Structure of a non-peptide inhibitor complexed with HIV-1 protease. Developing a cycle of structure-based drug design

Discovery of a Hidden Trypanosoma cruzi Spermidine Synthase Binding Site and Inhibitors through In Silico, In Vitro, and X-ray Crystallography

In drug discovery research, the selection of promising binding sites and understanding the binding mode of compounds are crucial fundamental studies. The current understanding of the proteins-ligand binding model extends beyond the simple lock and key model to include the induced-fit model, which alters the conformation to match the shape of the ligand, and the pre-existing equilibrium model, selectively binding structures with high binding affinity from a diverse ensemble of proteins. Although methods for detecting target protein binding sites and virtual screening techniques using docking simulation are well-established, with numerous studies reported, they only consider a very limited number of structures in the diverse ensemble of proteins, as these methods are applied to a single structure. Molecular dynamics (MD) simulation is a method for predicting protein dynamics and can detect potential ensembles of protein binding sites and hidden sites unobservable in a single-point structure. In this study, to demonstrate the utility of virtual screening with protein dynamics, MD simulations were performed on Trypanosoma cruzi spermidine synthase to obtain an ensemble of dominant binding sites with a high probability of existence. The structure of the binding site obtained through MD simulation revealed pockets in addition to the active site that was present in the initial structure. Using the obtained binding site structures, virtual screening of 4.8 million compounds by docking simulation, in vitro assays, and X-ray analysis was conducted, successfully identifying two hit compounds.

The Effect of Treatment-Associated Mutations on HIV Replication and Transmission Cycles

HIV/AIDS mortality has been decreasing over the last decade. While promising, this decrease correlated directly with increased use of antiretroviral drugs. As a natural consequence of its high mutation rate, treatments provide selection pressure that promotes the natural selection of escape mutants. Individuals may acquire drug-naive strains, or those that have already mutated due to treatment. Even within a host, mutation affects HIV tropism, where initial infection begins with R5-tropic virus, but the clinical transition to AIDS correlates with mutations that lead to an X4-tropic switch. Furthermore, the high mutation rate of HIV has spelled failure for all attempts at an effective vaccine. Pre-exposure drugs are currently the most effective drug-based preventatives, but their effectiveness is also threatened by viral mutation. From attachment and entry to assembly and release, the steps in the replication cycle are also discussed to describe the drug mechanisms and mutations that arise due to those drugs. Revealing the patterns of HIV-1 mutations, their effects, and the coordinated attempt to understand and control them will lead to effective use of current preventative measures and treatment options, as well as the development of new ones.

Docking with AutoDock4

AutoDock is one of the most popular receptor-ligand docking simulation programs. It was first released in the early 1990s and is in continuous development and adapted to specific protein targets. AutoDock has been applied to a wide range of biological systems. It has been used not only for protein-ligand docking simulation but also for the prediction of binding affinity with good correlation with experimental binding affinity for several protein systems. The latest version makes use of a semi-empirical force field to evaluate protein-ligand binding affinity and for selecting the lowest energy pose in docking simulation. AutoDock4.2.6 has an arsenal of four search algorithms to carry out docking simulation including simulated annealing, genetic algorithm, and Lamarckian algorithm. In this chapter, we describe a tutorial about how to perform docking with AutoDock4. We focus our simulations on the protein target cyclin-dependent kinase 2.

Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few closely related systems has guided our understanding of the mechanisms by which changes such as ligand binding or mutation can alter the function. The general problem of detecting and interpreting such mechanisms from simulations of many related systems, however, remains a challenge. This problem is addressed here by applying supervised and unsupervised machine learning techniques to a variety of thermodynamic observables extracted from molecular dynamics simulations of different systems. As an important test case, these methods are applied to understand the evasion by human immunodeficiency virus type-1 (HIV-1) protease of darunavir, a potent inhibitor to which resistance can develop via the simultaneous mutation of multiple amino acids. Complex mutational patterns have been observed among resistant strains, presenting a challenge to developing a mechanistic picture of resistance in the protease. In order to dissect these patterns and gain mechanistic insight into the role of specific mutations, molecular dynamics simulations were carried out on a collection of HIV-1 protease variants, chosen to include highly resistant strains and susceptible controls, in complex with darunavir. Using a machine learning approach that takes advantage of the hierarchical nature in the relationships among the sequence, structure, and function, an integrative analysis of these trajectories reveals key details of the resistance mechanism, including changes in the protein structure, hydrogen bonding, and protein-ligand contacts.

