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The AutoDock suite provides a comprehensive toolset for computational ligand docking and drug design and development. The suite builds on 30 years of methods development, including empirical free energy force fields, docking engines, methods for site prediction, and interactive tools for visualization and analysis. Specialized tools are available for challenging systems, including covalent inhibitors, peptides, compounds with macrocycles, systems where ordered hydration plays a key role, and systems with substantial receptor flexibility. All methods in the AutoDock suite are freely available for use and reuse, which has engendered the continued growth of a diverse community of primary users and third-party developers. This article is protected by copyright. All rights reserved.

The structural study of icosahedral viruses has a long and impactful history in both crystallographic methodology and molecular biology. The evolution of the Protein Data Bank has paralleled and supported these studies providing readily accessible formats dealing with novel features associated with viral particle symmetries and subunit interactions. This overview describes the growth in size and complexity of icosahedral viruses from the first early studies of small RNA plant viruses and human picornaviruses up to the larger and more complex bacterial phage, insect, and human disease viruses such as Zika, hepatitis B, Adeno and Polyoma virus. The analysis of icosahedral viral capsid protein domain folds has shown striking similarities, with the beta jelly roll motif observed across multiple evolutionarily divergent species. The icosahedral symmetry of viruses drove the development of noncrystallographic symmetry averaging as a powerful phasing method, and the constraints of maintaining this symmetry resulted in the concept of quasi-equivalence in viral structures. Symmetry also played an important early role in demonstrating the power of cryo-electron microscopy as an alternative to crystallography in generating atomic resolution structures of these viruses. The Protein Data Bank has been a critical resource for assembling and disseminating these structures to a wide community, and the virus particle explorer (VIPER) was developed to enable users to easily generate and view complete viral capsid structures from their asymmetric building blocks. Finally, we share a personal perspective on the early use of computer graphics to communicate the intricacies, interactions, and beauty of these virus structures.

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.

Visualization has been a key technology in the progress of structural molecular biology for as long as the field has existed. This perspective describes the nature of the visualization process in structural studies, how it has evolved over the years, and its relationship to the changes in technology that have supported and driven it. It focuses on how technical advances have changed the way we look at and interact with molecular structure, and how structural biology has fostered and challenged that technology.

A coarse-grain computational method integrates biophysical and structural data to generate models of HIV-1 genomic RNA, nucleocapsid and integrase condensed into a mature ribonucleoprotein complex. Several hypotheses for the initial structure of the genomic RNA and oligomeric state of integrase are tested. In these models, integrase interaction captures features of the relative distribution of gRNA in the immature virion and increases the size of the RNP globule, and exclusion of nucleocapsid from regions with RNA secondary structure drives an asymmetric placement of the dimerized 5’UTR at the surface of the RNP globule., Author summary The genome of HIV-1 is composed of two strands of RNA that are packaged in the mature virion as a condensed ribonucleoprotein complex with nucleocapsid, integrase, and other proteins. We have generated models of the HIV-1 ribonucleoprotein that integrate experimental results from multiple structural and biophysical experiments, exploring several hypotheses about the state of the RNA before condensation, and the role of crosslinking by integrase. The models suggest that the 5’UTR, which shows extensive secondary structure, has a propensity to be placed on the surface of the condensed globule, due to reduced binding of nucleocapsid to double-stranded regions within the 5’UTR. This unexpected localization of the 5’UTR may have consequences for the subsequent structural transitions that occur during the process of reverse transcription.

HIV-1 integrase (IN) is essential for virus replication and represents an important multifunctional therapeutic target. Recently discovered quinoline-based allosteric IN inhibitors (ALLINIs) potently impair HIV-1 replication and are currently in clinical trials. ALLINIs exhibit a multimodal mechanism of action by inducing aberrant IN multimerization during virion morphogenesis and by competing with IN for binding to its cognate cellular cofactor LEDGF/p75 during early steps of HIV-1 infection. However, quinoline-based ALLINIs impose a low genetic barrier for the evolution of resistant phenotypes, which highlights a need for discovery of second-generation inhibitors. Using crystallographic screening of a library of 971 fragments against the HIV-1 IN catalytic core domain (CCD) followed by a fragment expansion approach, we have identified thiophenecarboxylic acid derivatives that bind at the CCD-CCD dimer interface at the principal lens epithelium-derived growth factor (LEDGF)/p75 binding pocket. The most active derivative (5) inhibited LEDGF/p75-dependent HIV-1 IN activity in vitro with an IC50 of 72 μm and impaired HIV-1 infection of T cells at an EC50 of 36 μm. The identified lead compound, with a relatively small molecular weight (221 Da), provides an optimal building block for developing a new class of inhibitors. Furthermore, although structurally distinct thiophenecarboxylic acid derivatives target a similar pocket at the IN dimer interface as the quinoline-based ALLINIs, the lead compound, 5, inhibited IN mutants that confer resistance to quinoline-based compounds. Collectively, our findings provide a plausible path for structure-based development of second-generation ALLINIs.

We describe two methods of automated covalent docking using Autodock4: the two-point attractor method and the flexible side chain method. Both methods were applied to a training set of 20 diverse protein-ligand covalent complexes, evaluating their reliability in predicting the crystallographic pose of the ligands. The flexible side chain method performed best, recovering the pose in 75% of cases, with failures for the largest inhibitors tested. Both methods are freely available at the AutoDock website (http://autodock.scripps.edu).

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10-100 nm) between molecular and cellular biology scales. cellPACK's modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive three-dimensional models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is available as open-source code, with tools for validation of models and with 'recipes' and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org/.

The small program Illustrate generates non-photorealistic images of biological molecules for use in dissemination, outreach, and education. The method has been used as part of the "Molecule of the Month," an ongoing educational column at the RCSB Protein Data Bank (http://rcsb.org). Insights from 20 years of application of the program are presented, and the program has been released both as open-source Fortran at GitHub and through an interactive web-based interface.

Structural molecular biology is now becoming part of high school science curriculum thus posing a challenge for teachers who need to convey three-dimensional (3D) structures with conventional text and pictures. In many cases even interactive computer graphics does not go far enough to address these challenges. We have developed a flexible model of the polypeptide backbone using 3D printing technology. With this model we have produced a polypeptide assembly kit to create an idealized model of the Triosephosphate isomerase mutase enzyme (TIM), which forms a structure known as TIM barrel. This kit has been used in a laboratory practical where students perform a step-by-step investigation into the nature of protein folding, starting with the handedness of amino acids to the formation of secondary and tertiary structure. Based on the classroom evidence we collected, we conclude that these models are valuable and inexpensive resource for teaching structural molecular biology.

