Identification of a novel PHGDH covalent inhibitor by chemical proteomics and phenotypic profiling

The first rate-limiting enzyme of the serine synthesis pathway (SSP), phosphoglycerate dehydrogenase (PHGDH), is hyperactive in multiple tumors, which leads to the activation of SSP and promotes tumorigenesis. However, only a few inhibitors of PHGDH have been discovered to date, especially the covalent inhibitors of PHGDH. Here, we identified withangulatin A (WA), a natural small molecule, as a novel covalent inhibitor of PHGDH. Affinity-based protein profiling identified that WA could directly bind to PHGDH and inactivate the enzyme activity of PHGDH. Biolayer interferometry and LC-MS/MS analysis further demonstrated the selective covalent binding of WA to the cysteine 295 residue (Cys295) of PHGDH. With the covalent modification of Cys295, WA blocked the substrate-binding domain (SBD) of PHGDH and exerted an allosteric effect to induce PHGDH inactivation. Further studies revealed that with the inhibition of PHGDH mediated by WA, the glutathione synthesis was decreased and intracellular levels of reactive oxygen species (ROS) were elevated, leading to the inhibition of tumor proliferation. This study indicates WA as a novel PHGDH covalent inhibitor, which identifies Cys295 as a novel allosteric regulatory site of PHGDH and holds great potential in developing anti-tumor agents for targeting PHGDH.

Phytoconstituents from ten natural herbs as potent inhibitors of main protease enzyme of SARS-COV-2: In silico study

BACKGROUND

Lack of treatment of novel Coronavirus disease led to the search of specific antivirals that are capable to inhibit the replication of the virus. The plant kingdom has demonstrated to be an important source of new molecules with antiviral potential.

PURPOSE

The present study aims to utilize various computational tools to identify the most eligible drug candidate that have capabilities to halt the replication of SARS-COV-2 virus by inhibiting Main protease (Mpro) enzyme.

METHODS

We have selected plants whose extracts have inhibitory potential against previously discovered coronaviruses. Their phytoconstituents were surveyed and a library of 100 molecules was prepared. Then, computational tools such as molecular docking, ADMET and molecular dynamic simulations were utilized to screen the compounds and evaluate them against Mpro enzyme.

RESULTS

All the phytoconstituents showed good binding affinities towards Mpro enzyme. Among them laurolitsine possesses the highest binding affinity i.e. -294.1533 kcal/mol. On ADMET analysis of best three ligands were simulated for 1.2 ns, then the stable ligand among them was further simulated for 20 ns. Results revealed that no conformational changes were observed in the laurolitsine w.r.t. protein residues and low RMSD value suggested that the Laurolitsine-protein complex was stable for 20 ns.

CONCLUSION

Laurolitsine, an active constituent of roots of Lindera aggregata, was found to be having good ADMET profile and have capabilities to halt the activity of the enzyme. Therefore, this makes laurolitsine a good drug candidate for the treatment of COVID-19.

Phytoconstituents from ten natural herbs as potent inhibitors of main protease enzyme of SARS-COV-2: In silico study

BACKGROUND

Lack of treatment of novel Coronavirus disease led to the search of specific antivirals that are capable to inhibit the replication of the virus. The plant kingdom has demonstrated to be an important source of new molecules with antiviral potential.

PURPOSE

The present study aims to utilize various computational tools to identify the most eligible drug candidate that have capabilities to halt the replication of SARS-COV-2 virus by inhibiting Main protease (Mpro) enzyme.

METHODS

We have selected plants whose extracts have inhibitory potential against previously discovered coronaviruses. Their phytoconstituents were surveyed and a library of 100 molecules was prepared. Then, computational tools such as molecular docking, ADMET and molecular dynamic simulations were utilized to screen the compounds and evaluate them against Mpro enzyme.

RESULTS

All the phytoconstituents showed good binding affinities towards Mpro enzyme. Among them laurolitsine possesses the highest binding affinity i.e. -294.1533 kcal/mol. On ADMET analysis of best three ligands were simulated for 1.2 ns, then the stable ligand among them was further simulated for 20 ns. Results revealed that no conformational changes were observed in the laurolitsine w.r.t. protein residues and low RMSD value suggested that the Laurolitsine-protein complex was stable for 20 ns.

CONCLUSION

Laurolitsine, an active constituent of roots of Lindera aggregata, was found to be having good ADMET profile and have capabilities to halt the activity of the enzyme. Therefore, this makes laurolitsine a good drug candidate for the treatment of COVID-19.

Identification of SARS-CoV-2 RNA-dependent RNA polymerase inhibitors from the major phytochemicals of Nigella sativa: An in silico approach

The coronavirus disease 2019 (COVID-19), which emerged in December 2019, continues to be a serious health concern worldwide. There is an urgent need to develop effective drugs and vaccines to control the spread of this disease. In the current study, the main phytochemical compounds of Nigella sativa were screened for their binding affinity for the active site of the RNA-dependent RNA polymerase (RdRp) enzyme of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The binding affinity was investigated using molecular docking methods, and the interaction of phytochemicals with the RdRp active site was analyzed and visualized using suitable software. Out of the nine phytochemicals of N. sativa screened in this study, a significant docking score was observed for four compounds, namely α-hederin, dithymoquinone, nigellicine, and nigellidine. Based on the findings of our study, we report that α-hederin, which was found to possess the lowest binding energy (–8.6 kcal/mol) and hence the best binding affinity, is the best inhibitor of RdRp of SARS-CoV-2, among all the compounds screened here. Our results prove that the top four potential phytochemical molecules of N. sativa, especially α-hederin, could be considered for ongoing drug development strategies against SARS-CoV-2. However, further in vitro and in vivo testing are required to confirm the findings of this study.

Molecular dynamics simulation and binding free energy studies of novel leads belonging to the benzofuran class inhibitors of Mycobacterium tuberculosis Polyketide Synthase 13

In this work, the binding mechanism of new Polyketide Synthase 13 (Pks13) inhibitors has been studied through molecular dynamics simulation and free energy calculations. The drug Tam1 and its analogs, belonging to the benzofuran class, were submitted to 100 ns simulations, and according to the results obtained for root mean square deviation, all the simulations converged from approximately 30 ns. For the analysis of backbone flotation, the root mean square fluctuations were plotted for the Cα atoms; analysis revealed that the greatest fluctuation occurred in the residues that are part of the protein lid domain. The binding free energy value (ΔG_bind) obtained for the Tam16 lead molecule was of -51.43 kcal/mol. When comparing this result with the ΔG_bind values for the remaining analogs, the drug Tam16 was found to be the highest ranked: this result is in agreement with the experimental results obtained by Aggarwal and collaborators, where it was verified that the IC₅₀ for Tam16 is the smallest necessary to inhibit the Pks13 (IC₅₀ = 0.19 μM). The energy decomposition analysis suggested that the residues which most interact with inhibitors are: Ser1636, Tyr1637, Asn1640, Ala1667, Phe1670, and Tyr1674, from which the greatest energy contribution to Phe1670 was particularly notable. For the lead molecule Tam16, a hydrogen bond with the hydroxyl of the phenol not observed in the other analogs induced a more stable molecular structure. Aggarwal and colleagues reported this hydrogen bonding as being responsible for the stability of the molecule, optimizing its physic-chemical, toxicological, and pharmacokinetic properties.

A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics

5-HydroxyTriptamine 2A antagonists are potential targets for treatment of various cerebrovascular and cardiovascular disorders. In this study, we have developed and performed a unique screening pipeline for filtering ZINC database compounds on the basis of similarities to known antagonists to determine novel small molecule antagonists of 5-HydroxyTriptamine 2A. The screening pipeline is based on 2D similarity, 3D dissimilarity and a combination of 2D/3D similarity. The shortlisted compounds were docked to a 5-HydroxyTriptamine 2A homology-based model, and complexes with low binding energies (287 complexes) were selected for molecular dynamics (MD) simulations in a lipid bilayer. The MD simulations of the shortlisted compounds in complex with 5-HydroxyTriptamine 2A confirmed the stability of the complexes and revealed novel interaction insights. The receptor residues S239, N343, S242, S159, Y370 and D155 predominantly participate in hydrogen bonding. π-π stacking is observed in F339, F340, F234, W151 and W336, whereas hydrophobic interactions are observed amongst V156, F339, F234, V362, V366, F340, V235, I152 and W151. The known and potential antagonists shortlisted by us have similar overlapping molecular interaction patterns. The 287 potential 5-HydroxyTriptamine 2A antagonists may be experimentally verified.