Old friends in new guise: repositioning of known drugs with structural bioinformatics

Haupt, V. Joachim; Schroeder, Michael

doi:10.1093/bib/bbr011

Cited by 137 publications

(95 citation statements)

References 104 publications

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“…In this respect, detection of similar local surface regions can be used to identify proteins that could interact with the same molecule. [10,169] One of the first examples where similarities between binding sites of unrelated proteins could explain polypharmacology was reported by Weber et al [170] They realized that the unsubstituted arylsulfonamide moiety present in COX-2 selective inhibitors, such as celecoxib and valdecoxib, was also commonly present in carbonic anhydrase (CA) inhibitors. Using enzyme kinetics and X-ray crystallography, they were able to confirm an unexpected nanomolar affinity of celecoxib and valdecoxib for isoenzymes of the CA family.…”

Section: Detection Of Distant Polypharmacologymentioning

confidence: 99%

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Jalencas

Mestres

2013

Molecular Informatics

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The ability of small molecules to interact with multiple proteins is referred to as polypharmacology. This property is often linked to the therapeutic action of drugs but it is known also to be responsible for many of their side effects. Because of its importance, the development of computational methods that can predict drug polypharmacology has become an important line of research that led recently to the identification of many novel targets for known drugs. Nowadays, the majority of these methods are based on measuring the similarity of a query molecule against the hundreds of thousands of molecules for which pharmacological data on thousands of proteins are available in public sources. However, similarity-based methods are inherently biased by the chemical coverage offered by the active molecules present in those public repositories, which limits significantly their capacity to predict interactions with proteins structurally and functionally unrelated to any of the already known targets for drugs. It is in this respect that structure-based methods aiming at identifying similar binding sites may offer an alternative complementary means to ligand-based methods for detecting distant polypharmacology. The different existing approaches to binding site detection, representation, comparison, and fragmentation are reviewed and recent successful applications presented.

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Section: Detection Of Distant Polypharmacologymentioning

confidence: 99%

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Jalencas

Mestres

2013

Molecular Informatics

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“…For example, detailed knowledge of a target protein's three-dimensional structure facilitates the development of more selective drugs [169,325,326] and second-generation therapeutics for treating patients with unresponsive disease [327]. In addition, comparative analysis of target protein structures of currently marketed drugs allows for efficient drug repurposing to accelerate drug development for treating rare and orphan diseases [328][329][330]. Finally, structural knowledge of a drug target is critical for the intelligent combination of therapeutics acting on a single target in order to improve clinical efficacy and reduce the emergence of drug-resistant variants [331,332].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics and variability in drug response: a protein structural perspective

Lahti

Tang

Capriotti

et al. 2012

J. R. Soc. Interface.

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Marketed drugs frequently perform worse in clinical practice than in the clinical trials on which their approval is based. Many therapeutic compounds are ineffective for a large subpopulation of patients to whom they are prescribed; worse, a significant fraction of patients experience adverse effects more severe than anticipated. The unacceptable risk -benefit profile for many drugs mandates a paradigm shift towards personalized medicine. However, prior to adoption of patient-specific approaches, it is useful to understand the molecular details underlying variable drug response among diverse patient populations. Over the past decade, progress in structural genomics led to an explosion of available three-dimensional structures of drug target proteins while efforts in pharmacogenetics offered insights into polymorphisms correlated with differential therapeutic outcomes. Together these advances provide the opportunity to examine how altered protein structures arising from genetic differences affect protein -drug interactions and, ultimately, drug response. In this review, we first summarize structural characteristics of protein targets and common mechanisms of drug interactions. Next, we describe the impact of coding mutations on protein structures and drug response. Finally, we highlight tools for analysing protein structures and protein -drug interactions and discuss their application for understanding altered drug responses associated with protein structural variants.

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“…Similarly, ligand-based approaches include methods like reverse pharmacophore mapping, shape-and electrostatics screening. Reverse pharmacophore matching algorithms such as PharmMapper involve finding the best interaction mode between the potential target candidates and ligand molecule [10]. PharmMapper uses the pharmacophore mapping approach and carries a large, internal collection of pharmacophore databases, namely PharmTargetDB [11] annotated from all the targets information in BindingDB [12], DrugBank [13] and potential drug target database (PDTD) [14], including over 7000 receptor-based pharmacophore models (covering over 1500 drug targets information).…”

Section: Introductionmentioning

confidence: 99%

Inverse Virtual Screening in Drug Repositioning: Detailed Investigation and Case Studies

Warrier

Kharkar

2016

Crystallizing Ideas – The Role of Chemistry

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Inverse virtual screening is a useful tool for drug repositioning or repurposing. The utility of this tool lies in the identification of potential targets for small-molecule ligands. With reference to drug repositioning, approved/existing small-molecule drugs can be processed by inverse virtual screening for the discovery of potential new molecular targets for such drugs. Both the ligand-and structure-based approaches can be used for the in silico screening. PharmMapper is a web-based tool for ligand-based inverse screening that employs pharmacophore mapping approach and identifies potential target candidates for small molecules. The present study demonstrates the usefulness of this approach for computational repositioning of approved/existing drugs. Here, query molecules belonging to protein kinase inhibitors, monoamine transporter inhibitors and G protein-coupled receptor antagonists were used. The results revealed potential novel molecular targets for the query molecules. Detailed literature search involving the query molecule-novel target pair led to interesting findings. The book chapter summarizes the interesting outcomes of the ligand-based inverse virtual screening.

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Old friends in new guise: repositioning of known drugs with structural bioinformatics

Cited by 137 publications

References 104 publications

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Bioinformatics and variability in drug response: a protein structural perspective

Inverse Virtual Screening in Drug Repositioning: Detailed Investigation and Case Studies

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