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20 pages, 5109 KiB

Open AccessArticle

An Investigation into the Interaction between Double Hydroxide-Based Antioxidant Benzophenone Derivatives and Cyclooxygenase 2

by Yanan Qiao, Yuxi Qin, Lihua Liu, Xi Chen, Yunlan Li and Qingshan Li

Molecules 2021, 26(21), 6622; https://doi.org/10.3390/molecules26216622 - 1 Nov 2021

Cited by 3 | Viewed by 2002

Abstract

Cyclooxygenases 2 (COX2) is a therapeutic target for many inflammation and oxidative stress associated diseases. A high-throughput technique, biolayer interferometry, was performed to primarily screen the potential COX2 binding activities of twelve newly synthesized double hydroxide-based benzophenone derivatives. Binding confirmation was achieved by [...] Read more.

Cyclooxygenases 2 (COX2) is a therapeutic target for many inflammation and oxidative stress associated diseases. A high-throughput technique, biolayer interferometry, was performed to primarily screen the potential COX2 binding activities of twelve newly synthesized double hydroxide-based benzophenone derivatives. Binding confirmation was achieved by molecular docking and multi-spectroscopy studies. Such a combined method provided a comprehensive understanding of binding mechanism and conformational changes. Compounds DB2, SC2 and YB2 showed effective COX2 binding activity and underlined the benefits of three phenolic hydroxyl groups adjacent to each other on the B ring. The twelve tested derivatives were further evaluated for antioxidant activity, wherein compound SC2 showed the highest activity. Its concentration for the 50% of maximal effect (EC₅₀) value was approximately 1000 times greater than that of the positive controls. SC2 treatment effectively improved biochemical indicators caused by oxidative stress. Overall, compound SC2 could serve as a promising candidate for further development of a new potent COX2 inhibitor. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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21 pages, 9980 KiB

Open AccessArticle

Inhibition of Cysteine Proteases by 6,6′-Dihydroxythiobinupharidine (DTBN) from Nuphar lutea

by Kamran Waidha, Udi Zurgil, Efrat Ben-Zeev, Jacob Gopas, Saravanakumar Rajendran and Avi Golan-Goldhirsh

Molecules 2021, 26(16), 4743; https://doi.org/10.3390/molecules26164743 - 5 Aug 2021

Cited by 5 | Viewed by 2800

Abstract

The specificity of inhibition by 6,6′-dihydroxythiobinupharidine (DTBN) on cysteine proteases was demonstrated in this work. There were differences in the extent of inhibition, reflecting active site structural-steric and biochemical differences. Cathepsin S (IC₅₀ = 3.2 μM) was most sensitive to inhibition by [...] Read more.

The specificity of inhibition by 6,6′-dihydroxythiobinupharidine (DTBN) on cysteine proteases was demonstrated in this work. There were differences in the extent of inhibition, reflecting active site structural-steric and biochemical differences. Cathepsin S (IC₅₀ = 3.2 μM) was most sensitive to inhibition by DTBN compared to Cathepsin B, L and papain (IC₅₀ = 1359.4, 13.2 and 70.4 μM respectively). DTBN is inactive for the inhibition of M^pro of SARS-CoV-2. Docking simulations suggested a mechanism of interaction that was further supported by the biochemical results. In the docking results, it was shown that the cysteine sulphur of Cathepsin S, L and B was in close proximity to the DTBN thiaspirane ring, potentially forming the necessary conditions for a nucleophilic attack to form a disulfide bond. Covalent docking and molecular dynamic simulations were performed to validate disulfide bond formation and to determine the stability of Cathepsins-DTBN complexes, respectively. The lack of reactivity of DTBN against SARS-CoV-2 M^pro was attributed to a mismatch of the binding conformation of DTBN to the catalytic binding site of M^pro. Thus, gradations in reactivity among the tested Cathepsins may be conducive for a mechanism-based search for derivatives of nupharidine against COVID-19. This could be an alternative strategy to the large-scale screening of electrophilic inhibitors. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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21 pages, 4877 KiB

