A ternary complex model of Sirtuin4-NAD+-Glutamate dehydrogenase

Sirtuin4 (Sirt4) is one of the mammalian homologues of Silent information regulator 2 (Sir2), which promotes the longevity of yeast, C. elegans, fruit flies and mice. Sirt4 is localized in the mitochondria, where it contributes to preventing the development of cancers and ischemic heart disease through regulating energy metabolism. The ADP-ribosylation of glutamate dehydrogenase (GDH), which is catalyzed by Sirt4, downregulates the TCA cycle. However, this reaction mechanism is obscure, because the structure of Sirt4 is unknown. We here constructed structural models of Sirt4 by homology modeling and threading, and docked nicotinamide adenine dinucleotide+ (NAD+) to Sirt4. In addition, a partial GDH structure was docked to the Sirt4-NAD+ complex model. In the ternary complex model of Sirt4-NAD+-GDH, the acetylated lysine 171 of GDH is located close to NAD+. This suggests a possible mechanism underlying the ADP-ribosylation at cysteine 172, which may occur through a transient intermediate with ADP-ribosylation at the acetylated lysine 171. These results may be useful in designing drugs for the treatment of cancers and ischemic heart disease

Structure of a highly conserved domain of rock1 required for shroom-mediated regulation of cell morphology

Rho-associated coiled coil containing protein kinase (Rho-kinase or Rock) is a well-defined determinant of actin organization and dynamics in most animal cells characterized to date. One of the primary effectors of Rock is non-muscle myosin II. Activation of Rock results in increased contractility of myosin II and subsequent changes in actin architecture and cell morphology. The regulation of Rock is thought to occur via autoinhibition of the kinase domain via intramolecular interactions between the N-terminus and the C-terminus of the kinase. This autoinhibited state can be relieved via proteolytic cleavage, binding of lipids to a Pleckstrin Homology domain near the C-terminus, or binding of GTP-bound RhoA to the central coiled-coil region of Rock. Recent work has identified the Shroom family of proteins as an additional regulator of Rock either at the level of cellular distribution or catalytic activity or both. The Shroom-Rock complex is conserved in most animals and is essential for the formation of the neural tube, eye, and gut in vertebrates. To address the mechanism by which Shroom and Rock interact, we have solved the structure of the coiled-coil region of Rock that binds to Shroom proteins. Consistent with other observations, the Shroom binding domain is a parallel coiled-coil dimer. Using biochemical approaches, we have identified a large patch of residues that contribute to Shrm binding. Their orientation suggests that there may be two independent Shrm binding sites on opposing faces of the coiled-coil region of Rock. Finally, we show that the binding surface is essential for Rock colocalization with Shroom and for Shroom-mediated changes in cell morphology. © 2013 Mohan et al

