De la Mioglobina al SARS-CoV-2: ¡50 años del Protein Data Bank!

<p><span>La Mioglobina fue la primer proteína visualizada en tres dimensiones (3D) a través de la cristalografía de rayos-X, sentando las bases para una nueva era de comprensión biológica. A partir de este hecho, se comenzaron a determinar estructuralmente una serie de macromoléculas de considerable interés biológico. Sin embargo, este impresionante avance en las ciencias de la vida, contrastaba radicalmente con la ausencia de un repositorio global para archivar y compartir los datos cristalográficos colectados de los experimentos de difracción. Con el propósito de llenar este vacío, en 1971 se estableció el Protein Data Bank (PDB) en el Brookhaven National Laboratory, como el único almacén central de estructuras 3D de macromoléculas biológicas. Establecido con apenas siete estructuras, el PDB ha evolucionado a un gigantesco repositorio de acceso abierto, almacenando datos estructurales de más de 170,000 biomoléculas, principalmente de proteínas y ácidos nucleicos. Además de ser un banco de datos biológicos, el PDB sirve como un portal educativo a través del PDB-101, ofreciendo un conjunto de recursos extraordinarios para admirar el mundo biológico. En esta revisión, festejamos los 50 años de oro del PDB con una mirada a su historia y un recorrido por algunas herramientas educativas que el archivo pone a disposición de estudiantes, investigadores, profesores y público no especializado. Ilustramos el valor de estos recursos con la estructura 3D de la maquinaria biológica recientemente depositada en el archivo, del ubicuo y nuevo coronavirus causante del síndrome respiratorio agudo severo (SARS-CoV-2) o COVID-19.</span></p>

ANÁLISE COMPUTACIONAL DA INTERAÇÃO ENTRE O CANAL IÔNICO DE α-HL E COMPOSTOS TIAZOLIDÍNICOS

Introdução: Staphylococcus aureus (S. aureus) é uma bactéria associada a diversas infecções, tanto na comunidade quanto em ambiente hospitalar, ocasionando desde infecção cutânea até septicemia(1). Um importante fator de virulência é a exotoxina alfa-hemolisina (α-HL), que oligomeriza e forma canais iônicos transmembranares nas células-alvo, permitindo o fluxo livre de várias espécies químicas, resultando na morte celular(2). Diversas cepas de S. aureus exibem multirresistência aos antibióticos, limitando as opções de tratamento. Os derivados tiazolidínicos podem ser uma boa alternativa para bloquear a α-HL, pois possuem amplas propriedades bioativas, como por exemplo a antimicrobiana para cepas multirresistentes, sendo eficazes contra o S. aureus e inibindo o seu crescimento(3). Objetivos: Dada a importância da busca de compostos com ação antibacteriana, via bloqueio da α-HL, este trabalho visa analisar, via docagem molecular, a interação de derivados tiazolidínicos 5-benzilideno com o canal iônico formado pela toxina. Métodos: A estrutura cristalográfica da α-HL de S. aureus foi obtida pelo Protein Data Bank (PDB) e utilizou-se o MolView para modelagem dos compostos denominados GQ294 e GQ443, posteriormente submetidos ao Avogadro 1.1.1 para minimização de energia molecular. A docagem foi realizada pelo DockThor e os resultados foram analisados utilizando o Discovery Studio Visualizer. Resultados: A partir dos resultados de docagem pelo DockThor, foi obtida uma classificação dos compostos de acordo com suas energias totais e scores de afinidade com a toxina. Os valores de energia total do GQ443 e GQ294 foram iguais a -15,152 KJ/ mol e -19,009 KJ/ mol, respectivamente. Enquanto o score de afinidade de GQ443 e GQ294 foi de -6,820 Kcal/ mol e -5,902 Kcal/ mol respectivamente. As análises obtidas a partir do Discovery Studio Visualizer demonstraram que os dois compostos interagem com a região de constrição do canal iônico, principalmente com os resíduos GLU 111 e LYS 147, sendo estas interações mediadas principalmente por ligações de hidrogênio, além de interações do tipo cátionpi, pi-alquila, pi-enxofre. Esses dados corroboram com outros trabalhos já encontrados na literatura(4). Conclusões: Os resultados indicam, preditivamente, que os compostos GQ443 e GQ294 interagem com o canal da α-HL na região de constrição, sugerindo um bloqueio de sua atividade. São necessários dados experimentais para elucidar os dados teóricos já obtidos.

