Targeting SARS-CoV-2 main protease by teicoplanin: A mechanistic insight by docking, MM/GBSA and molecular dynamics simulation

Integrated network pharmacology analysis and experimental validation to investigate the mechanism of Flavan-3-ols and aromatic resins in depression

The present investigation delved into the pharmacological mechanisms underlying the management of depression through Flavan-3-ols and Aromatic Resins, employing in silico and in vivo methodologies. Network pharmacology was utilized to identify targets associated with the antidepressant activity of Flavan-3-ols and Aromatic Resins. Protein-protein interaction and KEGG analyses were conducted to enrich and explore key pathways. Molecular docking and simulation studies were executed to assess the targets. The antidepressant effects were studied using the Forced Swim Test and Tail Suspension Test on both unstressed mice and those subjected to the chronic unpredictable mild stress (CUMS) paradigm. The Compound-Target network analysis revealed a substantial impact of the components on numerous targets, with 332 nodes and 491 edges. Protein-protein interaction analysis indicated significant interactions with targets implicated in depression. KEGG analysis highlighted major pathways, including neuroactive ligand-receptor interaction, dopaminergic synapse, and long-term depression. Docking studies on EGCG demonstrated binding energies of -7.2 kcal/mol for serotonin 1 A (5-HT1A), -7.9 kcal/mol for D2, and - 9.6 kcal/mol for MOA-A. Molecular dynamics simulation indicated minute fluctuation, hence suggesting stable complexes formed between small molecules and proteins. The combination of Flavan-3-ols and Aromatic Resins significantly increased mobility time (p < 0.05) in the Forced Swim Test and Tail Suspension Test, while significantly decreasing immobility time and time freezing (p < 0.05) in both unstressed and CUMS mice. This study demonstrated the antidepressant characteristics of Flavan-3-ols and Aromatic Resins, underscoring the need for further research to develop a novel antidepressant medication.

Network pharmacology combined with molecular docking and experimental verification to elucidate the effect of flavan-3-ols and aromatic resin on anxiety

This study investigated the potential anxiolytic properties of flavan-3-ols and aromatic resins through a combined computational and experimental approach. Network pharmacology techniques were utilized to identify potential anxiolytic targets and compounds by analyzing protein-protein interactions and KEGG pathway data. Molecular docking and simulation studies were conducted to evaluate the binding interactions and stability of the identified targets. Behavioral tests, including the elevated plus maze test, open field test, light-dark test, actophotometer, and holeboard test, were used to assess anxiolytic activity. The compound-target network analysis revealed complex interactions involving 306 nodes and 526 edges, with significant interactions observed and an average node degree of 1.94. KEGG pathway analysis highlighted pathways such as neuroactive ligand-receptor interactions, dopaminergic synapses, and serotonergic synapses as being involved in anxiety modulation. Docking studies on EGCG (Epigallocatechin gallate) showed binding energies of -9.5 kcal/mol for MAOA, -9.2 kcal/mol for SLC6A4, and -7.4 kcal/mol for COMT. Molecular dynamic simulations indicated minimal fluctuations, suggesting the formation of stable complexes between small molecules and proteins. Behavioral tests demonstrated a significant reduction in anxiety-like behavior, as evidenced by an increased number of entries into and time spent in the open arm of the elevated plus maze test, light-dark test, open field center activity, hole board head dips, and actophotometer beam interruptions (p < 0.05 or p < 0.01). This research provides a comprehensive understanding of the multi-component, multi-target, and multi-pathway intervention mechanisms of flavan-3-ols and aromatic resins in anxiety treatment. Integrated network and behavioral analyses collectively support the anxiolytic potential of these compounds and offer valuable insights for future research in this area.

