Suxin Zheng

Nucleocapsid protein of SARS coronavirus tightly binds to human cyclophilin A

Abstract Severe acute respiratory syndrome coronavirus (SARS-CoV) is responsible for SARS infection. Nucleocapsid protein (NP) of SARS-CoV (SARS_NP) functions in enveloping the entire genomic RNA and interacts with viron structural proteins, thus playing important roles in the process of virus particle assembly and release. Protein–protein interaction analysis using bioinformatics tools indicated that SARS_NP may bind to human cyclophilin A (hCypA), and surface plasmon resonance (SPR) technology revealed this binding with the equilibrium dissociation constant ranging from 6 to 160nM. The probable binding sites of these two proteins were detected by modeling the three-dimensional structure of the SARS_NP–hCypA complex, from which the important interaction residue pairs between the proteins were deduced. Mutagenesis experiments were carried out for validating the binding model, whose correctness was assessed by the observed effects on the binding affinities between the proteins. The reliability of the binding sites derived by the molecular modeling was confirmed by the fact that the computationally predicted values of the relative free energies of the binding for SARS_NP (or hCypA) mutants to the wild-type hCypA (or SARS_NP) are in good agreement with the data determined by SPR. Such presently observed SARS_NP–hCypA interaction model might provide a new hint for facilitating the understanding of another possible SARS-CoV infection pathway against human cell.

A new rapid and effective chemistry space filter in recognizing a druglike database.

To develop a new chemistry space filter with high efficiency and accuracy, an analysis on distributions of as many as 50 structural and physicochemical properties was carried out on both druglike and nondruglike databases, viz. MACCS-II Drug Data Report (MDDR), Comprehensive Medicinal Chemistry (CMC), and Available Chemicals Directory (ACD). Based on the analysis results, a chemistry space filter was developed that can effectively discriminate a druglike database from a nondruglike database. The filter is composed of two descriptors: one is a molecular saturation related descriptor, and the other is associated with the proportion of heteroatoms in a molecule. Both are molecular size independent. Therefore, the profiles of a druglike database could be characterized as proper molecular saturation and proper percentage of heteroatoms, revealing direct indices for designing and optimizing combinatorial libraries. The application of the new filter on the Chinese Natural Product Database (CNPD) suggested that CNPD is, as expected, a potential druglike database, testifying that the new filter is reliable. Therefore, this newly developed chemistry space filter should be a potent tool for identifying druglike molecules, thus, it would have potential applications in the research of combinatorial library design and virtual high throughput screening using computational approaches for drug discovery.

Computational analysis of molecular basis of 1:1 interactions of NRG‐1β wild‐type and variants with ErbB3 and ErbB4

The neuregulin/ErbB system is a growth factor/receptor cascade that has been proven to be essential in the development of the heart and the sympathetic nervous system. However, the basis of the specificity of ligand–receptor recognition remains to be elucidated. In this study, the structures of NRG‐1β/ErbB3 and NRG‐1β/ErbB4 complexes were modeled based on the available structures of the homologous proteins. The binding free energies of NRG‐1β to ErbB3 and ErbB4 were calculated using the molecular mechanics Poisson–Boltzmann surface area (MM‐PBSA) computational method. In addition, computational alanine‐scanning mutagenesis was performed in the binding site of NRG‐1β and the difference in the binding free energies between NRG‐1β mutants and the receptors was calculated. The results specify the contribution of each residue at the interaction interfaces to the binding affinity of NRG‐1β with ErbB3 and ErbB4, identifying several important interaction residue pairs that are in agreement with previously acquired experimental data. This indicates that the presented structural models of NRG‐1β/ErbB3 and NRG‐1β/ErbB4 complexes are reliable and could be used to guide future studies, such as performing desirable mutations on NRG‐1β to increase the binding affinity and selectivity to the receptor and discovering new therapeutic agents for the treatment of heart failure. Proteins 2005.