Worldwide Protein Data Bank (wwPDB): A virtual treasure for research in biotechnology

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RSCB PDB) provides a wide range of digital data regarding biology and biomedicine. This huge internet resource involves a wide range of important biological data, obtained from experiments around the globe by different scientists. The Worldwide Protein Data Bank (wwPDB) represents a brilliant collection of 3D structure data associated with important and vital biomolecules including nucleic acids (RNAs and DNAs) and proteins. Moreover, this database accumulates knowledge regarding function and evolution of biomacromolecules which supports different disciplines such as biotechnology. 3D structure, functional characteristics and phylogenetic properties of biomacromolecules give a deep understanding of the biomolecules’ characteristics. An important advantage of the wwPDB database is the data updating time, which is done every week. This updating process helps users to have the newest data and information for their projects. The data and information in wwPDB can be a great support to have an accurate imagination and illustrations of the biomacromolecules in biotechnology. As demonstrated by the SARS-CoV-2 pandemic, rapidly reliable and accessible biological data for microbiology, immunology, vaccinology, and drug development are critical to address many healthcare-related challenges that are facing humanity. The aim of this paper is to introduce the readers to wwPDB, and to highlight the importance of this database in biotechnology, with the expectation that the number of scientists interested in the utilization of Protein Data Bank’s resources will increase substantially in the coming years.

A mosaic bulk-solvent model improves density maps and the fit between model and data

Bulk solvent is a major component of bio-macromolecular crystals and therefore contributes significantly to diffraction intensities. Accurate modeling of the bulk-solvent region has been recognized as important for many crystallographic calculations, from computing of R-factors and density maps to model building and refinement. Owing to its simplicity and computational and modeling power, the flat (mask-based) bulk-solvent model introduced by Jiang & Brunger (1994) is used by most modern crystallographic software packages to account for disordered solvent. In this manuscript we describe further developments of the mask-based model that improves the fit between the model and the data and aids in map interpretation. The new algorithm, here referred to as mosaic bulk-solvent model, considers solvent variation across the unit cell. The mosaic model is implemented in the computational crystallography toolbox and can be used in Phenix in most contexts where accounting for bulk-solvent is required. It has been optimized and validated using a sufficiently large subset of the Protein Data Bank entries that have crystallographic data available.

Investigation of molecular mechanisms of cannabinoids with neuromodulator activity using in silico tools

This work aims to complement the investigations of the molecular mechanisms of cannabinoids and their receptors, elucidating molecular targets that explain the effect of chemical compounds present in Cannabis sativa on central neuromodulation through in silico methods. Cannabis sativa metabolites were collected bibliographically, and the coding of molecules to perform the predictions were obtained from the PubChem website. Bioactivity screening was then performed with SwissADME, ProToxII, PASS, and Molinspiration programs and target search with SuperPred Webserver servers. After target identification, the selected structure was obtained from the Protein Data Bank (PDB) site for molecular docking with the GOLD program. Cannabis sativa metabolites had their physicochemical and biological properties analyzed. The targets for molecular docking were identified and verified for each compound, with their respective structures crystallized in the Protein Data Bank (PDB). The tetrahydrocannabivarin (THCV) molecule was selected because it predicted interaction with the N-arachidonylglycine receptor (PDB ID: 4UUQ). Docking reveals a potential interaction of THCV with the N-arachidonylglycine receptor. Furthermore, the binding structure of this study showed pharmacophoric alignment with the five most potent molecules capable of antagonizing the monoglycerate lipase receptor. TCHV docking showed anchoring of this molecule in the active site of the N-arachidonylglycine receptor due to the activities of this species. Thus, this marker could act as an antagonist of this receptor, behaving as an active metabolite with neuromodulatory activity through a possible alteration of microglial activity in the central nervous system, which may act as a therapeutic agent in neurodegenerative pathologies.

