Resources and Softwares

Our group has been developing a variety of resources such as algorithms, databases and visualization tools that are made freely available. Some of these resources were developed in partnership with researchers from other institutions, such as EMBL-EBI and Lancaster University in the UK, University of Melbourne in Australia, and UFMG in Brazil.


GRaSP (Graph-based Residue neighborhood Strategy to Predict binding sites) is a residue centric method to predict ligand biding site residues. It is based on a supervised learning strategy that models the residue environment as a graph at the atomic level. For each protein residue, physicochemical and topological properties of its atoms and non-covalent interactions are modeled as a graph which, in turn, is encoded as a feature vector. Then, a matrix of feature vectors representing a set of proteins is the input for the method. GRaSP is able to predict binding sites across multi-chain proteins.


To give an overview of protein structural bioinformatics research field, the main subareas of this topic are introduced with a brief description. Several online resources, such as methods, databases, and tools, are also pointed and discussed in this work. A web tool named PreStO (Protein Structural bioinformatics Overview) was developed to organize and make it possible to retrieve online resources based on a search term. 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, a visual interactive interface to explore protein-ligand interactions and their conserved substructures for a set of similar proteins. It is 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. visGReMLIN motifs can support users in gaining insights on the key atoms/residues responsible for protein-ligand interactions in a dataset of complexes.


ppiGReMLIN is a graph based strategy to infer interaction patterns in a set of protein-protein complexes. The method combines an unsupervised learning strategy with frequent subgraph mining in order to detect conserved structural arrangements (patterns) based on the physicochemical properties of atoms on protein interfaces. The method does not rely on sequence alignment nor structural superimposition, and can be used in large-scale datasets of protein-protein interactions. ppiGReMLIN is able to find highly conserved structures on the interfaces of protein-protein complexes.


VERMONT is a visual interactive platform that integrates sequence conservation, the intramolecular interaction network, solvent accessibility, physicochemical properties and complex network topological parameters, combining them with powerful interactive visualizations to make the impact of protein point mutations more understandable. VERMONT is able to identify these mutations in a completely visual manner, providing clues that help to identify those that potentially have an impact on structure/function.