

Complex Features

AbstractIn drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a pivotal task for lead optimization with acceptable on-target potency as well as pharmacological efficacy. Furthermore, researchers hope for a high correlation between docking score and pose with key interactive residues, although scoring functions as free energy surrogates of protein–ligand complexes have failed to provide collinearity. Recently, various machine learning or deep learning methods have been proposed to overcome the drawbacks of scoring functions. Despite being highly accurate, their featurization process is complex and the meaning of the embedded features cannot directly be interpreted by human recognition without an additional feature analysis. Here, we propose SMPLIP-Score (Substructural Molecular and Protein–Ligand Interaction Pattern Score), a direct interpretable predictor of absolute binding affinity. Our simple featurization embeds the interaction fingerprint pattern on the ligand-binding site environment and molecular fragments of ligands into an input vectorized matrix for learning layers (random forest or deep neural network). Despite their less complex features than other state-of-the-art models, SMPLIP-Score achieved comparable performance, a Pearson’s correlation coefficient up to 0.80, and a root mean square error up to 1.18 in pK units with several benchmark datasets (PDBbind v.2015, Astex Diverse Set, CSAR NRC HiQ, FEP, PDBbind NMR, and CASF-2016). For this model, generality, predictive power, ranking power, and robustness were examined using direct interpretation of feature matrices for specific targets.

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Design of peptides with strong binding affinity to poly(methyl methacrylate) resin by use of molecular simulation-based materials informatics

Polymer Journal ◽

10.1038/s41428-021-00543-6 ◽

2021 ◽

Author(s):

Tomio Iwasaki ◽

Masashi Maruyama ◽

Tatsuya Niwa ◽

Toshiki Sawada ◽

Takeshi Serizawa

Keyword(s):

Methyl Methacrylate ◽

Binding Affinity ◽

Molecular Simulation ◽

Dynamics Simulation ◽

Binding Affinities ◽

Materials Informatics ◽

Poly Methyl Methacrylate ◽

Strong Binding ◽

Experimental Values ◽

Pmma Resin

AbstractPeptides with strong binding affinities for poly(methyl methacrylate) (PMMA) resin were designed by use of materials informatics technology based on molecular dynamics simulation for the purpose of covering the resin surface with adhesive peptides, which were expected to result in eco-friendly and biocompatible biomaterials. From the results of binding affinity obtained with this molecular simulation, it was confirmed that experimental values could be predicted with errors <10%. By analyzing the simulation data with the response-surface method, we found that three peptides (RWWRPWW, EWWRPWR, and RWWRPWR), which consist of arginine (R), tryptophan (W), and proline (P), have strong binding affinity to the PMMA resin. These amino acids were effective because arginine and tryptophan have strong binding affinities for methoxycarbonyl groups and methyl groups, which are the main constituents of the PMMA resin, and proline stabilizes the flat zigzag structures of the peptides in water. The strong binding affinities of the three peptides were confirmed by experiments (surface plasmon resonance methods).

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Molecular Docking Senyawa Gingerol dan Zingiberol pada Tanaman Jahe sebagai Penanganan COVID-19

Jurnal e-Biomedik ◽

10.35790/ebm.v9i1.32361 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Belinda D. P. M. Ratu ◽

Widdhi Bodhi ◽

Fona Budiarso ◽

Billy J. Kepel ◽

. Fatimawali ◽

...

Keyword(s):

Molecular Docking ◽

Binding Affinity ◽

Amino Acid Residues ◽

Autodock Vina ◽

Discovery Studio ◽

Main Protease ◽

Docking Method ◽

Pubmed Database ◽

Almost All ◽

The Impact

Abstract: COVID-19 is a new disease. Many people feel the impact of this disease. There is no definite cure for COVID-19, so many people use traditional medicine to ward off COVID-19, including ginger. This study aims to determine whether there is an interaction between compounds in ginger (gingerol and zingiberol) and the COVID-19’s main protease (6LU7). This study uses a molecular docking method using 4 main applications, namely Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, and Open Babel GUI. The samples used were gingerol and zingiberol compounds in ginger plants downloaded from Pubchem. The data used in this study used Mendeley, Clinical Key, and PubMed database. The study showed that almost all of the amino acid residues in the gingerol compound acted on the 6LU7 active site, whereas the zingiberol did not. The results of the binding affinity of ginger compounds, both gingerol and zingiberol, do not exceed the binding affinity of remdesivir, a drug that is widely researched as a COVID-19 handling drug. In conclusion, gingerol and zingiberol compounds in ginger can’t be considered as COVID-19’s treatment.Keywords: molecular docking, gingerol, zingiberol Abstrak: COVID-19 merupakan sebuah penyakit yang baru. Banyak masyarakat yang merasakan dampak dari penyakit ini. Belum ada pengobatan pasti untuk menyembuhkan COVID-19, sehingga banyak masyarakat yang menggunakan pengobatan tradisional untuk menangkal COVID-19, termasuk jahe. Penelitian ini bertujuan untuk mengetahui apakah ada interaksi antara senyawa pada jahe (gingerol dan zingiberol) dengan main protease COVID-19 (6LU7). Penelitian ini menggunakan metode molecular docking dengan menggunakan 4 aplikasi utama, yaitu Autodock Tools, Autodock Vina, Biovia Discovery Studio 2020, dan Open Babel GUI. Sampel yang digunakan yaitu senyawa gingerol dan zingiberol pada tanaman jahe yang diunduh di Pubchem. Data yang digunakan dalam penelitian ini menggunakan database Mendeley, Clinical Key, dan PubMed. Penelitian menunjukkan bahwa hampir semua residu asam amino pada senyawa gingerol bekerja pada sisi aktif 6LU7, sedangkan tidak demikian pada zingiberol. Hasil binding affinity senyawa jahe, baik gingerol maupun zingiberol tidak melebihi binding affinity remdesivir, obat yang banyak diteliti sebagai obat penanganan COVID-19. Sebagai simpulan, senyawa gingerol dan zingiberol pada tanaman jahe tidak dapat dipertimbangkan sebagai penanganan COVID-19Kata Kunci: molecular docking, gingerol, zingiberol

