Amentoflavone derivatives significantly act towards the main protease (3CLPRO/MPRO) of SARS-CoV-2: in silico admet profiling, molecular docking, molecular dynamics simulation, network pharmacology.

SARS-CoV-2 is the foremost culprit of the novel coronavirus disease 2019 (nCoV-19 and/or simply COVID-19) and poses a threat to the continued life of humans on the planet and create pandemic issue globally. The 3-chymotrypsin-like protease (MPRO or 3CLPRO) is the crucial protease enzyme of SARS-CoV-2, which directly involves the processing and release of translated non-structural proteins (nsps), and therefore involves the development of virus pathogenesis along with outbreak the forecasting of COVID-19 symptoms. Moreover, SARS-CoV-2 infections can be inhibited by plant-derived chemicals like amentoflavone derivatives, which could be used to develop an anti-COVID-19 drug. Our research study is designed to conduct an in silico analysis on derivatives of amentoflavone (isoginkgetin, putraflavone, 4''''''-methylamentoflavone, bilobetin, ginkgetin, sotetsuflavone, sequoiaflavone, heveaflavone, kayaflavone, and sciadopitysin) for targeting the non-structural protein of SARS-CoV-2, and subsequently further validate to confirm their antiviral ability. To conduct all the in silico experiments with the derivatives of amentoflavone against the MPRO protein, both computerized tools and online servers were applied; notably the software used is UCSF Chimera (version 1.14), PyRx, PyMoL, BIOVIA Discovery Studio tool (version 4.5), YASARA (dynamics simulator), and Cytoscape. Besides, as part of the online tools, the SwissDME and pKCSM were employed. The research study was proposed to implement molecular docking investigations utilizing compounds that were found to be effective against the viral primary protease (MPRO). MPRO protein interacted strongly with 10 amentoflavone derivatives. Every time, amentoflavone compounds outperformed the FDA-approved antiviral medicine that is currently underused in COVID-19 in terms of binding affinity (- 8.9, - 9.4, - 9.7, - 9.1, - 9.3, - 9.0, - 9.7, - 9.3, - 8.8, and - 9.0 kcal/mol, respectively). The best-selected derivatives of amentoflavone also possessed potential results in 100 ns molecular dynamic simulation (MDS) validation. It is conceivable that based on our in silico research these selected amentoflavone derivatives more precisely 4''''''-methylamentoflavone, ginkgetin, and sequoiaflavone have potential for serving as promising lead drugs against SARS-CoV-2 infection. In consequence, it is recommended that additional in vitro as well as in vivo research studies have to be conducted to support the conclusions of this current research study.

Successes and Failures of Static Aptamer-Target 3D Docking Models.

While Molecular Dynamics simulation programs are probably superior for predicting the binding and affinity of aptamers and their cognate ligands, such molecular dynamics programs require more computing power and analysis time than static docking programs that are more widely accessible to the scientific community on the internet. Static docking programs can be used to investigate the geometric fit of rigid DNA or RNA aptamer 3D structures and their ligands to aid in predicting the relative affinities and cross-reactivity of various potential ligands. Herein, the author describes when such static 3D docking analysis has worked well to produce useful predictions or confirmation of high-affinity aptamer interactions or successful aptamer beacon behavior and when it has not worked well. The analysis of why failures may occur with static 3D computer models is also discussed.

Beacons Contribute Valuable Empirical Information to Theoretical 3-D Aptamer-Peptide Binding.

DNA aptamers were developed against five different peptides from the known binding regions of anti-Cytomegalovirus and anti-Herpes Simplex Virus-2 antibodies and the aptamers were ranked by relative affinity based on an ELISA-like (ELASA) microplate assay. The secondary structures of the top five highest affinity aptamers were studied for stem-loop commonalities and the most probable peptide binding sites. Two of these stem-loop structures were converted into beacons by addition of TYE 665 dye on the 5' end and Iowa Black quencher on the 3' end. When competed against increasing concentrations of each of the five peptides, only three of the possible ten interactions demonstrated "lights on" fluorescence beacon responses. When modeled by generation of PDB files, after passage through PATCHDOCK and YASARA, two of the aptamer beacon-peptide interactions showed no theoretical evidence of separating the G-C stem-loop region, despite clear empirical evidence of separation of the fluorophore and quencher beyond the Förster distance leading to abundant fluorescence. And in the second beacon's case, YASARA modeling suggested that the beacon was always open despite clear empirical evidence that it was not (no fluorescence response) and only opened in the presence of one of the five peptides. These results are interpreted as a demonstration that 3-dimensional docking software such as PATCHDOCK and YASARA, which are based on rigid receptor-ligand shape complementarity may not reflect the "induced-fit" interactions between aptamers and their cognate targets. Therefore, for the most complete and accurate picture of aptamer-peptide binding, several theoretical and empirical (e.g., beacon fluorescence) analysis methods may be needed.

