Structural interactomics: informatics approaches to aid the interpretation of genetic variation and the development of novel therapeutics

Lee, Semin; Brown, Alan; Pitt, William R.; Higueruelo, Alícia P.; Gong, Sungsam; Bickerton, G. Richard J.; Schreyer, Adrian; Tanramluk, Duangrudee; Baylay, Alison J.; Blundell, Tom L.

doi:10.1039/b906402h

Cited by 8 publications

(6 citation statements)

References 200 publications

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“…Such methods can be used on a large scale to predict whole interactomes (Juan et al , 2008) but their applicability has limitations. Protein structure information is often incorporated with interaction data (reviewed in Lee et al , 2009); however, this structural information has rarely been used for the large‐scale prediction of protein interaction partners, which is surprising given that it is the structural features of two proteins that determine if they interact. Aloy and Russell (2002) developed a method that mapped homologues of interacting proteins onto the structure of complexes and assessed if the homologues were likely to fit together and therefore interact.…”

Section: Introductionmentioning

confidence: 99%

Towards the prediction of protein interaction partners using physical docking

Wass

Fuentes

Pons

et al. 2011

Molecular Systems Biology

115

134

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Section: Introductionmentioning

confidence: 99%

Towards the prediction of protein interaction partners using physical docking

Wass

Fuentes

Pons

et al. 2011

Molecular Systems Biology

115

134

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show abstract

“…Through the mapping between sequence and structures, information about proteinprotein interaction (PICCOLO) [141], protein-nucleic acid interaction (BIPA) [133], protein-ligand interaction (CREDO) [134] and nsSNPs on protein structure are interconnected [55,142]. The structural annotations are mainly from the local structural environments of amino acid residues determined by JOY [143] and presented and highlighted using Jmol, a molecular viewer [144].…”

Section: Estimating Stability Change By Investigating Protein Structumentioning

confidence: 99%

Meet Me Halfway: When Genomics Meets Structural Bioinformatics

Gong

Worth

Cheng

et al. 2011

J. of Cardiovasc. Trans. Res.

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The DNA sequencing technology developed by Frederick Sanger in the 1970s established genomics as the basis of comparative genetics. The recent invention of next-generation sequencing (NGS) platform has added a new dimension to genome research by generating ultra-fast and high-throughput sequencing data in an unprecedented manner. The advent of NGS technology also provides the opportunity to study genetic diseases where sequence variants or mutations are sought to establish a causal relationship with disease phenotypes. However, it is not a trivial task to seek genetic variants responsible for genetic diseases and even harder for complex diseases such as diabetes and cancers. In such polygenic diseases, multiple genes and alleles, which can exist in healthy individuals, come together to contribute to common disease phenotypes in a complex manner. Hence, it is desirable to have an approach that integrates omics data with both knowledge of protein structure and function and an understanding of networks/pathways, i.e. functional genomics and systems biology; in this way, genotype-phenotype relationships can be better understood. In this review, we bring this 'bottom-up' approach alongside the current NGS-driven genetic study of genetic variations and disease aetiology. We describe experimental and computational techniques for assessing genetic variants and their deleterious effects on protein structure and function.

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“…Numerous databases describe PPIs in terms of their three-dimensional (3D) protein structures, and these are summarised in Table 1 (Bickerton, 2009; Lee et al 2009). 3D Interaction Domains (3DID; (Stein et al 2011)) describe intra- and inter-molecular interactions between protein families (Pfam) domains from high-resolution crystal structures, and includes functional annotations based on Gene Ontology and predicted similarity of interactions across families.…”

Section: Ppis and Their Chemical Modulatorsmentioning

confidence: 99%

Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery

Winter

Higueruelo

Marsh

et al. 2012

Quart. Rev. Biophys.

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Drug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein-protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Nevertheless, encouragement has come from the recognition that a few amino acids - so-called hotspots - may contribute the majority of interaction-free energy. The challenges posed by protein-protein interactions have led to a wellspring of creative approaches, including proteomimetics, stapled α-helical peptides and a plethora of antibody inspired molecular designs. Here, we review a more generic approach: fragment-based drug discovery. Fragments allow novel areas of chemical space to be explored more efficiently, but the initial hits have low affinity. This means that they will not normally disrupt PPIs, unless they are tethered, an approach that has been pioneered by Wells and co-workers. An alternative fragment-based approach is to stabilise the uncomplexed components of the multiprotein system in solution and employ conventional fragment-based screening. Here, we describe the current knowledge of the structures and properties of protein-protein interactions and the small molecules that can modulate them. We then describe the use of sensitive biophysical methods - nuclear magnetic resonance, X-ray crystallography, surface plasmon resonance, differential scanning fluorimetry or isothermal calorimetry - to screen and validate fragment binding. Fragment hits can subsequently be evolved into larger molecules with higher affinity and potency. These may provide new leads for drug candidates that target protein-protein interactions and have therapeutic value.

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Structural interactomics: informatics approaches to aid the interpretation of genetic variation and the development of novel therapeutics

Cited by 8 publications

References 200 publications

Towards the prediction of protein interaction partners using physical docking

Towards the prediction of protein interaction partners using physical docking

Meet Me Halfway: When Genomics Meets Structural Bioinformatics

Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery

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