Flavonostilbenes natural hybrids from Rhamnoneuron balansae as potential antitumors targeting ALDH1A1: molecular docking, ADMET, MM-GBSA calculations and molecular dynamics studies

Several studies have linked Cancer stem cells (CSCs) to cancer resistance development to chemotherapy and radiotherapy. ALDH1A1 is a key enzyme that regulates the gene expression of CSCs and creates an immunosuppressive tumor microenvironment. It was reported that quercetin and resveratrol were among the inhibitors of ALDH1A1. In early 2022, it was reported that new 11 flavonostilbenes (rhamnoneuronal D-N) were isolated from Rhamnoneuron balansae as potential antiaging natural products. Rhamnoneuronal H (5) could be envisioned as a natural hybrid of quercetin and resveratrol. It was therefore hypothesized that 5 and its analogous isolates rhamnoneuronal D-G (1-4) and rhamnoneuronal I-N (6-11) would have potential ALDH1A1 inhibitory activity. To this end, all isolates were subjected to molecular docking, MM-GBSA, ADMET, and molecular dynamics simulations studies to assess their potential as new leads for cancer treatment targeting ALDH1A1. In silico findings revealed that natural hybrid 5 has a similar binding affinity, judged by MM-GBSA, to the ALDH1A1 active site when compared to the co-crystalized ligand (-64.71 kcal/mole and -64.12 kcal/mole, respectively). Despite having lesser affinity than that of the co-crystalized ligand, the rest of the flavonostilbenes, except 2-4, displayed better binding affinities (-37.55 kcal/mole to -58.6 kcal/mole) in comparison to either resveratrol (-34.44 kcal/mole) or quercetin (-36.48 kcal/mole). Molecular dynamic simulations showed that the natural hybrids 1, 5-11 are of satisfactory stability up to 100 ns. ADMET outcomes indicate that these hybrids displayed acceptable properties and hence could represent an ideal starting point for the development of potent ALDH1A1 inhibitors for cancer treatment.Communicated by Ramaswamy H. Sarma.

Tinospora cordifolia ameliorates paclitaxel-induced neuropathic pain in albino rats

ETHNOPHARMACOLOGICAL RELEVANCE

Tinospora cordifolia (T. cordifolia) (Willd.) Miers, a member of the Menispermaceae, family documented in the ancient textbooks of the Ayurveda System of Medicine, has been used in the management of sciatica pain and diabetic neuropathy.

AIM

The study has been designed to evaluate the antinociceptive potential of various extracts of T. cordifolia stem in Paclitaxel (PT)-generated neuropathic pain model in albino rats and explore its possible mechanism employing molecular docking studies.

METHODS

Stems of T. cordifolia were shade dried, grinded in fine powder, and extracted separately with different solvents viz. ethanol, water & hydro-alcoholic and characterized using LCMS/MS. The antinociceptive property of T. cordifolia stem (200 and 400 mg/kg) was examined in albino rats using a PT-induced neuropathic pain model. Further, the effect of these extracts was also observed using different behavioral assays viz. cold allodynia, mechanical hyperalgesia (pin-prick test), locomotor activity test, walking track test, and Sciatic Functional Index (SFI) in rats. Tissue lysate of the sciatic nerve was used to determine various biochemical markers such as GSH, SOD, TBARS, tissue protein, and nitrite. Further to explore the possible mechanism of action, the most abundant and therapeutically active compounds available in aqueous extract were analyzed for binding affinity towards soluble epoxide hydrolase (sEH) enzyme (PDB ID: 3wk4) employing molecular docking studies.

RESULTS

The results of the LCMS/MS study of different extracts of T. cordifolia indicated presence of alkaloids, glycosides, terpenoids, sterols and sugars such as amritoside A, tinocordin, magnoflorine, N-methylcoclaurine, coridine, 20β-hydroxyecdysone and menaquinone-7 palmatin, cordifolioside A and tinosporine etc. Among all the three extracts, the hydroalcoholic extract (400 mg/kg) showed the highest response followed by aqueous and ethanolic extracts as evident in in vivo behavioral and biochemical evaluations. Furthermore, docking studies also exposed that these compounds viz. N-methylcoclaurine tinosporin, palmatine, tinocordin, 20β-hydroxyecdysone, and coridine exhibited well to excellent affinity towards target sEH protein.