SAnDReS: A Computational Tool for Docking

Since the early 1980s, we have witnessed considerable progress in the development and application of docking programs to assess protein-ligand interactions. Most of these applications had as a goal the identification of potential new binders to protein targets. Another remarkable progress is taking place in the determination of the structures of protein-ligand complexes, mostly using X-ray diffraction crystallography. Considering these developments, we have a favorable scenario for the creation of a computational tool that integrates into one workflow all steps involved in molecular docking simulations. We had these goals in mind when we developed the program SAnDReS. This program allows the integration of all computational features related to modern docking studies into one workflow. SAnDReS not only carries out docking simulations but also evaluates several docking protocols allowing the selection of the best approach for a given protein system. SAnDReS is a free and open-source (GNU General Public License) computational environment for running docking simulations. Here, we describe the combination of SAnDReS and AutoDock4 for protein-ligand docking simulations. AutoDock4 is a free program that has been applied to over a thousand receptor-ligand docking simulations. The dataset described in this chapter is available for downloading at https://github.com/azevedolab/sandres.

The X-ray Crystal Structure of the Sulfonated Azo Dye Congo Red, a Non-Peptidic Inhibitor of HIV-1 Protease which also Binds to Reverse Transcriptase and Amyloid Proteins

Congo Red is a sulfonated azo dye and widely used biological stain that has recently been the focus of intense interest because it has been shown to bind to proteins involved in viral recognition and replication. Congo Red also finds wide use as a histological stain for amyloid proteins of the type found in neurodegenerative conditions such as Alzheimer's disease, transmissible spongiform encephalopathies in cattle and mink, and scrapie in sheep. Congo Red has been demonstrated to protect normal prion protein from being converted to the protease-resistant form, an important step in the pathology of the so-called ‘slow viral’ diseases. The range of biological molecules to which Congo Red binds makes it an important lead compound in drug development, for example in the development of new anti-HIV and anti-Alzheimer's therapeutic agents. In this report we present the first high-resolution structure of Congo Red: the low-temperature (173 K) X-ray crystal structure determination of its calcium salt. Two conformations of the molecule are found in the same crystal structure, one in which the central biphenyl group assumes a twisted (25°) conformation, and one in which the biphenyl group is planar and is located on a crystallo-graphic inversion centre. In both conformations the sulfonate groups are oriented anti with respect to the long molecular axis and assume eclipsed conformations with respect to the naphthalene rings. A comparison is made with a published structure [Turned, W.G., and Finch, J.T. (1992) J Mol Biol 227: 1205-1223] in which Congo Red is bound to porcine insulin, this complex serving as a model for amyloid binding. The results illustrate the conformational flexibility possessed by the biphenyl spacer, which allows the hydrophobic portion of the molecule to assume an optimum fit in the hydrophobic binding pockets of target proteins. A model is presented for the binding of Congo Red to the HIV protease in which the sulfonate groups interact with the side-chains of arginine residues. This proposed binding mode is consistent with the observed binding for other sulfonated aromatic inhibitors such as Evans Blue.

The first catalytic asymmetric thioacetalization by chiral phosphoric acid catalysis

We report here the first catalytic asymmetric thioacetalization of salicylaldehyde and dithiol. Chiral phosphoric acid STRIP C5 is identified as a powerful catalyst for this reaction to afford various chiral dithioacetals in high to excellent yields and enantioselectivities under mild conditions.

HIV-1 Protease Dimerization Dynamics Reveals a Transient Druggable Binding Pocket at the Interface

The binding mechanism of HIV-1 protease monomers leading to the catalytically competent dimeric enzyme has been investigated by means of state-of-the-art atomistic simulations. The emerging picture allows a deeper understanding of experimental observations and reveals that water molecules trapped at the interface have an important role in slowing down the kinetics of the association process. Unexpectedly, a cryptic binding pocket is identified at the interface of the complex, corresponding to a partially bound dimer that lacks enzymatic function. The pocket has a transient nature with a lifetime longer than 1 μs, and it displays very favorable druggability features. Docking as well as MM-GBSA free-energy calculations further support the possibility to target the new binding site by means of inhibitors able to prevent the complete dimerization by capturing the inactive conformation. This discovery could open the way to the rational design of a new class of anti-HIV drugs.

Diffusion accessibility as a method for visualizing macromolecular surface geometry

Important three-dimensional spatial features such as depth and surface concavity can be difficult to convey clearly in the context of two-dimensional images. In the area of macromolecular visualization, the computer graphics technique of ray-tracing can be helpful, but further techniques for emphasizing surface concavity can give clearer perceptions of depth. The notion of diffusion accessibility is well-suited for emphasizing such features of macromolecular surfaces, but a method for calculating diffusion accessibility has not been made widely available. Here we make available a web-based platform that performs the necessary calculation by solving the Laplace equation for steady state diffusion, and produces scripts for visualization that emphasize surface depth by coloring according to diffusion accessibility. The URL is http://services.mbi.ucla.edu/DiffAcc/.

Catalytic asymmetric sulfenylation to structurally diverse dithioketals

We report the first example of highly enantioselective synthesis of structurally diverse chiral dithioketals via asymmetric sulfenylation of various types of S-based nucleophiles, catalyzed by a cheap cinchona alkaloid derivative, dihydroquinine.

