Chenlin Lu

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 (ΔGop) 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.

Advances in structural biology have improved our understanding of the relationship between protein structure and function, while also confirming a widely applicable principle: protein domains with highly conserved three-dimensional folds can perform radically disparate biochemical functions. To gain insight into this structural enigma, we mapped the energetic landscapes of a family of bacterial transcription factors and their anciently diverged structural homologues, the periplasmic binding proteins. Using hydrogen exchange–mass spectrometry, bioinformatics, X-ray crystallography and molecular dynamics, we uncovered an unexpected contrast: despite binding the same sugars, the two families have evolved unique ‘energetic blueprints’ to support their distinct functional requirements. To test if differences in ensemble energies have functional consequences, we rationally redesigned the protein fold for tunable ligand-driven transcriptional responses. Strikingly, energy-driven protein engineering produced synthetic transcription factors with the theoretically anticipated ligand-induced transcriptional outputs. Thus, decoding energetic blueprints among conserved protein folds provides diverse functional adaptations, paves an alternative roadmap for protein design, and offers a distinct approach for engineering challenging drug targets.

Allosteric regulation enables fine-tuned control of enzyme activity in response to cellular signals, yet its molecular basis often remains unclear. Phosphofructokinase-1 (PFK), the rate-limiting enzyme of glycolysis, is a paradigmatic, well-conserved system whose reaction kinetics conform to the Monod-Wyman-Changeux model of allostery. However, X-ray crystal structures of bacterial PFK orthologs in distinct ligand-bound states do not show the consistent, concerted structural rearrangements expected for classical “relaxed” and “tense” states, revealing a decades-long disconnect between structure and function. We resolve this paradox by integrating biophysical and computational approaches to show that activator and inhibitor binding to the same allosteric pocket differentially reweight the conformational ensemble of Escherichia coli PFK. Activator binding stabilizes conformational substates that preorganize the catalytic site, whereas inhibitor binding upweights apo-like, catalytically incompetent substates. These findings establish an ensemble-based mechanism for PFK regulation and provide an energetic framework for understanding the expanded allosteric architecture of higher PFK orthologs.

The residue-level free energy of opening (∆Gop) is the ultimate thermodynamic descriptor of localized protein stability, providing valuable information about the protein ensemble at physiologically relevant timescales and conditions. PFNet instantly determines ΔGop for arbitrarily large proteins and complexes from conventional peptide-level hydrogen exchange/mass spectrometry (HX-MS) datasets. It unlocks the full potential of HX-MS, democratizing the method and establishing quantitative, scalable and accessible analysis (https://github.com/glasgowlab/PFNet).

Artificial metalloenzymes, which are designed rationally as hybrids of proteins and catalytically active transition-metal complexes, have become a promising approach for catalyzing unprecedented reactions for natural enzymes. In this study, we described the design and synthesis of an artificial metalloenzyme, a cycloisomerase that utilizes Au(I) incorporated into an apo-ferritin cage (Fr−Au) to efficiently catalyze the cycloisomerization of alkynoic acids, with a conversion of 83% and a turnover frequency of 20.6 × 103· h−1 in aqueous solution under mild conditions. The remarkable catalytic activity indicates that the nano-confinement of the Au(I) active site within the ferritin cage enhances its catalytic properties by stabilizing and solubilizing it. The less protected Au atom in the cysteine bridged dinuclear Au(I) active center was identified as critical for the Fr−Au cycloisomerases to catalyze this reaction. In addition, we provide insight into the catalytic mechanism through quantum chemical (QC) calculations, which reveal an energy barrier of 32.29 kJ/mol.

Water-soluble and biocompatible protein-protected gold nanoclusters (Au NCs) hold great promise for numerous applications. However, design and precise regulation of their structure at an atomic level remain challenging. Herein, we have engineered and constructed a gold clustering site at the 4-fold symmetric axis channel of the apo-ferritin cage. Using a series of X-ray crystal structures, we evaluated the stepwise accumulation process of Au ions into the cage and the formation of a multinuclear Au cluster in our designed cavity. We also disclosed the role of key residues in the metal accumulation process. X-ray crystal structures in combination with quantum chemical (QC) calculation revealed a unique Au clustering site with up to 12 Au atoms positions in the cavity. Moreover, the structure of the gold nanocluster was precisely tuned by the dosage of the Au precursor. As the gold concentration increases, the number of Au atoms position at the clustering site increases from 8 to 12, and a structural rearrangement was observed at a higher Au concentration. Furthermore, the binding affinity order of the four Au binding sites on apo-ferritin was unveiled with a stepwise increase of Au precursor concentration.