CONCLUSION

T. cordifolia stem could alleviate neuropathic pain via soluble epoxide hydrolase inhibitory activity.

Effectiveness of estrogen and its derivatives over dexamethasone in the treatment of COVID-19

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus and dexamethasone is a glucocorticoid widely used for its treatment. Dexamethasone is not used in non-severe cases due to its immunosuppressant action. So, considering this, Estrogen and Estetrol were tested for the treatment of COVID-19 as they all possess a common steroid ring and dislike dexamethasone, they are immunoenhancer. Virtual screening of test ligands was performed through molecular docking, MM-GBSA, simulations, in silico ADMET and drug-likeness prediction to identify their potential to inhibit the effects of SARS-CoV-2. Results showed that test ligands possess drug-like properties and they are safe as drug candidates. The protein-ligand interaction study revealed that they bind with the amino acid residues at the active site of the target proteins and the test ligands possess better binding potential than Dexamethasone. With protein Mpro, Estetrol and Estrogen showed docking score of -7.240 and -5.491 kcal/mol, and with protein ACE2, Estetrol and Estrogen showed docking score of -5.269 and -4.732 kcal/mol, respectively. Further, MD Simulation was carried out and most of the interactions of molecular docking are preserved during simulation. The prominent interactions that our test ligands showed during MD Simulation are similar to drugs that possess in vitro anticovid activity as shown in recent studies. Hence, our test ligands possessed potential for anticovid activity and they should be further tested through in vitro and in vivo studies for their activity against COVID-19.Communicated by Ramaswamy H. Sarma.

Bioactive metabolites of licorice and thyme as potential inhibitors of Cox1 enzyme of phytopathogens of Capsicum annuum L.: In-silico approaches

Cytochrome c oxidase subunit 1 (Cox1), a key enzyme, has a crucial role in cellular respiration in eukaryotes and prokaryotes. Generally, respiratory inhibitors are considered one of the types of chemical pesticides. Thyme oil and licorice aqueous extract have been reported to have antifungal activities against fungal phytopathogens of Capsicum annuum L., i.e., Colletotrichum capsici, Fusarium oxysporum, and Pythium aphanidermatum. The present study focuses on identifying the key bioactive molecules of thyme and licorice botanicals inhibiting the activity of the Cox1 enzymes of the above mentioned phytopathogens, employing the in-silico approach. From a wide range of bioactive molecules screened, the molecular docking indicated trans-carveol, carvacrol, kaempferol 3-rhamnoside 7-xyloside, kaempferitrin, and astragalin 7-rhamnoside as the potential inhibitors for Cox1 of C. capsici, β-Caryophyllene, Caryophyllene acetate, hispaglabridin A, kaempferol 3-rhamnoside 7-xyloside and licorice glycoside A for Cox1 of F. oxysporum and (+)-Longifolen, Caryophyllene acetate, Hispaglabridin A, Neoliquiritin 2''-apioside and Licorice-saponin A3 for Cox1 of P. aphanidermatum. Most of the top-scoring bioactive molecules exhibited higher binding affinity with the targets than the chemical compound, i.e., carbendazim. Density functional theory (DFT) analysis confirmed the reactivity of the top-docked compounds. Molecular dynamic simulations confirmed the stability of docked complexes when evaluated through multiple descriptors. Additionally, MM/PBSA analysis supported the findings, indicating the spontaneous binding of the enzymes to the screened ligands. ADMET analysis revealed the safety of the selected bioactive compounds. The present findings could be useful in developing biopesticidal formulations as efficient and sustainable alternatives to chemical pesticides.Communicated by Ramaswamy H. Sarma.

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery

BACKGROUND

The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.

OBJECTIVE

Our goal here is to review the concept of scoring function space and how to explore it to develop machine learning models to address protein-ligand binding affinity.