PDBrt: A free database of complexes with measured drug-target residence time

Background: Difficulties in translating the in vitro potency determined by cellular assays into in vivo efficacy in living organisms complicates the design and development of drugs. However, the residence time of a drug in its molecular target is becoming a key parameter in the design and optimization of new drugs, as recent studies show that residence time can reliably predict drug efficacy in vivo. Experimental approaches to binding kinetics and target ligand complex solutions are currently available, but known bioinformatics databases do not usually report information about the ligand residence time in its molecular target. Methods: To extend existing databases we developed the Protein Data Bank (PDB) residence time database (PDBrt) which reports drug residence time. The database is implemented as an open access web-based tool. The front end uses Bootstrap with Hypertext Markup Language (HTML), jQuery for the interface and 3Dmol.js to visualize the complexes. The server-side code uses Python web application framework, Django Rest Framework and backend database PostgreSQL. Results: The PDBrt database is a free, non-commercial repository for 3D protein-ligand complex data, including the measured ligand residence time inside the binding pocket of the specific biological macromolecules as deposited in The Protein Data Bank. The PDBrt database contains information about both the protein and the ligand separately, as well as the protein-ligand complex, binding kinetics, and time of the ligand residence inside the protein binding site. Availability: https://pdbrt.polsl.pl

Random sampling of the Protein Data Bank: RaSPDB

A novel and simple procedure (RaSPDB) for Protein Data Bank mining is described. 10 PDB subsets, each containing 7000 randomly selected protein chains, are built and used to make 10 estimations of the average value of a generic feature F—the length of the protein chain, the amino acid composition, the crystallographic resolution, and the secondary structure composition. These 10 estimations are then used to compute an average estimation of F together with its standard error. It is heuristically verified that the dimension of these 10 subsets—7000 protein chains—is sufficiently small to avoid redundancy within each subset and sufficiently large to guarantee stable estimations amongst different subsets. RaSPDB has two major advantages over classical procedures aimed to build a single, non-redundant PDB subset: a larger fraction of the information stored in the PDB is used and an estimation of the standard error of F is possible.

STUDI AKTIVITAS BIOLOGI SECARA IN SILICO SENYAWA NONIVAMIDE DAN NORDIHYDROCAPSAICIN SEBAGAI ANTI INFLAMASI

<p>Cabai Merah Besar (<em>Capsicum Annum</em> L) merupakan tanaman holtikultura yang dibudidayakan dalam skala kecilnamun memiliki manfaat kesehatan. Cabai Merah Besar (<em>Capsicum Annum</em> L.) juga digunakan untuk pengobatan sakit gigi, bisul, anti parasit, anti inflamasi, antitusif dan juga digunakan sebagai antiseptik, nafsu makan. Penelitian ini memiliki tujuan untuk menganalisis potensi senyawa <em>nonivamide</em> dan <em>nordihydrocapsaicin </em>sebagai anti-inflamasi. Kajian penelitian metode in silico. Senyawa <em>Nonivamide</em> (CID :2998) dan <em>Nordihydrocapsaicin</em> (CID: 168836) diperoleh dari PubChem sedangkan COX-2 (6cox) dari Protein Data Bank. Analisis menggunakan HEX 8.0.0 dan ditampilkan Discovery studio client 4.1. Interaksi yang terjadi antara senyawa <em>Nonivamide</em> dan COX-2 membentuk ikatan hidrogen dengan tipe ikatan hidrogen konvensional (CYS47) dan ikatan hidrofobik (LEU152). Selain ikatan hidrogen, juga terdapat sembilan belas residu asam amino menunjukkan adanya gaya <em>V</em><em>an </em><em>D</em><em>er </em><em>W</em><em>aals</em> membentuk energi -339.48 cal/mol. Ikatan Nordihydrocapsaicin dengan COX-2 membentuk ikatan pada residu asam amino TRP139 bersifat Pi-Alkyl dan ikatan hidrogen sebagai donor dengan Residu asam amino SER143 energi ikatan sebesar -248.47 cal/mol.</p>