Beware of machine learning-based scoring functions-on the danger of developing black boxes

Training machine learning algorithms with protein-ligand descriptors has recently gained considerable attention to predict binding constants from atomic coordinates. Starting from a series of recent reports stating the advantages of this approach over empirical scoring functions, we could indeed reproduce the claimed superiority of Random Forest and Support Vector Machine-based scoring functions to predict experimental binding constants from protein-ligand X-ray structures of the PDBBind dataset. Strikingly, these scoring functions, trained on simple protein-ligand element-element distance counts, were almost unable to enrich virtual screening hit lists in true actives upon docking experiments of 10 reference DUD-E datasets; this is a a feature that, however, has been verified for an a priori less-accurate empirical scoring function (Surflex-Dock). By systematically varying ligand poses from true X-ray coordinates, we show that the Surflex-Dock scoring function is logically sensitive to the quality of docking poses. Conversely, our machine-learning based scoring functions are totally insensitive to docking poses (up to 10 Å root-mean square deviations) and just describe atomic element counts. This report does not disqualify using machine learning algorithms to design scoring functions. Protein-ligand element-element distance counts should however be used with extreme caution and only applied in a meaningful way. To avoid developing novel but meaningless scoring functions, we propose that two additional benchmarking tests must be systematically done when developing novel scoring functions: (i) sensitivity to docking pose accuracy, and (ii) ability to enrich hit lists in true actives upon structure-based (docking, receptor-ligand pharmacophore) virtual screening of reference datasets.

Structure-Based Approaches to Target Fishing and Ligand Profiling

Chemogenomics is an emerging interdisciplinary field aiming at identifying all possible ligands of all possible targets. If one groups targets in columns and ligands in rows, chemogenomic approaches to drug discovery just fill the interaction matrix. Since experimental data do not suffice, several computational methods are currently actively developed to supplement time-consuming and costly experiments. They are either designed to fill rows and thus profile a ligand towards a heterogeneous set of targets (target profiling) or to fill columns and thus identify novel ligands for an existing target (standard virtual screening). At the interface of both strategies are now true chemogenomic computational methods filling well defined areas in the matrix. The present review will focus on (protein) structure-based approaches and illustrates major advances in this novel exciting field which is supposed to massively impact rational drug design in the next decade.

Design, synthesis, protein-ligand X-ray structure, and biological evaluation of a series of novel macrocyclic human immunodeficiency virus-1 protease inhibitors to combat drug resistance

The structure-based design, synthesis, and biological evaluation of a series of nonpeptidic macrocyclic HIV protease inhibitors are described. The inhibitors are designed to effectively fill in the hydrophobic pocket in the S1'-S2' subsites and retain all major hydrogen bonding interactions with the protein backbone similar to darunavir (1) or inhibitor 2. The ring size, the effect of methyl substitution, and unsaturation within the macrocyclic ring structure were assessed. In general, cyclic inhibitors were significantly more potent than their acyclic homologues, saturated rings were less active than their unsaturated analogues and a preference for 10- and 13-membered macrocylic rings was revealed. The addition of methyl substituents resulted in a reduction of potency. Both inhibitors 14b and 14c exhibited marked enzyme inhibitory and antiviral activity, and they exerted potent activity against multidrug-resistant HIV-1 variants. Protein-ligand X-ray structures of inhibitors 2 and 14c provided critical molecular insights into the ligand-binding site interactions.

Perspectives on NMR in drug discovery: a technique comes of age

In the past decade, the potential of harnessing the ability of nuclear magnetic resonance (NMR) spectroscopy to monitor intermolecular interactions as a tool for drug discovery has been increasingly appreciated in academia and industry. In this Perspective, we highlight some of the major applications of NMR in drug discovery, focusing on hit and lead generation, and provide a critical analysis of its current and potential utility.

In silico screening of HIV-1 non-nucleoside reverse transcriptase and protease inhibitors

Two targets, reverse transcriptase (RT) and protease from HIV-1, were used during the past two decades to the discovery of non-nucleoside reverse transcriptase inhibitors (NNRTI) and protease inhibitors (PI) that belong to the arsenal of the antiretroviral therapy. Herein these enzymes were chosen as templates for conducting a computer-aided ligand design. Ligand and structure-based drug designs were the starting points to select compounds from a database bearing more than five million compounds by means of cheminformatic tools. New promising lead structures are retrieved from the database, which are open to acquisition and test. Classes of molecules already described as NNRTI or PI in the literature also came out and were useful to prove the reliability of the workflow, and thus validating the work carried out so far.

