Frontiers in Drug Design and Discovery

Bringing affordable, safe and therapeutically useful drugs to patients globally is a primary goal for many governmental, academic and pharmaceutical scientists worldwide. The Frontier in Drug Design and Discovery series is dedicated to assembling these eminent scientists and allowing them to present comprehensive reviews with fresh new ideas on drug design and drug discovery. The first volume (2005) brought together experts to review and discuss the advantages and limitations of modern screening techniques used in the drug discovery process to identify potential drug candidates. The second volume (2006) discussed new technological and conceptual approaches to accelerate and to improve the predictability of the discoveries made in the laboratory into clinical testing. In the third volume of this series, reviews and discussions are presented applying structurebased design to identify potent lead drug candidates for a variety of diseases using techniques such as in-silico virtual screening, peptidomimetics, fragment-based approaches, protein crystallography, and NMR spectroscopy.

The importance of understanding the fundamentals of the energetics of a drug molecule binding to a biomacromolecule target has emerged over the years enabling scientists to think intelligently about molecular modifications that will impact binding of a designed drug. Understanding the energetic of a drug interacting with a target has had a profound impact not only on drug design, but also on the elucidation of molecular mechanism of disease. An early structure of hemoglobin allowed the study of the basis of sickle-cell anemia as well as the mechanism of drugs that inhibited sickling. Initially, structurebased drug design was based on structural determination of related proteins where the protein of interest was yet unsolved. For example, drug design for important targets such as angiotensin converting enzyme and renin were aided by determination of related enzymes such as thermolysin and fungal aspartyl proteases. However today, higher throughput protein crystallography, NMR spectroscopy and computational techniques are providing key insights on a large variety of drug-protein complexes.

The drug design field has continued to evolve to encompass de novo design of ligands based on protein structure, transformation of peptide ligands into smaller, more druglike compounds and structure-based design of inhibitors of heretofore challenging classes such as protein-protein interfaces. In addition, NMR has come into its own as a new means of structure-based design. Technical advances in robotics, crystallization screens and computational analysis has raised x-ray crystallography to the level where it can support fragment-based design; where co-structures of small fragments are solved and the fragments are pieced together to yield tighter binding ligands.....

Protein-protein interactions are one of the most common modes of signaling, but can be one of the most challenging to disrupt. This is primarily due to the relatively shallow and hydrophobic nature of the interacting protein surfaces that may extend over large areas. Even so, progress has been made on this frontier using small molecules that mimic key secondary structural motifs, called proteomimetics. In particular, α-helix mimetics have been successful in disrupting protein-protein interactions. This chapter will discuss the variety of approaches taken to obtain α-helical mimicry in low molecular weight, druglike molecules. Targets such as the BCl-2 family of proteins, HDM2-p53, various calmodulin-binding proteins, and gp41 have a wealth of literature describing α-helix mimetics as protein-protein interaction disruptors having therapeutic value in the areas of cancer, Alzheimer's disease, and AIDS. The approaches taken vary from stabilizing the α-helical structure of short peptides to a diversity of non-peptide, small molecule scaffolds allowing for the correct spatial orientation of substituents for interaction with the protein target. This chapter will compare and contrast the various scaffolds successfully shown to inhibit protein-protein interactions.

The HIV/AIDS infection continues to be a major epidemic worldwide despite the initial promise of antiviral drugs. Current therapy includes a combination of drugs that inhibit two of the virally-encoded enzymes, the reverse transcriptase and the protease. The first generation of HIV protease inhibitors that have been in clinical use for treatment of AIDS since 1995 was developed with the aid of structural analysis of protease-inhibitor complexes. These drugs were successful in improving the life span of HIV-infected people. Subsequently, the rapid emergence of drug resistance has necessitated the design of new inhibitors that target mutant proteases. This second generation of antiviral protease inhibitors has been developed with the aid of data from medicinal chemistry, kinetics, and X-ray crystallographic analysis. Traditional computational methods such as molecular mechanics and dynamics can be supplemented with intelligent data mining approaches. One approach, based on similarities to the protease interactions with substrates, is to incorporate additional interactions with main chain atoms that cannot easily be eliminated by mutations. Our structural and inhibition data for darunavir have helped to understand its antiviral activity and effectiveness on drug resistant HIV and demonstrate the success of this approach.

