Identification of potential small-molecule protein-protein inhibitors of cancer metastasis by 3D epitope-based computational screening.

In cancer cells exposed to extracellular pressure or shear stress, AKT1-FAK interaction drives focal adhesion kinase (FAK) phosphorylation, leading to force-activated cancer cell adhesion and metastasis. Blocking the AKT1-FAK interaction is therefore an attractive target for cancer therapy, avoiding the side effects of global FAK inhibition. Starting with our previous identification of a short FAK peptide that binds AKT1, we identified a series of small-molecule inhibitor candidates using a novel approach for inhibiting protein-protein interactions. Using a 3D structural fragment of the FAK peptide as the query, millions of drug-like, commercially available molecules were screened to identify a subset mimicking the volume and chemistry of the FAK fragment to test for their ability to block pressure-sensitive FAK phosphorylation by AKT1. Two compounds reduced the stimulation of FAK phosphorylation in response to extracellular pressure in human SW620 colon cancer cells without affecting basal FAK phosphorylation. Thus, using a 3D protein interaction epitope as a novel query for ligand-based virtual screening can successfully identify small-molecules that show promise in modulating cancer cell adhesion and metastasis.

Knowledge discovery in medical and biological datasets using a hybrid Bayes classifier/evolutionary algorithm.

A key element of bioinformatics research is the extraction of meaningful information from large experimental data sets. Various approaches, including statistical and graph theoretical methods, data mining, and computational pattern recognition, have been applied to this task with varying degrees of success. Using a novel classifier based on the Bayes discriminant function, we present a hybrid algorithm that employs feature selection and extraction to isolate salient features from large medical and other biological data sets. We have previously shown that a genetic algorithm coupled with a k-nearest-neighbors classifier performs well in extracting information about protein-water binding from X-ray crystallographic protein structure data. The effectiveness of the hybrid EC-Bayes classifier is demonstrated to distinguish the features of this data set that are the most statistically relevant and to weight these features appropriately to aid in the prediction of solvation sites.

Protein flexibility predictions using graph theory.

Techniques from graph theory are applied to analyze the bond networks in proteins and identify the flexible and rigid regions. The bond network consists of distance constraints defined by the covalent and hydrogen bonds and salt bridges in the protein, identified by geometric and energetic criteria. We use an algorithm that counts the degrees of freedom within this constraint network and that identifies all the rigid and flexible substructures in the protein, including overconstrained regions (with more crosslinking bonds than are needed to rigidify the region) and underconstrained or flexible regions, in which dihedral bond rotations can occur. The number of extra constraints or remaining degrees of bond-rotational freedom within a substructure quantifies its relative rigidity/flexibility and provides a flexibility index for each bond in the structure. This novel computational procedure, first used in the analysis of glassy materials, is approximately a million times faster than molecular dynamics simulations and captures the essential conformational flexibility of the protein main and side-chains from analysis of a single, static three-dimensional structure. This approach is demonstrated by comparison with experimental measures of flexibility for three proteins in which hinge and loop motion are essential for biological function: HIV protease, adenylate kinase, and dihydrofolate reductase.

Synthesis of 2beta-acyl-3beta-(substituted naphthyl)-8-azabicyclo[3.2.1]octanes and their binding affinities at dopamine and serotonin transport sites.

A series of 3beta-naphthyltropane derivatives were synthesized and found to show high affinity at both the dopamine and serotonin transporter sites, leading to some of the most potent inhibitors known based on the tropane structure. Comparative molecular field analysis (CoMFA) models were developed for both dopamine and serotonin transporter binding data. These models provide insights into those factors that influence binding at the two transporters.

Protein flexibility and dynamics using constraint theory.

A new approach is presented for determining the rigid regions in proteins and the flexible joints between them. The short-range forces in proteins are modeled as constraints and we use a recently developed formalism from graph theory to analyze flexibility in the bond network. Forces included in the analysis are the covalent bond-stretching and bond-bending forces, salt bridges, and hydrogen bonds. We use a local function to associate an energy with individual hydrogen bonds, which then can be included or excluded depending on the bond strength. Colored maps of the rigid and flexible regions provide a direct visualization of where the motion of the protein can take place, consistent with these distance constraints. We also define a flexibility index that quantifies the local density of flexible or floppy modes, in terms of the dihedral angles that remain free to rotate in each flexible region. A negative flexibility index provides a measure of the density of redundant bonds in rigid regions. A new application of this approach is to simulate the maximal range of possible motions of the flexible regions by introducing Monte Carlo changes in the free dihedral angles, subject to the distance constraints. This is done using a method that maintains closure of the rings formed by covalent and hydrogen bonds in the flexible parts of the protein, and van der Waals overlaps between atoms are avoided. We use the locus of the possible motions of HIV protease as an example: movies of its motion can be seen at http://www.pa.msu.edu/~lei.