Virtual ligand screening: strategies, perspectives and limitations

In contrast to high-throughput screening, in virtual ligand screening (VS), compounds are selected using computer programs to predict their binding to a target receptor. A key prerequisite is knowledge about the spatial and energetic criteria responsible for protein–ligand binding. The concepts and prerequisites to perform VS are summarized here, and explanations are sought for the enduring limitations of the technology. Target selection, analysis and preparation are discussed, as well as considerations about the compilation of candidate ligand libraries. The tools and strategies of a VS campaign, and the accuracy of scoring and ranking of the results, are also considered.

Molecular model and ATPase activity of carboxyl-terminal nucleotide binding domain from human P-glycoprotein

ATP binding and hydrolysis are required for P-glycoprotein mediated multidrug resistance. To investigate the molecular mechanism involved in ATP binding and hydrolysis, a three-dimensional model of the carboxyl-terminal nucleotide binding domain (NBD2) was built by homology modeling. Modeling revealed the human P-glycoprotein ATP-binding site and the possible role of conserved Gln1118 residue. Recombinant NBD2 was overexpressed in Escherichia coli and the conserved Gln1118 residue was mutated to an alanine residue. The Vmax for ATP hydrolysis by the mutant NBD2 was approximately 56% of the Vmax of wild-type NBD2. But both proteins displayed similar affinity for ATP, with Km of 479 and 466 microM for mutant and wild-type NBD2, respectively. These results suggest that the possible role of Gln1118 is as an activating residue for ATP hydrolysis. The molecular model also provided structural information about the interactions between NBD2 and the chemosensitizer quercetin. The complex indicated that quercetin was tightly bound to the ATP-binding site and competed for binding. The three-dimensional model of NBD2 can be used to both guide enzymological studies and provide a theoretical basis for the design of potential multidrug resistance reversers.

Interaction of C60-Fullerene and Carboxyfullerene with Proteins: Docking and Binding Site Alignment

The unique properties of fullerenes have raised the interest of using them for biomedical applications. Within this framework, the interactions of fullerenes with proteins have been an exciting research target, yet little is known about how native proteins can bind fullerenes, and what is the nature of these interactions. Moreover, though some proteins have been shown to interact with fullerenes, up to date, no crystal structure of such complexes was obtained. Here we report docking studies aimed at examining the interactions of fullerene in two forms (C60 nonsubstituted fullerene and carboxyfullerene) with four proteins that are known to bind fullerene derivatives: HIV protease, fullerene-specific antibody, human serum albumin, and bovine serum albumin. Our work provides docking models with detailed binding pockets information, which closely match available experimental data. We further compare the predicted binding sites using a novel multiple binding site alignment method. A high similarity between the physicochemical properties and surface geometry was found for fullerene's binding sites of HIV protease and the human and bovine serum albumins.

X-ray Structure of Plasmepsin II Complexed with a Potent Achiral Inhibitor

The malaria parasite Plasmodium falciparum degrades host cell hemoglobin inside an acidic food vacuole during the blood stage of the infectious cycle. A number of aspartic proteinases called plasmepsins (PMs) have been identified to play important roles in this degradation process and therefore generated significant interest as new antimalarial targets. Several x-ray structures of PMII have been described previously, but thus far, structure-guided drug design has been hampered by the fact that only inhibitors comprising a statine moiety or derivatives thereof have been published. Our drug discovery efforts to find innovative, cheap, and easily synthesized inhibitors against aspartic proteinases yielded some highly potent non-peptidic achiral inhibitors. A highly resolved (1.6 A) x-ray structure of PMII is presented, featuring a potent achiral inhibitor in an unprecedented orientation, contacting the catalytic aspartates indirectly via the "catalytic" water. Major side chain rearrangements in the active site occur, which open up a new pocket and allow a new binding mode of the inhibitor. Moreover, a second inhibitor molecule could be located unambiguously in the active site of PMII. These newly obtained structural insights will further guide our attempts to improve compound properties eventually leading to the identification of molecules suitable as antimalarial drugs.

Evaluation of library ranking efficacy in virtual screening

We present the results of a comprehensive study in which we explored how the docking procedure affects the performance of a virtual screening approach. We used four docking engines and applied 10 scoring functions to the top-ranked docking solutions of seeded databases against six target proteins. The scores of the experimental poses were placed within the total set to assess whether the scoring function required an accurate pose to provide the appropriate rank for the seeded compounds. This method allows a direct comparison of library ranking efficacy. Our results indicate that the LigandFit/Ligscore1 and LigandFit/GOLD docking/scoring combinations, and to a lesser degree FlexX/FlexX, Glide/Ligscore1, DOCK/PMF (Tripos implementation), LigandFit1/Ligscore2 and LigandFit/PMF (Tripos implementation) were able to retrieve the highest number of actives at a 10% fraction of the database when all targets were looked upon collectively. We also show that the scoring functions rank the observed binding modes higher than the inaccurate poses provided that the experimental poses are available. This finding stresses the discriminatory ability of the scoring algorithms, when better poses are available, and suggests that the number of false positives can be lowered with conformers closer to bioactive ones.

