Abstract:An understanding of the interaction between the antibody and its targeted antigen and knowing of the epitopes are critical for the development of monoclonal antibody drugs. Complement factor H (CFH) is implied to play a role in tumor growth and metastasis. An autoantibody to CHF is associated with anti-tumor cell activity. The interaction of a human monoclonal antibody Ab42 that was isolated from a cancer patient with CFH polypeptide (pCFH) antigen was analyzed by molecular docking, molecular dynamics (MD) sim… Show more
“…According to the results of the residue contribution analysis in the MM–GBSA, for the three systems of LPV, NFV, and RTV, we selected five key points, including His41, Met49, Cys145, Met165, and Glu166 for CAS research, among which His41 and Cys145 are Mpro catalytic residues ( Figure 10 ). Detailed parameters of CAS are displayed in our previous work [ 28 ].…”
SARS-CoV-2 is highly homologous to SARS-CoV. To date, the main protease (Mpro) of SARS-CoV-2 is regarded as an important drug target for the treatment of Coronavirus Disease 2019 (COVID-19). Some experiments confirmed that several HIV protease inhibitors present the inhibitory effects on the replication of SARS-CoV-2 by inhibiting Mpro. However, the mechanism of action has still not been studied very clearly. In this work, the interaction mechanism of four HIV protease inhibitors Darunavir (DRV), Lopinavir (LPV), Nelfinavir (NFV), and Ritonavire (RTV) targeting SARS-CoV-2 Mpro was explored by applying docking, molecular dynamics (MD) simulations, and MM–GBSA methods using the broad-spectrum antiviral drug Ribavirin (RBV) as the negative and nonspecific control. Our results revealed that LPV, RTV, and NFV have higher binding affinities with Mpro, and they all interact with catalytic residues His41 and the other two key amino acids Met49 and Met165. Pharmacophore model analysis further revealed that the aromatic ring, hydrogen bond donor, and hydrophobic group are the essential infrastructure of Mpro inhibitors. Overall, this study applied computational simulation methods to study the interaction mechanism of HIV-1 protease inhibitors with SARS-CoV-2 Mpro, and the findings provide useful insights for the development of novel anti-SARS-CoV-2 agents for the treatment of COVID-19.
“…According to the results of the residue contribution analysis in the MM–GBSA, for the three systems of LPV, NFV, and RTV, we selected five key points, including His41, Met49, Cys145, Met165, and Glu166 for CAS research, among which His41 and Cys145 are Mpro catalytic residues ( Figure 10 ). Detailed parameters of CAS are displayed in our previous work [ 28 ].…”
SARS-CoV-2 is highly homologous to SARS-CoV. To date, the main protease (Mpro) of SARS-CoV-2 is regarded as an important drug target for the treatment of Coronavirus Disease 2019 (COVID-19). Some experiments confirmed that several HIV protease inhibitors present the inhibitory effects on the replication of SARS-CoV-2 by inhibiting Mpro. However, the mechanism of action has still not been studied very clearly. In this work, the interaction mechanism of four HIV protease inhibitors Darunavir (DRV), Lopinavir (LPV), Nelfinavir (NFV), and Ritonavire (RTV) targeting SARS-CoV-2 Mpro was explored by applying docking, molecular dynamics (MD) simulations, and MM–GBSA methods using the broad-spectrum antiviral drug Ribavirin (RBV) as the negative and nonspecific control. Our results revealed that LPV, RTV, and NFV have higher binding affinities with Mpro, and they all interact with catalytic residues His41 and the other two key amino acids Met49 and Met165. Pharmacophore model analysis further revealed that the aromatic ring, hydrogen bond donor, and hydrophobic group are the essential infrastructure of Mpro inhibitors. Overall, this study applied computational simulation methods to study the interaction mechanism of HIV-1 protease inhibitors with SARS-CoV-2 Mpro, and the findings provide useful insights for the development of novel anti-SARS-CoV-2 agents for the treatment of COVID-19.
“…2 . For a simple and efficient calculation, only the RMSD of the protein backbone is considered by the authors; this technique is typically employed in many previous studies [34] , [65] . Fig.…”
Section: Resultsmentioning
confidence: 99%
“…However, there have been no in-depth studies on IgG-spA/spG complexes, even though they are the most prevalent combination in affinity chromatography. This is because most of the few direct and quantitative measurement studies on protein binding have been primarily focused on monomeric ligand complexes (e.g., linear short peptide with a small amount of residue rather than multimeric complexes) [33] , [34] , [35] , [36] , [37] . Moreover, the studies on larger ligands have been hampered by the inconvenience of modeling many rotatable bonds in flexible peptides and obtaining accurate high-resolution models of binding interfaces [38] .…”
“…Beyond the use of experimental data, prediction accuracy can also be improved by integrating docking tools with other computational techniques, such as molecular dynamics-based approaches (47,48), key interactions (49), and prediction of the binding site (50); molecular dynamics was done by FG-MD server (51).…”
Background: Testis-specific protein on Y chromosome (TSPY) is the output of a tandem gene cluster. TSPY expression has been observed in gonadoblastoma and numerous distinct kinds of germ cell tumors, such as carcinoma in situ/intratubular germ cell neoplasia, seminoma, and extragonadal intracranial germ cell tumors (GCT). Myrtus communis extract rich in α-pinene showed high antioxidant and anticancer activity against a TSPY. Methods: The molecular weight and theoretical isoelectric of the TSPY proteins were calculated, using the ExPASSY ProtParam tools. Some software like mega 6, BioEdit, NEB cutter (New England Biolabs), and CAP3 were used to analyze clustering and find restriction enzymes on the TSPY sequence. To evaluate the nucleotide diversity of all sequences, the number of diverse situations and Tajima’s and Watterson’s estimators of theta were assessed. Nucleotide polymorphism can be measured by several parameters, such as haplotypes diversity, nucleotide diversity, Theta using Dnasp software. To find interaction networks of protein-protein search tool for the retrieval of interacting genes/proteins (STRING) tools and to predict 3D structure, SWISS-MODEL was used; however, for docking protein-peptide based on interaction, Swiss Dock, Galaxy web, and CABS-dock software were employed. Results: We report a high (0.91) dN/dS index, positive Tajima's D, Fu, and Li’s tests, and a non-significant D test suggesting the occurrence of old modifications or a decrease of newborn mutations in the TSPY gene family. Interestingly, several hub proteins produced a strong chain or an operative module within their protein groups, such as nucleosome assembly protein (1NAP1L), RBMXL2, TBL1Y, and AMELY, which are all associated with the same cellular appliance elements and/or genetic uses. The docking of the TSPY target with α-pinene using docking revealed that the computationally-prognosticated lowest energy networks of TSPY are established by intermolecular hydrogen bonds and stacking interactions. Conclusions: The results of this study demonstrated that α-pinene interacts with the TSPY protein target and could be developed as a promising candidate for the new anticancer agent.
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