Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator.

In May 2022, JCAMD published a Special Issue in honor of Gerald (Gerry) Maggiora, whose scientific leadership over many decades advanced the fields of computational chemistry and chemoinformatics for drug discovery. Along the way, he has impacted many researchers in both academia and the pharmaceutical industry. In this Epilogue, we explain the origins of the Festschrift and present a series of first-hand vignettes, in approximate chronological sequence, that together paint a picture of this remarkable man. Whether they highlight Gerry's endless curiosity about molecular life sciences or his willingness to challenge conventional wisdom or his generous support of junior colleagues and peers, these colleagues and collaborators are united in their appreciation of his positive influence. These tributes also reflect key trends and themes during the evolution of modern drug discovery, seen through the lens of people who worked with a visionary leader. Junior scientists will find an inspiring roadmap for creative collegiality and collaboration.

Machine Learning to Identify Flexibility Signatures of Class A GPCR Inhibition.

We show that machine learning can pinpoint features distinguishing inactive from active states in proteins, in particular identifying key ligand binding site flexibility transitions in GPCRs that are triggered by biologically active ligands. Our analysis was performed on the helical segments and loops in 18 inactive and 9 active class A G protein-coupled receptors (GPCRs). These three-dimensional (3D) structures were determined in complex with ligands. However, considering the flexible versus rigid state identified by graph-theoretic ProFlex rigidity analysis for each helix and loop segment with the ligand removed, followed by feature selection and k-nearest neighbor classification, was sufficient to identify four segments surrounding the ligand binding site whose flexibility/rigidity accurately predicts whether a GPCR is in an active or inactive state. GPCRs bound to inhibitors were similar in their pattern of flexible versus rigid regions, whereas agonist-bound GPCRs were more flexible and diverse. This new ligand-proximal flexibility signature of GPCR activity was identified without knowledge of the ligand binding mode or previously defined switch regions, while being adjacent to the known transmission switch. Following this proof of concept, the ProFlex flexibility analysis coupled with pattern recognition and activity classification may be useful for predicting whether newly designed ligands behave as activators or inhibitors in protein families in general, based on the pattern of flexibility they induce in the protein.

Deciphering the three-domain architecture in schlafens and the structures and roles of human schlafen12 and serpinB12 in transcriptional regulation.

Schlafen proteins are important in cell differentiation and defense against viruses, and yet this family of vertebrate proteins is just beginning to be understood at the molecular level. Here, the three-dimensional architecture and molecular interfaces of human schlafen12 (hSLFN12), which promotes intestinal stem cell differentiation, are analyzed by sequence conservation and structural modeling in light of the functions of its homologs and binding partners. Our analysis shows that the schlafen or divergent AAA ATPase domain described in the N-terminal region of schlafens in databases and the literature is a misannotation. This N-terminal region is conclusively an AlbA_2 DNA/RNA binding domain, forming the conserved core of schlafens and their sequence homologs from bacteria through mammals. Group III schlafens additionally contain a AAA NTPase domain in their C-terminal helicase region. In hSLFN12, we have uncovered a domain matching rho GTPases, which directly follows the AlbA_2 domain in all group II-III schlafens. Potential roles for the GTPase-like domain include antiviral activity and cytoskeletal interactions that contribute to nucleocytoplasmic shuttling and cell polarization during differentiation. Based on features conserved with rSlfn13, the AlbA_2 region in hSLFN12 is likely to bind RNA, possibly as a ribonuclease. We hypothesize that RNA binding by hSLFN12 contributes to an RNA-induced transcriptional silencing/E3 ligase complex, given the functions of hSLFN12's partners, SUV39H1, JMJD6, and PDLIM7. hSLFN12's partner hSerpinB12 may contribute to heterochromatin formation, based on its homology to MENT, or directly regulate transcription via its binding to RNA polymerase II. The analysis presented here provides clear architectural and transcriptional regulation hypotheses to guide experimental design for hSLFN12 and the thousands of schlafens that share its motifs.

Schlafen 12 Interaction with SerpinB12 and Deubiquitylases Drives Human Enterocyte Differentiation.

