RESUMO
The DNA binding domain (DBD) of the tumor suppressor p53 is the site of several oncogenic mutations. A subset of these mutations lowers the unfolding temperature of the DBD. Unfolding leads to the exposure of a hydrophobic ß-strand and nucleates aggregation which results in pathologies through loss of function and dominant negative/gain of function effects. Inspired by the hypothesis that structural changes that are associated with events initiating unfolding in DBD are likely to present opportunities for inhibition, we investigate the dynamics of the wild type (WT) and some aggregating mutants through extensive all atom explicit solvent MD simulations. Simulations reveal differential conformational sampling between the WT and the mutants of a turn region (S6-S7) that is contiguous to a known aggregation-prone region (APR). The conformational properties of the S6-S7 turn appear to be modulated by a network of interacting residues. We speculate that changes that take place in this network as a result of the mutational stress result in the events that destabilize the DBD and initiate unfolding. These perturbations also result in the emergence of a novel pocket that appears to have druggable characteristics. FDA approved drugs are computationally screened against this pocket.
Assuntos
Proteínas de Ligação a DNA/química , Proteínas Mutantes/química , Bibliotecas de Moléculas Pequenas/química , Proteína Supressora de Tumor p53/química , Proteínas de Ligação a DNA/genética , Avaliação Pré-Clínica de Medicamentos/métodos , Humanos , Interações Hidrofóbicas e Hidrofílicas/efeitos dos fármacos , Modelos Moleculares , Simulação de Dinâmica Molecular , Proteínas Mutantes/genética , Mutação/genética , Conformação Proteica/efeitos dos fármacos , Domínios Proteicos/efeitos dos fármacos , Domínios Proteicos/genética , Desdobramento de Proteína/efeitos dos fármacos , Proteína Supressora de Tumor p53/genéticaRESUMO
Dengue fever is a febrile illness caused by Dengue Virus, which belongs to the Flaviviridae family. Among its proteome, the nonstructural protein 5 (NS5) is the biggest and most conserved. It has a primer-independent RNA-dependent RNA polymerase (RdRp) domain at its C-Terminus. Zou et al. studied the biological relevance of the two conserved cavities (named A and B) within the NS5 proteins of dengue virus (DENV) and West Nile Virus (WNV) using mutagenesis and revertant analysis and found four mutations located at cavity B having effects on viral replication. They recommended Cavity B, but not Cavity A as a potential target for drugs against flavivirus RdRp. In this study, we virtually screened the MayBridge drug fragments dataset for potential small molecule binders of cavity B using both AutoDock Vina, the standard docking tool, and QuickVina 2, our previously developed tool. We selected 16 fragments that appeared in the top 100 docking results of each of the representative structures of NS5. Visual inspection suggests that they have reasonable binding poses. The 16 predicted fragments are plausible drug candidates and should be considered for further validation, optimization, and linking to come up with a suitable inhibitor of dengue virus.
Assuntos
Antivirais/farmacologia , Avaliação Pré-Clínica de Medicamentos/métodos , Simulação de Dinâmica Molecular , Proteínas não Estruturais Virais/metabolismo , Algoritmos , Antivirais/química , Antivirais/metabolismo , Simulação por Computador , Descoberta de Drogas , Bibliotecas Digitais , Simulação de Acoplamento Molecular , Conformação Proteica , Reprodutibilidade dos Testes , Proteínas não Estruturais Virais/químicaRESUMO
Pathological myopia is one of the leading causes of blindness worldwide. The condition is particularly prevalent in Asia. Unlike myopia, pathological myopia is accompanied by degenerative changes in the retina, which if left untreated can lead to irrecoverable vision loss. The accurate diagnosis of pathological myopia will enable timely intervention and facilitate better disease management to slow down the progression of the disease. Current methods of assessment typically consider only one type of data, such as that from retinal imaging. However, different kinds of data, including that of genetic, demographic and clinical information, may contain different and independent information, which can provide different perspectives on the visually observable, genetic or environmental mechanisms for the disease. The combination of these potentially complementary pieces of information can enhance the understanding of the disease, providing a holistic appreciation of the multiple risks factors as well as improving the detection outcomes. In this study, we propose a computer-aided diagnosis framework for Pathological Myopia diagnosis through Biomedical and Image Informatics(PM-BMII). Through the use of multiple kernel learning (MKL) methods, PM-BMII intelligently fuses heterogeneous biomedical information to improve the accuracy of disease diagnosis. Data from 2,258 subjects of a population-based study, in which demographic and clinical information, retinal fundus imaging data and genotyping data were collected, are used to evaluate the proposed framework. The experimental results show that PM-BMII achieves an AUC of 0.888, outperforming the detection results from the use of demographic and clinical information 0.607 (increase 46.3%, p<0.005), genotyping data 0.774 (increase 14.7%, P<0.005) or imaging data 0.852 (increase 4.2%, p=0.19) alone. The accuracy of the results obtained demonstrates the feasibility of using heterogeneous data for improved disease diagnosis through our proposed PM-BMII framework.