Rhodopsin is the only member of the G protein-coupled receptors (GPCRs) superfamily for which crystallographic data are available. Thus, the study of the structure-function relationships of most GPCRs relies on bioinformatics, rhodopsin-based homology modeling, and docking experiments conducted in an iterative manner utilizing site-directed mutagenesis and chemical modification of the ligands. Adenosine receptors (ARs) are presented as a case study to illustrate this indirect composite approach relying on an intimate combination of computational and experimental techniques. In the first section we discuss the phylogenesis of the ARs from an evolutionary perspective. Furthermore, we review sequence comparison studies from the perspective of similarities with other GPCRs, chemogenomics, and coupling to G proteins. In the second section, we review various rhodopsin-based homology models of the ARs and docking studies of agonists and antagonists. As reported for other GPCRs, several different modes have been hypothesized for ligands binding to ARs. Here, we critically review the proposed binding modes of agonists and antagonists in light of the available mutagenesis data and the structure-activity relationships of ligands. Lastly, we review an experimentally-supported strategy for validating theoretical binding hypotheses based on the complementary reengineering of receptors and ligands (neoceptors and neoligands).

The virtual docking and scoring of a large number of molecules in a protein active site has proven to be a useful method for selecting molecules for screening. It has the potential to be less biased than pharmacophore-based methods, since the only assumption one must make is the region of the protein surface to target. In this chapter, we will briefly outline the steps in a generic docking procedure, and compare and contrast how the more commonly used methods approach each of these steps. Several groups have recently compared a variety of popular docking methods using different test systems. These studies are remarkable for the similarity of their conclusions and as a group give a good picture of the state of the art. We will then focus in on two aspects of the docking problem that are receiving increased attention and have potential to significantly improve docking results: ligand preparation and protein flexibility. Ligand preparation is a fundamental aspect of virtual screening that has not been systematically investigated. Issues with ligand preparation include ionization states, tautomerization, and stereochemistry. If these are not treated accurately, one can miss a promising lead or overwhelm the docking with molecules that are unlikely to be present under physiologic conditions. Both false positives and false negatives can result. Proteins are not rigid entities. It is clear that docking to a rigid model of a protein, even if it is an experimentally determined model, does not capture the dynamic behavior of the protein in solution. Current approaches such as docking to different models of the same protein or allowing limited side chain flexibility are steps toward more realistic modeling of the protein target.

NMR is a powerful tool for fragment-based lead discovery comprising robust techniques for screening, core elaboration and fragment linking as well as 3D protein-ligand structure determination. Utilizing a direct binding assay that solely contains protein and ligand, NMR detects loose fragment binders with unparalleled sensitivity and robustness even in the millimolar affinity range. Excellent research during the last ten years established protein- and ligand- detected NMR screening assays for soluble proteins below and above 50 kD, respectively. Site-specific methods, such as spin-label perturbation and InterLigand- NOE (ILOE) NMR screening allow one to selectively detect fragment binding to allosteric or adjacent second sites. Target-immobilized NMR screening (TINS) reduces protein consumption and potentially enables screening of membrane proteins.

NMR supports fragment-to-lead optimization through chemical shift perturbation SAR maps and fragment linking through ILOE information at timely throughput of > = 20 compounds / day. 3D protein-ligand structures for structure- based design require more time ( > 1 month / compound) and thus are limited to few representative ligands.

Further research is required to make such NMR techniques amenable to proteins with poor expression yield, low solubility, sole expression in mammalian systems and ultimately to membrane proteins. Some of these bottlenecks are circumvented by integrating NMR into HTS, computational docking and cocrystallization platforms, which is an important future direction.