BACKGROUND/AIMS: Human enterocytic differentiation is altered during development, fasting, adaptation, and bariatric surgery, but its intracellular control remains unclear. We hypothesized that Schlafen 12 (SLFN12) regulates enterocyte differentiation. METHODS: We used laser capture dissection of epithelium, qRT-PCR, and immunohistochemistry to evaluate SLFN12 expression in biopsies of control and fasting human duodenal mucosa, and viral overexpression and siRNA to trace the SLFN12 pathway in human Caco-2 and HIEC6 intestinal epithelial cells. RESULTS: Fasting human duodenal mucosa expressed less SLFN12 mRNA and protein, accompanied by decreases in enterocytic markers like sucrase-isomaltase. SLFN12 overexpression increased Caco-2 sucrase-isomaltase promoter activity, mRNA, and protein independently of proliferation, and activated the SLFN12 putative promoter. SLFN12 coprecipitated Serpin B12 (SERPB12). An inactivating SLFN12 point mutation prevented both SERPB12 binding and sucrase-isomaltase induction. SERPB12 overexpression also induced sucrase-isomaltase, while reducing SERPB12 prevented the SLFN12 effect on sucrase-isomaltase. Sucrase-isomaltase induction by both SLFN12 and SERPB12 was attenuated by reducing UCHL5 or USP14, and blocked by reducing both. SERPB12 stimulated USP14 but not UCHL5 activity. SERPB12 coprecipitated USP14 but not UCHL5. Moreover, SLFN12 increased protein levels of the sucrase-isomaltase-promoter-binding transcription factor cdx2 without altering Cdx2 mRNA. This was prevented by reducing UCHL5 and USP14. We further validated this pathway in vitro and in vivo. SLFN12 or SERPB12 overexpression induced sucrase-isomaltase in human non-malignant HIEC-6 enterocytes. CONCLUSIONS: SLFN12 regulates human enterocytic differentiation by a pathway involving SERPB12, the deubiquitylases, and Cdx2. This pathway may be targeted to manipulate human enterocytic differentiation in mucosal atrophy, short gut or obesity.

Automated Inference of Chemical Discriminants of Biological Activity.

Ligand-based virtual screening has become a standard technique for the efficient discovery of bioactive small molecules. Following assays to determine the activity of compounds selected by virtual screening, or other approaches in which dozens to thousands of molecules have been tested, machine learning techniques make it straightforward to discover the patterns of chemical groups that correlate with the desired biological activity. Defining the chemical features that generate activity can be used to guide the selection of molecules for subsequent rounds of screening and assaying, as well as help design new, more active molecules for organic synthesis.The quantitative structure-activity relationship machine learning protocols we describe here, using decision trees, random forests, and sequential feature selection, take as input the chemical structure of a single, known active small molecule (e.g., an inhibitor, agonist, or substrate) for comparison with the structure of each tested molecule. Knowledge of the atomic structure of the protein target and its interactions with the active compound are not required. These protocols can be modified and applied to any data set that consists of a series of measured structural, chemical, or other features for each tested molecule, along with the experimentally measured value of the response variable you would like to predict or optimize for your project, for instance, inhibitory activity in a biological assay or ΔGbinding. To illustrate the use of different machine learning algorithms, we step through the analysis of a dataset of inhibitor candidates from virtual screening that were tested recently for their ability to inhibit GPCR-mediated signaling in a vertebrate.

Protein-ligand interfaces are polarized: discovery of a strong trend for intermolecular hydrogen bonds to favor donors on the protein side with implications for predicting and designing ligand complexes.

Understanding how proteins encode ligand specificity is fascinating and similar in importance to deciphering the genetic code. For protein-ligand recognition, the combination of an almost infinite variety of interfacial shapes and patterns of chemical groups makes the problem especially challenging. Here we analyze data across non-homologous proteins in complex with small biological ligands to address observations made in our inhibitor discovery projects: that proteins favor donating H-bonds to ligands and avoid using groups with both H-bond donor and acceptor capacity. The resulting clear and significant chemical group matching preferences elucidate the code for protein-native ligand binding, similar to the dominant patterns found in nucleic acid base-pairing. On average, 90% of the keto and carboxylate oxygens occurring in the biological ligands formed direct H-bonds to the protein. A two-fold preference was found for protein atoms to act as H-bond donors and ligand atoms to act as acceptors, and 76% of all intermolecular H-bonds involved an amine donor. Together, the tight chemical and geometric constraints associated with satisfying donor groups generate a hydrogen-bonding lock that can be matched only by ligands bearing the right acceptor-rich key. Measuring an index of H-bond preference based on the observed chemical trends proved sufficient to predict other protein-ligand complexes and can be used to guide molecular design. The resulting Hbind and Protein Recognition Index software packages are being made available for rigorously defining intermolecular H-bonds and measuring the extent to which H-bonding patterns in a given complex match the preference key.

Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control.

While the advantage of screening vast databases of molecules to cover greater molecular diversity is often mentioned, in reality, only a few studies have been published demonstrating inhibitor discovery by screening more than a million compounds for features that mimic a known three-dimensional (3D) ligand. Two factors contribute: the general difficulty of discovering potent inhibitors, and the lack of free, user-friendly software to incorporate project-specific knowledge and user hypotheses into 3D ligand-based screening. The Screenlamp modular toolkit presented here was developed with these needs in mind. We show Screenlamp's ability to screen more than 12 million commercially available molecules and identify potent in vivo inhibitors of a G protein-coupled bile acid receptor within the first year of a discovery project. This pheromone receptor governs sea lamprey reproductive behavior, and to our knowledge, this project is the first to establish the efficacy of computational screening in discovering lead compounds for aquatic invasive species control. Significant enhancement in activity came from selecting compounds based on one of the hypotheses: that matching two distal oxygen groups in the 3D structure of the pheromone is crucial for activity. Six of the 15 most active compounds met these criteria. A second hypothesis-that presence of an alkyl sulfate side chain results in high activity-identified another 6 compounds in the top 10, demonstrating the significant benefits of hypothesis-driven screening.

Inhibition of pressure-activated cancer cell adhesion by FAK-derived peptides.

Forces within the surgical milieu or circulation activate cancer cell adhesion and potentiate metastasis through signaling requiring FAK-Akt1 interaction. Impeding FAK-Akt1 interaction might inhibit perioperative tumor dissemination, facilitating curative cancer surgery without global FAK or AKT inhibitor toxicity. Serial truncation and structurally designed mutants of FAK identified a seven amino acid, short helical structure within FAK that effectively competes with Akt1-FAK interaction. Adenoviral overexpression of this FAK-derived peptide inhibited pressure-induced FAK phosphorylation and AKT-FAK coimmunoprecipitation in human SW620 colon cancer cells briefly exposed to 15mmHg increased pressure, consistent with laparoscopic or post-surgical pressures. Adenoviral FAK-derived peptide expression prevented pressure-activation of SW620 adhesion not only to collagen-I-coated plates but also to murine surgical wounds. A scrambled peptide did not. Finally, we modeled operative shedding of tumor cells before irrigation and closure by transient cancer cell adhesion to murine surgical wounds before irrigation and closure. Thirty minute preincubation of SW620 cells at 15mmHg increased pressure impaired subsequent tumor free survival in mice exposed to cells expressing the scrambled peptide. The FAK-derived sequence prevented this. These results suggest that blocking FAK-Akt1 interaction may prevent perioperative tumor dissemination and that analogs or mimics of this 7 amino acid FAK-derived peptide could impair metastasis.

Genome of the Asian longhorned beetle (Anoplophora glabripennis), a globally significant invasive species, reveals key functional and evolutionary innovations at the beetle-plant interface.

BACKGROUND: Relatively little is known about the genomic basis and evolution of wood-feeding in beetles. We undertook genome sequencing and annotation, gene expression assays, studies of plant cell wall degrading enzymes, and other functional and comparative studies of the Asian longhorned beetle, Anoplophora glabripennis, a globally significant invasive species capable of inflicting severe feeding damage on many important tree species. Complementary studies of genes encoding enzymes involved in digestion of woody plant tissues or detoxification of plant allelochemicals were undertaken with the genomes of 14 additional insects, including the newly sequenced emerald ash borer and bull-headed dung beetle. RESULTS: The Asian longhorned beetle genome encodes a uniquely diverse arsenal of enzymes that can degrade the main polysaccharide networks in plant cell walls, detoxify plant allelochemicals, and otherwise facilitate feeding on woody plants. It has the metabolic plasticity needed to feed on diverse plant species, contributing to its highly invasive nature. Large expansions of chemosensory genes involved in the reception of pheromones and plant kairomones are consistent with the complexity of chemical cues it uses to find host plants and mates. CONCLUSIONS: Amplification and functional divergence of genes associated with specialized feeding on plants, including genes originally obtained via horizontal gene transfer from fungi and bacteria, contributed to the addition, expansion, and enhancement of the metabolic repertoire of the Asian longhorned beetle, certain other phytophagous beetles, and to a lesser degree, other phytophagous insects. Our results thus begin to establish a genomic basis for the evolutionary success of beetles on plants.