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Climbing up and down binding landscapes: a high-throughput study of mutational effects in homologous protein-protein complexes

10.1101/2020.10.14.338756 ◽

2020 ◽

Author(s):

Michael Heyne ◽

Jason Shirian ◽

Itay Cohen ◽

Yoav Peleg ◽

Evette S. Radisky ◽

...

Keyword(s):

Binding Affinity ◽

Protein Interactions ◽

Enzyme Inhibitor ◽

Binding Free Energy ◽

Hot Spot ◽

Cold Spot ◽

Binding Affinities ◽

High Affinity ◽

Binding Interface ◽

Biological Complexes

AbstractEach protein-protein interaction (PPI) has evolved to possess binding affinity that is compatible with its cellular function. As such, cognate enzyme/inhibitor interactions frequently exhibit very high binding affinities, while structurally similar non-cognate PPIs possess substantially weaker binding affinities. To understand how slight differences in sequence and structure could lead to drastic changes in PPI binding free energy (ΔΔGbind), we study three homologous PPIs that span nine orders of magnitude in binding affinity and involve a serine protease interacting with an inhibitor BPTI. Using state-of-the-art methodology that combines protein randomization and affinity sorting coupled to next-generation sequencing and data normalization, we report quantitative binding landscapes consisting of ΔΔGbind values for the three PPIs, gleaned from tens of thousands of single and double mutations in the BPTI binding interface. We demonstrate that the three homologous PPIs possess drastically different binding landscapes and lie at different points in respect to the landscape maximum. Furthermore, the three PPIs demonstrate distinct patterns of coupling energies between two simultaneous mutations that depend not only on positions involved but also on the nature of the mutation. Interestingly, we find that in all three PPIs positive epistasis is frequently observed at hot-spot positions where mutations lead to loss of high affinity, while conversely negative epistasis is observed at cold-spot positions, where mutations lead to affinity enhancement. The new insights on PPI evolution revealed in this study will be invaluable in understanding evolution of other biological complexes and can greatly facilitate design of novel high-affinity protein inhibitors.SignificanceProtein-protein interactions (PPIs) have evolved to display binding affinities that can support their function. As such, cognate and non-cognate PPIs could be highly similar structurally but exhibit huge differences in binding affinities. To understand this phenomenon, we studied the effect of tens of thousands of single and double mutations on binding affinity of three homologous protease-inhibitor complexes. We show that binding landscapes of the three complexes are strikingly different and depend on the PPI evolutionary optimality. We observe different patterns of couplings between mutations for the three PPIs with negative and positive epistasis appearing most frequently at hot-spot and cold-spot positions, respectively. The evolutionary trends observed here are likely to be universal to all biological complexes in the cell.

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A Computational and Literature-Based Evaluation for a Combination of Chiral Anti-CoV Drugs to Block and Eliminate SARS-CoV-2 Safely

10.26434/chemrxiv.12550523.v4 ◽

2021 ◽

Author(s):

Mohd. Suhail

Keyword(s):

Side Effects ◽

Jc Virus ◽

Computational Study ◽

Human Cells ◽

The Body ◽

Binding Affinities ◽

Chiral Drugs ◽

Main Protease ◽

The World ◽

Second Wave

<a>It has been a great challenge for scientists to develop an anti-covid drug/vaccine with fewer side effects, since the coronavirus began. Of course, the prescription of chiral drugs (chloroquine or hydroxychloroquine) has been proved wrong because these chiral drugs neither kill the virus nor eliminate it from the body, but block SARS-CoV-2 from binding to human cells. Another hurdle in front of the world, is not only the positive test of the patient recovered from coronavirus but also the second wave of Covid 19. Hence, the word demands such a drug or drug combination which not only prevents the entry of SARS-CoV-2 in the human cell but also eliminates it or its material from the body completely. The presented computational study explains (i) why the prescription of chiral drugs was not satisfactory (ii) what types of modification can make their prescription satisfactory (iii) the mechanism of action of chiral drugs (chloroquine and hydroxychloroquine) to block SARS-CoV-2 from binding to human cells, and (iv) the strength of mefloquine to eliminate SARS-CoV-2. As the main protease (Mpro) of microbes is considered as an effective target for drug design and development, the binding affinities of mefloquine with the main proteases (Mpros) of JC virus and SARS-CoV-2, were calculated, and then compared to know the eliminating strength of mefloquine against SARS-CoV-2. The main protease (Mpro) of JC virus was taken because mefloquine has already shown a tremendous result of eliminating it from the body. The current study includes the docking results and literature data in support of the prescription of a combination of S-(+)-hydroxychloroquine and (+) mefloquine. Besides, the presented study also confirms that the prescription of only hydroxychloroquine would not be so effective as in combined form with mefloquine.</a>

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