A structure-based design approach to advance the allyltyrosine-based series of HIV integrase inhibitors

As of mid-2017, only one structure of the human immunodeficiency virus (HIV) integrase core domain co-crystallised with an active site inhibitor was reported. In this structure (1QS4), integrase is complexed with a diketo-acid based strand-transfer inhibitor (INSTI). This structure has been a preferred platform for the structure-based design of INSTIs despite concerns relating to structural irregularities arising from crystallographic packing effects. A survey of the current pool of 297 reported integrase catalytic core structures indicated that the anatomy of the active site in the complex structure 1QS4 exhibits subtle variations relative to all other structures examined. Consequently, the 1QS4 structure was employed for docking studies. From the docking of twenty-seven allyltyrosine analogues, a 3-point inhibitor binding motif required for activity was established and successfully utilised in the development of a tripeptide displaying an EC₅₀ value of 10 ± 5 μM in HIV infected human T-cells. Additional docking of “in-house” compound libraries unearthed a methyl ester based nitrile derivative displaying an IC₅₀ value of 0.5 μM in a combined 3′-processing and strand-transfer assay.     

Development of a protease production platform for structure-based drug design

Structure-based drug design (SBDD) has played an integral role in the development of highly specific, potent protease inhibitors resulting in a number of drugs in clinical trials and on the market. Possessing biochemical assays and structural information on both the target protease and homologous family members helps ensure compound selectivity. We have redesigned the path from clone to protein eliminating many of the traditional bottlenecks associated with protein production to ensure a constant supply to feed many diverse protease drug discovery programs. The process was initiated with the design of a multi-system vector, capable of expression in both eukaryotic and prokaryotic hosts; this vector also facilitated high-throughput cloning, expression and purification. When combined into an expression screen, supplemented with salvage screens for detergent extraction and refolding, a route for protein production was established rapidly. Using this process-orientated approach we have successfully expressed and purified all mechanistic classes of active human and viral proteases for enzymatic assays and crystallization studies. While exploiting recent developments in high-throughput biochemistry, we still employ classical biophysical techniques such as light-scattering and analytical ultracentrifugation, to ensure the highest quality protein enters crystallization trials. We have drawn on examples from our own research programs to illustrate how these strategies have been successfully used in the production of proteases for SBDD.     

Isothermal titration calorimetry: application to structure-based drug design

The road to market for drug compounds is a treacherous one, generally involving a huge temporal and financial investment. The role of structure-based drug design or lead optimisation ranges wildly in importance in different pharmaceutical companies. The adoption of these aids to provide routes to high affinity ligands has not received widespread acceptance. This is based on a number of factors, from the perceived failings of such methods, to the belief that rapid screening of compound libraries alone is the most effective way to discover drugs.

The panacea of being able to take a computer generated representation of the structure of a target site of a given biomolecule and rationally design an high affinity inhibiting compound has proved seemingly unreachable for three major reasons: (1) current capabilities in computing; (2) the requirement for atomic resolution structural detail; and (3) determination of how structural features can be related to the thermodynamics of interactions. It is the last of these points that this review seeks to address. In particular the use of isothermal titration calorimetry is discussed in the light of the accumulation of accurate thermodynamic data and examples are given where this has been applied to understand the structural aspects of formation of drug–biomolecular complexes.     

An integrated approach to knowledge-driven structure-based virtual screening

In many practical applications of structure-based virtual screening (VS) ligands are already known. This circumstance requires that the obtained hits need to satisfy initial made expectations i.e., they have to fulfill a predefined binding pattern and/or lie within a predefined physico-chemical property range. Based on the RApid Index-based Screening Engine (RAISE) approach, we introduce cRAISE—a user-controllable structure-based VS method. It efficiently realizes pharmacophore-guided protein-ligand docking to assess the library content but thereby concentrates only on molecules that have a chance to fulfill the given binding pattern. In order to focus only on hits satisfying given molecular properties, library profiles can be utilized to simultaneously filter compounds. cRAISE was evaluated on a range of strict to rather relaxed hypotheses with respect to its capability to guide binding-mode predictions and VS runs. The results reveal insights into a guided VS process. If a pharmacophore model is chosen appropriately, a binding mode below 2 Å is successfully reproduced for 85 % of well-prepared structures, enrichment is increased up to median AUC of 73 %, and the selectivity of the screening process is significantly enhanced leading up to seven times accelerated runtimes. In general, cRAISE supports a versatile structure-based VS approach allowing to assess hypotheses about putative ligands on a large scale.     