Detecting the native ligand orientation by interfacial rigidity: SiteInterlock.

Understanding the physical attributes of protein-ligand interfaces, the source of most biological activity, is a fundamental problem in biophysics. Knowing the characteristic features of interfaces also enables the design of molecules with potent and selective interactions. Prediction of native protein-ligand interactions has traditionally focused on the development of physics-based potential energy functions, empirical scoring functions that are fit to binding data, and knowledge-based potentials that assess the likelihood of pairwise interactions. Here we explore a new approach, testing the hypothesis that protein-ligand binding results in computationally detectable rigidification of the protein-ligand interface. Our SiteInterlock approach uses rigidity theory to efficiently measure the relative interfacial rigidity of a series of small-molecule ligand orientations and conformations for a number of protein complexes. In the majority of cases, SiteInterlock detects a near-native binding mode as being the most rigid, with particularly robust performance relative to other methods when the ligand-free conformation of the protein is provided. The interfacial rigidification of both the protein and ligand prove to be important characteristics of the native binding mode. This measure of rigidity is also sensitive to the spatial coupling of interactions and bond-rotational degrees of freedom in the interface. While the predictive performance of SiteInterlock is competitive with the best of the five other scoring functions tested, its measure of rigidity encompasses cooperative rather than just additive binding interactions, providing novel information for detecting native-like complexes. SiteInterlock shows special strength in enhancing the prediction of native complexes by ruling out inaccurate poses. Proteins 2016; 84:1888-1901. © 2016 Wiley Periodicals, Inc.

Translocator Protein 18 kDa (TSPO): An Old Protein with New Functions?

Translocator protein 18 kDa (TSPO) was previously known as the peripheral benzodiazepine receptor (PBR) in eukaryotes, where it is mainly localized to the mitochondrial outer membrane. Considerable evidence indicates that it plays regulatory roles in steroidogenesis and apoptosis and is involved in various human diseases, such as metastatic cancer, Alzheimer's and Parkinson's disease, inflammation, and anxiety disorders. Ligands of TSPO are widely used as diagnostic tools and treatment options, despite there being no clear understanding of the function of TSPO. An ortholog in the photosynthetic bacterium Rhodobacter was independently discovered as the tryptophan-rich sensory protein (TspO) and found to play a role in the response to changes in oxygen and light conditions that regulate photosynthesis and respiration. As part of this highly conserved protein family found in all three kingdoms, the rat TSPO is able to rescue the knockout phenotype in Rhodobacter, indicating functional as well as structural conservation. Recently, a major breakthrough in the field was achieved: the determination of atomic-resolution structures of TSPO from different species by several independent groups. This now allows us to reexamine the function of TSPO with a molecular perspective. In this review, we focus on recently determined structures of TSPO and their implications for potential functions of this ubiquitous multifaceted protein. We suggest that TSPO is an ancient bacterial receptor/stress sensor that has developed additional interactions, partners, and roles in its mitochondrial outer membrane environment in eukaryotes.

CholMine: Determinants and Prediction of Cholesterol and Cholate Binding Across Nonhomologous Protein Structures.

Identifying physiological ligands is necessary for annotating new protein structures, yet this presents a significant challenge to biologists and pharmaceutical chemists. Here we develop a predictor of cholesterol and cholate binding that works across diverse protein families, extending beyond sequence motif-based prediction. This approach combines SimSite3D site comparison with the detection of conserved interactions in cholesterol/cholate bound crystal structures to define three-dimensional interaction motifs. The resulting predictor identifies cholesterol sites with an ∼82% unbiased true positive rate in both membrane and soluble proteins, with a very low false positive rate relative to other predictors. The CholMine Web server can analyze users' structures, detect those likely to bind cholesterol/cholate, and predict the binding mode and key interactions. By deciphering the determinants of binding for these important steroids, CholMine may also aid in the design of selective inhibitors and detergents for targets such as G protein coupled receptors and bile acid receptors.

Structural and functional assessment of perilipin 2 lipid binding domain(s).

