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1.
Sci Rep ; 11(1): 12740, 2021 06 17.
Artigo em Inglês | MEDLINE | ID: mdl-34140558

RESUMO

The SARS-CoV-2 variants replacing the first wave strain pose an increased threat by their potential ability to escape pre-existing humoral protection. An angiotensin converting enzyme 2 (ACE2) decoy that competes with endogenous ACE2 for binding of the SARS-CoV-2 spike receptor binding domain (S RBD) and inhibits infection may offer a therapeutic option with sustained efficacy against variants. Here, we used Molecular Dynamics (MD) simulation to predict ACE2 sequence substitutions that might increase its affinity for S RBD and screened candidate ACE2 decoys in vitro. The lead ACE2(T27Y/H34A)-IgG1FC fusion protein with enhanced S RBD affinity shows greater live SARS-CoV-2 virus neutralization capability than wild type ACE2. MD simulation was used to predict the effects of S RBD variant mutations on decoy affinity that was then confirmed by testing of an ACE2 Triple Decoy that included an additional enzyme activity-deactivating H374N substitution against mutated S RBD. The ACE2 Triple Decoy maintains high affinity for mutated S RBD, displays enhanced affinity for S RBD N501Y or L452R, and has the highest affinity for S RBD with both E484K and N501Y mutations, making it a viable therapeutic option for the prevention or treatment of SARS-CoV-2 infection with a high likelihood of efficacy against variants.


Assuntos
Substituição de Aminoácidos , Enzima de Conversão de Angiotensina 2/química , Enzima de Conversão de Angiotensina 2/metabolismo , Antivirais/farmacologia , COVID-19/metabolismo , Descoberta de Drogas/métodos , Simulação de Dinâmica Molecular , SARS-CoV-2/metabolismo , Transdução de Sinais/efeitos dos fármacos , Sequência de Aminoácidos , COVID-19/virologia , Humanos , Mutação , Ligação Proteica/efeitos dos fármacos , Domínios Proteicos/genética , Glicoproteína da Espícula de Coronavírus/metabolismo , Internalização do Vírus/efeitos dos fármacos
2.
Proteins ; 63(1): 78-86, 2006 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-16435372

RESUMO

The protein kinase superfamily is an important group of enzymes controlling cellular signaling cascades. The increasing amount of available experimental data provides a foundation for deeper understanding of details of signaling systems and the underlying cellular processes. Here, we describe the Protein Kinase Resource, an integrated online service that provides access to information relevant to cell signaling and enables kinase researchers to visualize and analyze the data directly in an online environment. The data set is synchronized with Uniprot and Protein Data Bank (PDB) databases and is regularly updated and verified. Additional annotation includes interactive display of domain composition, cross-references between orthologs and functional mapping to OMIM records. The Protein Kinase Resource provides an integrated view of the protein kinase superfamily by linking data with their visual representation. Thus, human kinases can be mapped onto the human kinome tree via an interactive display. Sequence and structure data can be easily displayed using applications developed for the PKR and integrated with the website and the underlying database. Advanced search mechanisms, such as multiparameter lookup, sequence pattern, and blast search, enable fast access to the desired information, while statistics tools provide the ability to analyze the relationships among the kinases under study. The integration of data presentation and visualization implemented in the Protein Kinase Resource can be adapted by other online providers of scientific data and should become an effective way to access available experimental information.


Assuntos
Biologia Computacional/métodos , Proteínas Quinases/química , Proteômica/métodos , Sequência de Aminoácidos , Simulação por Computador , Bases de Dados Factuais , Bases de Dados de Proteínas , Recursos em Saúde , Humanos , Armazenamento e Recuperação da Informação , Internet , Modelos Moleculares , Modelos Estatísticos , Dados de Sequência Molecular , Fosforilação , Conformação Proteica , Alinhamento de Sequência , Análise de Sequência de Proteína , Integração de Sistemas
3.
BMC Bioinformatics ; 6: 21, 2005 Feb 06.
Artigo em Inglês | MEDLINE | ID: mdl-15694009

RESUMO

BACKGROUND: The large amount of data that are currently produced in the biological sciences can no longer be explored and visualized efficiently with traditional, specialized software. Instead, new capabilities are needed that offer flexibility, rapid application development and deployment as standalone applications or available through the Web. RESULTS: We describe a new software toolkit--the Molecular Biology Toolkit (MBT; http://mbt.sdsc.edu)--that enables fast development of applications for protein analysis and visualization. The toolkit is written in Java, thus offering platform-independence and Internet delivery capabilities. Several applications of the toolkit are introduced to illustrate the functionality that can be achieved. CONCLUSIONS: The MBT provides a well-organized assortment of core classes that provide a uniform data model for the description of biological structures and automate most common tasks associated with the development of applications in the molecular sciences (data loading, derivation of typical structural information, visualization of sequence and standard structural entities).