One site fits both: a model for the ternary complex of folate + NADPH in R67 dihydrofolate reductase, a D2 symmetric enzyme.

R67 dihydrofolate reductase (DHFR) is a novel enzyme that confers resistance to the antibiotic trimethoprim. The crystal structure of R67 DHFR displays a toroidal structure with a central active-site pore. This homotetrameric protein exhibits 222 symmetry, with only a few residues from each chain contributing to the active site, so related sites must be used to bind both substrate (dihydrofolate) and cofactor (NADPH) in the productive R67 DHFR.NADPH.dihydrofolate complex. Whereas the site of folate binding has been partially resolved crystallographically, an interesting question remains: how can the highly symmetrical active site also bind and orient NADPH for catalysis? To model this ternary complex, we employed DOCK and SLIDE, two methods for docking flexible ligands into proteins using quite different algorithms. The bound pteridine ring of folate (Fol I) from the crystal structure of R67 DHFR was used as the basis for docking the nicotinamide-ribose-Pi (NMN) moiety of NADPH. NMN was positioned by both DOCK and SLIDE on the opposite side of the pore from Fol I, where it interacts with Fol I at the pore's center. Numerous residues serve dual roles in binding. For example, Gln 67 from both the B and D subunits has several contacts with the pteridine ring, while the same residue from the A and C subunits has several contacts with the nicotinamide ring. The residues involved in dual roles are generally amphipathic, allowing them to make both hydrophobic and hydrophilic contacts with the ligands. The result is a 'hot spot' binding surface allowing the same residues to co-optimize the binding of two ligands, and orient them for catalysis.

Flexibility and critical hydrogen bonds in cytochrome c.

We show that protein flexibility can be characterized using graph theory, from a single protein conformation. Covalent and hydrogen bonds are modeled by distance and angular constraints, and a map is constructed of the regions in this network that are flexible or rigid, based on whether their dihedral bonds remain rotatable or are locked by other interactions in the network. This analysis takes only a second on a typical PC, and interatomic potentials; the most time-consuming aspect of molecular dynamics calculations, are not required. Our preliminary work has shown that this approach identifies the experimentally observed, biologically important flexible regions in HIV protease and lysine-arginine-ornithine binding protein. Here we analyze three evolutionarily distant cytochromes c, and find strong similarity between their flexible regions, despite having only 39% sequence identity. Furthermore, we show how the structural flexibility increases as the weaker hydrogen bonds are removed, as would happen under thermal denaturation of the protein. This approach identifies the critical hydrogen bonds that cross-link the tertiary structure.

Prediction of the active-site structure and NAD(+) binding in SQD1, a protein essential for sulfolipid biosynthesis in Arabidopsis.

Sulfolipids of photosynthetic bacteria and plants are characterized by their unique sulfoquinovose headgroup, a derivative of glucose in which the 6-hydroxyl group is replaced by a sulfonate group. These sulfolipids have been discussed as promising anti-tumor and anti-HIV therapeutics based on their inhibition of DNA polymerase and reverse transcriptase. To study sulfolipid biosynthesis, in particular the formation of UDP-sulfoquinovose, we have combined computational modeling with biochemical methods. A database search was performed employing the derived amino acid sequence from SQD1, a gene involved in sulfolipid biosynthesis of Arabidopsis thaliana. This sequence shows high similarity to other sulfolipid biosynthetic proteins of different organisms and also to sugar nucleotide modifying enzymes, including UDP-glucose epimerase and dTDP-glucose dehydratase. Additional biochemical data on the purified SQD1 protein suggest that it is involved in the formation of UDP-sulfoquinovose, the first step of sulfolipid biosynthesis. To understand which aspects of epimerase catalysis may be shared by SQD1, we built a three-dimensional model of SQD1 using the 1.8 A crystallographic structure of UDP-glucose 4-epimerase as a template. This model predicted an NAD(+) binding site, and the binding of NAD(+) was subsequently confirmed by enzymatic assay and mass spectrometry. The active-site interactions together with biochemical data provide the basis for proposing a reaction mechanism for UDP-sulfoquinovose formation.

The accessory subunit of mtDNA polymerase shares structural homology with aminoacyl-tRNA synthetases: implications for a dual role as a primer recognition factor and processivity clamp.

