Engineering Allostery into Proteins

Cooperative folding as a molecular switch in an evolved antibody binder

Designing proteins with tunable activities from easily accessible external cues remains a biotechnological challenge. Here, we set out to create a small antibody-binding domain equipped with a molecular switch inspired by the allosteric response to calcium seen in naturally derived proteins like calmodulin. We have focused on one of the three domains of Protein G that show inherent affinity to antibodies. By combining a semi-rational protein design with directed evolution, we engineered novel variants containing a calcium-binding loop rendering the inherent antibody affinity calcium-dependent. The evolved variants resulted from a designed selection strategy subjecting them to negative and positive selection pressures focused on conditional antibody binding. Hence, these variants contains molecular "on/off" switches, controlling the target affinity towards antibody fragments simply by the presence or absence of calcium. From NMR spectroscopy we found that the molecular mechanism underlying the evolved switching behavior was a coupled calcium-binding and folding event where the target binding surface was intact and functional only in the presence of bound calcium. Notably, it was observed that the response to the employed selection pressures gave rise to the evolution of a cooperative folding mechanism. This observation illustrates why the cooperative folding reaction is an effective solution seen repeatedly in the natural evolution of fine-tuned macromolecular recognition. Engineering binding moieties to confer conditional target interaction has great potential due to the exquisite interaction control that is tunable to application requirements. Improved understanding of the molecular mechanisms behind regulated interactions is crucial to unlock how to engineer switchable proteins useful in a variety of biotechnological applications.

Engineered reversible inhibition of SpyCatcher reactivity enables rapid generation of bispecific antibodies

The precise regulation of protein function is essential in biological systems and a key goal in chemical biology and protein engineering. Here, we describe a straightforward method to engineer functional control into the isopeptide bond-forming SpyTag/SpyCatcher protein ligation system. First, we perform a cysteine scan of the structured region of SpyCatcher. Except for two known reactive and catalytic residues, none of these mutations abolish reactivity. In a second screening step, we modify the cysteines with disulfide bond-forming small molecules. Here we identify 8 positions at which modifications strongly inhibit reactivity. This inhibition can be reversed by reducing agents. We call such a reversibly inhibitable SpyCatcher "SpyLock". Using "BiLockCatcher", a genetic fusion of wild-type SpyCatcher and SpyLock, and SpyTagged antibody fragments, we generate bispecific antibodies in a single, scalable format, facilitating the screening of a large number of antibody combinations. We demonstrate this approach by screening anti-PD-1/anti-PD-L1 bispecific antibodies using a cellular reporter assay.

Relaxation and single site multiple mutations to identify and control allosteric networks

Advances in Nuclear Magnetic Resonance (NMR) spectroscopy have allowed for the identification and characterization of movements in enzymes over the last 20 years that has also revealed the complexities of allosteric coupling. For example, many of the inherent movements of enzymes, and proteins in general, have been shown to be highly localized but nonetheless still coupled over long distances. Such partial couplings provide challenges to both identifying allosteric networks of dynamic communication and determining their roles in catalytic function. We have developed an approach to help identify and engineer enzyme function, called Relaxation And Single Site Multiple Mutations (RASSMM). This approach is a powerful extension of mutagenesis and NMR that is based on the observation that multiple mutations to a single site distal to the active site allosterically induces different effects to networks. Such an approach generates a panel of mutations that can also be subjected to functional studies in order to match catalytic effects with changes to coupled networks. In this review, the RASSMM approach is briefly outlined together with two applications that include cyclophilin-A and Biliverdin Reductase B.