Open AccessArticle

Search for Novel Lead Inhibitors of Yeast Cytochrome bc1, from Drugbank and COCONUT

by Ozren Jović and Tomislav Šmuc

Molecules 2021, 26(14), 4323; https://doi.org/10.3390/molecules26144323 - 16 Jul 2021

Cited by 1 | Viewed by 2140

Abstract

In this work we introduce a novel filtering and molecular modeling pipeline based on a fingerprint and descriptor similarity procedure, coupled with molecular docking and molecular dynamics (MD), to select potential novel quoinone outside inhibitors (QoI) of cytochrome bc1 with the aim of [...] Read more.

In this work we introduce a novel filtering and molecular modeling pipeline based on a fingerprint and descriptor similarity procedure, coupled with molecular docking and molecular dynamics (MD), to select potential novel quoinone outside inhibitors (QoI) of cytochrome bc1 with the aim of determining the same or different chromophores to usual. The study was carried out using the yeast cytochrome bc1 complex with its docked ligand (stigmatellin), using all the fungicides from FRAC code C3 mode of action, 8617 Drugbank compounds and 401,624 COCONUT compounds. The introduced drug repurposing pipeline consists of compound similarity with C3 fungicides and molecular docking (MD) simulations with final QM/MM binding energy determination, while aiming for potential novel chromophores and perserving at least an amide (R1HN(C=O)R2) or ester functional group of almost all up to date C3 fungicides. 3D descriptors used for a similarity test were based on the 280 most stable Padel descriptors. Hit compounds that passed fingerprint and 3D descriptor similarity condition and had either an amide or an ester group were submitted to docking where they further had to satisfy both Chemscore fitness and specific conformation constraints. This rigorous selection resulted in a very limited number of candidates that were forwarded to MD simulations and QM/MM binding affinity estimations by the ORCA DFT program. In this final step, stringent criteria based on (a) sufficiently high frequency of H-bonds; (b) high interaction energy between protein and ligand through the whole MD trajectory; and (c) high enough QM/MM binding energy scores were applied to further filter candidate inhibitors. This elaborate search pipeline led finaly to four Drugbank synthetic lead compounds (DrugBank) and seven natural (COCONUT database) lead compounds—tentative new inhibitors of cytochrome bc1. These eleven lead compounds were additionally validated through a comparison of MM/PBSA free binding energy for new leads against those obtatined for 19 QoIs. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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15 pages, 3802 KiB

Open AccessArticle

Targeting 3CLpro and SARS-CoV-2 RdRp by Amphimedon sp. Metabolites: A Computational Study

by Nourhan Hisham Shady, Alaa M. Hayallah, Mamdouh F. A. Mohamed, Mohammed M. Ghoneim, Garri Chilingaryan, Mohammad M. Al-Sanea, Mostafa A. Fouad, Mohamed Salah Kamel and Usama Ramadan Abdelmohsen

Molecules 2021, 26(12), 3775; https://doi.org/10.3390/molecules26123775 - 21 Jun 2021

Cited by 6 | Viewed by 3207

Abstract

Since December 2019, novel coronavirus disease 2019 (COVID-19) pandemic has caused tremendous economic loss and serious health problems worldwide. In this study, we investigated 14 natural compounds isolated from Amphimedon sp. via a molecular docking study, to examine their ability to act as [...] Read more.