The accessory subunit of the heterodimeric mtDNA polymerase (polgamma) from Drosophila embryos is required to maintain the structural integrity or catalytic efficiency of the holoenzyme. cDNAs for the accessory subunit from Drosophila, man, mouse, and rat have been identified, and comparative sequence alignment reveals that the C-terminal region of about 120 aa is the most conserved. Furthermore, we demonstrate that the accessory subunit of animal polgamma has both sequence and structural similarity with class IIa aminoacyl-tRNA synthetases. Based on sequence similarity and fold recognition followed by homology modeling, we have developed a model of the three-dimensional structure of the C-terminal region of the accessory subunit of polgamma. The model reveals a rare five-stranded beta-sheet surrounded by four alpha-helices with structural homology to the anticodon-binding domain of class IIa aminoacyl-tRNA synthetases. We postulate that the accessory subunit plays a role in the recognition of RNA primers in mtDNA replication, to recruit polgamma to the template-primer junction. A similar role is served by the gamma-complex in Escherichia coli DNA polymerase III, and indeed our accessory subunit model shows structural similarity with the N-terminal domain of the delta' subunit of the gamma-complex. Structural similarity is also found with E. coli thioredoxin, the accessory subunit and processivity factor in bacteriophage T7 DNA polymerase. Thus, we propose that the accessory subunit of polgamma is involved both in primer recognition and in processive DNA strand elongation.

Identification of mimotope peptides which bind to the mycotoxin deoxynivalenol-specific monoclonal antibody.

Monoclonal antibody 6F5 (mAb 6F5), which recognizes the mycotoxin deoxynivalenol (DON) (vomitoxin), was used to select for peptides that mimic the mycotoxin by employing a library of filamentous phages that have random 7-mer peptides on their surfaces. Two phage clones selected from the random peptide phage-displayed library coded for the amino acid sequences SWGPFPF and SWGPLPF. These clones were designated DONPEP.2 and DONPEP.12, respectively. The results of a competitive enzyme-linked immunosorbent assay (ELISA) suggested that the two phage displayed peptides bound to mAb 6F5 specifically at the DON binding site. The amino acid sequence of DONPEP.2 plus a structurally flexible linker at the C terminus (SWGPFPFGGGSC) was synthesized and tested to determine its ability to bind to mAb 6F5. This synthetic peptide (designated peptide C430) and DON competed with each other for mAb 6F5 binding. When translationally fused with bacterial alkaline phosphatase, DONPEP.2 bound specifically to mAb 6F5, while the fusion protein retained alkaline phosphatase activity. The potential of using DONPEP.2 as an immunochemical reagent in a DON immunoassay was evaluated with a DON-spiked wheat extract. When peptide C430 was conjugated to bovine serum albumin, it elicited antibody specific to peptide C430 but not to DON in both mice and rabbits. In an in vitro translation system containing rabbit reticulocyte lysate, synthetic peptide C430 did not inhibit protein synthesis but did show antagonism toward DON-induced protein synthesis inhibition. These data suggest that the peptides selected in this study bind to mAb 6F5 and that peptide C430 binds to ribosomes at the same sites as DON.

Database screening for HIV protease ligands: the influence of binding-site conformation and representation on ligand selectivity.

Screening for potential ligands and docking them into the binding sites of proteins is one of the main tasks in computer-aided drug design. Despite the progress in computational power, it remains infeasible to model all the factors involved in molecular recognition, especially when screening databases of more than 100,000 compounds. While ligand flexibility is considered in most approaches, the model of the binding site is rather simplistic, with neither solvation nor induced complementary usually taken into consideration. We present results for screening different databases for HIV-1 protease ligands with our tool Slide, and investigate the extent to which binding-site conformation, solvation, and template representation generate bias. The results suggest a strategy for selecting the optimal binding-site conformation, for cases in which more than one independent structure is available, and selecting a representation of that binding site that yields reproducible results and the identification of known ligands.

Cluster analysis of consensus water sites in thrombin and trypsin shows conservation between serine proteases and contributions to ligand specificity.