Biochemical methods to map and quantify allosteric motions in human glucokinase

Allosteric regulation of protein function is ubiquitous in biology. Allostery originates from ligand-mediated alterations in polypeptide structure and/or dynamics, which produce a cooperative kinetic or thermodynamic response to changing ligand concentrations. Establishing a mechanistic description of individual allosteric events requires both mapping the relevant changes in protein structure and quantifying the rates of differential conformational dynamics in the absence and presence of effectors. In this chapter, we describe three biochemical approaches to understand the dynamic and structural signatures of protein allostery using the well-established cooperative enzyme glucokinase as a case study. The combined application of pulsed proteolysis, biomolecular nuclear magnetic resonance spectroscopy and hydrogen-deuterium exchange mass spectrometry offers complementary information that can used to establish molecular models for allosteric proteins, especially when differential protein dynamics are involved.

Protein Function Analysis through Machine Learning

Machine learning (ML) has been an important arsenal in computational biology used to elucidate protein function for decades. With the recent burgeoning of novel ML methods and applications, new ML approaches have been incorporated into many areas of computational biology dealing with protein function. We examine how ML has been integrated into a wide range of computational models to improve prediction accuracy and gain a better understanding of protein function. The applications discussed are protein structure prediction, protein engineering using sequence modifications to achieve stability and druggability characteristics, molecular docking in terms of protein-ligand binding, including allosteric effects, protein-protein interactions and protein-centric drug discovery. To quantify the mechanisms underlying protein function, a holistic approach that takes structure, flexibility, stability, and dynamics into account is required, as these aspects become inseparable through their interdependence. Another key component of protein function is conformational dynamics, which often manifest as protein kinetics. Computational methods that use ML to generate representative conformational ensembles and quantify differences in conformational ensembles important for function are included in this review. Future opportunities are highlighted for each of these topics.

Catalyst-Based Biomolecular Logic Gates

Regulatory processes in biology can be re-conceptualized in terms of logic gates, analogous to those in computer science. Frequently, biological systems need to respond to multiple, sometimes conflicting, inputs to provide the correct output. The language of logic gates can then be used to model complex signal transduction and metabolic processes. Advances in synthetic biology in turn can be used to construct new logic gates, which find a variety of biotechnology applications including in the production of high value chemicals, biosensing, and drug delivery. In this review, we focus on advances in the construction of logic gates that take advantage of biological catalysts, including both protein-based and nucleic acid-based enzymes. These catalyst-based biomolecular logic gates can read a variety of molecular inputs and provide chemical, optical, and electrical outputs, allowing them to interface with other types of biomolecular logic gates or even extend to inorganic systems. Continued advances in molecular modeling and engineering will facilitate the construction of new logic gates, further expanding the utility of biomolecular computing.

Integrating dynamics into enzyme engineering

Enzyme engineering has become a widely adopted practice in research labs and industry. In parallel, the past decades have seen tremendous strides in characterizing the dynamics of proteins, using a growing array of methodologies. Importantly, links have been established between the dynamics of proteins and their function. Characterizing the dynamics of an enzyme prior to, and following, its engineering is beginning to inform on the potential of 'dynamic engineering', i.e. the rational modification of protein dynamics to alter enzyme function. Here we examine the state of knowledge at the intersection of enzyme engineering and protein dynamics, describe current challenges and highlight pioneering work in the nascent area of dynamic engineering.

Conserved allosteric ensembles in disordered proteins using TROSY/anti-TROSY R2-filtered spectroscopy

Defining the role of intrinsic disorder in proteins in the myriad of biological processes with which it is involved represents a significant goal in modern biophysics. Toward this end, NMR is uniquely suited for molecular studies of dynamic and disordered regions, but studying these regions in concert with their more structured domains and binding partners presents spectroscopic challenges. Here, we investigate the interactions between the structured and disordered regions of the human glucocorticoid receptor (GR). To do this, we developed an NMR strategy that relies on a novel relaxation filter for the simultaneous study of structured and unstructured regions. Using this approach, we conducted a comparative analysis of three translational isoforms of GR containing a folded DNA-binding domain (DBD) and two disordered regions that flank the DBD, one of which varies in size in the different isoforms. Notably, we were able to assign resonances that had previously been inaccessible because of the spectral complexity of the translational isoforms, which in turn allowed us to 1) identify a region of the structured DBD that undergoes significant changes in the local chemical environment in the presence of the disordered region and 2) determine differences in the conformational ensembles of the disordered regions of the translational isoforms. Furthermore, an ensemble-based thermodynamic analysis of the isoforms reveals conserved patterns of stability within the N-terminal domain of GR that persist despite low sequence conservation. These studies provide an avenue for further investigations of the mechanistic underpinnings of the functional relevance of the translational isoforms of GR while also providing a general NMR strategy for studying systems containing both structured and disordered regions.

