Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study.

Digital health technologies can provide continuous monitoring and objective, real-world measures of Parkinson's disease (PD), but have primarily been evaluated in small, single-site studies. In this 12-month, multicenter observational study, we evaluated whether a smartwatch and smartphone application could measure features of early PD. 82 individuals with early, untreated PD and 50 age-matched controls wore research-grade sensors, a smartwatch, and a smartphone while performing standardized assessments in the clinic.

Identifying and characterising sources of variability in digital outcome measures in Parkinson's disease.

Smartphones and wearables are widely recognised as the foundation for novel Digital Health Technologies (DHTs) for the clinical assessment of Parkinson's disease. Yet, only limited progress has been made towards their regulatory acceptability as effective drug development tools. A key barrier in achieving this goal relates to the influence of a wide range of sources of variability (SoVs) introduced by measurement processes incorporating DHTs, on their ability to detect relevant changes to PD.

Structural and kinetic basis for the selectivity of aducanumab for aggregated forms of amyloid-β.

Aducanumab, a human-derived antibody targeting amyloid-β (Aβ), is in Phase 3 clinical trials for the treatment of Alzheimer's disease. Biochemical and structural analyses show that aducanumab binds a linear epitope formed by amino acids 3-7 of the Aβ peptide. Aducanumab discriminates between monomers and oligomeric or fibrillar aggregates based on weak monovalent affinity, fast binding kinetics and strong avidity for epitope-rich aggregates.

Structure-based cross-docking analysis of antibody-antigen interactions.

Antibody-antigen interactions are critical to our immune response, and understanding the structure-based biophysical determinants for their binding specificity and affinity is of fundamental importance. We present a computational structure-based cross-docking study to test the identification of native antibody-antigen interaction pairs among cognate and non-cognate complexes. We picked a dataset of 17 antibody-antigen complexes of which 11 have both bound and unbound structures available, and we generated a representative ensemble of cognate and non-cognate complexes.

Functional loss of semaphorin 3C and/or semaphorin 3D and their epistatic interaction with ret are critical to Hirschsprung disease liability.

Innervation of the gut is segmentally lost in Hirschsprung disease (HSCR), a consequence of cell-autonomous and non-autonomous defects in enteric neuronal cell differentiation, proliferation, migration, or survival. Rare, high-penetrance coding variants and common, low-penetrance non-coding variants in 13 genes are known to underlie HSCR risk, with the most frequent variants in the ret proto-oncogene (RET). We used a genome-wide association (220 trios) and replication (429 trios) study to reveal a second non-coding variant distal to RET and a non-coding allele on chromosome 7 within the class 3 Semaphorin gene cluster.

Protein-protein docking with dynamic residue protonation states.

Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation.

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27.

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets.

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions.

Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing.

Targeted DNA methylation using an artificially bisected M.HhaI fused to zinc fingers.

Little is known about the effects of single DNA methylation events on gene transcription. The ability to direct the methylation toward a single unique site within a genome would have broad use as a tool to study the effects of specific epigenetic changes on transcription. A targeted enzyme might also be useful in a therapy for diseases with an epigenetic component or as a means to site-specifically label DNA.

Rapid calculation of protein pKa values using Rosetta.

We developed a Rosetta-based Monte Carlo method to calculate the pK(a) values of protein residues that commonly exhibit variable protonation states (Asp, Glu, Lys, His, and Tyr). We tested the technique by calculating pK(a) values for 264 residues from 34 proteins. The standard Rosetta score function, which is independent of any environmental conditions, failed to capture pK(a) shifts.

A generalized approach to sampling backbone conformations with RosettaDock for CAPRI rounds 13-19.

In CAPRI rounds 13-19, the most native-like structure predicted by RosettaDock resulted in two high, one medium, and one acceptable accuracy model out of 13 targets. The current rounds of CAPRI were especially challenging with many unbound and homology modeled starting structures. Novel docking methods, including EnsembleDock and SnugDock, allowed backbone conformational sampling during docking and enabled the creation of more accurate models.