New ways to boost molecular dynamics simulations.

We describe a set of algorithms that allow to simulate dihydrofolate reductase (DHFR, a common benchmark) with the AMBER all-atom force field at 160 nanoseconds/day on a single Intel Core i7 5960X CPU (no graphics processing unit (GPU), 23,786 atoms, particle mesh Ewald (PME), 8.0 Å cutoff, correct atom masses, reproducible trajectory, CPU with 3.6 GHz, no turbo boost, 8 AVX registers). The new features include a mixed multiple time-step algorithm (reaching 5 fs), a tuned version of LINCS to constrain bond angles, the fusion of pair list creation and force calculation, pressure coupling with a "densostat," and exploitation of new CPU instruction sets like AVX2. The impact of Intel's new transactional memory, atomic instructions, and sloppy pair lists is also analyzed. The algorithms map well to GPUs and can automatically handle most Protein Data Bank (PDB) files including ligands. An implementation is available as part of the YASARA molecular modeling and simulation program from www.YASARA.org.

Exploring the potential of Scabiosa columbaria in Alzheimer's disease treatment: An in silico approach.

Objectives: Alzheimer's disease (AD) is posing an increasing global threat and currently lacks effective treatments. Therefore, this study was aimed at exploring phytochemicals in Scabiosa columbaria (S. columbaria) as inhibitors of acetylcholinesterase (AChE), ß-site APP cleavage enzyme 1 (BACE1), and TNF-α converting enzyme (TACE) in AD. S. columbaria contains various bioactive compounds, such as chlorogenic acid, linalool, and catechins, which are known for their detoxification properties, capacity to resist and manage harmful moisture buildup, and therapeutic roles in COVID-19. Several studies have also shown that S. columbaria extract has strong antioxidant activity, and may potentially decrease neuroinflammation in AD. Therefore, this study investigated the interactions between S. columbaria phytochemicals and key enzymes associated with AD, thus providing opportunities for the development of new therapeutic candidates. Methods: A total of 27 phytochemicals were evaluated for their inhibitory activity against AChE, BACE1, and TACE with YASARA Structure. ADMET profiles and toxicity were assessed. The top candidate compounds underwent 100 ns MD simulations. Results: All ligands met Lipinski's rule and showed low toxicity. Catechins, compared with the known drug galantamine, showed higher inhibitory activity and interacted with additional active sites on AChE, thus suggesting potentially higher efficacy. Moreover, chlorogenic acid showed stronger inhibitory activity against TACE than the control drug (aryl-sulfonamide), thereby suggesting a different mechanism of action. MD simulation revealed that the formed complexes had good stability. However, further exploration is necessary. Conclusion: S. columbaria derivative compounds are promising drug candidates because of their properties, including the affinity of chlorogenic acid toward TACE and hydrogen bond enhancing ligand-receptor interactions. MD simulation indicated stable ligand-protein complexes, and the radius of gyration and MM-PBSA calculations revealed favorable binding and interaction energies. Our findings demonstrate the identified compounds' potential for further drug development.

Structural anomalies in a published NMR-derived structure of IRAK-M.

Signaling by Toll-Like Receptors and the Interleukin-1 Receptor (IL1-R) involves intracellular binding of MyD88, followed by assembly of IL1-R Associated Kinases (IRAKs) into the so-called Myddosome. Using NMR, Nechama et al. determined the structure of the IRAK-M death domain monomer (PDBid: 5UKE). With this structure, they performed a docking study to model the location of IRAK-M in the Myddosome. Based on this, they present a molecular basis for selectivity of IRAK-M towards IRAK1 over IRAK2 binding. When we attempted to use 5UKE as a homology modeling template, we noticed that our 5UKE-based models had structural issues, such as disallowed torsion angles and solvent exposed tryptophans. We therefore analyzed the NMR ensemble of 5UKE using structure validation tools and we compared 5UKE with homologous high-resolution X-ray structures. We identified several structural anomalies in 5UKE, including packing issues, frayed helices and improbable side chain conformations. We used Yasara to build a homology model, based on two high resolution death domain crystal structures, as an alternative model for the IRAK-M death domain (atomic coordinates, modeling details and validation are available at https://swift.cmbi.umcn.nl/gv/service/5uke/). Our model agrees better with known death domain structure information than 5UKE and also with the chemical shift data that was deposited for 5UKE.