Substitution of a Surface-Exposed Residue Involved in an Allosteric Network Enhances Tryptophan Synthase Function in Cells

Networks of noncovalent amino acid interactions propagate allosteric signals throughout proteins. Tryptophan synthase (TS) is an allosterically controlled bienzyme in which the indole product of the alpha subunit (αTS) is transferred through a 25 Å hydrophobic tunnel to the active site of the beta subunit (βTS). Previous nuclear magnetic resonance and molecular dynamics simulations identified allosteric networks in αTS important for its function. We show here that substitution of a distant, surface-exposed network residue in αTS enhances tryptophan production, not by activating αTS function, but through dynamically controlling the opening of the indole channel and stimulating βTS activity. While stimulation is modest, the substitution also enhances cell growth in a tryptophan-auxotrophic strain of Escherichia coli compared to complementation with wild-type αTS, emphasizing the biological importance of the network. Surface-exposed networks provide new opportunities in allosteric drug design and protein engineering, and hint at potential information conduits through which the functions of a metabolon or even larger proteome might be coordinated and regulated.

Distinct conformational dynamics and allosteric networks in alpha tryptophan synthase during active catalysis

Experimental observations of enzymes under active turnover conditions have brought new insight into the role of protein motions and allosteric networks in catalysis. Many of these studies characterize enzymes under dynamic chemical equilibrium conditions, in which the enzyme is actively catalyzing both the forward and reverse reactions during data acquisition. We have previously analyzed conformational dynamics and allosteric networks of the alpha subunit of tryptophan synthase under such conditions using NMR. We have proposed that this working state represents a four to one ratio of the enzyme bound with the indole-3-glycerol phosphate substrate (E:IGP) to the enzyme bound with the products indole and glyceraldehyde-3-phosphate (E:indole:G3P). Here, we analyze the inactive D60N variant to deconvolute the contributions of the substrate- and products-bound states to the working state. While the D60N substitution itself induces small structural and dynamic changes, the D60N E:IGP and E:indole:G3P states cannot entirely account for the conformational dynamics and allosteric networks present in the working state. The act of chemical bond breakage and/or formation, or possibly the generation of an intermediate, may alter the structure and dynamics present in the working state. As the enzyme transitions from the substrate-bound to the products-bound state, millisecond conformational exchange processes are quenched and new allosteric connections are made between the alpha active site and the surface which interfaces with the beta subunit. The structural ordering of the enzyme and these new allosteric connections may be important in coordinating the channeling of the indole product into the beta subunit.

Driving Protein Conformational Cycles in Physiology and Disease: "Frustrated" Amino Acid Interaction Networks Define Dynamic Energy Landscapes: Amino Acid Interaction Networks Change Progressively Along Alpha Tryptophan Synthase's Catalytic Cycle

A general framework by which dynamic interactions within a protein will promote the necessary series of structural changes, or "conformational cycle," required for function is proposed. It is suggested that the free-energy landscape of a protein is biased toward this conformational cycle. Fluctuations into higher energy, although thermally accessible, conformations drive the conformational cycle forward. The amino acid interaction network is defined as those intraprotein interactions that contribute most to the free-energy landscape. Some network connections are consistent in every structural state, while others periodically change their interaction strength according to the conformational cycle. It is reviewed here that structural transitions change these periodic network connections, which then predisposes the protein toward the next set of network changes, and hence the next structural change. These concepts are illustrated by recent work on tryptophan synthase. Disruption of these dynamic connections may lead to aberrant protein function and disease states.