Enzymatic Characterization and Homology Model of a Catalytically Active Recombinant West Nile Virus NS3 Protease

West Nile Virus (WNV) is a mosquito-borne flavivirus with a rapidly expanding global distribution. Infection causes severe neurological disease and fatalities in both human and animal hosts. The West Nile viral protease (NS2B-NS3) is essential for post-translational processing in host-infected cells of a viral polypeptide precursor into structural and functional viral proteins, and its inhibition could represent a potential treatment for viral infections. This article describes the design, expression, and enzymatic characterization of a catalytically active recombinant WNV protease, consisting of a 40-residue component of cofactor NS2B tethered via a noncleavable nonapeptide (G4SG4) to the N-terminal 184 residues of NS3. A chromogenic assay using synthetic para-nitroanilide (pNA) hexapeptide substrates was used to identify optimal enzyme-processing conditions (pH 9.5, I <0.1 m, 30% glycerol, 1 mm CHAPS), preferred substrate cleavage sites, and the first competitive inhibitor (Ac-FASGKR-H, IC50 approximately 1 microm). A putative three-dimensional structure of WNV protease, created through homology modeling based on the crystal structures of Dengue-2 and Hepatitis C NS3 viral proteases, provides some valuable insights for structure-based design of potent and selective inhibitors of WNV protease.

Crystal structures of a multidrug-resistant human immunodeficiency virus type 1 protease reveal an expanded active-site cavity

The goal of this study was to use X-ray crystallography to investigate the structural basis of resistance to human immunodeficiency virus type 1 (HIV-1) protease inhibitors. We overexpressed, purified, and crystallized a multidrug-resistant (MDR) HIV-1 protease enzyme derived from a patient failing on several protease inhibitor-containing regimens. This HIV-1 variant contained codon mutations at positions 10, 36, 46, 54, 63, 71, 82, 84, and 90 that confer drug resistance to protease inhibitors. The 1.8-angstrom (A) crystal structure of this MDR patient isolate reveals an expanded active-site cavity. The active-site expansion includes position 82 and 84 mutations due to the alterations in the amino acid side chains from longer to shorter (e.g., V82A and I84V). The MDR isolate 769 protease "flaps" stay open wider, and the difference in the flap tip distances in the MDR 769 variant is 12 A. The MDR 769 protease crystal complexes with lopinavir and DMP450 reveal completely different binding modes. The network of interactions between the ligands and the MDR 769 protease is completely different from that seen with the wild-type protease-ligand complexes. The water molecule-forming hydrogen bonds bridging between the two flaps and either the substrate or the peptide-based inhibitor are lacking in the MDR 769 clinical isolate. The S1, S1', S3, and S3' pockets show expansion and conformational change. Surface plasmon resonance measurements with the MDR 769 protease indicate higher k(off) rates, resulting in a change of binding affinity. Surface plasmon resonance measurements provide k(on) and k(off) data (K(d) = k(off)/k(on)) to measure binding of the multidrug-resistant protease to various ligands. This MDR 769 protease represents a new antiviral target, presenting the possibility of designing novel inhibitors with activity against the open and expanded protease forms.

Understanding protein flexibility through dimensionality reduction

This work shows how to decrease the complexity of modeling flexibility in proteins by reducing the number of dimensions necessary to model important macromolecular motions such as the induced-fit process. Induced fit occurs during the binding of a protein to other proteins, nucleic acids, or small molecules (ligands) and is a critical part of protein function. It is now widely accepted that conformational changes of proteins can affect their ability to bind other molecules and that any progress in modeling protein motion and flexibility will contribute to the understanding of key biological functions. However, modeling protein flexibility has proven a very difficult task. Experimental laboratory methods, such as x-ray crystallography, produce rather limited information, while computational methods such as molecular dynamics are too slow for routine use with large systems. In this work, we show how to use the principal component analysis method, a dimensionality reduction technique, to transform the original high-dimensional representation of protein motion into a lower dimensional representation that captures the dominant modes of motions of proteins. For a medium-sized protein, this corresponds to reducing a problem with a few thousand degrees of freedom to one with less than fifty. Although there is inevitably some loss in accuracy, we show that we can obtain conformations that have been observed in laboratory experiments, starting from different initial conformations and working in a drastically reduced search space.

A quantum chemical method for rapid optimization of protein structures

A quantum chemical method for rapid optimization of protein structures is proposed. In this method, a protein structure is treated as an assembly of amino acid units, and the geometry optimization of each unit is performed with taking the effect of its surrounding environment into account. The optimized geometry of a whole protein is obtained by repeated application of such a local optimization procedure over the entire part of the protein. Here, we implemented this method in the MOPAC program and performed geometry optimization for three different sizes of proteins. Consequently, these results demonstrate that the total energies of the proteins are much efficiently minimized compared with the use of conventional optimization methods, including the MOZYME algorithm (a representative linear-scaling method) with the BFGS routine. The proposed method is superior to the conventional methods in both CPU time and memory requirements.