Cluster analysis is presented as a technique for analyzing the conservation and chemistry of water sites from independent protein structures, and applied to thrombin, trypsin, and bovine pancreatic trypsin inhibitor (BPTI) to locate shared water sites, as well as those contributing to specificity. When several protein structures are superimposed, complete linkage cluster analysis provides an objective technique for resolving the continuum of overlaps between water sites into a set of maximally dense microclusters of overlapping water molecules, and also avoids reliance on any one structure as a reference. Water sites were clustered for ten superimposed thrombin structures, three trypsin structures, and four BPTI structures. For thrombin, 19% of the 708 microclusters, representing unique water sites, contained water molecules from at least half of the structures, and 4% contained waters from all 10. For trypsin, 77% of the 106 microclusters contained water sites from at least half of the structures, and 57% contained waters from all three. Water site conservation correlated with several environmental features: highly conserved microclusters generally had more protein atom neighbors, were in a more hydrophilic environment, made more hydrogen bonds to the protein, and were less mobile. There were significant overlaps between thrombin and trypsin conserved water sites, which did not localize to their similar active sites, but were concentrated in buried regions including the solvent channel surrounding the Na+ site in thrombin, which is associated with ligand selectivity. Cluster analysis also identified water sites conserved in thrombin but not trypsin, and vice versa, providing a list of water sites that may contribute to ligand discrimination. Thus, in addition to facilitating the analysis of water sites from multiple structures, cluster analysis provides a useful tool for distinguishing between conserved features within a protein family and those conferring specificity.

Screening a peptidyl database for potential ligands to proteins with side-chain flexibility.

The three key challenges addressed in our development of SPECITOPE, a tool for screening large structural databases for potential ligands to a protein, are to eliminate infeasible candidates early in the search, incorporate ligand and protein side-chain flexibility upon docking, and provide an appropriate rank for potential new ligands. The protein ligand-binding site is modeled by a shell of surface atoms and by hydrogen-bonding template points for the ligand to match, conferring specificity to the interaction. SPECITOPE combinatorially matches all hydrogen-bond donors and acceptors of the screened molecules to the template points. By eliminating molecules that cannot match distance or hydrogen-bond constraints, the transformation of potential docking candidates into the ligand-binding site and the shape and hydrophobic complementarity evaluations are only required for a small subset of the database. SPECITOPE screens 140,000 peptide fragments in about an hour and has identified and docked known inhibitors and potential new ligands to the free structures of four distinct targets: a serine protease, a DNA repair enzyme, an aspartic proteinase, and a glycosyltransferase. For all four, protein side-chain rotations were critical for successful docking, emphasizing the importance of inducible complementarity for accurately modeling ligand interactions. SPECITOPE has a range of potential applications for understanding and engineering protein recognition, from inhibitor and linker design to protein docking and macromolecular assembly.

The role of structure in antibody cross-reactivity between peptides and folded proteins.

Peptides have the potential for targeting vaccines against pre-specified epitopes on folded proteins. When polyclonal antibodies against native proteins are used to screen peptide libraries, most of the peptides isolated align to linear epitopes on the proteins. The mechanism of cross-reactivity is unclear; both structural mimicry by the peptide and induced fit of the epitope may occur. The most effective peptide mimics of protein epitopes are likely to be those that best mimic both the chemistry and the structure of epitopes. Our goal in this work has been to establish a strategy for characterizing epitopes on a folded protein that are candidates for structural mimicry by peptides. We investigated the chemical and structural bases of peptide-protein cross-reactivity using phage-displayed peptide libraries in combination with computational structural analysis. Polyclonal antibodies against the well-characterized antigens, hen eggwhite lysozyme and worm myohemerythrin, were used to screen a panel of phage-displayed peptide libraries. Most of the selected peptide sequences aligned to linear epitopes on the corresponding protein; the critical binding sequence of each epitope was revealed from these alignments. The structures of the critical sequences as they occur in other non-homologous proteins were analyzed using the Sequery and Superpositional Structural Assignment computer programs. These allowed us to evaluate the extent of conformational preference inherent in each sequence independent of its protein context, and thus to predict the peptides most likely to have structural preferences that match their protein epitopes. Evidence for sequences having a clear structural bias emerged for several epitopes, and synthetic peptides representing three of these epitopes bound antibody with sub-micromolar affinities. The strong preference for a type II beta-turn predicted for one peptide was confirmed by NMR and circular dichroism analyses. Our strategy for identifying conformationally biased epitope sequences provides a new approach to the design of epitope-targeted, peptide-based vaccines.

Predicting conserved water-mediated and polar ligand interactions in proteins using a K-nearest-neighbors genetic algorithm.

