Project description:ObjectiveEpilepsy is a suitable target for gene panel sequencing because a considerable portion of epilepsy is now explained by genetic components, especially in syndromic cases. However, previous gene panel studies on epilepsy have mostly focused on pediatric patients.MethodsWe enrolled adult epilepsy patients meeting any of the following criteria: family history of epilepsy, seizure onset age ≤ 19 years, neuronal migration disorder, and seizure freedom not achieved by dual anti-seizure medications. We sequenced the exonic regions of 211 epilepsy genes in these patients. To confirm the pathogenicity of a novel MTOR truncating variant, we electroporated vectors with different MTOR variants into developing mouse brains.ResultsA total of 92 probands and 4 affected relatives were tested, and the proportion of intellectual disability (ID) and/or developmental disability (DD) was 21.7%. As a result, twelve probands (13.0%) had pathogenic or likely pathogenic variants in the following genes or regions: DEPDC5, 15q12-q13 duplication (n = 2), SLC6A1, SYNGAP1, EEF1A2, LGI1, MTOR, KCNQ2, MEF2C, and TSC1 (n = 1). We confirmed the functional impact of a novel truncating mutation in the MTOR gene (c.7570C > T, p.Gln2524Ter) that disrupted neuronal migration in a mouse model. The diagnostic yield was higher in patients with ID/DD or childhood-onset seizures. We also identified additional candidate variants in 20 patients that could be reassessed by further studies.SignificanceOur findings underscore the clinical utility of gene panel sequencing in adult epilepsy patients suspected of having genetic etiology, especially those with ID/DD or early-onset seizures. Gene panel sequencing could not only lead to genetic diagnosis in a substantial portion of adult epilepsy patients but also inform more precise therapeutic decisions based on their genetic background.Plain language summaryThis study demonstrated the effectiveness of gene panel sequencing in adults with epilepsy, revealing pathogenic or likely pathogenic variants in 13.0% of patients. Higher diagnostic yields were observed in those with neurodevelopmental disorders or childhood-onset seizures. Additionally, we have shown that expanding genetic studies into adult patients would uncover new types of pathogenic variants for epilepsy, contributing to the advancement of precision medicine for individuals with epilepsy. In conclusion, our results highlight the practical value of employing gene panel sequencing in adult epilepsy patients, particularly when genetic etiology is clinically suspected.

Project description:Binding free energy calculations predict the potency of compounds to protein binding sites in a physically rigorous manner and see broad application in prioritizing the synthesis of novel drug candidates. Relative binding free energy (RBFE) calculations have emerged as an industry-standard approach to achieve highly accurate rank-order predictions of the potency of related compounds; however, this approach requires that the ligands share a common scaffold and a common binding mode, restricting the methods' domain of applicability. This is a critical limitation since complex modifications to the ligands, especially core hopping, are very common in drug design. Absolute binding free energy (ABFE) calculations are an alternate method that can be used for ligands that are not congeneric. However, ABFE suffers from a known problem of long convergence times due to the need to sample additional degrees of freedom within each system, such as sampling rearrangements necessary to open and close the binding site. Here, we report on an alternative method for RBFE, called Separated Topologies (SepTop), which overcomes the issues in both of the aforementioned methods by enabling large scaffold changes between ligands with a convergence time comparable to traditional RBFE. Instead of only mutating atoms that vary between two ligands, this approach performs two absolute free energy calculations at the same time in opposite directions, one for each ligand. Defining the two ligands independently allows the comparison of the binding of diverse ligands without the artificial constraints of identical poses or a suitable atom-atom mapping. This approach also avoids the need to sample the unbound state of the protein, making it more efficient than absolute binding free energy calculations. Here, we introduce an implementation of SepTop. We developed a general and efficient protocol for running SepTop, and we demonstrated the method on four diverse, pharmaceutically relevant systems. We report the performance of the method, as well as our practical insights into the strengths, weaknesses, and challenges of applying this method in an industrial drug design setting. We find that the accuracy of the approach is sufficiently high to rank order ligands with an accuracy comparable to traditional RBFE calculations while maintaining the additional flexibility of SepTop.

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Broadening instructional scope with network visualization.

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