Although perilipin 2 (Plin2) has been shown to bind lipids with high affinity, the Plin2 lipid binding site has yet to be defined. This is of interest since Plin2's affinity for lipids has been suggested to be important for lipid droplet biogenesis and intracellular triacylglycerol accumulation. To define these regions, mouse Plin2 and several deletion mutants expressed as recombinant proteins and in mammalian cells were assessed by molecular modeling, fluorescence binding, circular dichroic, and fluorescence resonance energy transfer techniques to identify the structural and functional requirements for lipid binding. Major findings of this study indicate (1) the N-terminal PAT domain does not bind cholesterol or stearic acid; (2) Plin2 residues 119-251, containing helix α4, the α-ß domain, and part of helix α6 form a Plin3-like cleft found to be important for highest affinity lipid binding; (3) both stearic acid and cholesterol interact favorably with the Plin2 cleft formed by conserved residues in helix α6 and adjacent strands, which is common to all the active lipid-binding constructs; and (4) discrete targeting of the Plin2 mutants to lipid droplets supports Plin2 containing two independent, nonoverlapping lipid droplet targeting domains in its central and C-terminal sequences. Thus, the current work reveals specific domains responsible for Plin2-lipid interactions that involves the protein's lipid binding and targeting functions.

The P-loop region of Schlafen 3 acts within the cytosol to induce differentiation of human Caco-2 intestinal epithelial cells.

Schlafen 3 (Slfn3) mediates rodent enterocyte differentiation in vitro and in vivo, required for intestinal function. Little is known about Schlafen protein structure-function relationships. To define the Slfn3 domain that promotes differentiation, we studied villin and sucrase isomaltase (SI) promoter activity in Slfn3-null human Caco-2BBE cells transfected with full-length rat Slfn3 DNA or truncated constructs. Confocal microscopy and Western blots showed that Slfn3 is predominantly cytosolic. Villin promoter activity, increased by wild type Slfn3, was further enhanced by adding a nuclear exclusion sequence, suggesting that Slfn3 does not affect transcription by direct nuclear action. We therefore sought to dissect the region in Slfn3 stimulating promoter activity. Since examination of the Slfn3 N-terminal region revealed sequences similar to both an aminopeptidase (App) and a divergent P-loop resembling those in NTPases, we initially divided Slfn3 into an N-terminal domain containing the App and P-loop regions, and a C-terminal region. Only the N-terminal construct stimulated promoter activity. Further truncation indicated that both the App and the smaller P-loop constructs enhanced promoter activity similarly to the N-terminal sequence. Point mutations within the N-terminal region (R128L, altering a critical active site residue in the App domain, and L212D, conserved in Schlafens but variable in P-loop proteins) did not affect activity. These results show that Slfn3 acts in the cytosol to trigger a secondary signal cascade that elicits differentiation marker expression and narrows the active domain to the third of the Slfn3 sequence homologous to P-loop NTPases, a first step in understanding its mechanism of action.

Structural determinants allowing transferase activity in SENSITIVE TO FREEZING 2, classified as a family I glycosyl hydrolase.

SENSITIVE TO FREEZING 2 (SFR2) is classified as a family I glycosyl hydrolase but has recently been shown to have galactosyltransferase activity in Arabidopsis thaliana. Natural occurrences of apparent glycosyl hydrolases acting as transferases are interesting from a biocatalysis standpoint, and knowledge about the interconversion can assist in engineering SFR2 in crop plants to resist freezing. To understand how SFR2 evolved into a transferase, the relationship between its structure and function are investigated by activity assay, molecular modeling, and site-directed mutagenesis. SFR2 has no detectable hydrolase activity, although its catalytic site is highly conserved with that of family 1 glycosyl hydrolases. Three regions disparate from glycosyl hydrolases are identified as required for transferase activity as follows: a loop insertion, the C-terminal peptide, and a hydrophobic patch adjacent to the catalytic site. Rationales for the effects of these regions on the SFR2 mechanism are discussed.

Computational prediction and in vitro analysis of potential physiological ligands of the bile acid binding site in cytochrome c oxidase.

A conserved bile acid site has been crystallographically defined in the membrane domain of mammalian and Rhodobacter sphaeroides cytochrome c oxidase (RsCcO). Diverse amphipathic ligands were shown previously to bind to this site and affect the electron transfer equilibrium between heme a and a3 cofactors by blocking the K proton uptake path. Current studies identify physiologically relevant ligands for the bile acid site using a novel three-pronged computational approach: ROCS comparison of ligand shape and electrostatics, SimSite3D comparison of ligand binding site features, and SLIDE screening of potential ligands by docking. Identified candidate ligands include steroids, nicotinamides, flavins, nucleotides, retinoic acid, and thyroid hormones, which are predicted to make key protein contacts with the residues involved in bile acid binding. In vitro oxygen consumption and ligand competition assays on RsCcO wildtype and its Glu101Ala mutant support regulatory activity and specificity of some of these ligands. An ATP analog and GDP inhibit RsCcO under low substrate conditions, while fusidic acid, cholesteryl hemisuccinate, retinoic acid, and T3 thyroid hormone are more potent inhibitors under both high and low substrate conditions. The sigmoidal kinetics of RsCcO inhibition in the presence of certain nucleotides is reminiscent of previously reported ATP inhibition of mammalian CcO, suggesting regulation involving the conserved core subunits of both mammalian and bacterial oxidases. Ligand binding to the bile acid site is noncompetitive with respect to cytochrome c and appears to arrest CcO in a semioxidized state with some resemblance to the "resting" state of the enzyme.