Water-mediated ligand interactions are essential to biological processes, from product displacement in thymidylate synthase to DNA recognition by Trp repressor, yet the structural chemistry influencing whether bound water is displaced or participates in ligand binding is not well characterized. Consolv, employing a hybrid k-nearest-neighbors classifier/genetic algorithm, predicts bound water molecules conserved between free and ligand-bound protein structures by examining the environment of each water molecule in the free structure. Four environmental features are used: the water molecule's crystallographic temperature factor, the number of hydrogen bonds between the water molecule and protein, and the density and hydrophilicity of neighboring protein atoms. After training on 13 non-homologous proteins, Consolv predicted the conservation of active-site water molecules upon ligand binding with 75% accuracy (Matthews coefficient Cm = 0.41) for seven new proteins. Mispredictions typically involved water molecules predicted to be conserved that were displaced by a polar ligand atom, indicating that Consolv correctly assesses polar binding sites; 90% accuracy (Cm = 0.78) was achieved for predicting conserved active-site water or polar ligand atom binding. Consolv thus provides an accurate means for optimizing ligand design by identifying sites favored to be occupied by either a mediating water molecule or a polar ligand atom, as well as water molecules likely to be displaced by the ligand. Accuracy for predicting first-shell water conservation between independently determined structures was 61% (Cm=0.23). The ability to predict water-mediated and polar interactions from the free protein structure indicates the surprising extent to which the conservation or displacement of active-site bound water is independent of the ligand, and shows that the protein micro-environment of each water molecule is the dominant influence.

Synthesis of 3 beta-aryl-8-azabicyclo[3.2.1]octanes with high binding affinities and selectivities for the serotonin transporter site.

A novel entry to tropane analogs of cocaine was developed based on the reaction of rhodium-stabilized vinylcarbenoids with pyrroles. These analogs were tested in binding to dopamine, serotonin (5-HT), and norepinephrine transporters in membranes from rat striatum and frontal cortex. In all the analogs, the aryl group at the 3 position was directly bound to the tropane ring and an ethyl ketone moiety was present at the 2 position. By appropriate modification of the aryl and nitrogen substituents, highly potent and 5-HT selective tropanes were prepared. The most potent and selective compound was 3 beta-[4-(1-methylethenyl)phenyl]-2 beta-propanoyl-8-azabicyclo[3.2.1]octane (13b) which had a Ki of 0.1 nM at 5-HT transporters and was 150 times more potent at 5-HT vs dopamine transporters and almost 1000 times more potent at 5-HT vs norepinephrine transporters.

Atomic and residue hydrophilicity in the context of folded protein structures.

Water-protein interactions drive protein folding, stabilize the folded structure, and influence molecular recognition and catalysis. We analyzed the closest protein contacts of 10,837 water molecules in crystallographic structures to define a specific hydrophilicity scale reflecting specific rather than bulk solvent interactions. The tendencies of different atom and residue types to be the nearest protein neighbors of bound water molecules correlated with other hydrophobicity scales, verified the relevance of crystallographically determined water positions, and provided a direct experimental measure of water affinity in the context of the folded protein. This specific hydrophilicity was highly correlated with hydrogen-bonding capacity, and correlated better with experimental than computationally derived measures of partitioning between aqueous and organic phases. Atoms with related chemistry clustered with respect to the number of bound water molecules. Neutral and negatively charged oxygen atoms were the most hydrophilic, followed by positively-charged then neutral nitrogen atoms, followed by carbon and sulfur atoms. Agreement between observed side-chain specific hydrophilicity values and values derived from the atomic hydrophilicity scale showed that hydrophilicity values can be synthesized for different functional groups, such as unusual side or main chains, discontinuous epitopes, and drug molecules. Two methods of atomic hydrophilicity analysis provided a measure of complementarity in the interfaces of trypsin:pancreatic trypsin inhibitor and HIV protease:U-75875 inhibitor complexes.

A role for acidic residues in di-leucine motif-based targeting to the endocytic pathway.

Recent reports have suggested that major histocompatibility complex class II molecules load peptide through a specialized compartment of the endocytic pathway and are targeted to this pathway by association with invariant chain (Iip31). Therefore we used a site-directed mutagenesis approach to determine whether Iip31 possesses novel protein targeting signals. Our results indicate that two di-leucine-like pairs mediate Iip31 targeting and that an acidic amino acid residue four or five residues N-terminal to each Iip31 di-leucine-like pair is required for endocytic targeting. Results from additional testing with hybrid Iip31 molecules indicate that the acidic residues N-terminal to di-leucine pairs are critical for accumulation of these molecules in large endocytic vesicles and in some cases provide a structure favorable for internalization. The acidic residues N-terminal to di-leucine pairs are important in some sequence contexts in providing a structure favorable for internalization, whereas in other contexts an acidic residue is critical for targeting to, and formation of, large endocytic vesicles. Although our results do not support the idea that Iip31 possesses unique protein targeting motifs, they do suggest that di-leucine motifs may be recognized as part of a larger secondary structure. In addition, our data imply that the targeting motif requirements for internalization may differ from the requirements for further transport in the endocytic pathway.