A structure-based design approach for the identification of novel inhibitors: application to an alanine racemase

We report a new structure-based strategy for the identification of novel inhibitors. This approach has been applied to Bacillus stearothermophilus alanine racemase (AlaR), an enzyme implicated in the biosynthesis of the bacterial cell wall. The enzyme catalyzes the racemization of l- and d-alanine using pyridoxal 5-phosphate (PLP) as a cofactor. The restriction of AlaR to bacteria and some fungi and the absolute requirement for d-alanine in peptidoglycan biosynthesis make alanine racemase a suitable target for drug design. Unfortunately, known inhibitors of alanine racemase are not specific and inhibit the activity of other PLP-dependent enzymes, leading to neurological and other side effects.This article describes the development of a receptor-based pharmacophore model for AlaR, taking into account receptor flexibility (i.e. a `dynamic' pharmacophore model). In order to accomplish this, molecular dynamics (MD) simulations were performed on the full AlaR dimer from Bacillus stearothermophilus (PDB entry, 1sft) with a d-alanine molecule in one active site and the non-covalent inhibitor, propionate, in the second active site of this homodimer. The basic strategy followed in this study was to utilize conformations of the protein obtained during MD simulations to generate a dynamic pharmacophore model using the property mapping capability of the LigBuilder program. Compounds from the Available Chemicals Directory that fit the pharmacophore model were identified and have been submitted for experimental testing.The approach described here can be used as a valuable tool for the design of novel inhibitors of other biomolecular targets.     

Hit diffusion: limitations to drug discovery and structure-based design

Journal of Computer-Aided Molecular Design - Modern drug discovery employs a ‘screening funnel’ to pick compounds worthy of advancing to the clinic, a multi-step process linking a...     

AstexViewer: a visualisation aid for structure-based drug design

AstexViewer is a Java molecular graphics program that can be used for visualisation in many aspects of structure-based drug design. This paper describes its functionality, implementation and examples of its use. The program can run as an Applet in a web browser allowing structures to be displayed without installing additional software. Applications of its use are described for visualisation and as part of a structure based design platform. The software is being made freely available to the community and may be downloaded from http://www.astex-technology.com/AstexViewer.     

Nonpeptide inhibitors of cathepsin G: optimization of a novel beta-ketophosphonic acid lead by structure-based drug design

The serine protease cathepsin G (EC 3.4.21.20; Cat G), which is stored in the azurophilic granules of neutrophils (polymorphonuclear leukocytes) and released on degranulation, has been implicated in various pathological conditions associated with inflammation. By employing high-throughput screening, we identified beta-ketophosphonic acid 1 as a moderate inhibitor of Cat G (IC(50) = 4.1 microM). We were fortunate to obtain a cocrystal of 1 with Cat G and solve its structure by X-ray crystallography (3.5 A). Structural details from the X-ray analysis of 1.Cat G served as a platform for optimization of this lead compound by structure-based drug design. With the aid of molecular modeling, substituents were attached to the 3-position of the 2-naphthyl ring of 1, which occupies the S1 pocket of Cat G, to provide an extension into the hydrophobic S3 region. Thus, we arrived at analogue 7 with an 80-fold potency improvement over 1 (IC(50) = 53 nM). From these results, it is evident that the beta-ketophosphonic acid unit can form the basis for a novel class of serine protease inhibitors.     

Discovery of a novel serine protease inhibitor utilizing a structure-based and experimental selection of fragments technique

We report a set of strategies to develop novel ligands (Structure Based and Experimental Selection of Fragments: SbE-SF). First, a docking simulation utilizing DOCK3.5 is performed in order to screen the fragment database, which was generated with the in-house program FRAGMENT++ specifically for docking simulation purposes. Although the affinity of these small molecules (fragments) is expected to be low, the affinity of fragments selected by computation is assayed by experiment to determine which ones can be potent inhibitors. After determining such key fragments, additional fragments are attached to the key ones in order to increase the binding affinity,taking into account the binding modes predicted by computation. This method has been applied to a thrombin inhibitor study, resulting in the discovery of a novel inhibitor exhibiting pIC₅₀ = 7.9.     

Identification of a serine protease inhibitor homologue in Bird's Nest by an integrated proteomics approach.

For centuries, the edible nests of Collocalia spp. ("Bird's Nests") have been used as a Chinese delicacy that had been claimed to be an effective health-giving tonic. However, clinical studies indicated that in Singapore, Bird's Nest is the most common cause of food-induced anaphylaxis in children, which could lead to potentially life-threatening allergenic reactions. The purpose of this study was to characterize the major allergens in Bird's Nest by using the combined technologies of two-dimensional gel electrophoresis (2-DE), immunochemistry, N-terminal protein sequencing, and mass spectrometry. Results from the immunostaining of the Western blots of the Bird's Nest 2-DE separated proteins with the sera from allergic patients indicated the presence of a major allergen of 66 kDa. Initial searches of the matrix assisted laser desorption/ionization--time of flight--mass spectrometry (MALDI-TOF-MS) tryptic peptide masses of the allergen in the SWISS-PROT and NCBI nonredundant databases revealed that this protein was novel. Based on the partial protein sequence information obtained from N-terminal microsequencing and nanoelectrospray-tandem MS, the 66 kDa immunoreactive allergen was found to be homologous to ovoinhibitor, a Kazal-type serine protease inhibitor, which is one of the dominant allergens found in chicken egg white.     