Tyrosine kinases regulate various biological processes including cell proliferation, migration, differentiation and survival. Src and Abl are cellular tyrosine kinases that play roles in cellular function, including proliferation and growth. Both are usually under tight regulatory control in normal cells. Disruption in certain regulatory mechanisms results in the activation of Src mediated pathways, which have been implicated in cancers, stroke, myocardial infarction, and bone disorders. The formation of the Philadelphia chromosome results in the production of the fusion protein Bcr-Abl with a constitutively active Abl kinase portion, causative for chronic myelogenous leukemia (CML). Gleevec (Imatinib) targeting the Abl ATP site is the current standard of care for treating CML. Drug resistance to treatment with Gleevec in 50-90% of cases arises due to mutations mostly clustered around the Gleevec binding site. Since all known inhibitors of Src that bind at the ATP site are also inhibitors of Abl, several Src and Abl inhibitors are being intensely studied as they target many of the Abl mutations seen in Gleevec resistance, potentially due to differential binding modes. Sprycel, a highly potent Src and Abl inhibitor was advanced and has now been approved for the treatment of Gleevec resistant CML. None of these inhibitors target the particularly challenging mutation of the gatekeeper residue, the T315I mutation. The gatekeeper residue sits at the entrance to the hydrophobic pocket - a region proximal to the hinge and one that several classes of ATP site binding inhibitors exploit since it serves to enhance both potency and selectivity. We describe a novel conceptual design used to obtain potent inhibitors targeting the active form of Src. This powerful concept was further applied to design inhibitors targeting the Abl-T315I mutant. The approach targets an acid functional group on the αC-helix located deep within this hydrophobic pocket and that is available only after kinase activation. This designed interaction provides a “magic bullet“ in overcoming the steric clashes arising from the Ile-315, and changes poor (ca. 10 μM) inhibitors into those with low nM potency. Targeting the active state of the kinase via this unique and relatively unexplored portion of the active kinase, the Glu on the αC-helix, has implications for targeting disease states with upregulated or constitutively activated kinase pathways.

The successful approval and launch of several small molecule protein kinase inhibitor drugs has stimulated further interest and research into therapeutics targeting kinases implicated in disease pathways. The use of protein structural information obtained from the kinase catalytic domain or substrate binding site has and continues to play a major role in the discovery and optimization of novel pharmacophores. A summary of progress made recently in the development of new structure based approaches for the discovery of kinase inhibitors is described. In addition, a number of case studies are presented demonstrating successful application of structure-guided design methods to the development of selective inhibitors targeting the cyclin dependent kinases, MAP kinases, and receptor tyrosine kinases. Inhibitors that preferentially bind to inactive kinase conformations are also covered as an area of recent exciting developments. In addition, the development of a new generation of selective kinase inhibitor drugs through targeting alternate binding sites distinct from the ATP cleft is presented.

Fragment-based lead discovery is a recent approach in which much lower molecular weight compounds are screened relative to those in high throughput screening campaigns. In theory, fragment-based methods offer the possibility of identifying novel leads with improved affinity, selectivity, and pharmaceutical properties, and the rationale behind these fragment-based strategies makes intuitive sense. However, fragment-based hits are typically weak inhibitors/binders (IC50/Kd ~ μM-mM range), and therefore need to be screened at higher concentrations using very sensitive detection techniques. Although fragment hits are simpler, less functionalized compounds with correspondingly lower potencies, they typically possess high 'ligand efficiency' and so are highly suitable for optimization into clinical candidates with good drug-like properties. Nevertheless, elaborating, linking or exploring weakbinding fragments into high-affinity binders can be challenging and fragmentbased lead discovery can be difficult in practice. Both the discovery of fragment hits and how to advance or link them are areas of intense research. This paper discusses the concepts of fragment-based lead discovery, the design of fragment-based screening libraries, various screening techniques utilized in this approach, and a choice of specific examples which illustrate diverse approaches to fragment-based lead discovery.

The family of nuclear hormone receptors continues to be a rich source of drug discovery targets. In addition to traditional structure-based design methods for receptor-ligand design, the nuclear hormone receptor family presents an additional challenge. The receptor-ligand complex can adopt a conformation that attracts a family of co-activators and co-repressor proteins leading to very specific biological profiles. Several specific receptor modulators have been discovered that exhibit novel biological properties that have either entered the clinic or are in the advanced stages of preclinical research. Some examples will be presented to highlight how this exciting area has emerged over the past decade while projecting some future trends. The focus of this chapter will not be a comprehensive summary of the many examples in the last decade since several reviews are available [1]. Rather, this chapter will highlight some of the strategies and challenges facing the design of specific ligands using X-ray and molecular modeling methods.

The protozoon Plasmodium falciparum is the causative agent of tropical malaria which causes up to three million human deaths and up to 500 million episodes of clinical illness throughout the world annually. Children in African countries bear the largest part of this burden. Due to the rapid development of resistance to clinically used drugs like chloroquine and mefloquine and the increasing risk of resistance to artemisinins, novel effective and affordable antimalarial agents are urgently required. The progress made over the last years in the fields of genomics, proteomics, and clinical medicine coupled with improved facilities as well as technical progress in structural biology and high throughput screening methods are essential to support these drug development approaches. Furthermore concerted programs supported by governments, industry and academia contribute significantly to the progress in the field of antimalarial chemotherapy. Among the most interesting antimalarial target proteins currently studied are proteases, like plasmepsins, falcipains and falcilysin, but also protein kinases, glycolytic enzymes and enzymes involved in lipid metabolism and DNA replication. In addition, redox active proteins like glutathione reductase, thioredoxin reductase and glutathione S-transferase have become increasingly interesting. In this article we summarize the major current structure-based antimalarial drug development approaches. We briefly review the presently available three-dimensional structures of Plasmodium proteins together with their potential as drug targets. In parallel, we give an overview over inhibitors that have been developed on the basis of these known parasite protein structures or related structures of proteins from other organisms.

