<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>19(1)</volume><submitter>Shimomura T</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>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.&lt;h4>Results&lt;/h4>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.&lt;h4>Conclusion&lt;/h4>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.</pubmed_abstract><journal>BMC structural biology</journal><pagination>3</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC6366092</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>A new technique for predicting intrinsically disordered regions based on average distance map constructed with inter-residue average distance statistics.</pubmed_title><pmcid>PMC6366092</pmcid><pubmed_authors>Shimomura T</pubmed_authors><pubmed_authors>Nishijima K</pubmed_authors><pubmed_authors>Kikuchi T</pubmed_authors></additional><is_claimable>false</is_claimable><name>A new technique for predicting intrinsically disordered regions based on average distance map constructed with inter-residue average distance statistics.</name><description>&lt;h4>Background&lt;/h4>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.&lt;h4>Results&lt;/h4>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.&lt;h4>Conclusion&lt;/h4>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.</description><dates><release>2019-01-01T00:00:00Z</release><publication>2019 Feb</publication><modification>2026-05-05T01:29:13.207Z</modification><creation>2025-06-01T12:40:34.336Z</creation></dates><accession>S-EPMC6366092</accession><cross_references><pubmed>30727987</pubmed><doi>10.1186/s12900-019-0101-3</doi></cross_references></HashMap>