Kimberly A. Reynolds

Structural and Computational Characterization of the SHV-1 β-Lactamase-β-Lactamase Inhibitor Protein Interface

β-Lactamase inhibitor protein (BLIP) binds a variety of class A β-lactamases with affinities ranging from micromolar to picomolar. Whereas the TEM-1 and SHV-1 β-lactamases are almost structurally identical, BLIP binds TEM-1 ∼1000-fold tighter than SHV-1. Determining the underlying source of this affinity difference is important for understanding the molecular basis of β-lactamase inhibition and mechanisms of protein-protein interface specificity and affinity. Here we present the 1.6Å resolution crystal structure of SHV-1 ·BLIP. In addition, a point mutation was identified, SHV D104E, that increases SHV ·BLIP binding affinity from micromolar to nanomolar. Comparison of the SHV-1 ·BLIP structure with the published TEM-1 ·BLIP structure suggests that the increased volume of Glu-104 stabilizes a key binding loop in the interface. Solution of the 1.8Å SHV D104K ·BLIP crystal structure identifies a novel conformation in which this binding loop is removed from the interface. Using these structural data, we evaluated the ability of EGAD, a program developed for computational protein design, to calculate changes in the stability of mutant β-lactamase ·BLIP complexes. Changes in binding affinity were calculated within an error of 1.6 kcal/mol of the experimental values for 112 mutations at the TEM-1 ·BLIP interface and within an error of 2.2 kcal/mol for 24 mutations at the SHV-1 ·BLIP interface. The reasonable success of EGAD in predicting changes in interface stability is a promising step toward understanding the stability of the β-lactamase ·BLIP complexes and computationally assisted design of tight binding BLIP variants.

Computational Redesign of the SHV-1 β-lactamase/β-lactamase Inhibitor Protein Interface

Beta-lactamases are enzymes that catalyze the hydrolysis of beta-lactam antibiotics. beta-lactamase/beta-lactamase inhibitor protein (BLIP) complexes are emerging as a well characterized experimental model system for studying protein-protein interactions. BLIP is a 165 amino acid protein that inhibits several class A beta-lactamases with a wide range of affinities: picomolar affinity for K1; nanomolar affinity for TEM-1, SME-1, and BlaI; but only micromolar affinity for SHV-1 beta-lactamase. The large differences in affinity coupled with the availability of extensive mutagenesis data and high-resolution crystal structures for the TEM-1/BLIP and SHV-1/BLIP complexes make them attractive systems for the further development of computational design methodology. We used EGAD, a physics-based computational design program, to redesign BLIP in an attempt to increase affinity for SHV-1. Characterization of several of designs and point mutants revealed that in all cases, the mutations stabilize the interface by 10- to 1000-fold relative to wild type BLIP. The calculated changes in binding affinity for the mutants were within a mean absolute error of 0.87 kcal/mol from the experimental values, and comparison of the calculated and experimental values for a set of 30 SHV-1/BLIP complexes yielded a correlation coefficient of 0.77. Structures of the two complexes with the highest affinity, SHV-1/BLIP (E73M) and SHV-1/BLIP (E73M, S130K, S146M), are presented at 1.7 A resolution. While the predicted structures have much in common with the experimentally determined structures, they do not coincide perfectly; in particular a salt bridge between SHV-1 D104 and BLIP K74 is observed in the experimental structures, but not in the predicted design conformations. This discrepancy highlights the difficulty of modeling salt bridge interactions with a protein design algorithm that approximates side chains as discrete rotamers. Nevertheless, while local structural features of the interface were sometimes miscalculated, EGAD is globally successful in designing complexes with increased affinity.