Development of KiBank, a database supporting structure-based drug design

KiBank is a database of inhibition constant (K_i) values with 3D structures of target proteins and chemicals. K_i values were accumulated from peer-reviewed literature searched via PubMed. The 3D structure files of target proteins were originally from Protein Data Bank (PDB), while the 2D structure files of the chemicals were collected together with the K_i values and then converted into 3D ones. In KiBank, the chemical and protein 3D structures with hydrogen atoms were optimized by energy minimization and stored in MDL MOL and PDB format, respectively.

KiBank is designed to support structure-based drug design. It provides structure files of proteins and chemicals ready for use in virtual screening through automated docking methods, while the K_i values can be applied for tests of docking/scoring combinations, program parameter settings, and calibration of empirical scoring functions. Additionally, the chemical structures and corresponding K_i values in KiBank are useful for lead optimization based on quantitative structure–activity relationship (QSAR) techniques.

KiBank is updated on a daily basis and is freely available at http://kibank.iis.u-tokyo.ac.jp/. As of August 2004, KiBank contains 8000 K_i values, over 6000 chemicals and 166 proteins covering the subtypes of receptors and enzymes.     

Quantitative structure-based design: formalism and application of receptor-dependent RD-4D-QSAR analysis to a set of glucose analogue inhibitors of glycogen phosphorylase

A method for performing quantitative structure-based design has been developed by extending the current receptor-independent RI-4D-QSAR methodology to include receptor geometry. The resultant receptor-dependent RD-4D-QSAR approach employs a novel receptor-pruning technique to permit effective processing of ligands with the lining of the binding site wrapped about them. Data reduction, QSAR model construction, and identification of possible pharmacophore sites are achieved by a three-step statistical analysis consisting of genetic algorithm optimization followed by backward elimination multidimensional regression and ending with another genetic algorithm optimization. The RD-4D-QSAR method is applied to a series of glucose inhibitors of glycogen phosphorylase b, GPb. The statistical quality of the best RI- and RD-4D-QSAR models are about the same. However, the predictivity of the RD- model is quite superior to that of the RI-4D-QSAR model for a test set. The superior predictive performance of the RD- model is due to its dependence on receptor geometry. There is a unique induced-fit between each inhibitor and the GPb binding site. This induced-fit results in the side chain of Asn-284 serving as both a hydrogen bond acceptor and donor site depending upon inhibitor structure. The RD-4D-QSAR model strongly suggests that quantitative structure-based design cannot be successful unless the receptor is allowed to be completely flexible.     

CrystalDock: a novel approach to fragment-based drug design

We present a novel algorithm called CrystalDock that analyzes a molecular pocket of interest and identifies potential binding fragments. The program first identifies groups of pocket-lining receptor residues (i.e., microenvironments) and then searches for geometrically similar microenvironments present in publically available databases of ligand-bound experimental structures. Germane fragments from the crystallographic or NMR ligands are subsequently placed within the novel binding pocket. These positioned fragments can be linked together to produce ligands that are likely to be potent; alternatively, they can be joined to an inhibitor with a known or suspected binding pose to potentially improve binding affinity. To demonstrate the utility of the algorithm, CrystalDock is used to analyze the principal binding pockets of influenza neuraminidase and Trypanosoma brucei RNA editing ligase 1, validated drug targets in the fight against pandemic influenza and African sleeping sickness, respectively. In both cases, CrystalDock suggests modifications to known inhibitors that may improve binding affinity.     

The estrogen receptor: a structure-based approach to the design of new specific hormone-receptor combinations

Background: The specificity of hormone action arises from complementary steric and electronic interactions between a hormonal ligand and its cognate receptor. An analysis of such key ligand-receptor contact sites, often delineated by mutational mapping and X-ray crystallographic studies, can suggest ways in which hormone-receptor specificity might be altered.Results: We have altered the hormonal specificity of the estrogen receptor alpha (ER) by making 'coordinated' changes in the A-ring of the ligand estradiol and in the A-ring binding subpocket of ER. These changes were designed to maintain a favorable interaction when both E and ER are changed, but to disfavor interaction when only E or ER is changed. We have evaluated several of these altered ligand and receptor pairs in quantitative ligand binding and reporter gene assays.Conclusions: In best cases, the new interaction is sufficiently favorable and orthogonal so as to represent the creation of a new hormone specificity, which might be useful in the regulation of transgene activity.     