Since December 2019, novel coronavirus disease 2019 (COVID-19) pandemic has caused tremendous economic loss and serious health problems worldwide. In this study, we investigated 14 natural compounds isolated from Amphimedon sp. via a molecular docking study, to examine their ability to act as anti-COVID-19 agents. Moreover, the pharmacokinetic properties of the most promising compounds were studied. The docking study showed that virtually screened compounds were effective against the new coronavirus via dual inhibition of SARS-CoV-2 RdRp and the 3CL main protease. In particular, nakinadine B (1), 20-hepacosenoic acid (11) and amphimedoside C (12) were the most promising compounds, as they demonstrated good interactions with the pockets of both enzymes. Based on the analysis of the molecular docking results, compounds 1 and 12 were selected for molecular dynamics simulation studies. Our results showed Amphimedon sp. to be a rich source for anti-COVID-19 metabolites. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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12 pages, 5153 KiB

Open AccessArticle

6,6′-Dihydroxythiobinupharidine (DTBN) Purified from Nuphar lutea Leaves Is an Inhibitor of Protein Kinase C Catalytic Activity

by Kamran Waidha, Nikhil Ponnoor Anto, Divya Ram Jayaram, Avi Golan-Goldhirsh, Saravanakumar Rajendran, Etta Livneh and Jacob Gopas

Molecules 2021, 26(9), 2785; https://doi.org/10.3390/molecules26092785 - 8 May 2021

Cited by 6 | Viewed by 2968

Abstract

Water lily (Nuphar) bioactive extracts have been widely used in traditional medicine owing to their multiple applications against human ailments. Phyto-active Nuphar extracts and their purified and synthetic derivatives have attracted the attention of ethnobotanists and biochemists. Here, we report that 6,6′-dihydroxythiobinupharidine [...] Read more.

Water lily (Nuphar) bioactive extracts have been widely used in traditional medicine owing to their multiple applications against human ailments. Phyto-active Nuphar extracts and their purified and synthetic derivatives have attracted the attention of ethnobotanists and biochemists. Here, we report that 6,6′-dihydroxythiobinupharidine (DTBN), purified from extracts of Nuphar lutea (L.) Sm. leaves, is an effective inhibitor of the kinase activity of members of the protein kinase C (PKC) family using in vitro and in silico approaches. We demonstrate that members of the conventional subfamily of PKCs, PKCα and PKCγ, were more sensitive to DTBN inhibition as compared to novel or atypical PKCs. Molecular docking analysis demonstrated the interaction of DTBN, with the kinase domain of PKCs depicting the best affinity towards conventional PKCs, in accordance with our in vitro kinase activity data. The current study reveals novel targets for DTBN activity, functioning as an inhibitor for PKCs kinase activity. Thus, this and other data indicate that DTBN modulates key cellular signal transduction pathways relevant to disease biology, including cancer. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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12 pages, 4577 KiB

Open AccessArticle

Field-Template, QSAR, Ensemble Molecular Docking, and 3D-RISM Solvation Studies Expose Potential of FDA-Approved Marine Drugs as SARS-CoVID-2 Main Protease Inhibitors

by Poonam Kalhotra, Veera C. S. R. Chittepu, Guillermo Osorio-Revilla and Tzayhri Gallardo-Velazquez

Molecules 2021, 26(4), 936; https://doi.org/10.3390/molecules26040936 - 10 Feb 2021

Cited by 19 | Viewed by 6032

Abstract

Currently, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has infected people among all countries and is a pandemic as declared by the World Health Organization (WHO). SARS-CoVID-2 main protease is one of the therapeutic drug targets that has been shown to reduce virus [...] Read more.

Currently, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has infected people among all countries and is a pandemic as declared by the World Health Organization (WHO). SARS-CoVID-2 main protease is one of the therapeutic drug targets that has been shown to reduce virus replication, and its high-resolution 3D structures in complex with inhibitors have been solved. Previously, we had demonstrated the potential of natural compounds such as serine protease inhibitors eventually leading us to hypothesize that FDA-approved marine drugs have the potential to inhibit the biological activity of SARS-CoV-2 main protease. Initially, field-template and structure–activity atlas models were constructed to understand and explain the molecular features responsible for SARS-CoVID-2 main protease inhibitors, which revealed that Eribulin Mesylate, Plitidepsin, and Trabectedin possess similar characteristics related to SARS-CoVID-2 main protease inhibitors. Later, protein–ligand interactions are studied using ensemble molecular-docking simulations that revealed that marine drugs bind at the active site of the main protease. The three-dimensional reference interaction site model (3D-RISM) studies show that marine drugs displace water molecules at the active site, and interactions observed are favorable. These computational studies eventually paved an interest in further in vitro studies. Finally, these findings are new and indeed provide insights into the role of FDA-approved marine drugs, which are already in clinical use for cancer treatment as a potential alternative to prevent and treat infected people with SARS-CoV-2. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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24 pages, 4131 KiB