METHODS

We searched the articles available in PubMed related to the scoring function space. We also utilized crystallographic structures found in the protein data bank (PDB) to represent the protein space.

RESULTS

The application of systems-level approaches to address receptor-drug interactions allows us to have a holistic view of the process of drug discovery. The scoring function space adds flexibility to the process since it makes it possible to see drug discovery as a relationship involving mathematical spaces.

CONCLUSION

The application of the concept of scoring function space has provided us with an integrated view of drug discovery methods. This concept is useful during drug discovery, where we see the process as a computational search of the scoring function space to find an adequate model to predict receptor-drug binding affinity.

Ehretia Species Phytoconstituents as Potential Lead Compounds against Klebsiella pneumoniae Carbapenemase: A Computational Approach

The evolution of antibiotic-resistant carbapenemase has negatively impacted the management of critical healthcare-associated infections. K. pneumoniae carbapenemase-2- (KPC-2-) expressing bacteria have developed resistance to conventional therapeutic options, including those used as a last resort for life-threatening diseases. In this study, Ehretia species phytoconstituents were screened for their potential to inhibit KPC-2 protein using in silico approaches. Molecular docking was used to identify strong KPC-2 protein binding phytoconstituents retrieved from the literature. The best-docked conformation of the ligands was selected based on their glide energy and binding interactions. To determine their binding free energies, these hit compounds were subjected to molecular mechanics with generalized born and surface area (MM-GBSA) in the PRIME module. Pharmacological assessments of the ligands were performed to evaluate their drug-likeness. Molecular dynamic (MD) simulations were used to analyze the conformational stability of the selected druglike compounds within the active site of the KPC-2 protein. Overall, a total of 69 phytoconstituents were compiled from the literature. Fourteen of these compounds exhibited a stronger binding affinity for the protein target than the reference drugs. Four of these top hit compounds, DB09, DB12, DB28, and DB66, revealed the highest efficacy in terms of drug-likeness properties. The MD simulation established that among the druglike compounds, DB66 attained stable conformations after 150 ns simulation in the active site of the protein. We concluded that DB66 from Ehretia species could play a significant role in therapeutic efforts against KPC-2-expressing bacteria.

A multitier virtual screening of antagonists targeting PD-1/PD-L1 interface for the management of triple-negative breast cancer

Immunotherapies are promising therapeutic options for the management of triple-negative breast cancer because of its high mutation rate and genomic instability. Of note, the blockade of the immune checkpoint protein PD-1 and its ligand PD-L1 has been proven to be an efficient and potent strategy to combat triple-negative breast cancer. To date, various anti-PD-1/anti-PD-L1 antibodies have been approved. However, the intrinsic constraints of these therapeutic antibodies significantly limit their application, making small molecules a potentially significant option for PD-1/PD-L1 inhibition. In light of this, the current study aims to use a high-throughput virtual screening technique to identify potential repurposed candidates as PD-L1 inhibitors. Thus, the present study explored binding efficiency of 2509 FDA-approved compounds retrieved from the drug bank database against PD-L1 protein. The binding affinity of the compounds was determined using the glide XP docking programme. Furthermore, prime-MM/GBSA, DFT calculations, and RF score were used to precisely re-score the binding free energy of the docked complexes. In addition, the ADME and toxicity profiles for the lead compounds were also examined to address PK/PD characteristics. Altogether, the screening process identified three molecules, namely DB01238, DB06016 and DB01167 as potential therapeutics for the PD-L1 protein. To conclude, a molecular dynamic simulation of 100 ns was run to characterise the stability and inhibitory action of the three lead compounds. The results from the simulation study confirm the robust structural and thermodynamic stability of DB01238 than other investigated molecules. Thus, our findings hypothesize that DB01238 could serve as potential PD-L1 inhibitor in the near future for triple-negative breast cancer patients.