Computational modeling is essential for structural characterization of biomolecular mechanisms across the broad spectrum of scales. Adequate understanding of biomolecular mechanisms inherently involves our ability to model them. Structural modeling of individual biomolecules and their interactions has been rapidly progressing. However, in terms of the broader picture, the focus is shifting toward larger systems, up to the level of a cell. Such modeling involves a more dynamic and realistic representation of the interactomes in vivo, in a crowded cellular environment, as well as membranes and membrane proteins, and other cellular components. Structural modeling of a cell complements computational approaches to cellular mechanisms based on differential equations, graph models, and other techniques to model biological networks, imaging data, etc. Structural modeling along with other computational and experimental approaches will provide a fundamental understanding of life at the molecular level and lead to important applications to biology and medicine. A cross section of diverse approaches presented in this review illustrates the developing shift from the structural modeling of individual molecules to that of cell biology. Studies in several related areas are covered: biological networks; automated construction of three-dimensional cell models using experimental data; modeling of protein complexes; prediction of non-specific and transient protein interactions; thermodynamic and kinetic effects of crowding; cellular membrane modeling; and modeling of chromosomes. The review presents an expert opinion on the current state-of-the-art in these various aspects of structural modeling in cellular biology, and the prospects of future developments in this emerging field.

SummaryIncreasingly complex research has made it more difficult to prepare data for publication, education, and outreach. Many scientists must also wade through black-box code to interface computational algorithms from diverse sources to supplement their bench work. To reduce these barriers we have developed an open-source plug-in, embedded Python Molecular Viewer (ePMV), that runs molecular modeling software directly inside of professional 3D animation applications (hosts) to provide simultaneous access to the capabilities of these newly connected systems. Uniting host and scientific algorithms into a single interface allows users from varied backgrounds to assemble professional quality visuals and to perform computational experiments with relative ease. By enabling easy exchange of algorithms, ePMV can facilitate interdisciplinary research, smooth communication between broadly diverse specialties, and provide a common platform to frame and visualize the increasingly detailed intersection(s) of cellular and molecular biology.

Nucleocytoplasmic transport of macromolecules is a fundamental process of eukaryotic cells. Translocation of proteins and many RNAs between the nucleus and cytoplasm is carried out by shuttling receptors of the β-karyopherin family, also called importins and exportins. Leptomycin B, a small molecule inhibitor of the exportin CRM1, has proved to be an invaluable tool for cell biologists, but up to now no small molecule inhibitors of nuclear import have been described. We devised a microtiter plate based permeabilized cell screen for small molecule inhibitors of the importin α/β pathway. By analyzing peptidomimetic libraries, we identified β-turn and α-helix peptidomimetic compounds that selectively inhibit nuclear import by importin α/β but not by transportin. Structure-activity relationship analysis showed that large aromatic residues and/or a histidine side chain are required for effective import inhibition by these compounds. Our validated inhibitors can be useful for in vitro studies of nuclear import, and can also provide a framework for synthesis of higher potency nuclear import inhibitors.

Structural biology is rapidly accumulating a wealth of detailed information about protein function, binding sites, RNA, large assemblies and molecular motions. These data are increasingly of interest to a broader community of life scientists, not just structural experts. Visualization is a primary means for accessing and using these data, yet visualization is also a stumbling block that prevents many life scientists from benefiting from three-dimensional structural data. In this review, we focus on key biological questions where visualizing three-dimensional structures can provide insight and describe available methods and tools. Supplementary information The online version of this article (doi:10.1038/nmeth.1427) contains supplementary material, which is available to authorized users.

Rediocides A and G, the principle components of Trigonostemon reidioides (Kurz) Craib, which is known as Lotthanong in Thai, were investigated for a detoxification mechanism against Naja kaouthia venom by in silico, in vitro, and in vivo methods. Molecular dockings of alpha-cobratoxin with rediocides A and G were performed, and the binding energies were found to be -14.17 and -14.14 kcal/mol, respectively. Rediocides bind to alpha-cobratoxin at the same location as alpha-cobratoxin binds to the nicotinic acetylcholine receptor (nAChR), i.e., at the Asp27, Phe29, Arg33, Gly34, Lys35, and Val37 residues. alpha-Cobratoxin cannot bind to nAChR, because some of its binding sites are occupied with rediocides. From in vitro SDS-PAGE, it was found that rediocides can diminish the bands of alpha-cobratoxin. In the presence of acetylcholine-binding protein (AChBP), it was apparent that rediocides can bind both alpha-cobratoxin and AChBP. From an in vivo test, it was found that injection of rediocides at 0.5 mg/kg immediately after an alpha-cobratoxin dose of three times LD(50) cannot prolong the survival time of mice. However, rediocide can prolong the survival time, if it is injected 30 min before the injection of alpha-cobratoxin. The in vitro SDS-PAGE and the in vivo results support the in silico detoxification mechanism of rediocides against cobra venom at a molecular level.

Many human cancers show constitutive or amplified expression of the transcriptional regulator and oncoprotein Myc, making Myc a potential target for therapeutic intervention. Here we report the down-regulation of Myc activity by reducing the availability of Max, the essential dimerization partner of Myc. Max is expressed constitutively and can form unstable homodimers. We have isolated stabilizers of the Max homodimer by applying virtual ligand screening (VLS) to identify specific binding pockets for small molecule interactors. Candidate compounds found by VLS were screened by fluorescence resonance energy transfer, and from these screens emerged a potent, specific stabilizer of the Max homodimer. In vitro binding assays demonstrated that the stabilizer enhances the formation of the Max-Max homodimer and interferes with the heterodimerization of Myc and Max in a dose-dependent manner. Furthermore, this compound interferes with Myc-induced oncogenic transformation, Myc-dependent cell growth, and Myc-mediated transcriptional activation. The Max-Max stabilizer can be considered a lead compound for the development of inhibitors of the Myc network.

Signaling of the tissue factor-FVIIa complex regulates angiogenesis, tumor growth, and inflammation. TF-FVIIa triggers cell signaling events by cleavage of protease activated receptor (PAR2) at the Arg36-Ser37 scissile bond. The recognition of PAR2 by the FVIIa protease domain is poorly understood. We perform molecular modeling and dynamics simulations to derive the PAR2-FVIIa interactions. Docking of the PAR2 Arg36-Ser37 scissile bond to the S1 site and subsequent molecular dynamics leads to interactions of the PAR2 ectodomain with P and P′ sites of the FVIIa catalytic cleft as well as to electrostatic interactions between a stably folded region of PAR2 and a cluster of basic residues remote from the catalytic cleft of FVIIa. To address the functional significance of this interaction for PAR2 cleavage, we employed two antibodies with epitopes previously mapped to this cluster of basic residues. Although these antibodies do not block the catalytic cleft, both antibodies completely abrogated PAR2 activation by TF-FVIIa. Our simulations indicate a conformation of the PAR2 ectodomain that limits the cleavage site to no more than 33 A from its membrane proximal residue. Since the active site of FVIIa in the TF-FVIIa complex is ∼75 A above the membrane, cleavage of the folded conformation of PAR2 would require tilting of the TF-FVIIa complex toward the membrane, indicating that additional cellular factors may be required to properly align the scissile bond of PAR2 with TF-FVIIa. Proteins 2009. © 2009 Wiley-Liss, Inc.

Phage-displayed peptides that selectively bind to aldolase catalytic antibody 93F3 when bound to a particular 1,3-diketone hapten derivative have been developed using designed selection strategies with libraries containing 7–12 randomized amino acid residues. These phage-displayed peptides discriminated the particular 93F3–diketone complex from ligand-free 93F3 and from 93F3 bound to other 1,3-diketone hapten derivatives. By altering the selection procedures, phage-displayed peptides that bind to antibody 93F3 in the absence of 1,3-diketone hapten derivatives have also been developed. With using these phage-displayed peptides, ligand-bound states of the antibody were distinguished from each other. A docking model of one of the peptides bound to the antibody 93F3–diketone complex was created using a sequential divide-and-conquer peptide docking strategy; the model suggests that the peptide interacts with both the antibody and the ligand through a delicate hydrogen bonding network.

We present a method, termed AutoLigand, for the prediction of ligand-binding sites in proteins of known structure. The method searches the space surrounding the protein and finds the contiguous envelope with the specified volume of atoms, which has the largest possible interaction energy with the protein. It uses a full atomic representation, with atom types for carbon, hydrogen, oxygen, nitrogen and sulfur (and others, if desired), and is designed to minimize the need for artificial geometry. Testing on a set of 187 diverse protein-ligand complexes has shown that the method is successful in predicting the location and approximate volume of the binding site in 73% of cases. Additional testing was performed on a set of 96 protein-ligand complexes with crystallographic structures of apo and holo forms, and AutoLigand was able to predict the binding site in 80% of the apo structures.

The inosine monophosphate cyclohydrolase (IMPCH) component (residues 1-199) of the bifunctional enzyme aminoimidazole-4-carboxamide ribonucleotide transformylase (AICAR Tfase, residues 200-593)/IMPCH (ATIC) catalyzes the final step in the de novo purine biosynthesis pathway that produces IMP. As a potential target for antineoplastic intervention, we designed IMPCH inhibitors, 1,5-dihydroimidazo[4,5-c][1,2,6]thiadiazin-4(3H)-one 2,2-dioxide (heterocycle, 1), the corresponding nucleoside (2), and the nucleoside monophosphate (nucleotide) (3), as mimics of the tetrahedral intermediate in the cyclization reaction. All compounds are competitive inhibitors against IMPCH (K(i) values = 0.13-0.23 microm) with the simple heterocycle 1 exhibiting the most potent inhibition (K(i) = 0.13 microm). Crystal structures of bifunctional ATIC in complex with nucleoside 2 and nucleotide 3 revealed IMPCH binding modes similar to that of the IMPCH feedback inhibitor, xanthosine 5'-monophosphate. Surprisingly, the simpler heterocycle 1 had a completely different IMPCH binding mode and was relocated to the phosphate binding pocket that was identified from previous xanthosine 5'-monophosphate structures. The aromatic imidazole ring interacts with a helix dipole, similar to the interaction with the phosphate moiety of 3. The crystal structures not only revealed the mechanism of inhibition of these compounds, but they now serve as a platform for future inhibitor improvements. Importantly, the nucleoside-complexed structure supports the notion that inhibitors lacking a negatively charged phosphate can still inhibit IMPCH activity with comparable potency to phosphate-containing inhibitors. Provocatively, the nucleotide inhibitor 3 also binds to the AICAR Tfase domain of ATIC, which now provides a lead compound for the design of inhibitors that simultaneously target both active sites of this bifunctional enzyme.

p130(cas) (Crk-associated substrate) is a docking protein that is involved in assembly of focal adhesions and concomitant cellular signaling. It plays a role in physiological regulation of cell adhesion, migration, survival, and proliferation, as well as in oncogenic transformation. The molecule consists of multiple protein-protein interaction motifs, including a serine-rich region that is positioned between Crk and Src-binding sites. This study reports the first structure of a functional domain of Cas. The solution structure of the serine-rich region has been determined by NMR spectroscopy, demonstrating that this is a stable domain that folds as a four-helix bundle, a protein-interaction motif. The serine-rich region bears strong structural similarity to four-helix bundles found in other adhesion components like focal adhesion kinase, alpha-catenin, or vinculin. Potential sites for phosphorylation and interaction with the 14-3-3 family of cellular regulators are identified in the domain and characterized by site-directed mutagenesis and binding assays. Mapping the degree of amino acid conservation onto the molecular surface reveals a patch of invariant residues near the C terminus of the bundle, which may represent a previously unidentified site for protein interaction.

SummaryThe evolving technology of computer autofabrication makes it possible to produce physical models for complex biological molecules and assemblies. Augmented reality has recently developed as a computer interface technology that enables the mixing of real-world objects and computer-generated graphics. We report an application that demonstrates the use of autofabricated tangible models and augmented reality for research and communication in molecular biology. We have extended our molecular modeling environment, PMV, to support the fabrication of a wide variety of physical molecular models, and have adapted an augmented reality system to allow virtual 3D representations to be overlaid onto the tangible molecular models. Users can easily change the overlaid information, switching between different representations of the molecule, displays of molecular properties, or dynamic information. The physical models provide a powerful, intuitive interface for manipulating the computer models, streamlining the interface between human intent, the physical model, and the computational activity.

CD134 is a primary binding receptor for feline immunodeficiency virus (FIV), and with CXCR4 facilitates infection of CD4(+) T cells. Human CD134 fails to support FIV infection. To delineate the regions important for defining virus specificity of CD134, we exchanged domains between human and feline CD134. The binding site for FIV surface glycoprotein (SU) is located in domain 1, in a region distinct from the natural ligand (CD134L)-binding site. Mutagenesis showed that Asp60 and Asp62 are required for interaction with FIV, and modeling studies localized these two residues to the outer edge of domain 1. Substitutions S60D and N62D, in conjunction with H45S, R59G and V64K, imparted both FIV SU binding and receptor function to human CD134. Finally, we demonstrated that soluble CD134 facilitates infection of CD134(-) CXCR4(+) target cells in a manner analogous to CD4 augmentation of HIV infection.

Catalytic aldolase antibodies, generated by reactive immunization, catalyze the aldol reaction with the efficiency of natural enzymes, but accept a much broader range of substrates. Two separate groups of aldolase antibodies that catalyze the same aldol reactions with antipodal selectivity were analyzed by comparing their amino acid sequences with their crystal structures, site-directed mutagenesis data, and computational docking of the transition states of the aldol reaction. The crystal structure of aldolase antibody 93F3 Fab' at 2.5A resolution revealed a combining site with two lysine residues, including LysL89 that reacts to form the covalent enamine intermediate. In contrast, antibody 33F12 has one active site lysine, LysH93. The reactive lysine residues in each group of antibodies are differentially located on the heavy and light chain variable regions in pseudo-symmetric opposite orientations, but both within highly hydrophobic environments. Thus, the defining feature for the observed enantioselectivities of these aldolase antibody catalysts is the respective location and relative disposition of the reactive lysine residues within the active sites of these catalysts.

Aminoimidazole-4-carboxamide ribonucleotide transformylase (AICAR Tfase), one of the two folate-dependent enzymes in the de novo purine biosynthesis pathway, is a promising target for anti-neoplastic chemotherapy. Although classic antifolates, such as methotrexate, have been developed as anticancer agents, their general toxicity and drug resistance are major issues associated with their clinical use and future development. Identification of inhibitors with novel scaffolds could be an attractive alternative. We present here the crystal structure of avian AICAR Tfase complexed with the first non-folate based inhibitor identified through virtual ligand screening of the National Cancer Institute Diversity Set. The inhibitor 326203-A (2-[5-hydroxy-3-methyl-1-(2-methyl-4-sulfophenyl)-1H-pyrazol-4-ylazo]-4-sulfo-benzoic acid) displayed competitive inhibition against the natural cofactor, 10-formyl-tetrahydrofolate, with a K(i) of 7.1 mum. The crystal structure of AICAR Tfase with 326203-A at 1.8 A resolution revealed a unique binding mode compared with antifolate inhibitors. The inhibitor also accessed an additional binding pocket that is not occupied by antifolates. The sulfonate group of 326203-A appears to form the dominant interaction of the inhibitor with the proposed oxyanion hole through interaction with a helix dipole and Lys(267). An aromatic interaction with Phe(316) also likely contributes to favorable binding. Based on these structural insights, several inhibitors with improved potency were subsequently identified in the National Cancer Institute Compound Library and the Available Chemical Directory by similarity search and molecular modeling methods. These results provide further support for our combined virtual ligand screening rational design approach for the discovery of novel, non-folate-based inhibitors of AICAR Tfase.

Factor X is activated to factor Xa (fXa) in the extrinsic coagulation pathway by the tissue factor (TF)/factor VIIa (fVIIa) complex. Upon activation, the fXa molecule remains associated with the TF/fVIIa complex, and this ternary complex is known to activate protease-activated receptors (PARs) 1 and 2. Activation of fVII in the TF complex by fXa is also seen at physiologic concentrations. The ternary complexes TF/fVII/fXa, TF/fVIIa/fX, and TF/fVIIa/fXa are therefore all physiologically relevant and of interest as targets for inhibition of both coagulation and cell-signaling pathways that are important in cardiovascular disease and inflammation. We therefore present a model of the TF/fVIIa/fXa complex, built with the use of the available structures of the TF/fVIIa complex and fXa by protein-protein docking calculations with the program Surfdock. The fXa model has an extended conformation, similar to that of fVIIa in the TF/fVIIa complex, with extensive interactions with TF and the protease domain of fVIIa. All four domains of fXa are involved in the interaction. The gamma-carboxyglutamate (Gla) and epithelial growth factor (EGF1 and EGF2) domains of fVIIa are not significantly involved in the interaction. Docking of the Gla domain of fXa to TF/fVIIa has been reported previously. The docking results identify potential interface residues, allowing rational selection of target residues for site-directed mutagenesis. This combination of docking and mutagenesis confirms that residues Glu51 and Asn57 in the EGF1 domain, Asp92 and Asp95 in the EGF2 domain, and Asp 185a, Lys 186, and Lys134 in the protease domain of factor Xa are involved in the interaction with TF/fVIIa. Other fX protease domain residues predicted to be involved in the interaction come from the 160s loop and the N-terminus of the fX protease domain, which is oriented in such a way that activation of both fVII by fXa, and the reciprocal fX activation by fVIIa, is possible.

Based on the substrate transition state and our strategy to tackle the problem of drug resistance, a series of HIV/FIV protease (HIV /FIV PR) monocyclic inhibitors incorporating a 15- or 17-membered macrocycle with an equivalent P3 or P3′ group and a unique unnatural amino acid, (2 R , 3 S )-3-amino-2-hydroxy-4-phenylbutyric acid, have been designed and synthesized. In addition, based on the structure of TL3 with small P3/P3′ group, we have synthesized two conformationally restricted bicyclic inhibitors containing the macrocycle, which mimic the P1/P1′-P3/P3′ tripeptide [Phe-Val-Ala] of TL3. We have found that the contribution of the macrocycle in our monocyclic inhibitors is important to the overall activity, but the ring size does not affect the activity to a significant extent. Several inhibitors that were developed in this work, exhibit low nanomolar inhibitory activity against the wild-type HIV/FIV PR and found to be highly effective against some drug-resistant as well as TL3-resistant mutants of HIV PRs. Compound 15 , in particular, is the most effective cyclic inhibitor in hand to inhibit FIV replication in tissue culture at a concentration of 1.0 μg/mL (1.2 μM).

Protein motion and heterogeneity of structural waters are approximated in ligand-docking simulations, using an ensemble of protein structures. Four methods of combining multiple target structures within a single grid-based lookup table of interaction energies are tested. The method is evaluated using complexes of 21 peptidomimetic inhibitors with human immunodeficiency virus type 1 (HIV-1) protease. Several of these structures show motion of an arginine residue, which is essential for binding of large inhibitors. A structural water is also present in 20 of the structures, but it must be absent in the remaining one for proper binding. Mean and minimum methods perform poorly, but two weighted average methods permit consistent and accurate ligand docking, using a single grid representation of the target protein structures.

TL-3 is a protease inhibitor developed using the feline immunodeficiency virus protease as a model. It has been shown to efficiently inhibit replication of human, simian, and feline immunodeficiency viruses and therefore has broad-based activity. We now demonstrate that TL-3 efficiently inhibits the replication of 6 of 12 isolates with confirmed resistance mutations to known protease inhibitors. To dissect the spectrum of molecular changes in protease and viral properties associated with resistance to TL-3, a panel of chronological in vitro escape variants was generated. We have virologically and biochemically characterized mutants with one (V82A), three (M46I/F53L/V82A), or six (L24I/M46I/F53L/L63P/V77I/V82A) changes in the protease and structurally modeled the protease mutant containing six changes. Virus containing six changes was found to be 17-fold more resistant to TL-3 in cell culture than was wild-type virus but maintained similar in vitro replication kinetics compared to the wild-type virus. Analyses of enzyme activity of protease variants with one, three, and six changes indicated that these enzymes, compared to wild-type protease, retained 40, 47, and 61% activity, respectively. These results suggest that deficient protease enzymatic activity is sufficient for function, and the observed protease restoration might imply a selective advantage, at least in vitro, for increased protease activity.

Methods and tools for visualizing biological data have improved considerably over the last decades, but they are still inadequate for some high-throughput data sets. For most users, a key challenge is to benefit from the deluge of data without being overwhelmed by it. This challenge is still largely unfulfilled and will require the development of truly integrated and highly useable tools.

The macrophage migration inhibitory factor (MIF) is a cytokine that is structurally similar to certain isomerases and for which multiple immune and catalytic roles have been proposed. Different catalytic activities have been reported for MIF, yet the exact mechanism by which MIF acts is not completely known. As a tautomerase, the enzyme uses a general acid–base mechanism of proton transfer in which the amino-terminal proline has been shown to function as the catalytic base. We report the results of molecular docking simulations of macrophage migration inhibitory factor with three substrates, D-dopachrome, L-dopachrome methyl ester and p-(hydroxyphenyl)pyruvate. Electrostatic pKa predictions were also performed for the free and complexed forms of the enzyme. The predicted binding mode of p-(hydroxyphenyl)pyruvate is in agreement with the recently published X-ray structure. A model for the binding mode of D-dopachrome and L-dopachrome methyl ester to MIF is proposed which offers insights into the catalytic mechanism of D-dopachrome tautomerase activity of MIF. The proposed catalytic mechanism is further supported by the pKa predictions, which suggest that residue Lys32 acts as the general acid for the enzymatic catalysis of D-dopachrome. Copyright © 2000 John Wiley & Sons, Ltd.

Drug resistance sharply limits the effectiveness of human immunodeficiency virus (HIV) protease inhibitors in acquired immunodeficiency syndrome therapy. In previous work, we presented methods for design of resistance-evading inhibitors using a computational coevolution technique. Here, we report subsite decomposition experiments that examine the relative importance and roles of each subsite in HIV protease, and the constraints on robust inhibitor design that are imposed by possible resistance mutations in each subsite. The results identify several structural features of robust resistance-evading inhibitors for use in drug design, and show their basis in the constraints imposed by the range of allowable mutation in the protease. In particular, the results identify the P3 and P3' sites as being particularly sensitive to protease mutation: inhibitors designed to fill the S3 and S3' sites of the wild-type protease will be susceptible to viral resistance, but inhibitors with side-chains smaller than a phenylalanine residue at P3 and P3', preferably medium-sized amino acids in the range from valine to leucine and isoleucine residues, will be more robust in the face of protease resistance mutation.

In order to understand the structural basis of Factor Xa (FXa) specificity, structural complexes of FXa with its synthetic inhibitors are determined using a computational docking approach. The AutoDock suite of programs is used to determine the binding modes of the synthetic inhibitors such as 3- and 4-amidinobenzylphenyl ether (ABP), amidinophenyl pyruvic acid (APPA), diamidinobenzofuranyl ethene (DABE), and DX-9065a 2-(5′-amidino-2′-benzofuranyl)-3-(7′amidino-2′-napthyl)-propionic acid (ABAP) to FXa. The synthetic inhibitors docked in the present study are different in size, nature of linkage, and properties. Two sets of simulations were carried out for synthetic inhibitors docking to FXa. In the first set of simulations, no explicit water molecules were included. In the second set of simulations two explicit solvent molecules were considered. In all the computationally predicted synthetic inhibitor complexes of FXa, the specificity pocket residue Asp-189 is involved in hydrogen bonding with the bound inhibitor. The active site water molecule WAT522 is involved in hydrogen bonding with all the bound inhibitors. The computed energies clearly discriminate the high affinity from low affinity binders. Proteins 1999;34:173–183. © 1999 Wiley-Liss, Inc.

Background: Most soluble proteins are active as low-number oligomers. Statistical surveys of oligomeric proteins have defined the roles of hydrophobicity and complementarity in the stability of protein interfaces, but tend to average structural features over a diverse set of protein–protein interfaces, blurring information on how individual interfaces are stabilized. Results: We report a visual survey of 136 homodimeric proteins from the Brookhaven Protein Data Bank, with images that highlight the major structural features of each protein–protein interaction surface. Nearly all of these proteins have interfaces formed between two globular subunits. Surprisingly, the pattern of hydrophilicity over the surface of these interfaces is quite variable. Approximately one-third of the interfaces show a recognizable hydrophobic core, with a single large, contiguous, hydrophobic patch surrounded by a ring of intersubunit polar interactions. The remaining two-thirds of the proteins show a varied mixture of small hydrophobic patches, polar interactions and water molecules scattered over the entire interfacial area. Ten proteins in the survey have intertwined interfaces formed by extensive interdigitation of the two subunit chains. These interfaces are very hydrophobic and are associated with proteins that require both stability and internal symmetry. Conclusions: The archetypal protein interface, with a defined hydrophobic core, is present in only a minority of the surveyed homodimeric proteins. Most homodimeric proteins are stabilized by a combination of small hydrophobic patches, polar interactions and a considerable number of bridging water molecules. The presence or absence of a hydrophobic core within these interfaces does not correlate with specific protein functions.

We present two new sets of energy functions for protein structure recognition, given the primary sequence of amino acids along the polypeptide chain. The first set of potentials is based on the positions of alpha- and the second on positions of beta- and alpha-carbon atoms of amino acid residues. The potentials are derived using a theory of Boltzmann-like statistics of protein structure. The energy terms incorporate both long-range interactions between residues remote along a chain and short-range interactions between near neighbors. Distance dependence is approximated by a piecewise constant function defined on intervals of equal size. The size of the interval is optimized to preserve as much detail as possible without introducing excessive error due to limited statistics. A database of 214 non-homologous proteins was used both for the derivation of the potentials, and for the 'threading' test originally suggested by Hendlich et al. (1990) J. Mol. Biol., 216, 167-180. Special care is taken to avoid systematic error in this test. For threading, we used 100 non-homologous protein chains of 60-205 residues. The energy of each of the native structures was compared with the energy of 43,000 to 19,000 alternative structures generated by threading. Of these 100 native structures, 92 have the lowest energy with alpha-carbon-based potentials and, even more, 98 of these 100 structures, have the lowest energy with the beta- and alpha-carbon based potentials.

We present an algorithm to build self-avoiding lattice models of chain molecules with low RMS deviation from their actual 3D structures. To find the optimal coordinates for the lattice chain model, we minimize a function that consists of three terms: (1) the sum of squared deviations of link coordinates on a lattice from their off-lattice values, (2) the sum of "short-range" terms, penalizing violation of chain connectivity, and (3) the sum of "long-range" repulsive terms, penalizing chain self-intersections. We treat this function as a chain molecule "energy" and minimize it using self-consistent field (SCF) theory to represent the pairwise link repulsions as 3D fields acting on the links. The statistical mechanics of chain molecules enables computation of the chain distribution in this field on the lattice. The field is refined by iteration to become self-consistent with the chain distribution, then dynamic programming is used to find the optimal lattice model as the "lowest-energy" chain pathway in this SCF. We have tested the method on one of the coarsest (and most difficult) lattices used for model building on proteins of all structural types and show that the method is adequate for building self-avoiding models of proteins with low RMS deviations from the actual structures.

Lattice models of proteins can approximate off-lattice structure to arbitrary precision with RMS (root mean squared) deviations roughly equal to half the lattice spacing (Rykunov et al., Proteins 22:100-109, 1995; Reva et al., J. Comp. Biol., 1996). However, even small distortions in the positions of chain links lead to significant errors in lattice-based energy calculations (Reva et al., J. Comp. Chem., 1996). These errors arise mainly from rigid interactions (such as steric repulsion) which change their energies considerably at a range which is much smaller than the usual accuracy of lattice modeling (> 1.0 A). To reduce this error, we suggest a procedure of adjusting energy functions to a given lattice. The general approach is illustrated with energy calculations based on pairwise potentials by Kolinski et al. (J. Chem. Phys. 98:1-14, 1993). At all the lattice spacings, from 0.5-3.8 A, the lattice-adjusted potentials improve the accuracy of lattice-based energy calculations and increase the correlations between off-lattice and lattice energies.

AutoDock is a suite of C programs used to predict the bound conformations of a small, flexible ligand to a macromolecular target of known structure. The technique combines simulated annealing for conformation searching with a rapid grid-based method of energy evaluation. This paper reviews recent applications of the technique and describes the enhancements included in the current release.

Since the early days of the discovery of HIV-1 protease (HIV-1 PR), this enzyme has been selected as an important target for the inhibition of viral replication. The enormous effort over the past two decades to develop effective molecules that inhibit the HIV1 PR has resulted in the discovery of drugs that have dramatically improved the quality of life and survival of the patients infected with HIV-1. To date there are six different HIV-1 PR inhibitors (PI) that are commercially available. These drugs are administered in combination with the reverse transcriptase inhibitors in what is called TMhighly active anti-retroviral therapy (HAART)∫. Unfortunately, many drug-resistant and cross-resistant mutant HIV-1 PRs have been identified, thus hampering long term suppression of the virus and resulting in return of AIDS symptoms. Therefore, the development of new protease inhibitors, which are efficacious against both the wild type and drug resistant HIV-1 PR and less prone to development of resistance, is urgently needed. During the last decade, the number and throughput of biological assays of protease activity has notably increased. However, the high rates of HIV-1 PR mutation still outpace conventional drug discovery efforts, mostly because of limitations associated with identification of the lead structures and, to a greater extent, slow structure ± activity profiling. While the former can be improved by rational design and computational studies, rapid synthesis of diverse analogues and their optimization still remains a challenge. We have recently developed a new strategy to facilitate the drug discovery process: diversityoriented organic synthesis in microtiter plates followed by in situ screening without product isolation and protecting group manipulation. This strategy was demonstrated with the use of amide-forming reaction in a rapid identification of new potent HIV protease inhibitors. Click chemistry has emerged as a strategy for the rapid and efficient assembly of molecules with diverse functionality on both laboratory and production scales. Enabled by a few nearly perfect reactions, it guarantees reliable synthesis of the desired products in high yield and purity. Modularity, selectivity, and wide scope make click chemistry ideal for achieving diversity in just a few steps and with no need for further purification. Advantages of click chemistry in biological studies have recently been demonstrated in several applications: construction of fluorescent oligonucleotides for DNA sequencing, in situ assembly of acetylcholinesterase inhibitors, chemically orthogonal high fidelity bioconjugation, and activity-based protein profiling in whole proteomes. In principle, this type of chemistry is well suited for microscale synthesis and for biological screening in situ. To demonstrate its feasibility we have used the copper(I)-catalysed triazole formation for the synthesis of sugar arrays in the above mentioned microtiter plate format, followed by in situ screening of glycosyltransferase inhibitors and enzyme glycosylation. Herein, we report an expedient approach to the discovery of novel HIV-1 PR inhibitors based on the latest advance in the copper(I)-catalyzed 1,2,3-triazole synthesis. 11] This highly reliable process, which proceeds well in aqueous solvents and tolerates virtually all functional groups without the need for protection, made it possible to quickly generate the desired libraries of potential inhibitors and to screen them directly in microtiter plates, without any purification, against HIV-1 PR and its mutants. The efficacy of hydroxyethylamine isosteres as transition-state mimics and as backbone replacements of amide bonds in the P1/P1 position of aspartyl protease inhibitors has been well documented, most notably in incorporation in the structures of three commercially available drugs, amprenavir, nelfinavir, and saquinavir. We, therefore, envisioned a library of compounds which retained this core, while diversifying the P2/P2 residues to generate new inhibitors. Starting from the optically active epoxy amine 1, two different azide cores were prepared as summarized in Scheme 1. Epoxy amine 1 in H2O/EtOH was

Automated docking of substrates to proteins of known structure aids the process of crystallographic analysis in two ways. First, automated docking can be used to generate a small number of starting models for substrates using only protein coordinates from an early stage of refinement. Second, automated docking provides a method for exploring aspects of catalysis that are inaccessible to crystallography by postulating binding modes of catalytic intermediates. This paper describes the use of automated docking to explore the binding of substrates to aconitase. The technique starts with a substrate molecule in an arbitrary configuration and position and finds favorable docked configurations in a (static) protein active site based on a molecular mechanics type force field. Using protein coordinates from an early stage of refinement of an aconitase-isocitrate complex, we successfully predicted the binding configuration of isocitrate. Four configurations were found, the energetically most favorable of which fit the observed electron density well and was used as a starting model for further refinement. Two configurations were found in citrate docking experiments, the second of which approximates the mode of substrate binding in an aconitase-nitrocitrate complex. We were also able to propose two binding modes of the catalytic intermediate cis-aconitate. These correspond closely to the isocitrate and the citrate binding modes. The relation of these new results to the proposed reaction mechanism is discussed.

Why are proteins so big? Why do cells build oligomeric proteins? A visual survey of the protein structures available in the Protein Data Bank sheds new light on these questions.

Biological complexes typically exhibit intermolecular interfaces of high shape complementarity. Many computational docking approaches use this surface complementarity as a guide in the search for predicting the structures of protein-protein complexes. Proteins often undergo conformational changes to create a highly complementary interface when associating. These conformational changes are a major cause of failure for automated docking procedures when predicting binding modes between proteins using their unbound conformations. Low resolution surfaces in which high frequency geometric details are omitted have been used to address this problem. These smoothed, or blurred, surfaces are expected to minimize the differences between free and bound structures, especially those that are due to side chain conformations or small backbone deviations. Despite the fact that this approach has been used in many docking protocols, there has yet to be a systematic study of the effects of such surface smoothing on the shape complementarity of the resulting interfaces. Here we investigate this question by computing shape complementarity of a set of 66 protein-protein complexes represented by multiresolution blurred surfaces. Complexed and unbound structures are available for these protein-protein complexes. They are a subset of complexes from a nonredundant docking benchmark selected for rigidity (i.e. the proteins undergo limited conformational changes between their bound and unbound states). In this work, we construct the surfaces by isocontouring a density map obtained by accumulating the densities of Gaussian functions placed at all atom centers of the molecule. The smoothness or resolution is specified by a Gaussian fall-off coefficient, termed "blobbyness." Shape complementarity is quantified using a histogram of the shortest distances between two proteins' surface mesh vertices for both the crystallographic complexes and the complexes built using the protein structures in their unbound conformation. The histograms calculated for the bound complex structures demonstrate that medium resolution smoothing (blobbyness = -0.9) can reproduce about 88% of the shape complementarity of atomic resolution surfaces. Complexes formed from the free component structures show a partial loss of shape complementarity (more overlaps and gaps) with the atomic resolution surfaces. For surfaces smoothed to low resolution (blobbyness = -0.3), we find more consistency of shape complementarity between the complexed and free cases. To further reduce bad contacts without significantly impacting the good contacts we introduce another blurred surface, in which the Gaussian densities of flexible atoms are reduced. From these results we discuss the use of shape complementarity in protein-protein docking.

The mitogen-activated protein (MAP) kinase protein family has a critical role in cellular signaling events, with MAP kinase p38alpha acting in inflammatory processes and being an important drug discovery target. MAP kinase drug design efforts have focused on small-molecule inhibitors of the ATP catalytic site, which exhibit dose-limiting adverse effects. Therefore, characterizing other potential sites that bind substrates, inhibitors, or allosteric effectors is of great interest. Here, we present the crystal structure of human p38alpha MAP kinase, which has a lead compound bound both in the active site and in the lipid-binding site of the C-terminal cap. This C-terminal cap is formed from an extension to the kinase fold, unique to the MAP kinase and cyclin-dependent kinase families and glycogen synthase kinase 3. Binding of this lead, 4-[3-(4-fluorophenyl)-1H-pyrazol-4-yl]pyridine, to wild-type p38alpha induces movement of the C-terminal cap region, creating a hydrophobic pocket centered around residue Trp197. Computational analysis of this C-terminal domain pocket indicates notable flexibility for potentially binding different-shaped compounds, including lipids, oxidized arachidonic acid species such as leukotrienes, and small-molecule effectors. Furthermore, our structural results defining the open p38alpha C-lobe pocket provide a detailed framework for the design of novel small molecules with affinities comparable to active-site binders: to bind and potentially modulate the shape and activity of p38alpha in predetermined ways. Moreover, these results and analyses of p38alpha suggest strategies for designing specific binding compounds applicable to other MAP kinases, as well as the cyclin-dependent kinase family and glycogen synthase kinase 3beta that also utilize the C-terminal insert in their interactions.

To understand the specificity and efficiency of protein-protein interactions promoting electron transfer, we evaluated the role of electrostatic forces in precollision orientation by the development of two new methods, computer graphics alignment of protein electrostatic fields and a systematic orientational search of intermolecular electrostatic energies for two proteins at present separation distances. We applied these methods to the plastocyanin/cytochrome c interaction, which is faster than random collision, but too slow for study by molecular dynamics techniques. Significant electrostatic potentials were concentrated on one-fourth (969 A2) of the plastocyanin surface, with the greatest negative potential centered on the Tyr-83 hydroxyl within the acidic patch, and on one-eighth (632 A2) of the cytochrome c surface, with the greatest positive potential centered near the exposed heme edge. Coherent electrostatic fields occurred only over these regions, suggesting that local, rather than global, charge complementarity controls productive recognition. The three energetically favored families of pre-collision orientations all directed the positive region surrounding the heme edge of cytochrome c toward the acidic patch of plastocyanin but differed in heme plane orientation. Analysis of electrostatic fields, electrostatic energies of precollision orientations with 12 and 6 A separation distances, and surface topographies suggested that the favored orientations should converge to productive complexes promoting a single electron-transfer pathway from the cytochrome c heme edge to Tyr-83 of plastocyanin. Direct interactions of the exposed Cu ligand in plastocyanin with the cytochrome c heme edge are not unfavorable sterically or electrostatically but should occur no faster than randomly, indicating that this is not the primary pathway for electron transfer.

Automated docking of drug-like molecules into receptors is an essential tool in structure-based drug design. While modeling receptor flexibility is important for correctly predicting ligand binding, it still remains challenging. This work focuses on an approach in which receptor flexibility is modeled by explicitly specifying a set of receptor side-chains a-priori. The challenges of this approach include the: 1) exponential growth of the search space, demanding more efficient search methods; and 2) increased number of false positives, calling for scoring functions tailored for flexible receptor docking. We present AutoDockFR–AutoDock for Flexible Receptors (ADFR), a new docking engine based on the AutoDock4 scoring function, which addresses the aforementioned challenges with a new Genetic Algorithm (GA) and customized scoring function. We validate ADFR using the Astex Diverse Set, demonstrating an increase in efficiency and reliability of its GA over the one implemented in AutoDock4. We demonstrate greatly increased success rates when cross-docking ligands into apo receptors that require side-chain conformational changes for ligand binding. These cross-docking experiments are based on two datasets: 1) SEQ17 –a receptor diversity set containing 17 pairs of apo-holo structures; and 2) CDK2 –a ligand diversity set composed of one CDK2 apo structure and 52 known bound inhibitors. We show that, when cross-docking ligands into the apo conformation of the receptors with up to 14 flexible side-chains, ADFR reports more correctly cross-docked ligands than AutoDock Vina on both datasets with solutions found for 70.6% vs. 35.3% systems on SEQ17, and 76.9% vs. 61.5% on CDK2. ADFR also outperforms AutoDock Vina in number of top ranking solutions on both datasets. Furthermore, we show that correctly docked CDK2 complexes re-create on average 79.8% of all pairwise atomic interactions between the ligand and moving receptor atoms in the holo complexes. Finally, we show that down-weighting the receptor internal energy improves the ranking of correctly docked poses and that runtime for AutoDockFR scales linearly when side-chain flexibility is added., Author Summary Docking programs are widely used to identify drug-like molecules interacting with a given receptor to inhibit its function. Although receptors are known to change conformation upon ligand binding, most docking programs model small molecules as flexible while modeling receptors as rigid, thus limiting the range of therapeutic targets for which docking can be applied. Here we introduce a new docking program, AutoDockFR, which simulates partial receptor flexibility by allowing a large number of explicitly specified receptor side-chains to explore their conformational space, while searching for energetically favorable binding poses for a given ligand. We show that we achieve higher docking success rates by including receptor flexibility in the binding site of receptor conformations that are experimentally determined without the ligand present (i.e. apo conformations). Previous approaches based on the a-priori and explicit specification of the part of the receptor to be considered flexible, have so far been limited to a small number of flexible protein side-chains (2–5), thus requiring prior knowledge of receptor side-chains undergoing conformational change upon binding of a given ligand. The demonstrated ability of AutoDockFR in identifying correct solutions for problems with up to 14 flexible receptor side-chains lessens this requirement.

The immunovariant N -ethyl- N -nitrosourea-induced mutations Pococurante (Poc) and Lackadaisical were found to alter MyD88, creating striking receptor-selective effects. Poc, in particular, prevented sensing of all MyD88-dependent Toll-like receptor (TLR) ligands except diacyl lipopeptides. Furthermore, Poc-site and classical BB loop mutations caused equivalent phenotypes when engrafted into any TLR/IL-1 receptor/resistance (TIR) domain. These observations, complemented by data from docking studies and site-directed mutagenesis, revealed that BB loops and Poc sites interact homotypically across the receptor:adapter signaling interface, whereas the C-terminal α E -helices support adapter:adapter and receptor:receptor oligomerization. We have thus defined the TIR domain surface that mediates association between TLRs and MyD88 and the surface required for MyD88 or TLR oligomerization. Moreover, MyD88 engages individual TLRs differently, suggesting the feasibility of selective pharmacologic TIR domain receptor blockade.

Siah1 is the central component of a multiprotein E3 ubiquitin ligase complex that targets beta-catenin for destruction in response to p53 activation. The E3 complex comprises, in addition to Siah1, Siah-interacting protein (SIP), the adaptor protein Skp1, and the F-box protein Ebi. Here we show that SIP engages Siah1 by means of two elements, both of which are required for mediating beta-catenin destruction in cells. An N-terminal dimerization domain of SIP sits across the saddle-shaped upper surface of Siah1, with two extended legs packing against the sides of Siah1 by means of a consensus PXAXVXP motif that is common to a family of Siah-binding proteins. The C-terminal domain of SIP, which binds to Skp1, protrudes from the lower surface of Siah1, and we propose that this surface provides the scaffold for bringing substrate and the E2 enzyme into apposition in the functional complex.

Given the ubiquitous nature of the peptide linkage in biological molecules, replacement of the amide bond with isosteres in potential drug candidates has been a continual goal of many laboratories. Successful replacements will provide improved stability, lipophilicity, and absorption. Many surrogates have been introduced already, yet the synthesis of many of these isosteres in a combinatorial way is difficult and requires several steps. Thus, the discovery of new peptide surrogates with easier syntheses is an important achievement that could open new opportunities for the study of amide-containing molecules and the development of inhibitors with novel physicochemical properties. We have used the copper(i)-catalyzed azide–alkyne [3+2] cycloaddition as a straightforward reaction for the preparation of inhibitor libraries. Over 100 compounds were synthesized in microtiter plates and screened in situ. Two of these compounds—AB2 (pdb-1zp8) and AB3 (pdb-1zpA)—showed the best activity against wild type and mutant HIV-1 proteases (Table 1). AB2 and AB3, were then computationally docked by using AutoDock3. The docking simulation produced two conformations of approximately equal energy. One conformation placed the triazole in the position normally adopted by the peptide unit—between P2’ and P1’—in peptidomimetic compounds. Furthermore, the central nitrogen of the triazole was perfectly positioned to form a hydrogen bond with the water molecule normally found under the protease flaps. This water molecule also formed a hydrogen bond with the sulfonamide as seen in the crystallographic structure of amprenavir when bound to HIV-1 protease. The other conformation positioned the compounds in a similar place, but with the triazole rotated by 180 8. This allowed for a slightly better fit of the triazole substituent but sacrificed the hydrogen bond with the water molecule. In this work we have solved the ambiguity in binding conformation by solving the crystal structure of two inhibitors derived from a library of triazole compounds with HIV-1 protease. Interestingly, the two structures show that the triazole ring is an effective amide surrogate that retains all hydrogen bonds in the active site (Figure 1). HIV-1 protease (3 mgmL 1 in 0.025m sodium acetate pH 5.4, 10 mm dithiothreitol, 1 mm EDTA) was combined with inhibitor (32 mm in 50% (v/v) dimethylsulfoxide and 2-methylpentane2,4-diol) at 4 8C to give a 2:1 molar ratio of inhibitor to protein, and the mixture was centrifuged to remove the precipitate. The complex was crystallized by the hanging-drop vapor-diffusion method by mixing 9.6 mL of protease solution with 4 mL of crystallization buffer (1.34m ammonium sulfate, 0.1m sodium acetate, pH 4.8–5.4). Plates were sealed at 20 8C for one to two weeks. Data were collected from frozen crystals at the Argonne National Laboratory SER-CAT beamline 22-ID and with a Rigaku Table 1. Binding constants of 1,2,3-triazole compounds to HIV-1 protease.