MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning.

Cryo-EM Single Particle Analysis workflows require tens of thousands of high-quality particle projections to unveil the three-dimensional structure of macromolecules. Conventional methods for automatic particle picking tend to suffer from high false-positive rates, hampering the reconstruction process. One common cause of this problem is the presence of carbon and different types of high-contrast contaminations.

BIPSPI: a method for the prediction of partner-specific protein-protein interfaces.

Motivation: Protein-Protein Interactions (PPI) are essentials for most cellular processes and thus, unveiling how proteins interact is a crucial question that can be better understood by identifying which residues are responsible for the interaction. Computational approaches are orders of magnitude cheaper and faster than experimental ones, leading to proliferation of multiple methods aimed to predict which residues belong to the interface of an interaction.

Results: We present BIPSPI, a new machine learning-based method for the prediction of partner-specific PPI sites.

3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures.

Many studies have used position-specific scoring matrices (PSSM) profiles to characterize residues in protein structures and to predict a broad range of protein features. Moreover, PSSM profiles of Protein Data Bank (PDB) entries have been recalculated in many works for different purposes. Although the computational cost of calculating a single PSSM profile is affordable, many statistical studies or machine learning-based methods used thousands of profiles to achieve their goals, thereby leading to a substantial increase of the computational cost.

3DBIONOTES v2.0: a web server for the automatic annotation of macromolecular structures.

Motivation: Complementing structural information with biochemical and biomedical annotations is a powerful approach to explore the biological function of macromolecular complexes. However, currently the compilation of annotations and structural data is a feature only available for those structures that have been released as entries to the Protein Data Bank.

Results: To help researchers in assessing the consistency between structures and biological annotations for structural models not deposited in databases, we present 3DBIONOTES v2.

3DBIONOTES: A unified, enriched and interactive view of macromolecular information.

With the advent of high throughput techniques like Next Generation Sequencing, the amount of biological information for genes and proteins is growing faster than ever. Structural information is also rapidly growing, especially in the cryo Electron Microscopy area. However, in many cases, the proteomic and genomic data are spread in multiple databases and with no simple connection to structural information.

3DIANA: 3D Domain Interaction Analysis: A Toolbox for Quaternary Structure Modeling.

Electron microscopy (EM) is experiencing a revolution with the advent of a new generation of Direct Electron Detectors, enabling a broad range of large and flexible structures to be resolved well below 1 nm resolution. Although EM techniques are evolving to the point of directly obtaining structural data at near-atomic resolution, for many molecules the attainable resolution might not be enough to propose high-resolution structural models. However, accessing information on atomic coordinates is a necessary step toward a deeper understanding of the molecular mechanisms that allow proteins to perform specific tasks.