Open AccessArticle

Improved Deep Learning Based Method for Molecular Similarity Searching Using Stack of Deep Belief Networks

by Maged Nasser, Naomie Salim, Hentabli Hamza, Faisal Saeed and Idris Rabiu

Molecules 2021, 26(1), 128; https://doi.org/10.3390/molecules26010128 - 29 Dec 2020

Cited by 19 | Viewed by 3337

Abstract

Virtual screening (VS) is a computational practice applied in drug discovery research. VS is popularly applied in a computer-based search for new lead molecules based on molecular similarity searching. In chemical databases similarity searching is used to identify molecules that have similarities to [...] Read more.

Virtual screening (VS) is a computational practice applied in drug discovery research. VS is popularly applied in a computer-based search for new lead molecules based on molecular similarity searching. In chemical databases similarity searching is used to identify molecules that have similarities to a user-defined reference structure and is evaluated by quantitative measures of intermolecular structural similarity. Among existing approaches, 2D fingerprints are widely used. The similarity of a reference structure and a database structure is measured by the computation of association coefficients. In most classical similarity approaches, it is assumed that the molecular features in both biological and non-biologically-related activity carry the same weight. However, based on the chemical structure, it has been found that some distinguishable features are more important than others. Hence, this difference should be taken consideration by placing more weight on each important fragment. The main aim of this research is to enhance the performance of similarity searching by using multiple descriptors. In this paper, a deep learning method known as deep belief networks (DBN) has been used to reweight the molecule features. Several descriptors have been used for the MDL Drug Data Report (MDDR) dataset each of which represents different important features. The proposed method has been implemented with each descriptor individually to select the important features based on a new weight, with a lower error rate, and merging together all new features from all descriptors to produce a new descriptor for similarity searching. Based on the extensive experiments conducted, the results show that the proposed method outperformed several existing benchmark similarity methods, including Bayesian inference networks (BIN), the Tanimoto similarity method (TAN), adapted similarity measure of text processing (ASMTP) and the quantum-based similarity method (SQB). The results of this proposed multi-descriptor-based on Stack of deep belief networks method (SDBN) demonstrated a higher accuracy compared to existing methods on structurally heterogeneous datasets. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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11 pages, 3061 KiB

Open AccessArticle

Ensemble Docking Coupled to Linear Interaction Energy Calculations for Identification of Coronavirus Main Protease (3CL^pro) Non-Covalent Small-Molecule Inhibitors

by Marko Jukič, Dušanka Janežič and Urban Bren

Molecules 2020, 25(24), 5808; https://doi.org/10.3390/molecules25245808 - 9 Dec 2020

Cited by 30 | Viewed by 3490

Abstract

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential [...] Read more.

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CL^pro or M^pro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CL^pro active site. These compounds will facilitate further 3CL^pro inhibitor design. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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15 pages, 2438 KiB

Open AccessArticle

Carnosine to Combat Novel Coronavirus (nCoV): Molecular Docking and Modeling to Cocrystallized Host Angiotensin-Converting Enzyme 2 (ACE2) and Viral Spike Protein

by Loai M. Saadah, Ghina’a I. Abu Deiab, Qosay Al-Balas and Iman A. Basheti

Molecules 2020, 25(23), 5605; https://doi.org/10.3390/molecules25235605 - 28 Nov 2020

Cited by 13 | Viewed by 5034

Abstract

Aims: Angiotensin-converting enzyme 2 (ACE2) plays an important role in the entry of coronaviruses into host cells. The current paper described how carnosine, a naturally occurring supplement, can be an effective drug candidate for coronavirus disease (COVID-19) on the basis of molecular docking [...] Read more.