Leveraging decagonal in-silico strategies for uncovering IL-6 inhibitors with precision

Interleukin-6 upregulation leads to various acute phase reactions such as local inflammation and systemic inflammation in many diseases like cancer, multiple sclerosis, rheumatoid arthritis, anemia, and Alzheimer's disease stimulating JAK/STAT3, Ras/MAPK, PI3K-PKB/Akt pathogenic pathways. Since no small molecules are available in the market against IL-6 till now, we have designed a class of small bioactive 1,3 - indanedione (IDC) molecules for inhibiting IL-6 using a decagonal approach computational studies. The IL-6 mutations were mapped in the IL-6 protein (PDB ID: 1ALU) from thorough pharmacogenomic and proteomics studies. The protein-drug interaction networking analysis for 2637 FFDA-approved drugs with IL-6 protein using Cytoscape software showed that 14 drugs have prominent interactions with IL-6. Molecular docking studies showed that the designed compound IDC-24 (-11.8 kcal/mol) and methotrexate (-5.20) bound most strongly to the 1ALU south asian population mutated protein. MMGBSA results indicated that IDC-24 (-41.78 kcal/mol) and methotrexate (-36.81 kcal/mol) had the highest binding energy when compared to the standard molecules LMT-28 (-35.87 kcal/mol) and MDL-A (-26.18 kcal/mol). These results we substantiated by the molecular dynamic studies in which the compound IDC-24 and the methotrexate had the highest stability. Further, the MMPBSA computations produced energies of -28 kcal/mol and -14.69 kcal/mol for IDC-24 and LMT-28. KDeep absolute binding affinity computations revealed energies of -5.81 kcal/mol and -4.74 kcal/mol for IDC-24 and LMT-28 respectively. Finally, our decagonal approach established the compound IDC-24 from the designed 1,3-indanedione library and methotrexate from protein drug interaction networking as suitable HITs against IL-6.

Discovery and evaluation of active compounds from Xuanfei Baidu formula against COVID-19 via SARS-CoV-2 Mpro

BACKGROUND

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) is still a widespread concern. As one of the effective traditional Chinese medicine (TCM) formulae, Xuanfei Baidu formula (XFBD) shows significant efficacy for treatment of COVID-19 patients. However, its antiviral active compounds and mechanism are still unclear.

PURPOSE

In this study, we explored the bioactive compounds of XFBD and its antiviral mechanism by integrating computational analysis and experimental testing.

METHODS

Focusing on the SARS-CoV-2 main protease (M^pro), as a key target in virus transcription and replication, the fluorescence resonance energy transfer (FRET) assay was built to screen out satisfactory natural inhibitors in XFBD. The surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC) were undertaken to verify the binding affinity of ligand-M^pro. Omicron BA.1.1 and BA.2.3 variants were used to evaluate the antiviral activity of the focused compounds in non-cytotoxicity concentrations. For introducing the molecular mechanism, computational modeling and NMR spectra were employed to characterize the ligand-binding modes and identify the ligand-binding site on M^pro.

RESULTS

From a library of 83 natural compounds, acteoside, licochalcone B, licochalcone D, linoleic acid, and physcion showed the satisfactory inhibition effects on M^pro with IC₅₀ ranging from 1.93 to 42.96 µM, which were further verified by SPR. Showing the excellent binding affinity, acteoside was witnessed to gain valuable insights into the thermodynamic signatures by ITC and presented antiviral activity on Omicron BA.1.1 and BA.2.3 variants in vitro. The results revealed that acteoside inhibited M^pro via forming the hydrogen bond between 7-H of acteoside and M^pro.

CONCLUSION

Acteoside is regarded as a representative active natural compound in XFBD to inhibit replication of SARS-CoV-2, which provides the antiviral evidence and some insights into the identification of SARS-CoV-2 M^pro natural inhibitors.