Interactions of Flavone and Steroid from A. subintegra as Potential Inhibitors for Porcine Pancreatic Lipase.

BACKGROUND: Obesity is one serious health condition that contributes to various chronic diseases. The inhibition of pancreatic lipase is a promising treatment for obesity. OBJECTIVE: The present study was designed to investigate anti-porcine pancreatic lipase effect of isolated compounds from Aquilaria subintegra and its mechanism. METHODS: Compounds were isolated with serial column chromatography and their structure were identified using spectroscopic methods. Isolated compounds were tested for anti-lipase potential activity using colorimetric assay. The prediction of energy binding between isolated compounds and enzyme was described using YASARA software. RESULTS: Four compounds were successfully isolated from the bark of A. subintegra, namely, 5- hydroxy-7,4'-dimethoxyflavone, luteolin-7,3',4'-trimethyl ether, 5,3'-dihydroxy-7,4'-dimethoxyflavone and ß-sitosterol. The results indicated that all compounds displayed promising pancreatic lipase inhibitory activity ranging between of 6% to 53% inhibition. Compound 5-hydroxy-7,4'- dimethoxyflavone was a competitive inhibitor and decreases the enzyme catalysis. Meanwhile, ß- sitosterol was a non- competitive inhibitor since the latter was bind allosterically toward enzyme. CONCLUSION: This finding is significant for further investigation of bioactive compounds from A. subintegra on animal study.

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease.

Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

An in silico approach to understand the structure-function properties of a serine protease (Bacifrinase) from Bacillus cereus and experimental evidence to support the interaction of Bacifrinase with fibrinogen and thrombin.

Microbial fibrinogenolytic serine proteases find therapeutic applications in the treatment of thrombosis- and hyperfibrinogenemia-associated disorders. However, analysis of structure-function properties of an enzyme is utmost important before its commercial application. In this study, an attempt has been made to understand the structure of a fibrinogenolytic protease enzyme, "Bacifrinase" from Bacillus cereus strain AB01. From the molecular dynamics trajectory analysis, the modelled three-dimensional structure of the protease was found to be stable and the presence of a catalytic triad made up of Asp102, His83 and Ser195 suggests that it is a serine protease. To understand the mechanism of enzyme-substrate and enzyme-inhibitor interactions, the equilibrated protein was docked with human fibrinogen (the physiological substrate of this enzyme), human thrombin and with ten selective protease inhibitors. The Bacifrinase-chymostatin interaction was the strongest among the selected protease inhibitors. The serine protease inhibitor phenyl methane sulphonyl fluoride was found to interact with the Ser134 residue of Bacifrinase. Furthermore, protein-protein docking study revealed the fibrinogenolytic property of Bacifrinase and its interaction with Aα-, Bß- and Cγ-chains human fibrinogen to a different extent. However, biochemical analysis showed that Bacifrinase did not hydrolyse the γ-chain of fibrinogen. The in silico and spectrofluorometric studies also showed interaction of Bacifrinase with thrombin as well as fibrinogen with a Kd value of 16.5 and .81 nM, respectively. Our findings have shed light on the salient structural features of Bacifrinase and confirm that it is a fibrinogenolytic serine protease.

Molecular Dynamics of Rab7::REP1::GGTase-II Ternary Complex and Identification of Their Putative Drug Binding Sites.

The structure-function correlation of membrane proteins have been a difficult task, particularly in context to transient protein complexes. The molecular simulation of ternary complex of Rab7::REP1::GGTase-II was carried out to understand the basic structural events occurring during the prenylation event of Rab proteins, using the software YASARA. The study suggested that the C-terminus of Rab7 has to be in completely extended conformation during prenylation to reach the active site of RabGGTase-II. Also, attempt was made to find putative drug binding sites on the ternary complex of Rab7::REP1::GGTase-II using Q-SiteFinder programme. The comprehensive consensus probe generated by the program revealed a total of 10 major pockets as putative drug binding sites on Rab7::REP:: GGTase-II ternary complex. These pockets were found on REP protein and GGTase protein subunits. The Rab7 was found to be devoid of any putative drug binding sites in the ternary complex. The phylogenetic analysis of 60 Rab proteins of human was carried out using PHYLIP and study indicated the close phylogenetic relationship between Rab7 and Rab9 proteins of human and hence with further in silico study, the present observations can be extrapolated to Rab9 proteins. The study paves a good platform for further experimental verifications of the findings and other in silico studies like identifying the potential drug targets by searching the putative drug binding sites, generating pharmacophoric pattern, searching or constructing suitable ligand and docking studies.