Protein structural bioinformatics: An overview.

Proteins play a crucial role in organisms in nature. They are able to perform structural, catalytic, transport and defense functions in cells, among others. We understand that a variety of resources do exist to work with protein structural bioinformatics, which perform tasks such as protein modeling, protein docking, protein molecular dynamics, protein interaction, active and binding site prediction and mutation analysis. Nonetheless, they are generally spread all over different online repositories. For the students or professionals interested in working with protein structural bioinformatics, it may not be trivial to know what resources he/she should learn/use or where these could be accessed. Here, the main subareas in the field of protein structural bioinformatics are introduced with a brief description, and we point to and discuss several online resources, such as methods, databases and tools, in order to give an overview of this research field. Furthermore, we developed Protein Structural bioinformatics Overview (PreStO), a web tool available at http://bioinfo.dcc.ufmg.br/presto/, to organize and make it possible to retrieve these online resources based on a search term. We believe that this paper can be a starting point for potential bioinformaticians to trace a path that can be followed to build competencies and achieve knowledge milestones in the context of protein structural bioinformatics.

visGReMLIN: graph mining-based detection and visualization of conserved motifs at 3D protein-ligand interface at the atomic level.

BACKGROUND: Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, the development of computational methods to support our understanding of the ligand-receptor recognition process is of fundamental importance since these methods are a major step towards ligand prediction, target identification, lead discovery, and more. This article presents visGReMLIN, a web server that couples a graph mining-based strategy to detect motifs at the protein-ligand interface with an interactive platform to visually explore and interpret these motifs in the context of protein-ligand interfaces. RESULTS: To illustrate the potential of visGReMLIN, we conducted two cases in which our strategy was compared with previous experimentally and computationally determined results. visGReMLIN allowed us to detect patterns previously documented in the literature in a totally visual manner. In addition, we found some motifs that we believe are relevant to protein-ligand interactions in the analyzed datasets. CONCLUSIONS: We aimed to build a visual analytics-oriented web server to detect and visualize common motifs at the protein-ligand interface. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.

PDBest: a user-friendly platform for manipulating and enhancing protein structures.

UNLABELLED: PDBest (PDB Enhanced Structures Toolkit) is a user-friendly, freely available platform for acquiring, manipulating and normalizing protein structures in a high-throughput and seamless fashion. With an intuitive graphical interface it allows users with no programming background to download and manipulate their files. The platform also exports protocols, enabling users to easily share PDB searching and filtering criteria, enhancing analysis reproducibility. AVAILABILITY AND IMPLEMENTATION: PDBest installation packages are freely available for several platforms at http://www.pdbest.dcc.ufmg.br CONTACT: wellisson@dcc.ufmg.br, dpires@dcc.ufmg.br, raquelcm@dcc.ufmg.br SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

VERMONT: Visualizing mutations and their effects on protein physicochemical and topological property conservation.

In this paper, we propose an interactive visualization called VERMONT which tackles the problem of visualizing mutations and infers their possible effects on the conservation of physicochemical and topological properties in protein families. More specifically, we visualize a set of structure-based sequence alignments and integrate several structural parameters that should aid biologists in gaining insight into possible consequences of mutations. VERMONT allowed us to identify patterns of position-specific properties as well as exceptions that may help predict whether specific mutations could damage protein function.