In Silico Design of New Dual Inhibitors of SARS-CoV-2 MPRO through Ligand- and Structure-Based Methods

The viral main protease is one of the most attractive targets among all key enzymes involved in the life cycle of SARS-CoV-2. Considering its mechanism of action, both the catalytic and dimerization regions could represent crucial sites for modulating its activity. Dual-binding the SARS-CoV-2 main protease inhibitors could arrest the replication process of the virus by simultaneously preventing dimerization and proteolytic activity. To this aim, in the present work, we identified two series' of small molecules with a significant affinity for SARS-CoV-2 M^PRO, by a hybrid virtual screening protocol, combining ligand- and structure-based approaches with multivariate statistical analysis. The Biotarget Predictor Tool was used to filter a large in-house structural database and select a set of benzo[b]thiophene and benzo[b]furan derivatives. ADME properties were investigated, and induced fit docking studies were performed to confirm the DRUDIT prediction. Principal component analysis and docking protocol at the SARS-CoV-2 M^PRO dimerization site enable the identification of compounds 1b,c,i,l and 2i,l as promising drug molecules, showing favorable dual binding site affinity on SARS-CoV-2 M^PRO.

In vitro and in silico evaluations of actinomycin X2and actinomycin D as potent anti-tuberculosis agents

Background

Multidrug-resistant tuberculosis (MDR-TB) is one of the world's most devastating contagious diseases and is caused by the MDR-Mycobacterium tuberculosis (MDR-Mtb) bacteria. It is therefore essential to identify novel anti-TB drug candidates and target proteins to treat MDR-TB. Here, in vitro and in silico studies were used to investigate the anti-TB potential of two newly sourced actinomycins, actinomycin-X₂ (act-X₂) and actinomycin-D (act-D), from the Streptomyces smyrnaeus strain UKAQ_23 (isolated from the Jubail industrial city of Saudi Arabia).

Methods

The anti-TB activity of the isolated actinomycins was assessed in vitro using the Mtb H37Ra, Mycobacterium bovis (BCG), and Mtb H37Rv bacterial strains, using the Microplate Alamar Blue Assay (MABA) method. In silico molecular docking studies were conducted using sixteen anti-TB drug target proteins using the AutoDock Vina 1.1.2 tool. The molecular dynamics (MD) simulations for both actinomycins were then performed with the most suitable target proteins, using the GROningen MAchine For Chemical Simulations (GROMACS) simulation software (GROMACS 2020.4), with the Chemistry at HARvard Macromolecular Mechanics 36m (CHARMM36m) forcefield for proteins and the CHARMM General Force Field (CGenFF) for ligands.

Results

In vitro results for the Mtb H37Ra, BCG, and Mtb H37Rv strains showed that act-X₂ had minimum inhibitory concentration (MIC) values of 1.56 ± 0.0, 1.56 ± 0.0, and 2.64 ± 0.07 µg/mL and act-D had MIC values of 1.56 ± 0.0, 1.56 ± 0.0, and 1.80 ± 0.24 µg/mL respectively. The in silico molecular docking results showed that protein kinase PknB was the preferred target for both actinomycins, while KasA and pantothenate synthetase were the least preferred targets for act-X₂and act-D respectively. The molecular dynamics (MD) results demonstrated that act-X₂ and act-D remained stable inside the binding region of PknB throughout the simulation period. The MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) binding energy calculations showed that act-X₂ was more potent than act-D.

Conclusion

In conclusion, our results suggest that both actinomycins X₂ and D are highly potent anti-TB drug candidates. We show that act-X₂is better able to antagonistically interact with the protein kinase PknB target than act-D, and thus has more potential as a new anti-TB drug candidate.