Structural Investigation of Binding Events in Proteins

Understanding the biophysical properties that describe protein binding events has allowed for the advancement of drug discovery through structure-based drug design and in silico methodology. The accuracy of these in silico methods depends entirely on the parameters that we determine for them. Many of these parameters are derived from the structural information we have obtained as a community and therein resides the importance of integrity of the quality of this structural data. First, the curation and contents of the Binding MOAD database are extensively described. This database serves as a repository of 25,759 high-quality, ligand-bound X-ray protein crystal structures complemented by 9138 hand-curated binding affinity data for as many of those ligands as appropriate. The newly implemented extended binding site feature is presented, establishing more robust definitions of ligand binding sites than those provided by other databases. Finally, the contents of Binding MOAD are compared to similar databases, establishing the value of our dataset and which purposes it best serves. Second, a robust dataset of 305 unique protein sequences with at least two ligand-bound and two ligand-free structures for each unique protein is cultivated from Binding MOAD and the PDB. Protein flexibility is assessed using C-alpha RMSD for backbone motion and chi-1 angles to quantify side-chain motions. We establish that there is no statistically significant difference between the available conformational space for the backbones or the side chains of unbound proteins when compared to their bound structures. Examining the change in occupied conformational space upon ligand binding reveals a statistically significant increase in backbone conformational space of miniscule magnitude, but a significant increase of side-chain conformational space. To quantify the conformational space available to the side chains, flexibility profiles are established for each amino acid. We found no correlation between backbone and side-chain flexibility. Parallels are then made to common practices in flexible docking techniques. Six binding-site prediction algorithms are then benchmarked on a derivation of the previously established dataset of 305 proteins. We assessed the performance of ligand-bound vs ligand-free structures with these methods and concluded that five of the six methods showed no preference for either structure type. The remaining method, Fpocket, showed decreased performance for ligand-free structures. There was a staggering amount of inconsistency in performance with the methods; different structures of the exact same protein could achieve wildly different rates of success with the same method. The performance of individual structures for all six methods indicated that success and failure rates were seemingly random. Finally, we establish no correlation between the performance of the same structures with different methods, or the performance of the structures with structure resolution, Cruickshank DPI, or number of unresolved residues in their binding sites. Last, we examine the chemical and physical properties of protein-protein interactions (PPIs) with regard to their geometric location in the interface. First, we found that the relative elevation changes of the protein interface landscapes demonstrate that these interfaces are not as flat as previously described. Second, the hollows of druggable PPI interfaces are more sharply shaped and nonpolar in nature, and the protrusions of these druggable PPI interfaces are very polar in character. Last, no correlations exist between the binding affinity describing the subunits of a PPI and other physical and chemical parameters that we measured.PHDMedicinal ChemistryUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145943/1/jordanjc_1.pd

The Shu complex is a conserved regulator of Rad51 filament formation

The budding yeast Shu complex, a heterotetramer of Shu1, Shu2, Csm2, and Psy3, is important for homologous recombination (HR)-mediated chromosome damage repair and was first characterized a decade ago as promoting Rad51-dependent HR in response to replicative stress, but its mechanistic function and conservation in eukaryotes has remained unknown. Here we provide evidence that the Shu complex is evolutionarily conserved throughout eukaryotes, where it is comprised of a clear Shu2 orthologue physically associating with Rad51 paralogues. The Shu complex itself physically interacts with the rest of the HR machinery during DNA damage repair. Finally, we uncover that the mechanistic function of the Shu complex as a stimulatory co-factor of Rad51 filament formation in vitro, likely explaining the in vivo function of the eukaryotic Shu complex in suppressing error-prone repair. Moving forward, our findings provide a framework for studying the function of the human Shu complex, which will have broad importance in our understanding of DNA damage repair

Identification of protein binding surfaces using surface triplet propensities

Motivation: The ability to reliably predict protein-protein and protein-ligand interactions is important for identifying druggable binding sites and for understanding how proteins communicate. Most currently available algorithms identify cavities on the protein surface as potential ligand recognition sites. The method described here does not explicitly look for cavities but uses small surface patches consisting of triplets of adjacent surface atomic groups that can be touched simultaneously by a probe sphere representing a solvent molecule. A total of 455 different types of triplets can be identified. A training set of 309 protein-ligand protein X-ray structures has been used to generate interface propensities for the triplets, which can be used to predict their involvement in ligand-binding interactions. Results: The success rate for locating protein-ligand binding sites on protein surfaces using this new surface triplet propensities (STP) algorithm is 88% which compares well with currently available grid-based and energy-based approaches. Q-SiteFinder's dataset (Laurie and Jackson, 2005. Bioinformatics, 21, 1908-1916) was used to show the favorable performance of STP. An analysis of the different triplet types showed that higher ligand binding propensity is related to more polarizable surfaces. The interaction statistics between triplet atoms on the protein surface and ligand atoms have been used to estimate statistical free energies of interaction. The delta G(stat) for halogen atoms interacting with hydrophobic triplets is -0.6 kcal/mol and an estimate of the maximal delta G(stat) for a ligand atom interacting with a triplet in a binding pocket is -1.45 kcal/mol

Large-Scale Analysis of Protein-Ligand Binding Sites using the Binding MOAD Database.

