Editing MotiveValidator (section)

=Background=

The advancement of research in structural biology has provided a large body of structural data deposited in various databases. One great example is the Protein Data Bank (PDB), which has been growing exponentially, and which currently consists of more than 100,000 structures of biomolecules and their complexes. Such large bodies of data, especially accumulated over a short period of time and using high throughput techniques, will inherently be plagued by a variety of problems.

Validation arose as a major issue in the structural biology community when it became apparent that some published structures contained serious errors, either documented (e.g., due to insufficient electron density in a certain area), or not. Structural databases generally require that the new submissions be checked prior to acceptance. The tools employed for presubmission validations work fairly well for well studied residues like amino acids or nucleotides. However, an essential step in the validation process is checking the ligand structure, because ligands play a key role in protein function, and also because they are the main source of errors in structures. A notable case of ligand validation is the analysis of carbohydrate structures<ref name="Lutteke_2004"/>, because they have complex topology and many chiral atoms. Yet carbohydrates are involved in a variety of fundamental biological processes and they have large pharmaceutical and diagnostic potential. Additionally, more than 60% of nontrivial-sized ligands (> 10 atoms) from the Protein Data Bank contain a carbohydrate. In recent years, many algorithms for validation, ligand validation and carbohydrate validation have been developed. Nonetheless, significant limitations persist, such as insufficient coverage of ligands and time inefficiency (i.e., calculations are time demanding and only one entry can be validated in each run).