New chemotherapies to treat malaria and leishmania are needed to combat the growing resistance of available drugs and rapid spread of the diseases in many parts of the world. In the past, drug development efforts have primarily focused on identifying compounds that inhibited the growth of these parasites in culture. With the emergence of structure-based drug design and in silco methodologies, drug development efforts have shifted to targeting specific proteins in the parasites that are unique yet critical for their growth and survival. However, target proteins for potent antimalarial agents are often unknown. The review discusses how in silico methodologies have been successfully applied to virtual screening of compound libraries to aid discovery and design of antimalarial and antileishmanial agents in recent years. The main focus will be on how by developing ligand-based and 3D shape-based pharmacophores from known structure-activity studies, virtual screening of compound libraries are performed to identify potent lead candidates. In silico pharmacophores are geometric distribution of chemical features, such as hydrogen bond acceptor, hydrogen bond donor, aliphatic and aromatic hydrophobic functions, ring aromatic, etc., in three-dimensional space of a molecular structure which are considered responsible for target specific biological activity. Pharmacophores are generated from multiple conformations from a set of molecules having experimental activity data. When the structure of a protein is unknown, this methodology is a very efficient approach to determine the active conformation of a set of molecules.

Replication-dependent or independent DNA lesions induced by DNA damaging agents or radiation have been a useful strategy for cancer treatment. A growing number of novel anti-cancer agents have been designed on the basis of their ability to inhibit DNA repair processes or promote cellular senescence. The functions of DNA helicases in the DNA damage response, replication, or avoidance of cellular senescence suggest that this class of enzymes may be a useful target for the development of a new generation of chemotherapy drugs. Biochemical, cellular and genetic characterization of helicases has proven to be insightful for the delineation of their respective functions and biological roles in pathways of DNA metabolism that confer genomic stability. In this review, we will discuss the rationale for development of helicase inhibitors that might improve chemotherapeutic options for treating cancers. As a guide for the discovery of novel anti-cancer agents, the human helicases implicated in disorders associated with age-related disease, cancer, and/or chromosomal instability will be considered to elucidate potential mechanisms of chemotherapy drug action. Interactions of these DNA helicases with the tumor suppressor and genome stability factors p53, BRCA1, and BRCA2 suggest potential anti-cancer strategies.

The docking and scoring paradigm can be considered as the combination of two separate problems. The first aspect is a geometric, or more broadly an informatics problem: how can we place a solid object (ligand) within a “cavity“ of another solid (protein) or close to another molecule in a well-defined Cartesian space? The second one is a more intriguing chemical problem: how can we properly predict the free energy of binding considering all the possible contributions involved in biological interactions? There is a wide range of algorithms and approaches used to produce docking poses and, consequently, a wide range of associated scoring functions used to judge the possible poses. In several cases the scoring functions are deeply entwined with the search method and can not be considered separately. In other cases, more than one scoring function is provided in docking programs, each showing different strengths and limitations. Consensus scoring approaches, combining multiple methods into a single metric, have been created to overcome the weaknesses characterizing the different docking algorithms and the associated scoring functions. Correctly predicting not just the binding mode, but also the binding energy, is a primary exigency in all docking simulations and, in particular, in virtual screening applications. Accurate estimation of binding free energy would allow, not only good discrimination between active and inactive molecules, but also among closely related analogs, this latter case being particularly important for drug design. In this chapter we discuss problems related to docking/scoring techniques for in silico screening and we review the most common scoring methods.

Acetylcholinesterase (AChE; EC 3.1.1.7) reactivators (called oximes) are important group of drugs used as antidotes in the treatment of intoxications with highly toxic organophosphorus compounds such as pesticides (paraoxon, chlorpyrifos etc.) and nerve agents (sarin, tabun etc.). After the sarin terroristic attack in Tokyo subway, their development employed many scientists from both - military and civilian sectors. Due to the rapid synthesis and evaluation of the biological activity of many new structurally different potential antidotes in our laboratories, we would like to discuss relationship between the structure of currently available AChE reactivators and their biological activity.

