Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database.

BACKGROUND: Structural studies are increasingly providing huge amounts of information on multi-protein assemblies. Although a complete understanding of cellular processes will be dependent on an explicit characterization of the intermolecular interactions that underlie these assemblies and mediate molecular recognition, these are not well described by standard representations. RESULTS: Here we present PICCOLO, a comprehensive relational database capturing the details of structurally characterized protein-protein interactions. Interactions are described at the level of interacting pairs of atoms, residues and polypeptide chains, with the physico-chemical nature of the interactions being characterized. Distance and angle terms are used to distinguish 12 different interaction types, including van der Waals contacts, hydrogen bonds and hydrophobic contacts. The explicit aim of PICCOLO is to underpin large-scale analyses of the properties of protein-protein interfaces. This is exemplified by an analysis of residue propensity and interface contact preferences derived from a much larger data set than previously reported. However, PICCOLO also supports detailed inspection of particular systems of interest. CONCLUSIONS: The current PICCOLO database comprises more than 260 million interacting atom pairs from 38,202 protein complexes. A web interface for the database is available at http://www-cryst.bioc.cam.ac.uk/piccolo.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

SInCRe—structural interactome computational resource for Mycobacterium tuberculosis

We have developed an integrated database for Mycobacterium tuberculosis H37Rv (Mtb) that collates information on protein sequences, domain assignments, functional annotation and 3D structural information along with protein–protein and protein–small molecule interactions. SInCRe (Structural Interactome Computational Resource) is developed out of CamBan (Cambridge and Bangalore) collaboration. The motivation for development of this database is to provide an integrated platform to allow easily access and interpretation of data and results obtained by all the groups in CamBan in the field of Mtb informatics. In-house algorithms and databases developed independently by various academic groups in CamBan are used to generate Mtb-specific datasets and are integrated in this database to provide a structural dimension to studies on tuberculosis. The SInCRe database readily provides information on identification of functional domains, genome-scale modelling of structures of Mtb proteins and characterization of the small-molecule binding sites within Mtb. The resource also provides structure-based function annotation, information on small-molecule binders including FDA (Food and Drug Administration)-approved drugs, protein–protein interactions (PPIs) and natural compounds that bind to pathogen proteins potentially and result in weakening or elimination of host–pathogen protein–protein interactions. Together they provide prerequisites for identification of off-target binding

What Can We Learn from the Evolution of Protein-Ligand Interactions to Aid the Design of New Therapeutics?

<div><p>Efforts to increase affinity in the design of new therapeutic molecules have tended to lead to greater lipophilicity, a factor that is generally agreed to be contributing to the low success rate of new drug candidates. Our aim is to provide a structural perspective to the study of lipophilic efficiency and to compare molecular interactions created over evolutionary time with those designed by humans. We show that natural complexes typically engage in more polar contacts than synthetic molecules bound to proteins. The synthetic molecules also have a higher proportion of unmatched heteroatoms at the interface than the natural sets. These observations suggest that there are lessons to be learnt from Nature, which could help us to improve the characteristics of man-made molecules. In particular, it is possible to increase the density of polar contacts without increasing lipophilicity and this is best achieved early in discovery while molecules remain relatively small.</p> </div

Linear regression of the proportion of heteroatoms to the polar ratio (as number of polar contacts divided by the total [polar + apolar] number of contacts) for the natural-product-like subset of molecules.

<p>Linear regression of the proportion of heteroatoms to the polar ratio (as number of polar contacts divided by the total [polar + apolar] number of contacts) for the natural-product-like subset of molecules.</p

Examples of polar ratio in protein complexes.

<p>Polar ratio is the number of polar contacts divided by the total [polar + apolar] number of contacts. These protein complexes are for proteins that bind to both protein partners (ratio p-p, left) and synthetic small molecules (ratio p-sm, right). The PDB code includes the interacting chains, for example 1TNF(AB:C) denotes chain A and B interacting with chain C of the TNF trimer, whereas 2AZ5 (C&D) denotes chains C and D interacting with the small molecule. When available, affinity measure and units is specified in table.</p

Binding affinity versus interaction profile.

<p>Binned binding affinity (BA) data for synthetic small molecules (A and B) and for small peptides (C and D). Bars in (A) and (C) denote the average of molecular properties for each affinity bin: rotatable bonds (red), sum of hydrogen bond donors and acceptors (blue), number of atoms (black) and AlogP (yellow, in the secondary right axis scale for clarity). Bars in (B) and (D) denote the average of polar ratio (orange) and the average heteroatom content (cyan). Error bars are the standard error of the mean.</p

Calculated properties versus interaction profile.

<p>The polar ratio (as number of polar contacts divided by the total [polar + apolar] number of contacts) versus molecular weight (A), AlogP (B), buried area upon binding (C) and sum of contacts (D) for protein complexes with synthetic small molecules. Different colors denote SCOP families: Protein kinase catalytic subunit (green), nuclear receptor ligand-binding domain (blue), eukaryotic proteases (red), retroviral proteases – retropepsin (cyan), reverse transcriptase (magenta), Higher-molecular weight phosphotyrosine protein phosphatases (yellow), HSP90 N-terminal domain (black). For clarity, only SCOP families binding to more than 20 different ligands are shown.</p

Scissors plots for the non-redundant-by-complex (Table S2) sets of protein complexes.

<p>a: synthetic small molecules bound to proteins; b: protein-protein interactions small molecule inhibitors bound to proteins; c: small peptides bound to proteins; d: natural small molecules bound to proteins; e: natural small molecules not containing phosphorus bound to proteins; f: transient protein-protein dimers; g: obligate protein-protein dimers; h: homo protein-protein interfaces from quaternary structures; i: hetero protein-protein interfaces from quaternary structures; polar (red) and apolar (blue) contacts are scattered against sum of contacts.</p