Publications

Calmodulin (CaM) is a ubiquitous second messenger protein that regulates a variety of structurally and functionally diverse targets in response to changes in Ca(2+) concentration. CaM-dependent protein kinase II (CaMKII) and calcineurin (CaN) are the prominent CaM targets that play an opposing role in many cellular functions including synaptic regulation. Since CaMKII and CaN compete for the available Ca(2+)/CaM, the differential affinity of these enzymes for CaM is crucial for achieving a balance in Ca(2+) signaling. We used the computational protein design approach to modify CaM binding specificity for these two targets. Starting from the X-ray structure of CaM in complex with the CaM-binding domain of CaMKII, we optimized CaM interactions with CaMKII by introducing mutations into the CaM sequence. CaM optimization was performed with a protein design program, ORBIT, using a modified energy function that emphasized intermolecular interactions in the sequence selection procedure. Several CaM variants were experimentally constructed and tested for binding to the CaMKII and CaN peptides using the surface plasmon resonance technique. Most of our CaM mutants demonstrated small increase in affinity for the CaMKII peptide and substantial decrease in affinity for the CaN peptide compared to that of wild-type CaM. Our best CaM design exhibited an about 900-fold increase in binding specificity towards the CaMKII peptide, becoming the highest specificity switch achieved in any protein-protein interface through the computational protein design approach. Our results show that computational redesign of protein-protein interfaces becomes a reliable method for altering protein binding affinity and specificity.

Predicting mutations that enhance protein-protein affinity remains a challenging task, especially for high-affinity complexes. To test our capability to improve the affinity of such complexes, we studied interaction of acetylcholinesterase with the snake toxin, fasciculin. Using the program ORBIT, we redesigned fasciculin's sequence to enhance its interactions with Torpedo californica acetylcholinesterase. Mutations were predicted in 5 out of 13 interfacial residues on fasciculin, preserving most of the polar inter-molecular contacts seen in the wild-type toxin/enzyme complex. To experimentally characterize fasciculin mutants, we developed an efficient strategy to over-express the toxin in Escherichia coli, followed by refolding to the native conformation. Despite our predictions, a designed quintuple fasciculin mutant displayed reduced affinity for the enzyme. However, removal of a single mutation in the designed sequence produced a quadruple mutant with improved affinity. Moreover, one designed mutation produced 7-fold enhancement in affinity for acetylcholinesterase. This led us to reassess our criteria for enhancing affinity of the toxin for the enzyme. We observed that the change in the predicted inter-molecular energy, rather than in the total energy, correlates well with the change in the experimental free energy of binding, and hence may serve as a criterion for enhancement of affinity in protein-protein complexes.

Natural proteins often partake in several highly specific protein-protein interactions. They are thus subject to multiple opposing forces during evolutionary selection. To be functional, such multispecific proteins need to be stable in complex with each interaction partner, and, at the same time, to maintain affinity toward all partners. How is this multispecificity acquired through natural evolution? To answer this compelling question, we study a prototypical multispecific protein, calmodulin (CaM), which has evolved to interact with hundreds of target proteins. Starting from high-resolution structures of sixteen CaM-target complexes, we employ state-of-the-art computational methods to predict a hundred CaM sequences best suited for interaction with each individual CaM target. Then, we design CaM sequences most compatible with each possible combination of two, three, and all sixteen targets simultaneously, producing almost 70,000 low energy CaM sequences. By comparing these sequences and their energies, we gain insight into how nature has managed to find the compromise between the need for favorable interaction energies and the need for multispecificity. We observe that designing for more partners simultaneously yields CaM sequences that better match natural sequence profiles, thus emphasizing the importance of such strategies in nature. Furthermore, we show that the CaM binding interface can be nicely partitioned into positions that are critical for the affinity of all CaM-target complexes and those that are molded to provide interaction specificity. We reveal several basic categories of sequence-level tradeoffs that enable the compromise necessary for the promiscuity of this protein. We also thoroughly quantify the tradeoff between interaction energetics and multispecificity and find that facilitating seemingly competing interactions requires only a small deviation from optimal energies. We conclude that multispecific proteins have been subjected to a rigorous optimization process that has fine-tuned their sequences for interactions with a precise set of targets, thus conferring their multiple cellular functions.