There is a wide range of organophosphorus nerve agents and pesticides and, therefore, our article was focused on reactivators of tabun-inhibited AChE only. This agent was chosen for its poor ability of currently commercially available oximes to reactivate AChE inhibited by this nerve agent.

Presented results arised from our in vitro studies comprising more than one hundred structurally different AChE reactivators, which were published during last five years. In this article, the main structural requirements (presence of the quaternary nitrogens; choice, presence, and position of the nucleophilic group; length, shape, and rigidity of the connection chain) influencing reactivation potency of currently available oximes is discussed.

Solid-phase peptide synthesis is the archetypal example of combinatorial chemistry. Advances in amino acid synthesis allow unprecedented structural diversity using automated synthesis. In this chapter we briefly introduce the history and advances in peptide synthesis and include strategies for peptidomimetic development. We highlight examples of the use of peptides in drug development, including pharmacophore extrapolation, substrate/ligand mimicry, and post-genomics target protein identification. We also describe methods for virtual combinatorial peptide construction, using databases of commercially available, non-natural amino acids, as well as strategies for high throughput virtual screening and de novo design of inhibitors. Finally, we offer suggestions for using peptide diversity for lead compound identification and optimisation, as well as a number of pitfalls in both peptide synthesis and virtual screening that need to be avoided.

The blood-brain barrier (BBB) in brain microvessels maintains homeostasis of the brain microenvironment mostly through maintenance of tight junctions between brain vascular endothelial cells, thereby preventing passage of hydrophilic molecules or toxic substances from the blood to the brain. Vascular damage following embolic stoke leads to disruption of BBB, thereby eliciting brain edema. Therefore, microvascular endothelial cell is likely potential therapeutic target to rescue neurons from brain edema. Vasoprotective agents such as free radical scavengers, matrix metalloproteinase inhibitors and HMGCoA reductase inhibitors are potential candidates to inhibit BBB disruption. In this review, we focus on mechanisms of decreased brain infarction by these vasoprotective agents. In addition, nitric oxide and peroxynitrite are known to elicit cerebral microvascular injury resulting BBB disruption following cerebral ischemia. Of note, inhibition of nitric oxide synthase (NOS) attenuates BBB disruption following brain ischemia. We recently introduced a novel vasoprotective drug, DY-9760e, which is a novel calmodulin-dependent NOS inhibitor. We confirmed that DY-9760e, can protect microvascular endothelial cells in rat embolic stoke model, thereby attenuating BBB disruption. Taken together, we propose a therapeutic modality that target cerebrovascular would represent powerful approaches to prevent brain edema following cerebral ischemia.

Initially, structure-based drug design (SBDD) approaches relied on the validity of the “lock and key” model, although this assumption leads to clear limitations. Thus, there are considerable efforts nowadays to incorporate the influence of (changes of) protein flexibility and mobility into recent drug design approaches. These efforts are grounded on the “induced-fit” and “conformational selection” models of ligand binding to proteins. Here we will summarize computational approaches in SBDD that address these issues, with a focus on methods that account for receptor plasticity. In particular, we consider how protein plasticity can be incorporated into docking strategies. Two requirements need to be met for this: first, one needs to detect what can move and how; second, this knowledge needs to be transformed into a docking algorithm. With regard to the former, knowledge about moving protein parts can be gained from experimental information as well as established techniques such as molecular dynamics simulations, graph theoretical and geometry-based approaches, or harmonic analysis-based methods. With regard to the latter, a plethora of approaches has been presented recently that range from considering protein plasticity only implicitly to modeling sidechain movements to also including backbone changes. A hallmark of all these approaches is that they need to balance accuracy and efficiency. Case studies of SBDD for which the inclusion of protein plasticity was crucial to success are noted along these lines. This provides a picture of scope and limitations of the current approaches as well as guidelines for further developments.

Drug discovery and development is an expensive and timeconsuming process; taking from identification and validation of disease target through lead discovery and optimisation to clinical tests and regulatory approval. High-throughput in silico screening techniques offer an enormous benefit to drug discovery being both fast and practical for a seamless integration into daily research routines.

Structural genomics and high-throughput X-ray crystallography initiated a growth in the number of available X-ray structures that enabled structure-based virtual screening approaches to be dominant techniques in drug discovery. Ligand-supported homology modelling provides improved 3D structures in quality to further promote the application of structure-based methods.

