Protein Conformational Ensemble Docking for Drug Discovery
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Solution Overview
Problem
Current drug discovery methods, such as high-throughput screening and rational drug design, face limitations in identifying compounds that bind to various conformations of proteins, particularly missing compounds that interact with alternative structures, leading to inefficiencies in drug development.
Innovation Solution
A computational method and ranking system that determines and quantifies different protein conformations, docks compounds against these conformations, and calculates weighted scores to rank compounds based on their binding affinity, incorporating Markov State Models and Boltzmann docking to account for protein conformational heterogeneity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If high-throughput screening is used to search through large libraries of chemicals, then the screening speed is improved, but the ability to identify compounds binding to alternative protein conformations deteriorates
Solution Approach 1:
The method performs preliminary action by generating an ensemble of protein conformations through molecular dynamics simulations before the actual screening process. This pre-computation of multiple structural states allows the subsequent screening to account for conformational heterogeneity, improving the reliability of compound identification without sacrificing screening throughput.
Solution Approach 2:
The invention applies dynamics by transitioning from static crystal structure-based screening to dynamic ensemble-based screening. By incorporating time-dependent conformational changes and sampling multiple protein states, the method captures the dynamic nature of protein-ligand interactions, thereby improving identification accuracy while maintaining computational efficiency through selective sampling.
2Manufacturing precision
If rational drug design is used to design small molecules for specific crystal structures, then the design precision is improved, but the ability to identify compounds for alternative structures deteriorates
Solution Approach 1:
The method achieves universality by creating a multi-functional framework that evaluates compounds against multiple protein conformations simultaneously. The ensemble docking approach allows a single compound to be assessed for binding to various structural states, making the design process adaptable to different conformations while maintaining precision through weighted scoring based on conformational populations.
Solution Approach 2:
The invention applies parameter changes by modifying the structural parameters from a single crystal structure to an ensemble of conformations with varying structural parameters. By sampling conformational space and weighting structures by their population, the method adjusts the structural parameters to reflect physiological reality, improving both precision and conformational coverage.
3Loss of information
If only crystal structures are used for drug design, then the structural information availability is improved, but the conformational heterogeneity representation deteriorates
Solution Approach 1:
The method applies dynamics by replacing static crystal structure information with dynamic conformational ensembles. Molecular dynamics simulations generate time-dependent structural information that captures protein flexibility and conformational heterogeneity, providing a more complete picture of protein structure while maintaining computational tractability through selective sampling and ensemble weighting.
Data Source
AI summary
Aspects of the present disclosure relate to computing systems and computational methods for docking a library of compounds against a massive amount of conformations of a protein of interest.