title: AutoBind: automatic extraction of protein-ligand-binding affinity data from biological literature.
abstract: BACKGROUND
  Determination of the binding affinity of a protein-ligand complex is important to quantitatively specify whether a particular small molecule will bind to the target protein. Besides, collection of comprehensive datasets for protein-ligand complexes and their corresponding binding affinities is crucial in developing accurate scoring functions for the prediction of the binding affinities of previously unknown protein-ligand complexes. In the past decades, several databases of protein-ligand-binding affinities have been created via visual extraction from literature. However, such approaches are time-consuming and most of these databases are updated only a few times per year. Hence, there is an immediate demand for an automatic extraction method with high precision for binding affinity collection.
  
  
  RESULTS
  We have created a new database of protein-ligand-binding affinity data, AutoBind, based on automatic information retrieval. We first compiled a collection of 1586 articles where the binding affinities have been marked manually. Based on this annotated collection, we designed four sentence patterns that are used to scan full-text articles as well as a scoring function to rank the sentences that match our patterns. The proposed sentence patterns can effectively identify the binding affinities in full-text articles. Our assessment shows that AutoBind achieved 84.22% precision and 79.07% recall on the testing corpus. Currently, 13 616 protein-ligand complexes and the corresponding binding affinities have been deposited in AutoBind from 17 221 articles.
  
  
  BACKGROUND
  AutoBind is automatically updated on a monthly basis, and it is freely available at http://autobind.csie.ncku.edu.tw/ and http://autobind.mc.ntu.edu.tw/. All of the deposited binding affinities have been refined and approved manually before being released.
authors: Department of Electrical Engineering, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
authors: Darby Tien-Hao
authors: DT
authors: Chang
authors: Chao-Hsuan
authors: CH
authors: Ke
authors: Jung-Hsin
authors: JH
authors: Lin
authors: Jung-Hsien
authors: JH
authors: Chiang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D016208:Databases, Factual; D016247:Information Storage and Retrieval / Q000379:methods*; D008024:Ligands; D011485:Protein Binding; D012984:Software
chemical_list: D008024:Ligands