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Evaluation of the Storage Stability of Extracellular Vesicles
Published on: May 22, 2019
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High throughput evaluation of macrocyclization strategies for conformer stabilization
Dan Sindhikara1, Ken Borrelli2
1Schrodinger, Inc. Department of Life Sciences, New York, NY, 10036, USA. dan.sindhikara@schrodinger.com.
Scientific Reports
|April 28, 2018
Summary
Computational methods can accelerate the discovery of potent macrocyclic drugs by predicting their ability to mimic known active linear compounds. This approach prioritizes macrocycles likely to adopt beneficial conformations for drug design.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Drug Discovery
Background:
- Macrocyclization stabilizes bioactive conformations, enhancing drug potency.
- Synthesis challenges limit traditional screening of macrocyclic compounds.
- Computational methods offer high-throughput screening for macrocycle design.
Purpose of the Study:
- To develop a computational method for assessing macrocycle conformational similarity to known active linear compounds.
- To enable rapid screening and prioritization of macrocyclic drug candidates.
- To leverage the correlation between conformational propensity and binding affinity.
Main Methods:
- Implementation of a method using an RMSD-based structural descriptor.
- Application of a Boltzmann-weighted propensity calculation.
- Retrospective analysis on three macrocycle linker optimization projects.
Main Results:
- The developed method successfully prioritized more potent macrocyclic compounds.
- The approach demonstrated effectiveness in differentiating compounds based on conformational adoption.
- Retrospective application validated the method's predictive capabilities.
Conclusions:
- The computational method serves as a fast screening tool for macrocycle design.
- It effectively prioritizes compounds by evaluating their propensity to adopt bioactive conformations.
- This strategy aids in overcoming synthesis limitations in macrocyclic drug discovery.
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