An object-oriented library for computational protein design

Recent advances in computational protein design have established it as a viable technique for the rational generation of stable protein sequences, novel protein folds, and even enzymatic activity. We present a new and object‐oriented library of code, written specifically for protein design applications in C++, called EGAD Library. The modular fashion in which this library is written allows developers to tailor various energy functions and minimizers for a specific purpose. It also allows for the generation of novel protein design applications with a minimal amount of code investment. It is our hope that this will permit labs that have not considered protein design to apply it to their own systems, thereby increasing its potential as a tool in biology. We also present various uses of EGAD Library: in the development of Interaction Viewer, a PyMOL plug‐in for viewing interactions between protein residues; in the repacking of protein cores; and in the prediction of protein–protein complex stabilities.

Evolution-Based Functional Decomposition of Proteins

The essential biological properties of proteins—folding, biochemical activities, and the capacity to adapt—arise from the global pattern of interactions between amino acid residues. The statistical coupling analysis (SCA) is an approach to defining this pattern that involves the study of amino acid coevolution in an ensemble of sequences comprising a protein family. This approach indicates a functional architecture within proteins in which the basic units are coupled networks of amino acids termed sectors. This evolution-based decomposition has potential for new understandings of the structural basis for protein function. To facilitate its usage, we present here the principles and practice of the SCA and introduce new methods for sector analysis in a python-based software package (pySCA). We show that the pattern of amino acid interactions within sectors is linked to the divergence of functional lineages in a multiple sequence alignment—a model for how sector properties might be differentially tuned in members of a protein family. This work provides new tools for studying proteins and for generally testing the concept of sectors as the principal units of function and adaptive variation.

Specificity and cooperativity at β-lactamase position 104 in TEM-1/BLIP and SHV-1/BLIP interactions.

Establishing a quantitative understanding of the determinants of affinity in protein–protein interactions remains challenging. For example, TEM‐1/β‐lactamase inhibitor protein (BLIP) and SHV‐1/BLIP are homologous β‐lactamase/β‐lactamase inhibitor protein complexes with disparate Kd values (3 nM and 2 μM, respectively), and a single substitution, D104E in SHV‐1, results in a 1000‐fold enhancement in binding affinity. In TEM‐1, E104 participates in a salt bridge with BLIP K74, whereas the corresponding SHV‐1 D104 does not in the wild type SHV‐1/BLIP co‐structure. Here, we present a 1.6 Å crystal structure of the SHV‐1 D104E/BLIP complex that demonstrates that this point mutation restores this salt bridge. Additionally, mutation of a neighboring residue, BLIP E73M, results in salt bridge formation between SHV‐1 D104 and BLIP K74 and a 400‐fold increase in binding affinity. To understand how this salt bridge contributes to complex affinity, the cooperativity between the E/K or D/K salt bridge pair and a neighboring hot spot residue (BLIP F142) was investigated using double mutant cycle analyses in the background of the E73M mutation. We find that BLIP F142 cooperatively stabilizes both interactions, illustrating how a single mutation at a hot spot position can drive large perturbations in interface stability and specificity through a cooperative interaction network. Proteins 2011.

Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily

In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNase tertiary structure into spatially distributed yet physically connected networks of co-evolving amino acids, termed sectors. Comparison of this statistics-based description with new NMR experiments data shows that discrete amino acid networks, termed sectors, control the tuning of distinct functional properties in different enzyme homologs. Further, experimental characterization of evolutionarily distant sequences reveals that sequence variation at sector positions can distinguish homologs with a conserved dynamic pattern and optimal catalytic activity from those with altered dynamics and diminished catalytic activities. Taken together, these results provide important insights into the mechanistic design of the ptRNase superfamily, and presents a structural basis for evolutionary tuning of function in functionally diverse enzyme homologs.