From static structure to living protein: computational analysis of cytochrome c oxidase main-chain flexibility.

Crystallographic structure and deuterium accessibility comparisons of CcO in different redox states have suggested conformational changes of mechanistic significance. To predict the intrinsic flexibility and low energy motions in CcO, this work has analyzed available high-resolution crystallographic structures with ProFlex and elNémo computational methods. The results identify flexible regions and potential conformational changes in CcO that correlate well with published structural and biochemical data and provide mechanistic insights. CcO is predicted to undergo rotational motions on the interior and exterior of the membrane, driven by transmembrane helical tilting and bending, coupled with rocking of the ß-sheet domain. Consequently, the proton K-pathway becomes sufficiently flexible for internal water molecules to alternately occupy upper and lower parts of the pathway, associated with conserved Thr-359 and Lys-362 residues. The D-pathway helices are found to be relatively rigid, with a highly flexible entrance region involving the subunit I C-terminus, potentially regulating the uptake of protons. Constriction and dilation of hydrophobic channels in RsCcO suggest regulation of the oxygen supply to the binuclear center. This analysis points to coupled conformational changes in CcO and their potential to influence both proton and oxygen access.

Interleukin-8-like activity in a filarial asparaginyl-tRNA synthetase.

A wide range of secondary biological functions have been documented for eukaryotic aminoacyl-tRNA synthetases including roles in transcriptional regulation, mitochondrial RNA splicing, cell growth, and chemokine-like activities. The asparaginyl-tRNA synthetase (AsnRS) of the filarial nematode, Brugia malayi, is a highly expressed excretory-secretory molecule which activates interleukin 8 (IL-8) receptors via extracellular domains that are different from those used by IL-8. Recent success in determining the complete atomic structure of the B. malayi AsnRS provided the opportunity to map its chemokine-like activity. Chemotaxis assays demonstrated that IL-8-like activity is localized in a novel 80 amino acid amino terminal substructure. Structural homology searches revealed similarities between that domain in B. malayi AsnRS and substructures involved in receptor binding by human IL-8. These observations provide important new insights into how parasite-derived molecules may play a role in the modulation of immune cell function.

DNA binding by the Arabidopsis CBF1 transcription factor requires the PKKP/RAGRxKFxETRHP signature sequence.

The CBF/DREB1 transcriptional activators are key regulators of plant freezing tolerance. They are members of the AP2/ERF multi-gene family, which in Arabidopsis comprises about 145 members. Common to these proteins is the AP2/ERF DNA-binding domain, a 60-amino-acid fold composed of a three-stranded beta-sheet followed by a C-terminal alpha-helix. A feature that distinguishes the CBF proteins from the other AP2/ERF proteins is the presence of "signature sequences," PKKP/RAGRxKFxETRHP (abbreviated PKKPAGR) and DSAWR, which are located immediately upstream and downstream, respectively, of the AP2/ERF DNA-binding domain. The signature sequences are highly conserved in CBF proteins from diverse plant species suggesting that they have an important functional role. Here we show that the PKKPAGR sequence of AtCBF1 is essential for its transcriptional activity. Deletion of the sequence or mutations within it greatly impaired the ability of CBF1 to induce expression of its target genes. This impairment was not due to the mutations eliminating CBF1 localization to the nucleus or preventing protein accumulation. Rather, we show that this loss of function was due to the mutations greatly impairing the ability of the CBF1 protein to bind to its DNA recognition sequence, the CRT/DRE element. These results establish that the ability of the CBF proteins to bind to the CRT/DRE element requires amino acids that extend beyond the AP2/ERF DNA-binding domain and raise the possibility that the PKKPAGR sequence contributes to determining the DNA-binding specificity of the CBF proteins.

Scoring ligand similarity in structure-based virtual screening.

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds.