Setmelanotide optimization through fragment-growing, molecular docking in-silico method targeting MC4 receptor

Obesity has emerged as a global issue, but with the complex structures of multiple related important targets and their agonists or antagonists determined, the mechanism of ligand-protein interaction may offer new chances for developing new generation agonists anti-obesity. Based on the molecule surface of the cryo-EM protein structure 7AUE, we tried to replace D-Ala3 with D-Met in setmelanotide as the linker site for fragment-growing with De novo evolution. The simulation results indicate that the derivatives could improve the binding abilities with the melanocortin 4 receptor and the selectivity over the melanocortin 1 receptor. The improved selectivity of the newly designed derivatives is mainly due to the shape difference of the molecular surface at the orthosteric peptide-binding pocket between melanocortin 4 receptor and melanocortin 1 receptor. The new extended fragments could not only enhance the binding affinities but also function as a gripper to seize the pore, making it easier to balance and stabilize the other component of the new derivatives. Although it is challenging to synthesize the compounds designed in silico, this study may perhaps serve as a trigger for additional anti-obesity research. Communicated by Ramaswamy H. Sarma</p

DataSheet2_Identification of potential inhibitors of omicron variant of SARS-Cov-2 RBD based virtual screening, MD simulation, and DFT.docx

Emergence of the SARS-CoV-2 Omicron variant of concern (VOC; B.1.1.529) resulted in a new peak of the COVID-19 pandemic, which called for development of effective therapeutics against the Omicron VOC. The receptor binding domain (RBD) of the spike protein, which is responsible for recognition and binding of the human ACE2 receptor protein, is a potential drug target. Mutations in receptor binding domain of the S-protein have been postulated to enhance the binding strength of the Omicron VOC to host proteins. In this study, bioinformatic analyses were performed to screen for potential therapeutic compounds targeting the omicron VOC. A total of 92,699 compounds were screened from different libraries based on receptor binding domain of the S-protein via docking and binding free energy analysis, yielding the top 5 best hits. Dynamic simulation trajectory analysis and binding free energy decomposition were used to determine the inhibitory mechanism of candidate molecules by focusing on their interactions with recognized residues on receptor binding domain. The ADMET prediction and DFT calculations were conducted to determine the pharmacokinetic parameters and precise chemical properties of the identified molecules. The molecular properties of the identified molecules and their ability to interfere with recognition of the human ACE2 receptors by receptor binding domain suggest that they are potential therapeutic agents for SARS-CoV-2 Omicron VOC.</p

DataSheet1_Identification of potential inhibitors of omicron variant of SARS-Cov-2 RBD based virtual screening, MD simulation, and DFT.CSV

Emergence of the SARS-CoV-2 Omicron variant of concern (VOC; B.1.1.529) resulted in a new peak of the COVID-19 pandemic, which called for development of effective therapeutics against the Omicron VOC. The receptor binding domain (RBD) of the spike protein, which is responsible for recognition and binding of the human ACE2 receptor protein, is a potential drug target. Mutations in receptor binding domain of the S-protein have been postulated to enhance the binding strength of the Omicron VOC to host proteins. In this study, bioinformatic analyses were performed to screen for potential therapeutic compounds targeting the omicron VOC. A total of 92,699 compounds were screened from different libraries based on receptor binding domain of the S-protein via docking and binding free energy analysis, yielding the top 5 best hits. Dynamic simulation trajectory analysis and binding free energy decomposition were used to determine the inhibitory mechanism of candidate molecules by focusing on their interactions with recognized residues on receptor binding domain. The ADMET prediction and DFT calculations were conducted to determine the pharmacokinetic parameters and precise chemical properties of the identified molecules. The molecular properties of the identified molecules and their ability to interfere with recognition of the human ACE2 receptors by receptor binding domain suggest that they are potential therapeutic agents for SARS-CoV-2 Omicron VOC.</p

Probing and Engineering Key Residues for Bis‑<i>C</i>‑glycosylation and Promiscuity of a <i>C</i>‑Glycosyltransferase

<i>C</i>-Glycosyltransferases (CGTs) are powerful tools for the <i>C</i>-glycosylation of natural and unnatural products. However, CGTs able to catalyze bis-<i>C</i>-glycosylation are very rare and the key amino acids of which have not been uncovered. Here, we discovered a <i>C</i>-glycosyltransferase MiCGTb from Mangifera indica that has the capacity for bis-<i>C</i>-glycosylation. Further studies on active-site motifs revealed that I152 of MiCGTb was the critical amino acid residue for the second <i>C</i>-glycosylation and its S60/V100/T104 residues were pivotal for bis-<i>C</i>-glycosylation activity. Moreover, we developed a panel of variants with acceptor and donor promiscuity by site-directed mutagenesis. Among these variants, a mutant MiCGT-E152L displayed a broader acceptor scope for bis-<i>C</i>-glycosylation, and three mutants of MiCGTb exhibited sugar donor promiscuity toward structurally varied α-d- and β-l-glycosyl donors. Our work provides insights into the pivotal amino acid residues of CGTs for bis-<i>C</i>-glycosylation and biocatalytic tools to efficiently produce structurally diverse bis-<i>C</i>-glycosides with two identical or different sugar moieties in drug discovery