Assuntos
Biologia Computacional/métodos , Biologia Molecular/métodos , Software , Algoritmos , Gráficos por Computador , Simulação por Computador , Sistemas de Gerenciamento de Base de Dados , Bases de Dados Genéticas , Bases de Dados de Proteínas , Humanos , Sistemas de Informação , Internet , Ligantes , Modelos Moleculares , Conformação Molecular , Linguagens de Programação , Conformação Proteica , Proteínas/química , Design de Software , Interface Usuário-Computador
4.
Proc Natl Acad Sci U S A ; 102(40): 14344-9, 2005 Oct 04.
Artigo em Inglês | MEDLINE | ID: mdl-16186508

RESUMO

It is now clear that tyrosine kinases represent attractive targets for therapeutic intervention in cancer. Recent advances in DNA sequencing technology now provide the opportunity to survey mutational changes in cancer in a high-throughput and comprehensive manner. Here we report on the sequence analysis of members of the receptor tyrosine kinase (RTK) gene family in the genomes of glioblastoma brain tumors. Previous studies have identified a number of molecular alterations in glioblastoma, including amplification of the RTK epidermal growth factor receptor. We have identified mutations in two other RTKs: (i) fibroblast growth receptor 1, including the first mutations in the kinase domain in this gene observed in any cancer, and (ii) a frameshift mutation in the platelet-derived growth factor receptor-alpha gene. Fibroblast growth receptor 1, platelet-derived growth factor receptor-alpha, and epidermal growth factor receptor are all potential entry points to the phosphatidylinositol 3-kinase and mitogen-activated protein kinase intracellular signaling pathways already known to be important for neoplasia. Our results demonstrate the utility of applying DNA sequencing technology to systematically assess the coding sequence of genes within cancer genomes.


Assuntos
Neoplasias Encefálicas/genética , Evolução Molecular , Glioblastoma/genética , Modelos Moleculares , Mutação/genética , Receptores Proteína Tirosina Quinases/genética , Adulto , Sequência de Aminoácidos , Sequência de Bases , Criança , Feminino , Genômica/métodos , Humanos , Masculino , Modelos Genéticos , Dados de Sequência Molecular , Receptor Tipo 1 de Fator de Crescimento de Fibroblastos/genética , Receptor alfa de Fator de Crescimento Derivado de Plaquetas/genética , Análise de Sequência de DNA
5.
Bioinformatics ; 18(9): 1274-5, 2002 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-12217924

RESUMO

UNLABELLED: The Kinase Sequence Database (KSD) located at http://kinase.ucsf.edu/ksd contains information on 290 protein kinase families derived by profile-based clustering of the non-redundant list of sequences obtained from a GenBank-wide search. Included in the database are a total of 5,041 protein kinases from over 100 organisms. Clustering into families is based on the extent of homology within the kinase catalytic domain (250-300 residues in length). Alignments of the families are viewed by interactive Excel-based sequence spreadsheets. In addition, KSD features evolutionary trees derived for each family and detailed information on each sequence as well as links to the corresponding GenBank entries. Sequence manipulation tools, such as evolutionary tree generation, novel sequence assignment, and statistical analysis, are also provided. AVAILABILITY: The kinase sequence database is a web-based service accessible at http://kinase.ucsf.edu/ksd CONTACT: buzko@cmp.ucsf.edu; shokat@cmp.ucsf.edu/ksd


Assuntos
Sistemas de Gerenciamento de Base de Dados , Bases de Dados de Proteínas , Proteínas Quinases/classificação , Proteínas Quinases/genética , Alinhamento de Sequência/métodos , Análise de Sequência de Proteína/métodos , Análise por Conglomerados , Armazenamento e Recuperação da Informação/métodos , Internet , Homologia de Sequência
6.
J Comput Aided Mol Des ; 16(2): 113-27, 2002 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-12188021

RESUMO

Protein kinases are an important class of enzymes controlling virtually all cellular signaling pathways. Consequently, selective inhibitors of protein kinases have attracted significant interest as potential new drugs for many diseases. Computational methods, including molecular docking, have increasingly been used in the inhibitor design process [1]. We have considered several docking packages in order to strengthen our kinase inhibitor work with computational capabilities. In our experience, AutoDock offered a reasonable combination of accuracy and speed, as opposed to methods that specialize either in fast database searches or detailed and computationally intensive calculations. However, AutoDock did not perform well in cases where extensive hydrophobic contacts were involved, such as docking of SB203580 to its target protein kinase p38. Another shortcoming was a hydrogen bonding energy function, which underestimated the attraction component and, thus, did not allow for sufficiently accurate modeling of the key hydrogen bonds in the kinase-inhibitor complexes. We have modified the parameter set used to model hydrogen bonds, which increased the accuracy of AutoDock and appeared to be generally applicable to many kinase-inhibitor pairs without customization. Binding to largely hydrophobic sites, such as the active site of p38, was significantly improved by introducing a correction factor selectively affecting only carbon and hydrogen energy grids, thus, providing an effective, although approximate, treatment of solvation.


Assuntos
Simulação por Computador , Inibidores Enzimáticos/química , Modelos Moleculares , Inibidores de Proteínas Quinases , Difosfato de Adenosina/química , Difosfato de Adenosina/farmacologia , Proteína Tirosina Quinase CSK , Domínio Catalítico , Inibidores Enzimáticos/farmacologia , Ligantes , Proteínas Quinases Ativadas por Mitógeno/antagonistas & inibidores , Proteínas Quinases Ativadas por Mitógeno/química , Mutação , Proteínas Quinases/química , Proteínas Tirosina Quinases/antagonistas & inibidores , Proteínas Tirosina Quinases/química , Proteínas Tirosina Quinases/genética , Software , Termodinâmica , Proteínas Quinases p38 Ativadas por Mitógeno , Quinases da Família src
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