Functional sites in protein families uncovered via an objective and automated graph theoretic approach

We report a method for detection of recurring side-chain patterns (DRESPAT) using an unbiased and automated graph theoretic approach. We first list all structural patterns as sub-graphs where the protein is represented as a graph. The patterns from proteins are compared pair-wise to detect patterns common to a protein pair based on content and geometry criteria. The recurring pattern is then detected using an automated search algorithm from the all-against-all pair-wise comparison data of proteins. Intra-protein pattern comparison data are used to enable detection of patterns recurring within a protein. A method has been proposed for empirical calculation of statistical significance of recurring pattern. The method was tested on 17 protein sets of varying size, composed of non-redundant representatives from SCOP superfamilies. Recurring patterns in serine proteases, cysteine proteases, lipases, cupredoxin, ferredoxin, ferritin, cytochrome c, aspartoyl proteases, peroxidases, phospholipase A2, endonuclease, SH3 domain, EF-hand and lectins show additional residues conserved in the vicinity of the known functional sites. On the basis of the recurring patterns in ferritin, EF-hand and lectins, we could separate proteins or domains that are structurally similar yet different in metal ion-binding characteristics. In addition, novel recurring patterns were observed in glutathione-S-transferase, phospholipase A2 and ferredoxin with potential structural/functional roles. The results are discussed in relation to the known functional sites in each family. Between 2000 and 50,000 patterns were enumerated from each protein with between ten and 500 patterns detected as common to an evolutionarily related protein pair. Our results show that unbiased extraction of functional site pattern is not feasible from an evolutionarily related protein pair but is feasible from protein sets comprising five or more proteins. The DRESPAT method does not require a user-defined pattern, size or location of the pattern and therefore, has the potential to uncover new functional sites in protein families.

Virtual screening to enrich hit lists from high-throughput screening: a case study on small-molecule inhibitors of angiogenin

"Hit lists" generated by high-throughput screening (HTS) typically contain a large percentage of false positives, making follow-up assays necessary to distinguish active from inactive substances. Here we present a method for improving the accuracy of HTS hit lists by computationally based virtual screening (VS) of the corresponding chemical libraries and selecting hits by HTS/VS consensus. This approach was applied in a case study on the target-enzyme angiogenin, a potent inducer of angiogenesis. In conjunction with HTS of the National Cancer Institute Diversity Set and ChemBridge DIVERSet E (approximately 18,000 compounds total), VS was performed with two flexible library docking/scoring methods, DockVision/Ludi and GOLD. Analysis of the results reveals that dramatic enrichment of the HTS hit rate can be achieved by selecting compounds in consensus with one or both of the VS functions. For example, HTS hits ranked in the top 2% by GOLD included 42% of the true hits, but only 8% of the false positives; this represents a sixfold enrichment over the HTS hit rate. Notably, the HTS/VS method was effective in selecting out inhibitors with midmicromolar dissociation constants typical of leads commonly obtained in primary screens.

Rational design and evaluation of new lead compound structures for selective betaARK1 inhibitors

Beta-adrenergic receptor kinase 1 (betaARK1) and cyclic adenosine 5'-monophosphate-dependent protein kinase A (PKA) have structurally similar adenine-binding pockets but have different physiologic functions. To obtain specific betaARK1 inhibitors, a two step rational drug design process was used. First, a search was conducted on three-dimensional models of commercially available compounds to find compounds that fit the adenine-binding pocket of betaARK1. Second, a comparative docking study that focused on the differences between the adenine-binding pockets of the two enzymes was used to evaluate the binding specificity of each compound that inhibited betaARK1 activity. The results of these analyses yielded three betaARK1-selective inhibitor leads from 11 candidates, a hit rate for selectivity of 27%. Although the IC50 values of these compounds for betaARK1 ranged from only 1.3 x 10(-4) M to 5.6 x 10(-4) M, the compounds did not inhibit PKA at concentrations up to 1.0 x 10(-3) M. Thus, the present study shows the usefulness of a rational drug design strategy in finding specific kinase inhibitors for proteins with similar drug target binding sites.

