000131333 001__ 131333
000131333 005__ 20260217205452.0
000131333 0247_ $$2doi$$a10.1002/advs.202305177
000131333 0248_ $$2sideral$$a136787
000131333 037__ $$aART-2024-136787
000131333 041__ $$aeng
000131333 100__ $$aLarrea-Sebal, Asier
000131333 245__ $$aOptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues
000131333 260__ $$c2024
000131333 5060_ $$aAccess copy available to the general public$$fUnrestricted
000131333 5203_ $$aFamilial hypercholesterolemia (FH) is an inherited metabolic disease affecting cholesterol metabolism, with 90% of cases caused by mutations in the LDL receptor gene (LDLR), primarily missense mutations. This study aims to integrate six commonly used predictive software to create a new model for predicting LDLR mutation pathogenicity and mapping hot spot residues. Six predictive‐software are selected: Polyphen‐2, SIFT, MutationTaster, REVEL, VARITY, and MLb‐LDLr. Software accuracy is tested with the characterized variants annotated in ClinVar and, by bioinformatic and machine learning techniques all models are integrated into a more accurate one. The resulting optimized model presents a specificity of 96.71% and a sensitivity of 98.36%. Hot spot residues with high potential of pathogenicity appear across all domains except for the signal peptide and the O‐linked domain. In addition, translating this information into 3D structure of the LDLr highlights potentially pathogenic clusters within the different domains, which may be related to specific biological function. The results of this work provide a powerful tool to classify LDLR pathogenic variants. Moreover, an open‐access guide user interface (OptiMo‐LDLr) is provided to the scientific community. This study shows that combination of several predictive software results in a more accurate prediction to help clinicians in FH diagnosis.
000131333 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000131333 590__ $$a14.1$$b2024
000131333 592__ $$a3.775$$b2024
000131333 591__ $$aMATERIALS SCIENCE, MULTIDISCIPLINARY$$b33 / 461 = 0.072$$c2024$$dQ1$$eT1
000131333 591__ $$aNANOSCIENCE & NANOTECHNOLOGY$$b15 / 147 = 0.102$$c2024$$dQ1$$eT1
000131333 591__ $$aCHEMISTRY, MULTIDISCIPLINARY$$b19 / 239 = 0.079$$c2024$$dQ1$$eT1
000131333 593__ $$aBiochemistry, Genetics and Molecular Biology (miscellaneous)$$c2024$$dQ1
000131333 593__ $$aChemical Engineering (miscellaneous)$$c2024$$dQ1
000131333 593__ $$aPhysics and Astronomy (miscellaneous)$$c2024$$dQ1
000131333 593__ $$aMaterials Science (miscellaneous)$$c2024$$dQ1
000131333 593__ $$aMedicine (miscellaneous)$$c2024$$dQ1
000131333 593__ $$aEngineering (miscellaneous)$$c2024$$dQ1
000131333 594__ $$a18.2$$b2024
000131333 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000131333 700__ $$aSasiain, Iñaki
000131333 700__ $$aJebari-Benslaiman, Shifa
000131333 700__ $$aGalicia-Garcia, Unai
000131333 700__ $$aUribe, Kepa B.
000131333 700__ $$aBenito-Vicente, Asier
000131333 700__ $$0(orcid)0000-0003-1028-8581$$aGracia-Rubio, Irene$$uUniversidad de Zaragoza
000131333 700__ $$aBediaga-Bañeres, Harbil
000131333 700__ $$aArrasate, Sonia
000131333 700__ $$aCenarro, Ana
000131333 700__ $$0(orcid)0000-0001-7043-0952$$aCiveira, Fernando$$uUniversidad de Zaragoza
000131333 700__ $$aGonzález-Díaz, Humberto
000131333 700__ $$aMartín, Cesar
000131333 7102_ $$11003$$2027$$aUniversidad de Zaragoza$$bDpto. Anatom.Histolog.Humanas$$cArea Anatom.Embriol.Humana
000131333 7102_ $$11007$$2610$$aUniversidad de Zaragoza$$bDpto. Medicina, Psiqu. y Derm.$$cArea Medicina
000131333 773__ $$g11, 13 (2024), 2305177 [15 pp.]$$pAdv. sci.$$tAdvanced Science$$x2198-3844
000131333 8564_ $$s8211033$$uhttps://zaguan.unizar.es/record/131333/files/texto_completo.pdf$$yVersión publicada
000131333 8564_ $$s2548920$$uhttps://zaguan.unizar.es/record/131333/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000131333 909CO $$ooai:zaguan.unizar.es:131333$$particulos$$pdriver
000131333 951__ $$a2026-02-17-20:19:24
000131333 980__ $$aARTICLE