S. Banu Ozkan

Structure and dynamic regulation of Src-family kinases

Abstract.Src-family kinases are modular signaling proteins involved in a diverse array of cellular processes. All members of the Src family share the same domain organization, with modular SH3, SH2 and kinase domains followed by a C-terminal negative regulatory tail. X-ray crystallographic analyses of several Src family members have revealed critical roles for the SH3 and SH2 domains in the down-regulation of the kinase domain. This review focuses on biological, biophysical, and computational studies that reveal conformationally distinct active states within this unique kinase family.

Protein folding by zipping and assembly

How do proteins fold so quickly? Some denatured proteins fold to their native structures in only microseconds, on average, implying that there is a folding “mechanism,” i.e., a particular set of events by which the protein short-circuits a broader conformational search. Predicting protein structures using atomically detailed physical models is currently challenging. The most definitive proof of a putative folding mechanism would be whether it speeds up protein structure prediction in physical models. In the zipping and assembly (ZA) mechanism, local structuring happens first at independent sites along the chain, then those structures either grow (zip) or coalescence (assemble) with other structures. Here, we apply the ZA search mechanism to protein native structure prediction by using the AMBER96 force field with a generalized Born/surface area implicit solvent model and sampling by replica exchange molecular dynamics. Starting from open denatured conformations, our algorithm, called the ZA method, converges to an average of 2.2 Å from the Protein Data Bank native structures of eight of nine proteins that we tested, which ranged from 25 to 73 aa in length. In addition, experimental Φ values, where available on these proteins, are consistent with the predicted routes. We conclude that ZA is a viable model for how proteins physically fold. The present work also shows that physics-based force fields are quite good and that physics-based protein structure prediction may be practical, at least for some small proteins.

Change in allosteric network affects binding affinities of PDZ domains: analysis through perturbation response scanning.

The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation.

Fast-folding protein kinetics, hidden intermediates, and the sequential stabilization model

Do two‐state proteins fold by pathways or funnels? Native‐state hydrogen exchange experiments show discrete nonnative structures in equilibrium with the native state. These could be called hidden intermediates (HI) because their populations are small at equilibrium, and they are not detected in kinetic experiments. HIs have been invoked as disproof of funnel models, because funnel pictures appear to indicate (1) no specific sequences of events in folding; (2) a continuum, rather than a discrete ladder, of structures; and (3) smooth landscapes. In the present study, we solve the exact dynamics of a simple model. We find, instead, that the present microscopic model is indeed consistent with HIs and transition states, but such states occur in parallel, rather than along the single pathway predicted by the sequential stabilization model. At the microscopic level, we observe a huge multiplicity of trajectories. But at the macroscopic level, we observe two pathways of specific sequences of events that are relatively traditional except that they are in parallel, so there is not a single reaction coordinate. Using singular value decomposition, we show an accurate representation of the shapes of the model energy landscapes. They are highly complex funnels.

Evolution of Conformational Dynamics Determines the Conversion of a Promiscuous Generalist into a Specialist Enzyme

β-Lactamases are produced by many modern bacteria as a mechanism of resistance toward β-lactam antibiotics, the most common antibiotics in use. β-Lactamases, however, are ancient enzymes that originated billions of years ago. Recently, proteins corresponding to 2- to 3-Gy-old Precambrian nodes in the evolution of Class A β-lactamases have been prepared and shown to be moderately efficient promiscuous catalysts, able to degrade a variety of antibiotics with catalytic efficiency levels similar to those of an average modern enzyme. Remarkably, there are few structural differences (in particular at the active-site regions) between the resurrected enzymes and a penicillin-specialist modern β-lactamase. Here, we propose that the ancestral promiscuity originates from conformational dynamics. We investigate the differences in conformational dynamics of the ancient and extant β-lactamases through MD simulations and quantify the contribution of each position to functionally related dynamics through Dynamic Flexibility Index. The modern TEM-1 lactamase shows a comparatively rigid active-site region, likely reflecting adaptation for efficient degradation of a specific substrate (penicillin), whereas enhanced deformability at the active-site neighborhood in the ancestral resurrected proteins likely accounts for the binding and subsequent degradation of antibiotic molecules of different size and shape. Clustering of the conformational dynamics on the basis of Principal Component Analysis is in agreement with the functional divergence, as the ancient β-lactamases cluster together, separated from their modern descendant. Finally, our analysis leads to testable predictions, as sites of potential relevance for the evolution of dynamics are identified and mutations at those sites are expected to alter substrate-specificity.

