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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
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Efficient Crystal Structure Prediction for Structurally Related Molecules with Accurate and Transferable Tailor-Made
Alessandra Mattei1, Richard S Hong1, Hanno Dietrich2
1Solid State Chemistry, Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States.
Journal of Chemical Theory and Computation
|August 5, 2022
Summary
Quick-Crystal Structure Prediction (CSP) accelerates drug design by efficiently predicting crystal structures for related molecules. This novel approach uses tailored force fields, reducing computational costs significantly.
Area of Science:
- Computational chemistry
- Materials science
- Drug discovery
Background:
- Crystal structure prediction (CSP) is crucial for drug development, typically applied to individual molecules.
- Advancements in algorithms and computing power enable earlier CSP integration into the drug design cycle.
Purpose of the Study:
- Introduce Quick-CSP, a novel CSP paradigm for structurally related molecules.
- Enhance efficiency and accuracy in crystal structure prediction for drug design.
Main Methods:
- Utilize robust, transferable tailor-made force fields (TMFFs) with electrostatic multipoles for improved accuracy.
- Employ a fragment-based force field parameterization scheme for chemical families.
- Implement a new convergence criterion for efficient ab initio optimizations.
Main Results:
- Demonstrate TMFF transferability for chemically related molecules, benchmarked with BET domain inhibitors.
- Achieve significant cost savings (3-8x) compared to full CSP workflows.
- Validate the efficiency and accuracy of the Quick-CSP protocol.
Conclusions:
- Quick-CSP offers a cost-effective and efficient alternative for crystal structure prediction.
- The advancements expand CSP applications earlier in the drug design cycle.
- This approach guides molecular design and selection through accurate structural insights.
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