Computation of the physio-chemical properties and data mining of large molecular collections

Very large data sets of molecules screened against a broad range of targets have become available due to the advent of combinatorial chemistry. This information has led to the realization that ADME (absorption, distribution, metabolism, and excretion) and toxicity issues are important to consider prior to library synthesis. Furthermore, these large data sets provide a unique and important source of information regarding what types of molecular shapes may interact with specific receptor or target classes. Thus, the requirement for rapid and accurate data mining tools became paramount. To address these issues Pharmacopeia, Inc. formed a computational research group, The Center for Informatics and Drug Discovery (CIDD).* In this review we cover the work done by this group to address both in silico ADME modeling and data mining issues faced by Pharmacopeia because of the availability of a large and diverse collection (over 6 million discrete compounds) of drug-like molecules. In particular, in the data mining arena we discuss rapid docking tools and how we employ them, and we describe a novel data mining tool based on a ID representation of a molecule followed by a molecular sequence alignment step. For the ADME area we discuss the development and application of absorption, blood-brain barrier (BBB) and solubility models. Finally, we summarize the impact the tools and approaches might have on the drug discovery process.

Anti-HIV activity of medicinal herbs: usage and potential development

The acquired immunodeficiency syndrome (AIDS) is a result of human immunodeficiency virus (HIV) infection which subsequently leads to significant suppression of immune functions. AIDS is a significant threat to the health of mankind, and the search for effective therapies to treat AIDS is of paramount importance. Several chemical anti-HIV agents have been developed. However, besides the high cost, there are adverse effects and limitations associated with using chemotherapy for the treatment of HIV infection. Thus, herbal medicines have frequently been used as an alternative medical therapy by HIV positive individuals and AIDS patients. The aim of this review is to summarize research findings for herbal medicines, which are endowed with the ability to inhibit HIV. In this article, we will emphasize a Chinese herbal medicine, Scutellaria baicalensis Georgi and its identified components (i.e., baicalein and baicalin), which have been shown to inhibit infectivity and replication of HIV. Potential development of anti-AIDS compounds using molecular modeling methods will also be discussed.

Rapid genetic selection of inhibitor-resistant protease mutants: clinically relevant and novel mutants of the HIV protease

Site-specific proteolysis is an important regulatory mechanism in many basic cellular processes as well as playing critical roles in the life cycle of viruses and other pathogenic organisms. For the human immunodeficiency virus (HIV) the encoded protease is required for the replication of the virus and has been the target of novel antiviral therapeutics. However, the emergence of inhibitor-resistant viral strains has become an increasingly significant clinical problem. Using a bacteriophage-based genetic selection, a bank of inhibitor-resistant mutants in this protease has been isolated that includes mutations that correlate with resistant clinical isolates. The rapid selection of such mutations has implications for the prediction of relevant mutations and may be applicable to other viral systems.

Polyoxometalate HIV-1 protease inhibitors. A new mode of protease inhibition

Nb-containing polyoxometalates (POMs) of the Wells-Dawson class inhibit HIV-1 protease (HIV-1P) by a new mode based on kinetics, binding, and molecular modeling studies. Reaction of alpha(1)-K(9)Li[P(2)W(17)O(61)] or alpha(2)-K(10)[P(2)W(17)O(61)] with aqueous H(2)O(2) solutions of K(7)H[Nb(6)O(19)] followed by treatment with HCl and KCl and then crystallization affords the complexes alpha(1)-K(7)[P(2)W(17)(NbO(2))O(61)] (alpha(1)()1) and alpha(2)-K(7)[P(2)W(17)(NbO(2))O(61)] (alpha(2)()1) in 63 and 86% isolated yields, respectively. Thermolysis of the crude peroxoniobium compounds (72-96 h in refluxing H(2)O) prior to treatment with KCl converts the peroxoniobium compounds to the corresponding polyoxometalates (POMs), alpha(1)-K(7)[P(2)W(17)NbO(62)] (alpha(1)()2) and alpha(2)-K(7)[P(2)W(17)NbO(62)] (alpha(2)()2), in moderate yields (66 and 52%, respectively). The identity and high purity of all four compounds were confirmed by (31)P NMR and (183)W NMR. The acid-induced dimerization of the oxo complexes differentiates sterically between the cap (alpha(2)) site and the belt (alpha(1)) site in the Wells-Dawson structure (alpha(2)()2 dimerizes in high yield; alpha(1)()2 does not). All four POMs exhibit high activity in cell culture against HIV-1 (EC(50) values of 0.17-0.83 microM), are minimally toxic (IC(50) values of 50 to >100 microM), and selectively inhibit purified HIV-1 protease (HIV-1P) (IC(50) values for alpha(1)()1, alpha(2)()1, alpha(1)()2, and alpha(2)()2 of 2.0, 1.2, 1.5, and 1.8 microM, respectively). Thus, theoretical, binding, and kinetics studies of the POM/HIV-1P interaction(s) were conducted. Parameters for [P(2)W(17)NbO(62)](7)(-) were determined for the Kollman all-atom (KAA) force field in Sybyl 6.2. Charges for the POM were obtained from natural population analysis (NPA) at the HF/LANL2DZ level of theory. AutoDock 2.2 was used to explore possible binding locations for the POM with HIV-1P. These computational studies strongly suggest that the POMs function not by binding to the active site of HIV-1P, the mode of inhibition of all other HIV-1P protease inhibitors, but by binding to a cationic pocket on the "hinge" region of the flaps covering the active site (2 POMs and cationic pockets per active homodimer of HIV-1P). The kinetics and binding studies, conducted after the molecular modeling, are both in remarkable agreement with the modeling results: 2 POMs bind per HIV-1P homodimer with high affinities (K(i) = 1.1 +/- 0.5 and 4.1 +/- 1.8 nM in 0.1 and 1.0 M NaCl, respectively) and inhibition is noncompetitive (k(cat) but not K(m) is affected by the POM concentration).

