Background:Human myxovirus resistant protein A(MxA),encoded by the myxovirus resistance 1(Mx1) gene,is an interferon(IFN)-triggered dynamin-like multi-domain GTPase involved in innate immune responses against viral in...Background:Human myxovirus resistant protein A(MxA),encoded by the myxovirus resistance 1(Mx1) gene,is an interferon(IFN)-triggered dynamin-like multi-domain GTPase involved in innate immune responses against viral infections.Recent studies suggest that MxA is associated with several human cancers and may be a tumor suppressor and a promising biomarker for IFN therapy.Mxl gene mutations in the coding region for MxA have been discovered in many types of cancer,suggesting potential biological associations between mutations in MxA protein and corresponding cancers.In this study,we performed a systematic analysis based on the crystal structures of MxA and elucidated how these mutations specifically affect the structure and therefore the function of MxA protein.Methods:Cancer-associated Mxl mutations were collected and screened from the COSMIC database.Twenty-two unique mutations that cause single amino acid alterations in the MxA protein were chosen for the analysis.Amino acid sequence alignment was performed using Clustal W to check the conservation level of mutation sites in Mx proteins and dynamins.Structural analysis of the mutants was carried out with Coot.Structural models of selected mutants were generated by the SWISS-MODEL server for comparison with the corresponding non-mutated structures.All structural figures were generated using PyMOL.Results:We analyzed the conservation level of the single-point mutation sites and mapped them on different domains of MxA.Through individual structural analysis,we found that some mutations severely affect the stability and function of MxA either by disrupting the intraVinter-molecular interactions supported by the original residues or by incurring unfavorable configuration alterations,whereas other mutations lead to gentle or no interference to the protein stability and function because of positions or polarity features.The potential clinical value of the mutations that lead to drastic influence on MxA protein is also assessed.Conclusions:Among all of the reported tumor-as展开更多
Background:Computer simulation studies complement in vitro experiments and provide avenue to understand allosteric regulation in the absence of other molecular viewing techniques.Molecular dynamics captures internal m...Background:Computer simulation studies complement in vitro experiments and provide avenue to understand allosteric regulation in the absence of other molecular viewing techniques.Molecular dynamics captures internal motion within the protein and enables tracing the communication path between a catalytic site and a distal allosteric site.In this article,we have identified the communication pathway between the viral protein genome linked(VPg)binding region and catalytic active site in nuclear inclusion protein-a protease(NIa-Pro).Methods:Molecular dynamics followed by in silico analyses have been used to map the allosteric pathway.Results:This study delineates the residue interaction network involved in allosteric regulation of NIa-Pro activity by VPg.Simulation studies indicate that point mutations in the VPg interaction interface of NIa-Pro lead to disruption in these networks and change the orientation of catalytic residues.His142Ala and His167Ala mutations do not show a substantial change in the overall protease structure,but rather in the residue interaction network and catalytic site geometry.Conclusion:Our mutagenic study delineates the allosteric pathway and facilitates the understanding of the modulation of NIa-Pro activity on a molecular level in the absence of the structure of its complex with the known regulator VPg.Additionally,our in silico analysis explains the molecular concepts and highlights the dynamics behind the previously reported wet lab study findings.展开更多
Background： Protein-protein interactions are essential to many biological processes. The binding site information of protein-protein complexes is extremely useful to obtain their structures from biochemical experimen...Background： Protein-protein interactions are essential to many biological processes. The binding site information of protein-protein complexes is extremely useful to obtain their structures from biochemical experiments. Geometric description of protein structures is the precondition of protein binding site prediction and protein-protein interaction analysis. The previous description of protein surface residues is incomplete, and little attention are paid to the implication of residue types for binding site prediction. Methods： Here, we found three new geometric features to characterize protein surface residues which are very effective for protein-protein interface residue prediction. The new features and several commonly used descriptors were employed to train millions of residue type-nonspecific or specific protein binding site predictors. Results： The amino acid type-specific predictors are superior to the models without distinction of amino acid types. The performances of the best predictors are much better than those of the sophisticated methods developed before. Conclusions： The results demonstrate that the geometric properties and amino acid types are very likely to determine if a protein surface residue would become an interface one when the protein binds to its partner.展开更多
