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Russ, W. P.

Publications and source records attributed to Russ, W. P..

3 recordsLinked to original sources

Selective Targeting of Pathogenic Tau Seeds via a Novel VHH

In Alzheimers disease (AD) and related tauopathies, progressive pathology has been linked to prion mechanisms, whereby ordered tau assemblies, or "seeds," form in one cell and transit to neighboring or connected cells where they serve as templates for their own replication. Despite intensive efforts to develop early diagnosis and effective treatment, none has emerged. This is due partly to the structural heterogeneity of tau seeds and limitations in selectively targeting their pathogenic conformations. Here we report the discovery of a camelid variable heavy domain of heavy chain (VHH) that preferentially binds tau seeds of AD, corticobasal degeneration (CBD), and PS19 tauopathy mouse brains. From a published synthetic VHH yeast display library, we identified VHH clones that bound 2N4R tau monomer. After counter-screening for immunoprecipitation of seeding from human brain, we identified two seed-selective anti-tau VHH--VHH(510) and VHH(50)--that preferentially bound pathological tau. We enhanced the stability of these VHHs through framework mutations without affecting their seed-binding characteristics. We characterized VHH(510) in detail, determining that it binds the carboxy terminus of tau, maintains robust seed avidity even in the presence of competing monomer, and stains pathological tau inclusions in mouse and human AD tissues. These results highlight the power of seed-selective VHH to bind pathogenic tau, paving the way for future therapeutic and diagnostic applications across a wide range of neurodegenerative disorders.

neuroscience↗

Undersampling and the inference of coevolution in proteins

Protein structure, function, and evolution depend on local and collective epistatic interactions between amino acids. A powerful approach to defining these interactions is to construct models of couplings between amino acids that reproduce the empirical statistics (frequencies and correlations) observed in sequences comprising a protein family. The top couplings are then interpreted. Here, we show that as currently implemented, this inference is always biased, a problem that fundamentally arises from the distinct scales at which epistasis occurs in proteins in the context of limited sampling. We show that these issues explain the ability of current approaches to predict tertiary contacts between amino acids and the inability to obviously expose larger networks of functionally-relevant, collectively evolving residues called sectors. This work provides a necessary foundation for more deeply understanding and improving evolution-based models of proteins.

biophysics↗

Evolution-based design of chorismate mutase enzymes

The rational design of enzymes is an important goal for both fundamental and practical reasons. Here, we describe a design process in which we learn the constraints for specifying proteins purely from evolutionary sequence data, build libraries of synthetic genes, and test them for activity in vivo using a quantitative complementation assay. For chorismate mutase, a key enzyme in the biosynthesis of aromatic amino acids, we demonstrate the design of natural-like catalytic function with substantial sequence diversity. Further optimization focuses the generative model towards function in a specific genomic context. The data show that sequence-based statistical models suffice to specify proteins and provide access to an enormous space of synthetic functional sequences. This result provides a foundation for a general process for evolution-based design of artificial proteins. One-sentence summaryAn evolution-based, data-driven engineering process can build synthetic functional enzymes.

biochemistry↗