Interactions of a novel inhibitor from an extremophilic Bacillus sp. with HIV-1 protease: implications for the mechanism of inactivation

The active site cleft of the HIV-1 protease (PR) is bound by two identical conformationally mobile loops known as flaps, which are important for substrate binding and catalysis. The present article reports, for the first time, an HIV-1 PR inhibitor, ATBI, from an extremophilic Bacillus sp. The inhibitor is found to be a hydrophilic peptide with Mr of 1147, and an amino acid sequence of Ala-Gly-Lys-Lys-Asp-Asp-Asp-Asp-Pro-Pro-Glu. Sequence homology exhibited no similarity with the reported peptidic inhibitors of HIV-1 PR. Investigation of the kinetics of the enzyme-inhibitor interactions revealed that ATBI is a noncompetitive and tight binding inhibitor with the IC(50) and K(i) values 18.0 and 17.8 nm, respectively. The binding of the inhibitor with the enzyme and the subsequent induction of the localized conformational changes in the flap region of the HIV-1 PR were monitored by exploiting the intrinsic fluorescence of the surface exposed Trp-42 residues, which are present at the proximity of the flaps. We have demonstrated by fluorescence and circular dichroism studies that ATBI binds in the active site of the HIV-1 PR and thereby leads to the inactivation of the enzyme. Based on our results, we propose that the inactivation is due to the reorganization of the flaps impairing its flexibility leading toward inaccessibility of the substrate to the active site of the enzyme.

Identification of HIV-1 integrase inhibitors via three-dimensional database searching using ASV and HIV-1 integrases as targets

Integration of viral DNA into the host cell genome is a critical step in the life cycle of HIV. This essential reaction is catalyzed by integrase (IN) through two steps, 3'-processing and DNA strand transfer. Integrase is an attractive target for drug design because there is no known cellular analogue and integration is essential for successful replication of HIV. A computational three-dimensional (3-D) database search was used to identify novel HIV-1 integrase inhibitors. Starting from the previously identified Y3 (4-acetylamino-5-hydroxynaphthalene-2,7-disulfonic acid) binding site on the avian sarcoma virus integrase (ASV IN), a preliminary search of all compounds in the nonproprietary, open part of the National Cancer Institute 3-D database yielded a collection of 3100 compounds. A more rigorous scoring method was used to rescreen the 3100 compounds against both ASV IN and HIV-1 IN. Twenty-two of those compounds were selected for inhibition assays against HIV-1 IN. Thirteen of the 22 showed inhibitory activity against HIV-1 IN at concentrations less than 200 microM and three of them showed antiviral activities in HIV-1 infected CEM cells with effective concentrations (EC50) ranging from 0.8 to 200 microM. Analysis of the computer-generated binding modes of the active compounds to HIV-1 IN showed that simultaneous interaction with the Y3 site and the catalytic site is possible. In addition, interactions between the active compounds and the flexible loop involved in the binding of DNA by IN are indicated to occur. The structural details and the unique binding motif between the HIV-1 IN and its inhibitors identified in the present work may contribute to the future development of IN inhibitors.

Identification of novel small molecule ligands that bind to tetanus toxin

Tetanus toxin belongs to a family of clostridial protein neurotoxins for which there are no known antidotes. Another closely related member of this family, botulinum toxin, is being used with increasing frequency by physicians to treat severe muscle disorders. Botulinum toxin has also been produced in large quantities by terrorists for use as a biological weapon. To identify small molecule ligands that might bind to the targeting domain of tetanus and botulinum toxins and to facilitate the design of inhibitors and new reagents for their detection, molecular docking calculations were used to screen a large database of compounds for their potential to bind to the C fragment of tetanus toxin. Eleven of the predicted ligands were assayed by electrospray ionization mass spectrometry (ESI-MS) for binding to the tetanus toxin C fragment, and five ligands (45%) were found to bind to the protein. One of these compounds, doxorubicin, was observed to have strong hydrophobic interactions with the C fragment. To check the ligands for their ability to compete with ganglioside binding, each was also tested using a GT1b liposome assay. Doxorubicin was the only ligand found to competitively bind the tetanus toxin C fragment with an appreciable binding constant (9.4 microM).