Multistate protein design is the task of predicting the amino acid sequence that is best suited to selectively and stably fold to one state out of a set of competing structures. Computationally, it entails solving a challenging optimization problem. Therefore, notwithstanding the increased interest in multistate design, the only implementations reported are based on either genetic algorithms or Monte Carlo methods. The dead-end elimination (DEE) theorem cannot be readily transfered to multistate design problems despite its successful application to single-state protein design. In this article we propose a variant of the standard DEE, called type-dependent DEE. Our method reduces the size of the conformational space of the multistate design problem, while provably preserving the minimal energy conformational assignment for any choice of amino acid sequence. Type-dependent DEE can therefore be used as a preprocessing step in any computational multistate design scheme. We demonstrate the applicability of type-dependent DEE on a set of multistate design problems and discuss its strength and limitations.

Changes in synaptic strength that underlie memory formation in the CNS are initiated by pulses of Ca2+ flowing through NMDA-type glutamate receptors into postsynaptic spines. Differences in the duration and size of the pulses determine whether a synapse is potentiated or depressed after repetitive synaptic activity. Calmodulin (CaM) is a major Ca2+ effector protein that binds up to four Ca2+ ions. CaM with bound Ca2+ can activate at least six signaling enzymes in the spine. In fluctuating cytosolic Ca2+, a large fraction of free CaM is bound to fewer than four Ca2+ ions. Binding to targets increases the affinity of CaM's remaining Ca2+-binding sites. Thus, initial binding of CaM to a target may depend on the target's affinity for CaM with only one or two bound Ca2+ ions. To study CaM-dependent signaling in the spine, we designed mutant CaMs that bind Ca2+ only at the two N-terminal or two C-terminal sites by using computationally designed mutations to stabilize the inactivated Ca2+-binding domains in the ``closed'' Ca2+-free conformation. We have measured their interactions with CaMKII, a major Ca2+/CaM target that mediates initiation of long-term potentiation. We show that CaM with two Ca2+ ions bound in its C-terminal lobe not only binds to CaMKII with low micromolar affinity but also partially activates kinase activity. Our results support the idea that competition for binding of CaM with two bound Ca2+ ions may influence significantly the outcome of local Ca2+ signaling in spines and, perhaps, in other signaling pathways.

Calmodulin (CaM) is a second messenger protein that has evolved to bind tightly to a variety of targets and, as such, exhibits low binding specificity. We redesigned CaM by using a computational protein design algorithm to improve its binding specificity for one of its targets, smooth muscle myosin light chain kinase (smMLCK). Residues in or near the CaM/smMLCK binding interface were optimized; CaM interactions with alternative targets were not directly considered in the optimization. The predicted CaM sequences were constructed and tested for binding to a set of eight targets including smMLCK. The best CaM variant, obtained from a calculation that emphasized intermolecular interactions, showed up to a 155-fold increase in binding specificity. The increase in binding specificity was not due to improved binding to smMLCK, but due to decreased binding to the alternative targets. This finding is consistent with the fact that the sequence of wild-type CaM is nearly optimal for interactions with numerous targets.

We report the computational redesign of the protein-binding interface of calmodulin (CaM), a small, ubiquitous Ca(2+)-binding protein that is known to bind to and regulate a variety of functionally and structurally diverse proteins. The CaM binding interface was optimized to improve binding specificity towards one of its natural targets, smooth muscle myosin light chain kinase (smMLCK). The optimization was performed using optimization of rotamers by iterative techniques (ORBIT), a protein design program that utilizes a physically based force-field and the Dead-End Elimination theorem to compute sequences that are optimal for a given protein scaffold. Starting from the structure of the CaM-smMLCK complex, the program considered 10(22) amino acid residue sequences to obtain the lowest-energy CaM sequence. The resulting eightfold mutant, CaM_8, was constructed and tested for binding to a set of seven CaM target peptides. CaM_8 displayed high binding affinity to the smMLCK peptide (1.3nM), similar to that of the wild-type protein (1.8nM). The affinity of CaM_8 to six other target peptides was reduced, as intended, by 1.5-fold to 86-fold. Hence, CaM_8 exhibited increased binding specificity, preferring the smMLCK peptide to the other targets. Studies of this type may increase our understanding of the origins of binding specificity in protein-ligand complexes and may provide valuable information that can be used in the design of novel protein receptors and/or ligands.

