Dataset Information

Predicting potentially pathogenic effects of hRPE65 missense mutations: a computational strategy based on molecular dynamics simulations.

ABSTRACT: The human retinal pigment epithelium-specific 65-kDa protein (hRPE65) plays a crucial role within the retinoid visual cycle and several mutations affecting either its expression level or its enzymatic function are associated with inherited retinal diseases such as Retinitis Pigmentosa. The gene therapy product voretigene neparvovec (Luxturna) has been recently approved for treating hereditary retinal dystrophies; however, the treatment is currently accessible only to patients presenting confirmed biallelic mutations that severely impair hRPE65 function, and many reported hRPE65 missense mutations lack sufficient evidences for proving their pathogenicity. In this context, we developed a computational approach aimed at evaluating the potential pathogenic effect of hRPE65 missense variants located on the dimerisation domain of the protein. The protocol evaluates how mutations may affect folding and conformation stability of this protein region, potentially helping clinicians to evaluate the eligibility for gene therapy of patients diagnosed with this type of hRPE65 variant of uncertain significance.

SUBMITTER: Poli G

PROVIDER: S-EPMC9225791 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting potentially pathogenic effects of <i>h</i>RPE65 missense mutations: a computational strategy based on molecular dynamics simulations.

Poli Giulio G Barravecchia Ivana I Demontis Gian Carlo GC Sodi Andrea A Saba Alessandro A Rizzo Stanislao S Macchia Marco M Tuccinardi Tiziano T

Journal of enzyme inhibition and medicinal chemistry 20221201 1

The human retinal pigment epithelium-specific 65-kDa protein (<i>h</i>RPE65) plays a crucial role within the retinoid visual cycle and several mutations affecting either its expression level or its enzymatic function are associated with inherited retinal diseases such as Retinitis Pigmentosa. The gene therapy product voretigene neparvovec (Luxturna) has been recently approved for treating hereditary retinal dystrophies; however, the treatment is currently accessible only to patients presenting c ...[more]

PMID: 35726567

Similar Datasets

Project description:BackgroundRecent advances in sequencing technologies have greatly increased the identification of mutations in cancer genomes. However, it remains a significant challenge to identify cancer-driving mutations, since most observed missense changes are neutral passenger mutations. Various computational methods have been developed to predict the effects of amino acid substitutions on protein function and classify mutations as deleterious or benign. These include approaches that rely on evolutionary conservation, structural constraints, or physicochemical attributes of amino acid substitutions. Here we review existing methods and further examine eight tools: SIFT, PolyPhen2, Condel, CHASM, mCluster, logRE, SNAP, and MutationAssessor, with respect to their coverage, accuracy, availability and dependence on other tools.ResultsSingle nucleotide polymorphisms with high minor allele frequencies were used as a negative (neutral) set for testing, and recurrent mutations from the COSMIC database as well as novel recurrent somatic mutations identified in very recent cancer studies were used as positive (non-neutral) sets. Conservation-based methods generally had moderately high accuracy in distinguishing neutral from deleterious mutations, whereas the performance of machine learning based predictors with comprehensive feature spaces varied between assessments using different positive sets. MutationAssessor consistently provided the highest accuracies. For certain combinations metapredictors slightly improved the performance of included individual methods, but did not outperform MutationAssessor as stand-alone tool.ConclusionsOur independent assessment of existing tools reveals various performance disparities. Cancer-trained methods did not improve upon more general predictors. No method or combination of methods exceeds 81% accuracy, indicating there is still significant room for improvement for driver mutation prediction, and perhaps more sophisticated feature integration is needed to develop a more robust tool.

Dataset Information

Predicting potentially pathogenic effects of hRPE65 missense mutations: a computational strategy based on molecular dynamics simulations.

Publications

Predicting potentially pathogenic effects of <i>h</i>RPE65 missense mutations: a computational strategy based on molecular dynamics simulations.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets