Christopher L. McClendon

Bio: Christopher L. McClendon is an academic researcher from University of Montana. The author has contributed to research in topics: Allosteric regulation & Protein structure. The author has an hindex of 16, co-authored 23 publications receiving 2712 citations. Previous affiliations of Christopher L. McClendon include California Institute of Technology & University of California, San Diego.

Reaching for high-hanging fruit in drug discovery at protein–protein interfaces

Abstract: Targeting the interfaces between proteins has huge therapeutic potential, but discovering small-molecule drugs that disrupt protein-protein interactions is an enormous challenge. Several recent success stories, however, indicate that protein-protein interfaces might be more tractable than has been thought. These studies discovered small molecules that bind with drug-like potencies to 'hotspots' on the contact surfaces involved in protein-protein interactions. Remarkably, these small molecules bind deeper within the contact surface of the target protein, and bind with much higher efficiencies, than do the contact atoms of the natural protein partner. Some of these small molecules are now making their way through clinical trials, so this high-hanging fruit might not be far out of reach.

Quantifying Correlations Between Allosteric Sites in Thermodynamic Ensembles.

Abstract: Allostery describes altered protein function at one site due to a perturbation at another site. One mechanism of allostery involves correlated motions, which can occur even in the absence of substantial conformational change. We present a novel method, “MutInf”, to identify statistically significant correlated motions from equilibrium molecular dynamics simulations. Our approach analyzes both backbone and sidechain motions using internal coordinates to account for the gear-like twists that can take place even in the absence of the large conformational changes typical of traditional allosteric proteins. We quantify correlated motions using a mutual information metric, which we extend to incorporate data from multiple short simulations and to filter out correlations that are not statistically significant. Applying our approach to uncover mechanisms of cooperative small molecule binding in human interleukin-2, we identify clusters of correlated residues from 50 ns of molecular dynamics simulations. Interestingly, two of the clusters with the strongest correlations highlight known cooperative small-molecule binding sites and show substantial correlations between these sites. These cooperative binding sites on interleukin-2 are correlated not only through the hydrophobic core of the protein but also through a dynamic polar network of hydrogen bonding and electrostatic interactions. Since this approach identifies correlated conformations in an unbiased, statistically robust manner, it should be a useful tool for finding novel or “orphan” allosteric sites in proteins of biological and therapeutic importance.

Dynamic architecture of a protein kinase

Abstract: Protein kinases are dynamically regulated signaling proteins that act as switches in the cell by phosphorylating target proteins. To establish a framework for analyzing linkages between structure, function, dynamics, and allostery in protein kinases, we carried out multiple microsecond-scale molecular-dynamics simulations of protein kinase A (PKA), an exemplar active kinase. We identified residue–residue correlated motions based on the concept of mutual information and used the Girvan–Newman method to partition PKA into structurally contiguous “communities.” Most of these communities included 40–60 residues and were associated with a particular protein kinase function or a regulatory mechanism, and well-known motifs based on sequence and secondary structure were often split into different communities. The observed community maps were sensitive to the presence of different ligands and provide a new framework for interpreting long-distance allosteric coupling. Communication between different communities was also in agreement with the previously defined architecture of the protein kinase core based on the “hydrophobic spine” network. This finding gives us confidence in suggesting that community analyses can be used for other protein kinases and will provide an efficient tool for structural biologists. The communities also allow us to think about allosteric consequences of mutations that are linked to disease.

Turning a protein kinase on or off from a single allosteric site via disulfide trapping

Abstract: There is significant interest in identifying and characterizing allosteric sites in enzymes such as protein kinases both for understanding allosteric mechanisms as well as for drug discovery. Here, we apply a site-directed technology, disulfide trapping, to interrogate structurally and functionally how an allosteric site on the Ser/Thr kinase, 3-phosphoinositide-dependent kinase 1 (PDK1)--the PDK1-interacting-fragment (PIF) pocket--is engaged by an activating peptide motif on downstream substrate kinases (PIFtides) and by small molecule fragments. By monitoring pairwise disulfide conjugation between PIFtide and PDK1 cysteine mutants, we defined the PIFtide binding orientation in the PIF pocket of PDK1 and assessed subtle relationships between PIFtide positioning and kinase activation. We also discovered a variety of small molecule fragment disulfides (< 300 Da) that could either activate or inhibit PDK1 by conjugation to the PIF pocket, thus displaying greater functional diversity than is displayed by PIFtides conjugated to the same sites. Biochemical data and three crystal structures provided insight into the mechanism of action of the best fragment activators and inhibitors. These studies show that disulfide trapping is useful for characterizing allosteric sites on kinases and that a single allosteric site on a protein kinase can be exploited for both activation and inhibition by small molecules.

A dynamic hydrophobic core orchestrates allostery in protein kinases

Abstract: Eukaryotic protein kinases (EPKs) constitute a class of allosteric switches that mediate a myriad of signaling events. It has been postulated that EPKs’ active and inactive states depend on the structural architecture of their hydrophobic cores, organized around two highly conserved spines: C-spine and R-spine. How the spines orchestrate the transition of the enzyme between catalytically uncommitted and committed states remains elusive. Using relaxation dispersion nuclear magnetic resonance spectroscopy, we found that the hydrophobic core of the catalytic subunit of protein kinase A, a prototypical and ubiquitous EPK, moves synchronously to poise the C subunit for catalysis in response to binding adenosine 5′-triphosphate. In addition to completing the C-spine, the adenine ring fuses the β structures of the N-lobe and the C-lobe. Additional residues that bridge the two spines (I150 and V104) are revealed as part of the correlated hydrophobic network; their importance was validated by mutagenesis, which led to inactivation. Because the hydrophobic architecture of the catalytic core is conserved throughout the EPK superfamily, the present study suggests a universal mechanism for dynamically driven allosteric activation of kinases mediated by coordinated signal transmission through ordered motifs in their hydrophobic cores.

The re-emergence of natural products for drug discovery in the genomics era

Abstract: Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.

K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions

Abstract: Somatic mutations in the small GTPase K-Ras are the most common activating lesions found in human cancer, and are generally associated with poor response to standard therapies. Efforts to target this oncogene directly have faced difficulties owing to its picomolar affinity for GTP/GDP and the absence of known allosteric regulatory sites. Oncogenic mutations result in functional activation of Ras family proteins by impairing GTP hydrolysis. With diminished regulation by GTPase activity, the nucleotide state of Ras becomes more dependent on relative nucleotide affinity and concentration. This gives GTP an advantage over GDP and increases the proportion of active GTP-bound Ras. Here we report the development of small molecules that irreversibly bind to a common oncogenic mutant, K-Ras(G12C). These compounds rely on the mutant cysteine for binding and therefore do not affect the wild-type protein. Crystallographic studies reveal the formation of a new pocket that is not apparent in previous structures of Ras, beneath the effector binding switch-II region. Binding of these inhibitors to K-Ras(G12C) disrupts both switch-I and switch-II, subverting the native nucleotide preference to favour GDP over GTP and impairing binding to Raf. Our data provide structure-based validation of a new allosteric regulatory site on Ras that is targetable in a mutant-specific manner.

Improved Docking of Polypeptides with Glide

Abstract: Predicting the binding mode of flexible polypeptides to proteins is an important task that falls outside the domain of applicability of most small molecule and protein–protein docking tools. Here, we test the small molecule flexible ligand docking program Glide on a set of 19 non-α-helical peptides and systematically improve pose prediction accuracy by enhancing Glide sampling for flexible polypeptides. In addition, scoring of the poses was improved by post-processing with physics-based implicit solvent MM-GBSA calculations. Using the best RMSD among the top 10 scoring poses as a metric, the success rate (RMSD ≤ 2.0 A for the interface backbone atoms) increased from 21% with default Glide SP settings to 58% with the enhanced peptide sampling and scoring protocol in the case of redocking to the native protein structure. This approaches the accuracy of the recently developed Rosetta FlexPepDock method (63% success for these 19 peptides) while being over 100 times faster. Cross-docking was performed for a su...