In search of new lead compounds for trypanosomiasis drug design: A protein structure-based linked-fragment approach

Summary A modular method for pursuing structure-based inhibitor design in the framework of a design cycle is presented. The approach entails four stages: (1) a design pathway is defined in the three-dimensional structure of a target protein; (2) this pathway is divided into subregions; (3) complementary building blocks, also called fragments, are designed in each subregion; complementarity is defined in terms of shape, hydrophobicity, hydrogen bond properties and electrostatics; and (4) fragments from different subregions are linked into potential lead compounds. Stages (3) and (4) are qualitatively guided by force-field calculations. In addition, the designed fragments serve as entries for retrieving existing compounds from chemical databases. This linked-fragment approach has been applied in the design of potentially selective inhibitors of triosephosphate isomerase from Trypanosoma brucei, the causative agent of sleeping sickness.     

Identification of novel malarial cysteine protease inhibitors using structure-based virtual screening of a focused cysteine protease inhibitor library

Malaria, in particular that caused by Plasmodium falciparum , is prevalent across the tropics, and its medicinal control is limited by widespread drug resistance. Cysteine proteases of P. falciparum , falcipain-2 (FP-2) and falcipain-3 (FP-3), are major hemoglobinases, validated as potential antimalarial drug targets. Structure-based virtual screening of a focused cysteine protease inhibitor library built with soft rather than hard electrophiles was performed against an X-ray crystal structure of FP-2 using the Glide docking program. An enrichment study was performed to select a suitable scoring function and to retrieve potential candidates against FP-2 from a large chemical database. Biological evaluation of 50 selected compounds identified 21 diverse nonpeptidic inhibitors of FP-2 with a hit rate of 42%. Atomic Fukui indices were used to predict the most electrophilic center and its electrophilicity in the identified hits. Comparison of predicted electrophilicity of electrophiles in identified hits with those in known irreversible inhibitors suggested the soft-nature of electrophiles in the selected target compounds. The present study highlights the importance of focused libraries and enrichment studies in structure-based virtual screening. In addition, few compounds were screened against homologous human cysteine proteases for selectivity analysis. Further evaluation of structure-activity relationships around these nonpeptidic scaffolds could help in the development of selective leads for antimalarial chemotherapy.     

Mini-review: computational structure-based design of inhibitors that target protein surfaces

Finding drugs that inhibit protein-protein interactions is usually difficult. While computer-aided design is used widely to facilitate the drug discovery process for protein targets with well-defined binding pockets, its application to the design of inhibitors targeting a protein surface is very limited. In this mini-review we address two aspects of this issue: firstly, we overview the current state of design methodology for inhibitors specifically targeting protein surfaces, and secondly, we briefly outline recent advances in computational methods for structure-based drug design. These methods are closely related to protein docking and protein recognition, the difference being that in ligand design, ligands are built on a fragment-by-fragment basis. A novel scheme of computational combinatorial ligand design developed for the design of inhibitors that interfere with protein-protein interaction is described in detail. Current applications and limitations of this methodology, as well as its future prospects, are discussed.     

The multi-copy simultaneous search methodology: a fundamental tool for structure-based drug design

Fragment-based ligand design approaches, such as the multi-copy simultaneous search (MCSS) methodology, have proven to be useful tools in the search for novel therapeutic compounds that bind pre-specified targets of known structure. MCSS offers a variety of advantages over more traditional high-throughput screening methods, and has been applied successfully to challenging targets. The methodology is quite general and can be used to construct functionality maps for proteins, DNA, and RNA. In this review, we describe the main aspects of the MCSS method and outline the general use of the methodology as a fundamental tool to guide the design of de novo lead compounds. We focus our discussion on the evaluation of MCSS results and the incorporation of protein flexibility into the methodology. In addition, we demonstrate on several specific examples how the information arising from the MCSS functionality maps has been successfully used to predict ligand binding to protein targets and RNA.     

Incorporating protein flexibility in structure-based drug discovery: using HIV-1 protease as a test case

We have developed a receptor-based pharmacophore method which utilizes a collection of protein structures to account for inherent protein flexibility in structure-based drug design. Several procedures were systematically evaluated to derive the most general protocol for using multiple protein structures. Most notably, incorporating more protein flexibility improved the performance of the method. The pharmacophore models successfully discriminate known inhibitors from drug-like non-inhibitors. Furthermore, the models correctly identify the bound conformations of some ligands. We used unliganded HIV-1 protease to develop and validate this method. Drug design is always initiated with a protein-ligand structure, and such success with unbound protein structures is remarkable - particularly in the case of HIV-1 protease, which has a large conformational change upon binding. This technique holds the promise of successful computer-based drug design before bound crystal structures are even discovered, which can mean a jump-start of 1-3 years in tackling some medically relevant systems with computational methods.