Binding MOAD, a high-quality protein ligand database

Benson, Mark L.; Smith, Richard; Khazanov, Nickolay A.; Dimcheff, Brandon; Beaver, John; Dresslar, Peter; Nerothin, Jason; Carlson, Heather A.

doi:10.1093/nar/gkm911

Cited by 161 publications

(153 citation statements)

References 20 publications

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“…In this respect, there is an increasing amount of protein structures having a co-crystallized ligand in the binding cavity. [4,63,64] In these cases, identifying the binding cavity is straightforward and the residues defining it can be readily selected by its proximity to the interacting ligand. However, in many other instances, protein structure entries do not contain any ligand.…”

Section: Binding Site Detectionmentioning

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: Binding Site Detectionmentioning

confidence: 99%

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Jalencas

Mestres

2013

Molecular Informatics

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“…[70][71][72] BindingMOAD is thus particularly relevant to structure-based drug discovery. One may browse and search structure and affinity data via a protein classification, PDB ID, enzyme classification number, keyword or author.…”

Section: Other Small Molecule Databases Ofmentioning

confidence: 99%

Public Domain Databases for Medicinal Chemistry

Nicola

and

Gilson

2013

Methods and Principles in Medicinal Chemistry

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“…A growing number of publications address the errors in Xray structures in order to generate clean structure datasets. [13,[55][56][57][58][59] Here, we want to highlight only the most common issues with X-ray structures.…”

Section: Issues With Protein Structural Datamentioning

confidence: 99%

“…Examples of databases containing such data are ChEMBL, [9] PubChem, [10,11] BindingDB, [12] BindingMOAD [13] and PDBbind. [14,15] Similarities and differences between these databases are extensively examined in several recent papers and therefore not discussed here.…”

Section: Introductionmentioning

confidence: 99%

Quality Issues with Public Domain Chemogenomics Data

Kalliokoski

Krämer

Vulpetti

2013

Molecular Informatics

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The key concept in chemogenomics is the similarity principle that states that similar ligands should bind similar targets. Chemogenomic analysis requires large amounts of data and both powerful computational algorithms and computers. Data used for chemogenomics analysis can either be compiled from open sources, or they can be produced in-house as is often done in the pharmaceutical industry. The chemogenomic modeller often has to resort to mixing activity values from different laboratories and even assay types to facilitate chemogenomic analysis. The amount of chemogenomics data available in the public domain has dramatically increased in recent years, allowing fully traceable analysis on a continuously increasing scale. However, some warning flags about the data quality have been raised and because the primary data determine the accuracy of chemogenomic analysis, the quality of the data is one of the key questions in chemogenomics. This mini-review discusses some of the most common issues with public domain biological data related to chemogenomic analysis. The errors in data can originate from problems with the experiments themselves and their interpretation, or from more mundane issues such as data extraction and annotation. These issues are not unique for a certain database but are shared by all the public domain databases and can plague commercial and in-house bioactivity databases as well.

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Binding MOAD, a high-quality protein ligand database

Cited by 161 publications

References 20 publications

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Identification of Similar Binding Sites to Detect Distant Polypharmacology

Public Domain Databases for Medicinal Chemistry

Quality Issues with Public Domain Chemogenomics Data

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