Binding Interaction Analysis of the Active Site and Its Inhibitors for Neuraminidase (N1 Subtype) of Human Influenza Virus by the Integration of Molecular Docking, FMO Calculation and 3D-QSAR CoMFA Modeling

Abstract

Recently, the worldwide spread of A/H5N1 avian influenza with high virulence has highlighted the potential threat of human influenza pandemic. Tamiflu and Relenza are currently the only two anti-influenza drugs targeting the neuraminidase (NA) enzyme of human influenza virus. Reports of the emergence of drug resistance further make the development of new potent anti-influenza inhibitors a priority. The X-ray crystallographic study of A/H5N1 avian influenza NA subtypes (Russell, R. J. Nature 2006, 443, 45-49) has demonstrated that there exist two genetically distinct groups, group-1 (N1, N4, N5 and N8) and group-2 (N2, N3, N6, N7 and N9), whose conformations are substantially different. The detailed comparison of their active sites has established, heretofore, the most accurate and solid molecular basis of structure and mechanism for the development of new anti-influenza drugs. In the present study, a three-dimensional structure of N1 subtype of human influenza type A virus (N1hA) has been generated by homology modeling using the X-ray crystallographic structure of N1 subtype of avian influenza virus (N1aA) as the template. Binding interaction analysis between the active site and its inhibitors has been performed by combining ab initio fragment molecular orbital (FMO) calculations and three-dimensional quantitative structure-activity relationship with comparative molecular field analysis (3D-QSAR CoMFA) modeling. Integrated with docking-based 3D-QSAR CoMFA modeling, molecular surface property (electrostatic and steric) mapping and FMO pair interaction analysis, a set of new receptor-ligand binding models and bioaffinity predictive models for rational design and virtual screening of more potent inhibitors of N1hA are established. In addition, the flexibility of the loop-150 of N1hA and N1aA has been examined by a series of molecular dynamics simulations.

Two Birds with One Stone? Possible Dual-Targeting H1N1 Inhibitors from Traditional Chinese Medicine

“…The optimal CoMSIA model (r 2 = 0.937, q 2 = 0.673, ONC = 5) consisted of steric and hydrophobic fields, H-bond acceptors and donors. When compared against actual observed activities [102], both CoMFA and CoMSIA models had good predictability, predicting pIC 50 values that differed only marginally from the actual pIC 50 values of 24 compounds ( Table 5).…”

Detection of Molecular Markers of Antiviral Resistance in Influenza A (H5N1) Viruses Using a Pyrosequencing Method

“…It is worth noting that because our assay was designed to encompass all seven currently known markers associated with drug resistance in the influenza virus NA, it differs markedly from other described methods (18,27), which were designed to target only one or two markers. Moreover, recent work that elucidated the structure of N1 NA showed that previous work on the design of NA inhibitors may not have been optimal for targeting the NA of the N1 subtype, and natural resistance to such designed drugs can be conferred by changes in residues outside of the immediate active site of N1 (10,30,38,47,49). Indeed, drug susceptibility testing using the NA inhibition assay showed that naturally occurring amino acid replacements outside of the NA active site (e.g., V116 and I117) can alter the susceptibility of avian H5N1 viruses to oseltamivir and/or zanamivir (25,32).…”

“…Unlike that to NAIs, resistance to amantadine and rimantadine is relatively high among clade 1 and 2.1 H5N1 viruses (11,24,25,49). Using pyrosequencing methodology, we were able to analyze the presence of the 5 molecular markers of resistance to M2 blockers in a wide variety of H5N1 viruses.…”

Literature Review of Cellulase and Approaches to Increase Its Stability

“…Recently, in MD simulations, estimated free energy and hydrogen bond energy calculations were integrated to reveal the structure-activity interactions. Similarly, the integration of diverse prediction for structure methods can be used in RPD of enzymes as is the case of molecular docking, fragment molecular orbital method (FMO) calculation, Quantitative structure-activity relationship (3D-QSAR), Comparative Molecular Field Analysis (CoMFA) modelling [12].…”