Up to date many success stories and excellent reviews have been published revealing the importance of docking preparation and drawing attention to protein conformation, protonation states or tautomerism. Evaluation and ranking of predicted ligand conformations proves to be another crucial aspect of structurebased virtual screening. As the incorporation of the protein flexibility in docking calculations still reserves some untapped possibilities further improvements are expected in this field.

Here, we provide a full-length review of structure-based virtual screening approaches supporting our views by various case studies. The applicability and the performance of structure-based virtual screening processes in industrial environment are also demonstrated through some in-house studies. Hereby a picturesque review of structure-based virtual screening from the protocol development to its application focusing on the critical aspects is given.

G protein-coupled receptors (GPCRs) represent the largest family of signal transduction membrane proteins and play a critical role in many key physiological processes such as neurotransmission, cellular metabolism, secretion, cell growth, immune defence, and differentiation. Therefore, it is not surprising that these receptors represent a realized and ongoing opportunity for drug development. In this scenario, structure-based drug design techniques turned out to be a really attractive approach, leading to a breakthrough in the discovery of novel therapeutic agents. Indeed, much of this success has to be attributed to the pioneering elucidation of the bovine rhodopsin crystal structure, which represents a milestone in the understanding of GPCRs structures. Starting from the experimentally found rhodopsin 3D coordinates, the tandem application of homology building techniques and molecular docking has become one the most important approaches for structure and ligand binding analysis. Nevertheless, the construction of realistic models of certain GPCRs still remains time consuming and requires many refinements of the models in close association with experiments. This review is aimed at providing a deep view into the current status of GPCR modeling, highlighting the recent progresses made in the rhodopsin-based homology building together with alternative computational approaches. The application of these techniques in the detection of GPCR ligands and the elucidation on how they impact the world of drug discovery is also discussed.

An antibody-drug conjugate consists of a potent cytotoxic drug attached to a monoclonal antibody specially targeted on cancer associated antigen. The antigen targeted chemotherapy can improve therapeutic index by increasing potential efficacy and decreasing systemic toxicity. In this review, we described the study and the progress in antibody engineering, the process of drug selection, and the development of linker to optimize the clinical trials. We also discussed about the possible mechanism of cell death induced by an antibody- drug conjugate and the potential resistance to an antibody-drug conjugate. Nonetheless, the successful results from Gentuzumab ozogamicin and other encouraging clinical trials will continue to drive the preclinical development of antibody-drug conjugates.

One of the most exciting area of research in drug design concerns with the synthesis and 3D-structural characterisation of molecules containing peptidomimetics, since they can be expected to possess similar biological effects as their natural peptide counterparts, so that they could be used as therapeutics, with the potential, added advantages of higher metabolic stability, enhanced interactions with the receptor, and improved pharmacokinetic properties. In this review, we report the structural properties of the main constrained non coded aminoacids as examples of peptidomimetics or molecular tools able to induce specific conformations in bioactive peptide analogues.

The evolution and subsequent design of clinically effective antimalarial drugs particularly 4-aminoquinolines, 8-aminoquinolines and 9-aminoacridines are reviewed. These molecules benefited from scientific advances in medicinal and synthetic chemistry guided by pharmacological screening, including animal models of malaria. The mechanism of action of antimalarials, especially against the heme receptor, and the impact of this knowledge on drug design is critically discussed. Modelling investigations and quantum mechanics calculations reveal close contacts between the porphyrin ring and selected atoms within compounds such as the bisquinoline, metaquine. Analysis of these close contacts can be used to design compounds with modulated antimalarial activity to further clarify the drug action. Knowledge of mammalian drug metabolism and pharmacokinetics, together with detailed in vitro and in vivo pharmacology has aided (a) resurrection of old compounds and (b) redesign of existing compounds. The latter includes judicious modification (e.g. inversion of oxidizable functional groups as in SN-13,730 i.e. isoquine) or introduction of groups blocking metabolism (e.g. exploiting bond strength viz. fluorine or steric effects with the t-butyl group). This simultaneous modulation of both drug metabolism and interaction with the heme receptor can be used to enhance antimalarial activity. Compounds benefiting from such modifications include primaquine, pyronaridine, isoquine, metaquine and AQ-13, together with selected analogues with useful activity against drug-resistant Plasmodia in vivo. It is concluded that optimisation of the privileged quinoline and acridine scaffolds, discovered in the early part of the 20th century, still has a vital role to play in the future discovery of cost effective solutions to malaria.