Tau Protein Cryptic Pocket Stabilization for Aggregation Inhibition
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Solution Overview
Problem
Current understanding of amyloid fibril formation from disjoint monomers is elusive, and there is no agreed description of the primary stages of nucleation from a pool of disjoint soluble oligomeric species, making it challenging to develop effective inhibitors for tau aggregation in neurodegenerative diseases like Alzheimer's.
Innovation Solution
A multistep computational protocol is used to explore the conformational flexibility of a truncated tau fragment, identifying a cryptic binding pocket that stabilizes the tau protein, preventing its aggregation into paired helical filaments by binding small molecules such as LMT, which are designed to interact with specific residues like Leu315, Ser341, and Lys347.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computational methods are used to identify binding pockets and design modulators, then the ability to inhibit tau aggregation is improved, but the complexity of the method increases
Solution Approach 1:
The method segments the tau protein structure into specific regions (residues 315-378) and identifies discrete binding pockets within this segment. The computational protocol divides the analysis into distinct steps: structure preparation, binding pocket identification, and modulator design, making the complex process more manageable and systematic
Solution Approach 2:
The method performs preliminary computational analysis to identify cryptic binding pockets and characterize their properties before actual modulator design begins. This preliminary characterization of residue interactions and pocket geometry enables more efficient and targeted drug design, reducing overall complexity
2Manufacturing precision
If structure coordinates of tau intermediates are used for rational drug design, then the precision of modulator design is improved, but the difficulty of obtaining and using these coordinates increases
Solution Approach 1:
The method uses computational models and molecular dynamics simulations as intermediaries to bridge the gap between available experimental structure data and the desired high-precision modulator design. These computational tools translate limited experimental coordinates into comprehensive structural insights about binding pockets and intermediate states
Solution Approach 2:
The method creates computational copies and models of tau protein structures, including intermediate aggregation states. By working with these computational replicas rather than requiring direct experimental determination of every intermediate state, the method achieves high precision in modulator design without the prohibitive difficulty of obtaining all necessary experimental coordinates
Data Source
AI summary
The present invention relates generally to methods for selecting or designing a compound for modulating the aggregation of a Tau protein. The method comprising using computer-implemented molecular modelling means to compare the three-dimensional structure of a candidate compound with a three-dimensional structure of at least a part of the Tau protein comprising amino acids 315-378 and determine whether the candidate compound is able to simultaneously form non-covalent interactions with two or more of Leu315, Ser341, Glu342, Lys343, Phe346, Lys347, Val350, Ser352, Ile354, Lys369, Ile371, Glu372, Phe378 and Thr373. A candidate compound that is able to form said interactions is predicted to modulate the aggregation of the Tau protein or truncated form thereof. Methods using a three-dimensional structural model of at least a part of the Tau protein comprising amino acids 315-378, wherein the model is an intermediate in the aggregation process of the part of the Tau protein with a paired helical filament (PHF) are also described, as are computing systems and products.