We have taken a computational approach to design mutations that stabilize a large protein domain of approximately 200 residues in two alternative conformations. Mutations in the hydrophobic core of the alphaMbeta2 integrin I domain were designed to stabilize the crystallographically defined open or closed conformers. When expressed on the cell surface as part of the intact heterodimeric receptor, binding of the designed open and closed I domains to the ligand iC3b, a form of the complement component C3, was either increased or decreased, respectively, compared to wild type. Moreover, when expressed in isolation from other integrin domains using an artificial transmembrane domain, designed open I domains were active in ligand binding, whereas designed closed and wild type I domains were inactive. Comparison to a human expert designed open mutant showed that the computationally designed mutants are far more active. Thus, computational design can be used to stabilize a molecule in a desired conformation, and conformational change in the I domain is physiologically relevant to regulation of ligand binding.

The effects of various mechanisms of metalloporphyrin reduction potential modulation were investigated experimentally using a robust, well-characterized heme protein maquette, synthetic protein scaffold H10A24 [\?\`CH(3)()CONH-CGGGELWKL.HEELLKK.FEELLKL.AEERLKK. L-CONH(2)()\?\`(2)](2). Removal of the iron porphyrin macrocycle from the high dielectric aqueous environment and sequestration within the hydrophobic core of the H10A24 maquette raises the equilibrium reduction midpoint potential by 36-138 mV depending on the hydrophobicity of the metalloporphyrin structure. By incorporating various natural and synthetic metalloporphyrins into a single protein scaffold, we demonstrate a 300-mV range in reduction potential modulation due to the electron-donating/withdrawing character of the peripheral macrocycle substituents. Solution pH is used to modulate the metalloporphyrin reduction potential by 160 mV, regardless of the macrocycle architecture, by controlling the protonation state of the glutamate involved in partial charge compensation of the ferric heme. Attempts to control the reduction potential by inserting charged amino acids into the hydrophobic core at close proximity to the metalloporphyrin lead to varied success, with H10A24-L13E lowering the E(m8.5) by 40 mV, H10A24-E11Q raising it by 50 mV, and H10A24-L13R remaining surprisingly unaltered. Modifying the charge of the adjacent metalloporphyrin, +1 for iron(III) protoporphyrin IX or neutral for zinc(II) protoporphyrin IX resulted in a loss of 70 mV [Fe(III)PPIX](+) - [Fe(III)PPIX](+) interaction observed in maquettes. Using these factors in combination, we illustrate a 435-mV variation of the metalloporphyrin reduction midpoint potential in a simple heme maquette relative to the about 800-mV range observed for natural cytochromes. Comparison between the reduction potentials of the heme maquettes and other de novo designed heme proteins reveals global trends in the E(m) values of synthetic cytochromes.

Proton exchange with aqueous media coupled to heme oxidation/reduction is commonly seen but not understood in natural cytochromes. Our synthetic tetrahelix bundle heme protein maquettes successfully reproduce natural proton coupling to heme oxidation/reduction. Potentiometry reveals major pK shifts from 4.2 to 7.0 and from 9.4 to 10.3 in the maquette-associated acid/base group(s) upon heme reduction. Consequently, a 210 mV decrease in the heme redox potential is observed between the two extremes of pH. Potentiometry with resonance Raman and FTIR spectroscopy performed over a wide pH range strongly implicates glutamate side chains as the source of proton coupling below pH 8.0, whereas lysine side chains are suggested above pH 8.0. Remarkably, the pK values of several glutamates in the maquette are elevated from their solution value (4.4) to values as high as 7.0. It is suggested that these glutamates are recruited into the interior of the bundle as part of a structural rearrangement that occurs upon heme binding. Glutamate to glutamine variants of the prototype protein demonstrate that removal of the glutamate closest to the heme diminishes but does not abolish proton exchange. It is necessary to remove additional glutamates before pH-independent heme oxidation/reduction profiles are achieved. The mechanism of redox-linked proton coupling appears to be rooted in distributed partial charge compensation, the magnitude of which is governed by the dielectric distance between the ferric heme and acid/base side chains. A similar mechanism is likely to exist in native redox proteins which undergo charge change upon cofactor oxidation/reduction.