Aims: Angiotensin-converting enzyme 2 (ACE2) plays an important role in the entry of coronaviruses into host cells. The current paper described how carnosine, a naturally occurring supplement, can be an effective drug candidate for coronavirus disease (COVID-19) on the basis of molecular docking and modeling to host ACE2 cocrystallized with nCoV spike protein. Methods: First, the starting point was ACE2 inhibitors and their structure–activity relationship (SAR). Next, chemical similarity (or diversity) and PubMed searches made it possible to repurpose and assess approved or experimental drugs for COVID-19. Parallel, at all stages, the authors performed bioactivity scoring to assess potential repurposed inhibitors at ACE2. Finally, investigators performed molecular docking and modeling of the identified drug candidate to host ACE2 with nCoV spike protein. Results: Carnosine emerged as the best-known drug candidate to match ACE2 inhibitor structure. Preliminary docking was more optimal to ACE2 than the known typical angiotensin-converting enzyme 1 (ACE1) inhibitor (enalapril) and quite comparable to known or presumed ACE2 inhibitors. Viral spike protein elements binding to ACE2 were retained in the best carnosine pose in SwissDock at 1.75 Angstroms. Out of the three main areas of attachment expected to the protein–protein structure, carnosine bound with higher affinity to two compared to the known ACE2 active site. LibDock score was 92.40 for site 3, 90.88 for site 1, and inside the active site 85.49. Conclusion: Carnosine has promising inhibitory interactions with host ACE2 and nCoV spike protein and hence could offer a potential mitigating effect against the current COVID-19 pandemic. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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28 pages, 6488 KiB

Open AccessFeature PaperArticle

Targeting Beta-Blocker Drug–Drug Interactions with Fibrinogen Blood Plasma Protein: A Computational and Experimental Study

by Michael González-Durruthy, Riccardo Concu, Laura F. Osmari Vendrame, Ivana Zanella, Juan M. Ruso and M. Natália D. S. Cordeiro

Molecules 2020, 25(22), 5425; https://doi.org/10.3390/molecules25225425 - 19 Nov 2020

Cited by 7 | Viewed by 3330

Abstract

In this work, one of the most prevalent polypharmacology drug–drug interaction events that occurs between two widely used beta-blocker drugs—i.e., acebutolol and propranolol—with the most abundant blood plasma fibrinogen protein was evaluated. Towards that end, molecular docking and Density Functional Theory (DFT) calculations [...] Read more.

In this work, one of the most prevalent polypharmacology drug–drug interaction events that occurs between two widely used beta-blocker drugs—i.e., acebutolol and propranolol—with the most abundant blood plasma fibrinogen protein was evaluated. Towards that end, molecular docking and Density Functional Theory (DFT) calculations were used as complementary tools. A fibrinogen crystallographic validation for the three best ranked binding-sites shows 100% of conformationally favored residues with total absence of restricted flexibility. From those three sites, results on both the binding-site druggability and ligand transport analysis-based free energy trajectories pointed out the most preferred biophysical environment site for drug–drug interactions. Furthermore, the total affinity for the stabilization of the drug–drug complexes was mostly influenced by steric energy contributions, based mainly on multiple hydrophobic contacts with critical residues (THR22: P and SER50: Q) in such best-ranked site. Additionally, the DFT calculations revealed that the beta-blocker drug–drug complexes have a spontaneous thermodynamic stabilization following the same affinity order obtained in the docking simulations, without covalent-bond formation between both interacting beta-blockers in the best-ranked site. Lastly, experimental ultrasound density and velocity measurements were performed and allowed us to validate and corroborate the computational obtained results. Full article

(This article belongs to the Special Issue Molecular Docking in Drug Discovery)

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