In silico investigations identified Butyl Xanalterate to competently target CK2α (CSNK2A1) for therapy of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is an incurable malignancy of B-cells. In this study, bioinformatics analyses were conducted to identify possible pathogenic roles of CK2α, which is a protein encoded by CSNK2A1, in the progression and aggressiveness of CLL. Furthermore, various computational tools were used to search for a competent inhibitor of CK2α from fungal metabolites that could be proposed for CLL therapy. In CLL patients, high-expression of CSNK2A1 was associated with early need for therapy (n = 130, p < 0.0001) and short overall survival (OS; n = 107, p = 0.005). Consistently, bioinformatics analyses showed CSNK2A1 to associate with/play roles in CLL proliferation and survival-dependent pathways. Furthermore, PPI network analysis identified interaction partners of CK2α (PPI enrichment p value = 1 × 10^-16) that associated with early need for therapy (n = 130, p < 0.003) and have been known to heavily impact on the progression of CLL. These findings constructed a rational for targeting CK2α for CLL therapy. Consequently, computational analyses reported 35 fungal metabolites out of 5820 (filtered from 19,967 metabolites) to have lower binding energy (ΔG: - 10.9 to - 11.7 kcal/mol) and better binding affinity (Kd: 9.77 × 10⁷ M^-1 to 3.77 × 10⁸ M^-1) compared with the native ligand (ΔG: - 10.8, Kd: 8.3 × 10⁷ M-^-1). Furthermore, molecular dynamics simulation study established that Butyl Xanalterate-CK2α complex continuously remained stable throughout the simulation time (100 ns). Moreover, Butyl Xanalterate interacted with most of the catalytic residues, where complex was stabilized by more than 65% hydrogen bond interactions, and a significant hydrophobic interaction with residue Phe113. Here, high-expression of CSNK2A1 was implicated in the progression and poor prognosis of CLL, making it a potential therapeutic target in the disease. Butyl Xanalterate showed stable and strong interactions with CK2α, thus we propose it as a competitive inhibitor of CK2α for CLL therapy.

Interaction of the new inhibitor paxlovid (PF-07321332) and ivermectin with the monomer of the main protease SARS-CoV-2: A volumetric study based on molecular dynamics, elastic networks, classical thermodynamics and SPT

The COVID-19 pandemic has accelerated the study of drugs, most notably ivermectin and more recently Paxlovid (PF-07321332) which is in phase III clinical trials with experimental data showing covalent binding to the viral protease M^pro. Theoretical developments of catalytic site-directed docking support thermodynamically feasible non-covalent binding to M^pro. Here we show that Paxlovid binds non-covalently at regions other than the catalytic sites with energies stronger than reported and at the same binding site as the ivermectin B1a homologue, all through theoretical methodologies, including blind docking. We volumetrically characterize the non-covalent interaction of the ivermectin homologues (avermectins B1a and B1b) and Paxlovid with the mM^pro monomer, through molecular dynamics and scaled particle theory (SPT). Using the fluctuation-dissipation theorem (FDT), we estimated the electric dipole moment fluctuations at the surface of each of complex involved in this study, with similar trends to that observed in the interaction volume. Using fluctuations of the intrinsic volume and the number of flexible fragments of proteins using anisotropic and Gaussian elastic networks (ANM+GNM) suggests the complexes with ivermectin are more dynamic and flexible than the unbound monomer. In contrast, the binding of Paxlovid to mM^pro shows that the mM^pro-PF complex is the least structurally dynamic of all the species measured in this investigation. The results support a differential molecular mechanism of the ivermectin and PF homologues in the mM^pro monomer. Finally, the results showed that Paxlovid despite beingbound in different sites through covalent or non-covalent forms behaves similarly in terms of its structural flexibility and volumetric behaviour.

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.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Toward the Discovery of a Novel Class of Leads for High Altitude Disorders by Virtual Screening and Molecular Dynamics Approaches Targeting Carbonic Anhydrase