Current structure-based drug design (SBDD) methods require understanding of general tends of protein-ligand interactions. Informative descriptors of ligand-binding sites provide powerful heuristics to improve SBDD methods designed to infer function from protein structure. These descriptors must have a solid statistical foundation for assessing general trends in large sets of protein-ligand complexes. This dissertation focuses on mining the Binding MOAD database of highly curated protein-ligand complexes to determine frequently observed patterns of binding-site composition. An extension to Binding MOAD’s framework is developed to store structural details of binding sites and facilitate large-scale analysis. This thesis uses the framework to address three topics. It first describes a strategy for determining over-representation of amino acids within ligand-binding sites, comparing the trends of residue propensity for binding sites of biologically relevant ligands to those of spurious molecules with no known function. To determine the significance of these trends and to provide guidelines for residue-propensity studies, the effect of the data set size on the variation in propensity values is evaluated. Next, binding-site residue propensities are applied to improve the performance of a geometry-based, binding-site prediction algorithm. Propensity-based scores are found to perform comparably to the native score in successfully ranking correct predictions. For large proteins, propensity-based and consensus scores improve the scoring success. Finally, current protein-ligand scoring functions are evaluated using a new criterion: the ability to discern biologically relevant ligands from “opportunistic binders,” molecules present in crystal structures due to their high concentrations in the crystallization medium. Four different scoring functions are evaluated against a diverse benchmark set. All are found to perform well for ranking biologically relevant sites over spurious ones, and all performed best when penalties for torsional strain of ligands were included. The final chapter describes a structural alignment method, termed HwRMSD, which can align proteins of very low sequence homology based on their structural similarity using a weighted structure superposition. The overall aims of the dissertation are to collect high-quality binding-site composition data within the largest available set of protein-ligand complexes and to evaluate the appropriate applications of this data to emerging methods for computational proteomics.Ph.D.BioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91400/1/nickolay_1.pd

Database mining studies on protein-peptide and protein-protein interactions

A major area of interest is the identification of proteins that play a role in hormone dependent cancers and in collaboration with the MRC Centre for Reproductive Health we studied the gonadotropin releasing hormone receptor (GnRH-R). Other targets described in the thesis are the SH3 domain of PSD-95 and the protein BLyS. In order to identify potential inhibitory small molecules we have used a variety of computational data base mining approaches as well as using and developing experimental binding assays. It has become increasingly challenging to evaluate the most representative drug like small molecule compounds when using traditional high throughput screening methods. This thesis assesses the use of in silico tools to probe key protein-protein and protein-peptide interactions. These tools provide a means to identify enriched compound datasets which can be purchased and tested in vitro in a time and cost efficient way. The transmembrane protein GnRH-R provides an interesting opportunity to identify small molecules that could inhibit the binding of its peptide ligand GnRH. This is a challenging project as there are few examples in the literature of drug-like molecules that bind to such protein-peptide interfaces. The first step involved receptor modelling using solved crystal structures of homologous proteins. The model was then validated by developing structure activity relationships for established high affinity ligands. We also performed crystallographic and biophysical studies on the native GnRH decapeptide. Two other protein-protein systems were also examined using the same virtual screening and experimental ligand binding methodology. SH3 domains play an important role in cell signalling and we used the PSD-95 protein as our target for study as a crystal structure has been published. As well as identifying potential ligands we characterised structural properties of PSD-95 fusion proteins and also developed the basis for compound assay. The third system studied was B Lymphocyte Stimulator (BLyS) which is a target for treatment of a number of autoimmune diseases. This presented an interesting target for study as the protein binds to multiple receptors depending on its multimeric state. BLyS protein was characterised using electron microscopy and other biophysical techniques

Molecular dynamics study of the allosteric control mechanisms of the glycolytic pathway

