Jeffrey M. Lotthammer

This paper introduces GOOSE, a computational framework for designing intrinsically disordered proteins, and demonstrates its ability to create IDRs with specific functional responses.

The paper develops a method to predict intermolecular interactions between intrinsically disordered regions and partner proteins using chemical physics principles.

This paper introduces an algorithm to quantify local conformational heterogeneity in protein simulations, distinguishing between well-sampled, poorly-sampled, and folded regions of disordered proteins.

STARLING predicts conformational ensembles of disordered proteins from sequence, enabling rapid analysis of their structural plasticity and functional implications.

The paper shows that CIB2/3 and TMC1/2 form complexes essential for hair-cell mechanotransduction in vertebrates, supported by structural and functional analyses.

Metapredict V3 predicts intrinsically disordered regions across 20,000 proteomes to assess disorder prevalence across life kingdoms.

This study quantifies direct interactions between 204 human activation domains and eight co-activators using a microfluidic platform, revealing 334 novel binding pairs and demonstrating the utility of analytical models for predicting activation.

Rhythmidia is a Python-based GUI tool for analyzing circadian periods and growth rates in Neurospora crassa race tube experiments, offering efficient and accurate results.

The paper identifies protein surface chemistry as a determinant of desiccation tolerance and shows that modifying surface amino acids can confer tolerance to otherwise sensitive proteins.