Malcolm L. Wells’s research while affiliated with Columbia University and other places

Many protein sequences occupy similar three-dimensional structures known as protein folds. In nature, protein folds are well-conserved over the course of evolution, such that there are 100,000 times as many extant protein sequences than there are folds. Despite their common shapes, similar protein folds can adopt wide-ranging functions, raising the question: are protein folds so strongly conserved for the purpose of maintaining function-driving energetic changes in protein families? Here we show that a set of key energetic relationships in a family of bacterial transcription factors (TFs) is conserved using high-resolution hydrogen exchange/mass spectrometry, bioinformatics, X-ray crystallography, and molecular dynamics simulations. We compared the TFs to their anciently diverged structural homologs, the periplasmic binding proteins (PBPs), expecting that protein families that share the same fold and bind the same sugars would have similar energetic responses. Surprisingly, our findings reveal the opposite: the "energetic blueprints" of the PBPs and the TFs are largely distinct, with the allosteric network of the TFs evolving specifically to support the functional requirements of genome regulation, versus conserved interactions with membrane transport machinery in PBPs. These results demonstrate how the same fold can be adapted for different sense/response functions via family-specific energetic requirements - even when responding to the same chemical trigger. Understanding the evolutionarily conserved energetic blueprint for a protein family provides a roadmap for designing functional proteins de novo, and will help us treat aberrant protein behavior in conserved domains in disease-related drug targets, where engineering selectivity is challenging.

While bioinformatics reveals patterns in protein sequences and structural biology methods elucidate atomic details of protein structures, it is difficult to attain equally high-resolution energetic information about protein conformational ensembles. We present PIGEON-FEATHER, a method for calculating free energies of opening (∆Gop) at single- or near-single-amino acid resolution for protein ensembles of all sizes from hydrogen exchange/mass spectrometry (HX/MS) data. PIGEON-FEATHER disambiguates and reconstructs all experimentally measured isotopic mass envelopes using a Bayesian Monte Carlo sampling approach. We applied PIGEON-FEATHER to reveal how E. coli and human dihydrofolate reductase orthologs (ecDHFR, hDHFR) have evolved distinct ensembles tuned to their catalytic cycles, and how two competitive inhibitors of ecDHFR arrest its ensemble in different ways. Extending the method to a large protein-DNA complex, we mapped ligand-induced ensemble reweighting in the E. coli lac repressor to understand the functional switching mechanism crucial for transcriptional regulation.

Biological regulation ubiquitously depends on protein allostery, but the regulatory mechanisms are incompletely understood, especially in proteins that undergo ligand-induced allostery with few structural changes. Here we used hydrogen-deuterium exchange with mass spectrometry (HDX/MS) to map allosteric effects in a paradigm ligand-responsive transcription factor, the lac repressor (LacI), in different functional states (apo, or bound to inducer, anti-inducer, and/or DNA). Although X-ray crystal structures of the LacI core domain in these states are nearly indistinguishable, HDX/MS experiments reveal widespread differences in flexibility. We integrate these results with modeling of protein-ligand-solvent interactions to propose a revised model for allostery in LacI, where ligand binding allosterically shifts the conformational ensemble as a result of distinct changes in the rigidity of secondary structures in the different states. Our model provides a mechanistic basis for the altered function of distal mutations. More generally, our approach provides a platform for characterizing and engineering protein allostery. Using hydrogen-deuterium exchange, the authors propose a model explaining how a classic transcription factor undergoes changes in its conformational ensemble in response to different ligands.