{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["19(1)"],"submitter":["Shimomura T"],"pubmed_abstract":["BACKGROUND:It had long been thought that a protein exhibits its specific function through its own specific 3D-structure under physiological conditions. However, subsequent research has shown that there are many proteins without specific 3D-structures under physiological conditions, so-called intrinsically disordered proteins (IDPs). This study presents a new technique for predicting intrinsically disordered regions in a protein, based on our average distance map (ADM) technique. The ADM technique was developed to predict compact regions or structural domains in a protein. In a protein containing partially disordered regions, a domain region is likely to be ordered, thus it is unlikely that a disordered region would be part of any domain. Therefore, the ADM technique is expected to also predict a disordered region between domains. RESULTS:The results of our new technique are comparable to the top three performing techniques in the community-wide CASP10 experiment. We further discuss the case of p53, a tumor-suppressor protein, which is the most significant protein among cell cycle regulatory proteins. This protein exhibits a disordered character as a monomer but an ordered character when two p53s form a dimer. CONCLUSION:Our technique can predict the location of an intrinsically disordered region in a protein with an accuracy comparable to the best techniques proposed so far. Furthermore, it can also predict a core region of IDPs forming definite 3D structures through interactions, such as dimerization. The technique in our study may also serve as a means of predicting a disordered region which would become an ordered structure when binding to another protein."],"journal":["BMC structural biology"],"pagination":["3"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6366092"],"repository":["biostudies-literature"],"pubmed_title":["A new technique for predicting intrinsically disordered regions based on average distance map constructed with inter-residue average distance statistics."],"pmcid":["PMC6366092"],"pubmed_authors":["Shimomura T","Nishijima K","Kikuchi T"],"additional_accession":[]},"is_claimable":false,"name":"A new technique for predicting intrinsically disordered regions based on average distance map constructed with inter-residue average distance statistics.","description":"BACKGROUND:It had long been thought that a protein exhibits its specific function through its own specific 3D-structure under physiological conditions. However, subsequent research has shown that there are many proteins without specific 3D-structures under physiological conditions, so-called intrinsically disordered proteins (IDPs). This study presents a new technique for predicting intrinsically disordered regions in a protein, based on our average distance map (ADM) technique. The ADM technique was developed to predict compact regions or structural domains in a protein. In a protein containing partially disordered regions, a domain region is likely to be ordered, thus it is unlikely that a disordered region would be part of any domain. Therefore, the ADM technique is expected to also predict a disordered region between domains. RESULTS:The results of our new technique are comparable to the top three performing techniques in the community-wide CASP10 experiment. We further discuss the case of p53, a tumor-suppressor protein, which is the most significant protein among cell cycle regulatory proteins. This protein exhibits a disordered character as a monomer but an ordered character when two p53s form a dimer. CONCLUSION:Our technique can predict the location of an intrinsically disordered region in a protein with an accuracy comparable to the best techniques proposed so far. Furthermore, it can also predict a core region of IDPs forming definite 3D structures through interactions, such as dimerization. The technique in our study may also serve as a means of predicting a disordered region which would become an ordered structure when binding to another protein.","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Feb","modification":"2024-11-20T18:37:31.677Z","creation":"2019-03-26T22:55:34Z"},"accession":"S-EPMC6366092","cross_references":{"pubmed":["30727987"],"doi":["10.1186/s12900-019-0101-3"]}}