Identification of specificity and promiscuity of PDZ domain interactions through their dynamic behavior.

PDZ domains (PDZs), the most common interaction domain proteins, play critical roles in many cellular processes. PDZs perform their job by binding specific protein partners. However, they are very promiscuous, binding to more than one protein, yet selective at the same time. We examined the binding related dynamics of various PDZs to have insight about their specificity and promiscuity. We used full atomic normal mode analysis and a modified coarse‐grained elastic network model to compute the binding related dynamics. In the latter model, we introduced specificity for each single parameter constant and included the solvation effect implicitly. The modified model, referred to as specific‐Gaussian Network Model (s‐GNM), highlights some interesting differences in the conformational changes of PDZs upon binding to Class I or Class II type peptides. By clustering the residue fluctuation profiles of PDZs, we have shown: (i) binding selectivities can be discriminated from their dynamics, and (ii) the dynamics of different structural regions play critical roles for Class I and Class II specificity. s‐GNM is further tested on a dual‐specific PDZ which showed only Class I specificity when a point mutation exists on the βA‐βB loop. We observe that the binding dynamics change consistently in the mutated and wild type structures. In addition, we found that the binding induced fluctuation profiles can be used to discriminate the binding selectivity of homolog structures. These results indicate that s‐GNM can be a powerful method to study the changes in binding selectivities for mutant or homolog PDZs. Proteins 2009.

A flexible docking scheme to explore the binding selectivity of PDZ domains

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density‐95/Dlg/ZO‐1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

Blind test of physics-based prediction of protein structures

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences.

BP-Dock: A Flexible Docking Scheme for Exploring Protein–Ligand Interactions Based on Unbound Structures

Molecular docking serves as an important tool in modeling protein-ligand interactions. However, it is still challenging to incorporate overall receptor flexibility, especially backbone flexibility, in docking due to the large conformational space that needs to be sampled. To overcome this problem, we developed a novel flexible docking approach, BP-Dock (Backbone Perturbation-Dock) that can integrate both backbone and side chain conformational changes induced by ligand binding through a multi-scale approach. In the BP-Dock method, we mimic the nature of binding-induced events as a first-order approximation by perturbing the residues along the protein chain with a small Brownian kick one at a time. The response fluctuation profile of the chain upon these perturbations is computed using the perturbation response scanning method. These response fluctuation profiles are then used to generate binding-induced multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, we applied our approach on a large and diverse data set using unbound structures as receptors. We also compared the BP-Dock results with bound and unbound docking, where overall receptor flexibility was not taken into account. Our results highlight the importance of modeling backbone flexibility in docking for recapitulating the experimental binding affinities, especially when an unbound structure is used. With BP-Dock, we can generate a wide range of binding site conformations realized in nature even in the absence of a ligand that can help us to improve the accuracy of unbound docking. We expect that our fast and efficient flexible docking approach may further aid in our understanding of protein-ligand interactions as well as virtual screening of novel targets for rational drug design.

A hinge migration mechanism unlocks the evolution of green-to-red photoconversion in GFP-like proteins.

In proteins, functional divergence involves mutations that modify structure and dynamics. Here we provide experimental evidence for an evolutionary mechanism driven solely by long-range dynamic motions without significant backbone adjustments, catalytic group rearrangements, or changes in subunit assembly. Crystallographic structures were determined for several reconstructed ancestral proteins belonging to a GFP class frequently employed in superresolution microscopy. Their chain flexibility was analyzed using molecular dynamics and perturbation response scanning. The green-to-red photoconvertible phenotype appears to have arisen from a common green ancestor by migration of a knob-like anchoring region away from the active site diagonally across the β barrel fold. The allosterically coupled mutational sites provide active site conformational mobility via epistasis. We propose that light-induced chromophore twisting is enhanced in a reverse-protonated subpopulation, activating internal acid-base chemistry and backbone cleavage to enlarge the chromophore. Dynamics-driven hinge migration may represent a more general platform for the evolution of novel enzyme activities.