RESUMO
Modern structural biology still draws the vast majority of information from crystallography, a technique where the objects being investigated are embedded in a crystal lattice. Given the complexity and variety of those objects, it becomes fundamental to computationally assess which of the interfaces in the lattice are biologically relevant and which are simply crystal contacts. Since the mid-1990s, several approaches have been applied to obtain high-accuracy classification of crystal contacts and biological protein-protein interfaces. This review provides an overview of the concepts and main approaches to protein interface classification: thermodynamic estimation of interface stability, evolutionary approaches based on conservation of interface residues, and co-occurrence of the interface across different crystal forms. Among the three categories, evolutionary approaches offer the strongest promise for improvement, thanks to the incessant growth in sequence knowledge. Importantly, protein interface classification algorithms can also be used on multimeric structures obtained using other high-resolution techniques or for protein assembly design or validation purposes. A key issue linked to protein interface classification is the identification of the biological assembly of a crystal structure and the analysis of its symmetry. Here, we highlight the most important concepts and problems to be overcome in assembly prediction. Over the next few years, tools and concepts of interface classification will probably become more frequently used and integrated in several areas of structural biology and structural bioinformatics. Among the main challenges for the future are better addressing of weak interfaces and the application of interface classification concepts to prediction problems like protein-protein docking.
Assuntos
Algoritmos , Biologia Computacional/métodos , Proteínas/química , Cristalografia por Raios X , Humanos , Modelos Moleculares , Ligação Proteica , Conformação ProteicaRESUMO
Most of the Earth's biosphere is cold and is populated by cold-adapted microorganisms. To explore the natural enzyme diversity of these environments and identify new carboxylesterases, we have screened three marine metagenome gene libraries for esterase activity. The screens identified 23 unique active clones, from which five highly active esterases were selected for biochemical characterization. The purified metagenomic esterases exhibited high activity against α-naphthyl and p-nitrophenyl esters with different chain lengths. All five esterases retained high activity at 5 °C indicating that they are cold-adapted enzymes. The activity of MGS0010 increased more than two times in the presence of up to 3.5 M NaCl or KCl, whereas the other four metagenomic esterases were inhibited to various degrees by these salts. The purified enzymes showed different sensitivities to inhibition by solvents and detergents, and the activities of MGS0010, MGS0105 and MGS0109 were stimulated three to five times by the addition of glycerol. Screening of purified esterases against 89 monoester substrates revealed broad substrate profiles with a preference for different esters. The metagenomic esterases also hydrolyzed several polyester substrates including polylactic acid suggesting that they can be used for polyester depolymerization. Thus, esterases from marine metagenomes are cold-adapted enzymes exhibiting broad biochemical diversity reflecting the environmental conditions where they evolved.
Assuntos
Organismos Aquáticos/enzimologia , Hidrolases de Éster Carboxílico/isolamento & purificação , Hidrolases de Éster Carboxílico/metabolismo , Temperatura Baixa , Metagenoma , Organismos Aquáticos/genética , Hidrolases de Éster Carboxílico/genética , Ativadores de Enzimas/metabolismo , Dados de Sequência Molecular , Cloreto de Potássio/metabolismo , Análise de Sequência de DNA , Cloreto de Sódio/metabolismo , Especificidade por SubstratoRESUMO
Structure-based computational drug discovery efforts have traditionally focused on the structure of a single, well-known drug target. Important applications, such as target deconvolution and the analysis of polypharmacology, require proteome-scale molecular docking and have been inaccessible to structure-based in silico approaches. One important reason for this inaccessibility was that the structure of most proteins was not known. Lately, this 'structure gap' has been closing rapidly, and proteome-scale molecular docking seems within reach. Here, we survey the current state of structural coverage of the human genome and find that coverage is truly proteome-wide, both overall and in most pharmaceutically relevant categories of proteins. The time is right for structure-based approaches to target deconvolution and polypharmacology.