基金supported by research grants from the National Natural Science Foundation of China(No.31200553)the National Basic Research Program of China(No.2013CB910500)+1 种基金the Program of New Century Excellent Talents in University(NCET-12-0567)the Recruitment Program for Young Professionals
文摘Background:Human myxovirus resistant protein A(MxA),encoded by the myxovirus resistance 1(Mx1) gene,is an interferon(IFN)-triggered dynamin-like multi-domain GTPase involved in innate immune responses against viral infections.Recent studies suggest that MxA is associated with several human cancers and may be a tumor suppressor and a promising biomarker for IFN therapy.Mxl gene mutations in the coding region for MxA have been discovered in many types of cancer,suggesting potential biological associations between mutations in MxA protein and corresponding cancers.In this study,we performed a systematic analysis based on the crystal structures of MxA and elucidated how these mutations specifically affect the structure and therefore the function of MxA protein.Methods:Cancer-associated Mxl mutations were collected and screened from the COSMIC database.Twenty-two unique mutations that cause single amino acid alterations in the MxA protein were chosen for the analysis.Amino acid sequence alignment was performed using Clustal W to check the conservation level of mutation sites in Mx proteins and dynamins.Structural analysis of the mutants was carried out with Coot.Structural models of selected mutants were generated by the SWISS-MODEL server for comparison with the corresponding non-mutated structures.All structural figures were generated using PyMOL.Results:We analyzed the conservation level of the single-point mutation sites and mapped them on different domains of MxA.Through individual structural analysis,we found that some mutations severely affect the stability and function of MxA either by disrupting the intraVinter-molecular interactions supported by the original residues or by incurring unfavorable configuration alterations,whereas other mutations lead to gentle or no interference to the protein stability and function because of positions or polarity features.The potential clinical value of the mutations that lead to drastic influence on MxA protein is also assessed.Conclusions:Among all of the reported tumor-as
文摘Background:Computer simulation studies complement in vitro experiments and provide avenue to understand allosteric regulation in the absence of other molecular viewing techniques.Molecular dynamics captures internal motion within the protein and enables tracing the communication path between a catalytic site and a distal allosteric site.In this article,we have identified the communication pathway between the viral protein genome linked(VPg)binding region and catalytic active site in nuclear inclusion protein-a protease(NIa-Pro).Methods:Molecular dynamics followed by in silico analyses have been used to map the allosteric pathway.Results:This study delineates the residue interaction network involved in allosteric regulation of NIa-Pro activity by VPg.Simulation studies indicate that point mutations in the VPg interaction interface of NIa-Pro lead to disruption in these networks and change the orientation of catalytic residues.His142Ala and His167Ala mutations do not show a substantial change in the overall protease structure,but rather in the residue interaction network and catalytic site geometry.Conclusion:Our mutagenic study delineates the allosteric pathway and facilitates the understanding of the modulation of NIa-Pro activity on a molecular level in the absence of the structure of its complex with the known regulator VPg.Additionally,our in silico analysis explains the molecular concepts and highlights the dynamics behind the previously reported wet lab study findings.
文摘Background： Protein-protein interactions are essential to many biological processes. The binding site information of protein-protein complexes is extremely useful to obtain their structures from biochemical experiments. Geometric description of protein structures is the precondition of protein binding site prediction and protein-protein interaction analysis. The previous description of protein surface residues is incomplete, and little attention are paid to the implication of residue types for binding site prediction. Methods： Here, we found three new geometric features to characterize protein surface residues which are very effective for protein-protein interface residue prediction. The new features and several commonly used descriptors were employed to train millions of residue type-nonspecific or specific protein binding site predictors. Results： The amino acid type-specific predictors are superior to the models without distinction of amino acid types. The performances of the best predictors are much better than those of the sophisticated methods developed before. Conclusions： The results demonstrate that the geometric properties and amino acid types are very likely to determine if a protein surface residue would become an interface one when the protein binds to its partner.