For decades, carbonic anhydrase (CA) inhibitors, most notably the acetazolamide-bearing 1,3,4-thiadiazole moiety, have been exploited at high altitudes to alleviate acute mountain sickness, a syndrome of symptomatic sensitivity to the altitude characterized by nausea, lethargy, headache, anorexia, and inadequate sleep. Therefore, inhibition of CA may be a promising therapeutic strategy for high-altitude disorders. In this study, co-crystallized inhibitors with 1,3,4-thiadiazole, 1,3-benzothiazole, and 1,2,5-oxadiazole scaffolds were employed for pharmacophore-based virtual screening of the ZINC database, followed by molecular docking and molecular dynamics simulation studies against CA to find possible ligands that may emerge as promising inhibitors. Compared to the co-crystal ligands of PDB-1YDB, 6BCC, and 6IC2, ZINC12336992, ZINC24751284, and ZINC58324738 had the highest docking scores of -9.0, -9.0, and -8.9 kcal/mol, respectively. A molecular dynamics (MD) simulation analysis of 100 ns was conducted to verify the interactions of the top-scoring molecules with CA. The system's backbone revealed minor fluctuations, indicating that the CA-ligand complex was stable during the simulation period. Simulated trajectories were used for the MM-GBSA analysis, showing free binding energies of -16.00 ± 0.19, -21.04 ± 0.17, and -19.70 ± 0.18 kcal/mol, respectively. In addition, study of the frontier molecular orbitals of these compounds by DFT-based optimization at the level of B3LYP and the 6-311G(d,p) basis set showed negative values of the HOMO and LUMO, indicating that the ligands are energetically stable, which is essential for forming a stable ligand-protein complex. These molecules may prove to be a promising therapy for high-altitude disorders, necessitating further investigations.

Strain Improvement and Strain Maintenance Revisited. The Use of Actinoplanes teichomyceticus ATCC 31121 Protoplasts in the Identification of Candidates for Enhanced Teicoplanin Production

Multicellular cooperation in actinomycetes is a division of labor-based beneficial trait where phenotypically specialized clonal subpopulations, or genetically distinct lineages, perform complementary tasks. The division of labor improves the access to nutrients and optimizes reproductive and vegetative tasks while reducing the costly production of secondary metabolites and/or of secreted enzymes. In this study, we took advantage of the possibility to isolate genetically distinct lineages deriving from the division of labor, for the isolation of heterogeneous teicoplanin producer phenotypes from Actinoplanes teichomyceticus ATCC 31121. In order to efficiently separate phenotypes and associated genomes, we produced and regenerated protoplasts. This approach turned out to be a rapid and effective strain improvement method, as it allowed the identification of those phenotypes in the population that produced higher teicoplanin amounts. Interestingly, a heterogeneous teicoplanin complex productivity pattern was also identified among the clones. This study suggests that strain improvement and strain maintenance should be integrated with the use of protoplasts as a strategy to unravel the hidden industrial potential of vegetative mycelium.

Host Cell and SARS-CoV-2-Associated Molecular Structures and Factors as Potential Therapeutic Targets

Coronavirus disease 19 (COVID-19) is caused by an enveloped, positive-sense, single-stranded RNA virus, referred to as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which belongs to the realm Riboviria, order Nidovirales, family Coronaviridae, genus Betacoronavirus and the species Severe acute respiratory syndrome-related coronavirus. This viral disease is characterized by a myriad of varying symptoms, such as pyrexia, cough, hemoptysis, dyspnoea, diarrhea, muscle soreness, dysosmia, lymphopenia and dysgeusia amongst others. The virus mainly infects humans, various other mammals, avian species and some other companion livestock. SARS-CoV-2 cellular entry is primarily accomplished by molecular interaction between the virus’s spike (S) protein and the host cell surface receptor, angiotensin-converting enzyme 2 (ACE2), although other host cell-associated receptors/factors, such as neuropilin 1 (NRP-1) and neuropilin 2 (NRP-2), C-type lectin receptors (CLRs), as well as proteases such as TMPRSS2 (transmembrane serine protease 2) and furin, might also play a crucial role in infection, tropism, pathogenesis and clinical outcome. Furthermore, several structural and non-structural proteins of the virus themselves are very critical in determining the clinical outcome following infection. Considering such critical role(s) of the abovementioned host cell receptors, associated proteases/factors and virus structural/non-structural proteins (NSPs), it may be quite prudent to therapeutically target them through a multipronged clinical regimen to combat the disease.