An evolutionary hotspot defines functional differences between CRYPTOCHROMES

Mammalian circadian clocks are driven by a transcription/translation feedback loop composed of positive regulators (CLOCK/BMAL1) and repressors (CRYPTOCHROME 1/2 (CRY1/2) and PER1/2). To understand the structural principles of regulation, we used evolutionary sequence analysis to identify co-evolving residues within the CRY/PHL protein family. Here we report the identification of an ancestral secondary cofactor-binding pocket as an interface in repressive CRYs, mediating regulation through direct interaction with CLOCK and BMAL1. Mutations weakening binding between CLOCK/BMAL1 and CRY1 lead to acceleration of the clock, suggesting that subtle sequence divergences at this site can modulate clock function. Divergence between CRY1 and CRY2 at this site results in distinct periodic output. Weaker interactions between CRY2 and CLOCK/BMAL1 at this pocket are strengthened by co-expression of PER2, suggesting that PER expression limits the length of the repressive phase in CRY2-driven rhythms. Overall, this work provides a model for the mechanism and evolutionary variation of clock regulatory mechanisms.The molecular mechanisms that define the periodicity or rate of the circadian clock are not well understood. Here the authors use a multidisciplinary approach and identify a mechanism for period regulation that depends on the affinity of the core clock proteins for one another.

High-order epistasis in catalytic power of dihydrofolate reductase gives rise to a rugged fitness landscape in the presence of trimethoprim selection

Evolutionary fitness landscapes of certain antibiotic target enzymes have been comprehensively mapped showing strong high order epistasis between mutations, but understanding these effects at the biochemical and molecular levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim induced selection. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct resistance mechanisms. Next, we experimentally measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the epistasis between DHFR mutations is high-order for catalytic power of DHFR (kcat and Km), but less prevalent for trimethoprim affinity (Ki). Taken together our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

An evolutionary module in central metabolism

The activity of a gene may be influenced or modified by other genes in the genome. Here, we show that co-evolution can be used to identify quasi-independent gene groups inside of larger cellular systems. Using folate metabolism as a case study, we show that co-evolution indicates a sparse architecture of interactions, with three small groups of genes co-evolving in the midst of others that evolve independently. For one such module - dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS) - we use epistasis measurements and forward evolution to demonstrate both internal functional coupling and independence from the remainder of the genome. Mechanistically, the coupling is driven by a constraint on their relative activities, which must be balanced to prevent accumulation of a metabolic intermediate. Applying co-evolution analyses genome-wide reveals a number of other gene pairs with statistical signatures similar to DHFR/TYMS, suggesting that small adaptive units are a general feature of cellular systems.The ability to predict cell behavior is complicated by an unknown pattern of functional interdependence among genes. Here, we use the conservation of gene proximity across species (synteny) to infer functional couplings between genes. For the folate metabolic pathway, we observe a sparse, modular architecture of interactions, with two small groups of genes coevolving in the midst of others that evolve independently. For one such module – dihydrofolate reductase and thymidylate synthase – we use epistasis measurements and forward evolution to demonstrate both internal functional coupling and independence from the remainder of the genome. Mechanistically, the coupling is driven by a constraint on their relative activities, which must be balanced to prevent accumulation of a metabolic intermediate. The results indicate an organization of cellular systems not apparent from inspection of biochemical pathways or physical complexes, and support the strategy of using evolutionary information to decompose cellular systems into functional units.

Evolution and Engineering of Allosteric Regulation in Protein Kinases

Allosteric regulation – the control of protein function by sites far from the active site – is a common feature of proteins that enables dynamic cellular responses. Reversible modifications such as phosphorylation are well suited to mediate such regulatory dynamics, yet the evolution of new allosteric regulation demands explanation. To understand this, we mutationally scanned the surface of a prototypical kinase to identify readily evolvable phosphorylation sites. The data reveal a set of spatially distributed “hotspots” that coevolve with the active site and preferentially modulate kinase activity. By engineering simple consensus phosphorylation sites at these hotspots we successfully rewired in vivo cell signaling. Beyond synthetic biology, the hotspots are frequently used by the diversity of natural allosteric regulatory mechanisms in the kinase family and exploited in human disease. ONE SENTENCE SUMMARY Cell signaling is easily rewired by introducing new phosphoregulation at latent allosteric surface sites.