There is a growing body of interest to understand the regulation of allosteric proteins. Allostery is a phenomenon of protein regulation whereby binding of an effector molecule at a remote site affects binding and activity at the protein‟s active site. Over the years, these sites have become popular drug targets as they provide advantages in terms of selectivity and saturability. Both experimental and computational methods are being used to study and identify allosteric sites. Although experimental methods provide us with detailed structures and have been relatively successful in identifying these sites, they are subject to time and cost limitations. In the present dissertation, Molecular Dynamics Simulations (MDS) and Principal Component Analysis (PCA) have been employed to enhance our understanding ofallostery and protein dynamics. MD simulations generated trajectories which were then qualitatively assessed using PCA. Both of these techniques were applied to two important trypanosomatid drug targets and controlling enzymes of the glycolytic pathway - pyruvate kinase (PYK) and phosphofructokinase (PFK). Molecular Dynamics simulations were first carried out on both the effector bound and unbound forms of the proteins. This provided a framework for direct comparison and inspection of the conformational changes at the atomic level. Following MD simulations, PCA was run to further analyse the motions. The principal components thus captured are in quantitative agreement with the previously published experimental data which increased our confidence in the reliability of our simulations. Also, the binding of FBP affects the allosteric mechanism of PYK in a very interesting way. The inspection of the vibrational modes reveals interesting patterns in the movement of the subunits which differ from the conventional symmetrical pattern. Also, lowering of B-factors on effector binding provides evidence that the effector is not only locking the R-state but is also acting as a general heat-sink to cool down the whole tetramer. This observation suggests that protein rigidity and intrinsic heat capacity are important factors in stabilizing allosteric proteins. Thus, this work also provides new and promising insights into the classical Monod-Wyman-Changeux model of allostery

Drug screening to identify inhibitors of the structure-specific endonuclease ERCC1-XPF

Malignant melanoma results in 132,000 cases worldwide each year with an incidence rate that is increasing faster than for any other skin cancer. In the UK, cutaneous melanoma is the sixth most commonly diagnosed cancer and the second most common in young people aged 15-34 (excluding non-melanoma skin cancer). Furthermore, while less common than NMSC, malignant melanoma accounts for 4% of skin cancer cases and 74% of skin cancer-related deaths. Although early surgical removal of primary tumours is an effective treatment, patients that develop metastatic melanoma have a very poor prognosis (5 year survival rate is only 5%). Elevated expression of a number of DNA repair genes has been reported in primary melanomas that subsequently metastasised when compared to non-recurrent primary tumours. In addition, patients who do not respond to chemotherapy have elevated expression of DNA repair genes. One chemotherapeutic that is effective against a range of other cancers, but not melanoma is cisplatin. Elevated levels of the DNA repair protein ERCC1, which is needed to remove cisplatin-induced DNA damage, has been found to be an indicator of poor prognosis in ovarian and lung cancer. To test our hypothesis that elevated ERCC1 levels account for an increased resistance to cisplatin in melanoma, a xenograft experiment was performed. Our results show that ERCC1 proficient melanoma xenografts initially responded to cisplatin treatment however resistance soon followed. Tumours deficient in ERCC1 however could be cured after only two treatments of cisplatin, indicating a novel method to overcome chemoresistance in metastatic melanoma. The aim of the project was to identify novel compounds to improve therapy of melanoma. To achieve this, in collaboration with Dr Patton we performed a cell culture screen to identify compounds which display specificity against melanoma cell lines. In addition, we sought to identify compounds which would overcome cisplatin resistance. We identified a series of nitrofuran compounds which are potent against melanoma and neuroblastoma cell lines and enhanced the toxicity of cisplatin through an ERCC1 independent pathway. In addition, we showed that melanin pigmentation is protective against nitrofuran toxicity. We have proposed the structure specific endonuclease, ERCC1-XPF, as a drug target to overcome chemoresistance. We collaborated with Professor Walkinshaw to perform an in silico screen for protein-protein interaction inhibitors to disrupt the obligate dimerization between ERCC1 and XPF. In addition we directly inhibited the endonuclease activity by developing XPF endonuclease domain inhibitors and utilised a range of biochemical, molecular biology and cell culture assays to validate ERCC1-XPF inhibitors. Furthermore, we developed an in vitro endonuclease assay for ERCC1-XPF, FEN1 and DNase1 and utilised these to demonstrate compound specificity of our validated ERCC1-XPF inhibitors. In collaboration with MRC Technology we utilised the ERCC1-XPF endonuclease assay to perform a high throughput screen. We characterised hit compounds to demonstrate physical binding and in vitro specificity for ERCC1-XPF. In conclusion, we have discovered new compounds which may prove beneficial for the treatment of malignant melanoma