Structural Prediction of Protein–Protein Interactions by Docking: Application to Biomedical Problems

A huge amount of genetic information is available thanks to the recent advances in sequencing technologies and the larger computational capabilities, but the interpretation of such genetic data at phenotypic level remains elusive. One of the reasons is that proteins are not acting alone, but are specifically interacting with other proteins and biomolecules, forming intricate interaction networks that are essential for the majority of cell processes and pathological conditions. Thus, characterizing such interaction networks is an important step in understanding how information flows from gene to phenotype. Indeed, structural characterization of protein–protein interactions at atomic resolution has many applications in biomedicine, from diagnosis and vaccine design, to drug discovery. However, despite the advances of experimental structural determination, the number of interactions for which there is available structural data is still very small. In this context, a complementary approach is computational modeling of protein interactions by docking, which is usually composed of two major phases: (i) sampling of the possible binding modes between the interacting molecules and (ii) scoring for the identification of the correct orientations. In addition, prediction of interface and hot-spot residues is very useful in order to guide and interpret mutagenesis experiments, as well as to understand functional and mechanistic aspects of the interaction. Computational docking is already being applied to specific biomedical problems within the context of personalized medicine, for instance, helping to interpret pathological mutations involved in protein–protein interactions, or providing modeled structural data for drug discovery targeting protein–protein interactions.Spanish Ministry of Economy grant number BIO2016-79960-R; D.B.B. is supported by a predoctoral fellowship from CONACyT; M.R. is supported by an FPI fellowship from the Severo Ochoa program. We are grateful to the Joint BSC-CRG-IRB Programme in Computational Biology.Peer ReviewedPostprint (author's final draft

Crystal structure of a DNA aptamer bound to PvLDH elucidates novel single-stranded DNA structural elements for folding and recognition

Structural elements are key elements for understanding single-stranded nucleic acid folding. Although various RNA structural elements have been documented, structural elements of single-stranded DNA (ssDNA) have rarely been reported. Herein, we determined a crystal structure of PvLDH in complex with a DNA aptamer called pL1. This aptamer folds into a hairpin-bulge contact by adopting three novel structural elements, viz, DNA T-loop-like motif, base-phosphate zipper, and DNA G.G metal ion zipper. Moreover, the pL1: PvLDH complex shows unique properties compared with other protein: nucleic acid complexes. Generally, extensive intermolecular hydrogen bonds occur between unpaired nucleotides and proteins for specific recognitions. Although most protein-interacting nucleotides of pL1 are unpaired nucleotides, pL1 recognizes PvLDH by predominant shape complementarity with many bridging water molecules owing to the combination of three novel structural elements making protein-binding unpaired nucleotides stable. Moreover, the additional set of Plasmodium LDH residues which were shown to form extensive hydrogen bonds with unpaired nucleotides of 2008s does not participate in the recognition of pL1. Superimposition of the pL1: PvLDH complex with hLDH reveals steric clashes between pL1 and hLDH in contrast with no steric clashes between 2008s and hLDH. Therefore, specific protein recognition mode of pL1 is totally different from that of 2008s.1152Ysciescopu

A novel strategy for molecular interfaces optimization: the case of ferritin-transferrin receptor interaction

Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces

Computational analyses of the surface properties of protein–protein interfaces

This paper presents a survey of techniques that explore the surface properties of protein:protein interfaces so as to inform the prediction of probable sites of protein:protein interaction on newly determined protein structures

Bio-Communication of Bacteria and its Evolutionary Interrelations to Natural Genome Editing Competences of Viruses

Communicative competences enable bacteria to develop, organise and coordinate rich social life with a great variety of behavioral patterns even in which they organise themselves like multicellular organisms. They have existed for almost four billion years and still survive, being part of the most dramatic changes in evolutionary history such as DNA invention, cellular life, invention of nearly all protein types, partial constitution of eukaryotic cells, vertical colonisation of all eukaryotes, high adaptability through horizontal gene transfer and co-operative multispecies colonisation of all ecological niches. Recent research demonstrates that these bacterial competences derive from the aptitude of viruses for natural genome editing. 
	In contrast to a book which would be the appropriate space to outline in depth all communicative pathways inherent in bacterial life in this current article I want to give an overview for a broader readership over the great variety of bacterial bio-communication: In a first step I describe how they interpret and coordinate, what semiochemical vocabulary they share and which goals they try to reach. In a second stage I describe the main categories of sign-mediated interactions between bacterial and non-bacterial organisms, and between bacteria of the same or related species. In a third stage I will focus on the relationship between bacteria and their obligate settlers, i.e. viruses. We will see that bacteria are important hosts for multiviral colonisation and virally-determined order of nucleic acid sequences.

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The structure of human CD23 and its interactions with IgE and CD21

The low-affinity immunoglobulin E (IgE) receptor, CD23 (FcɛRII), binds both IgE and CD21 and, through these interactions, regulates the synthesis of IgE, the antibody isotype that mediates the allergic response. We have determined the three-dimensional structure of the C-type lectin domain of CD23 in solution by nuclear magnetic resonance spectroscopy. An analysis of concentration-dependent chemical shift perturbations have allowed us to identify the residues engaged in self-association to the trimeric state, whereas ligand-induced changes have defined the binding sites for IgE and CD21. The results further reveal that CD23 can bind both ligands simultaneously. Despite the C-type lectin domain structure, none of the interactions require calcium. We also find that IgE and CD23 can interact to form high molecular mass multimeric complexes. The interactions that we have described provide a solution to the paradox that CD23 is involved in both up- and down-regulation of IgE and provide a structural basis for the development of inhibitors of allergic disease

Analysis of the binding loops configuration and surface adaptation of different crystallized single‐domain antibodies in response to various antigens

Monoclonal antibodies have revolutionized the biomedical field through their ubiquitous utilization in different diagnostics and therapeutic applications. Despite this widespread use, their large size and structural complexity have limited their versatility in specific applications. The antibody variable region that is responsible for binding antigen is embodied within domains that can be rescued individually as single-domain antibody (sdAb) fragments. Because of the unique characteristics of sdAbs, such as low molecular weight, high physicochemical stability, and the ability to bind antigens inaccessible to conventional antibodies, they represent a viable alternative to full-length antibodies. Consequently, 149 crystal structures of sdAbs, originating from human (VH), camelids (VHH), or sharks (VNAR), were retrieved from the Protein Data Bank, and their structures were compared. The 3 types of sdAbs displayed complementarity determining regions (CDRs) with different lengths and configurations. CDR3 of the VHH and VNAR domains were dominated by pleated and extended orientations, respectively. Although VNAR showed the smallest average molecular weight and molecular surface area compared with VHH and VH antibodies. However, the solvent accessible surface area measurements of the 3 tested sdAbs types were very similar. All the antihapten VHH antibodies showed pleated CDR3, which were sufficient to create a binding pocket to accommodate haptens (methotrexate and azo dyes) in terms of shape and electrostatic potential. The sdAbs that recognized lysozyme showed more diversity in their CDR3 orientation to enable them to recognize various topographies of lysozyme. Subsequently, the three sdAb classes were different in size and surface area and have shown distinguishable ability to optimize their CDR length and orientation to recognize different antigen classes