What to expect from rational drug design

For more than 20 years, rational methods of drug design have belonged to the methodological core of drug development. Rational drug design based on structural knowledge of protein targets and on computational modelling of drug–target interaction holds out the promise of a predictable development process for highly innovative drugs. Still, it remains a challenge to make the available structural information fruitful for lead design. As a consequence, rational design is becoming increasingly interwoven with high-throughput screening. In addition, the relationship to the emerging systems-oriented approaches has yet to be specified.     

Toward Rational Fragment-Based Lead Design without 3D Structures

Fragment-based lead discovery (FBLD) has become a prime component of the armamentarium of modern drug design programs. FBLD identifies low molecular weight ligands that weakly bind to important biological targets. Three-dimensional structural information about the binding mode is provided by X-ray crystallography or NMR spectroscopy and is subsequently used to improve the lead compounds. Despite tremendous success rates, FBLD relies on the availability of high-resolution structural information, still a bottleneck in drug discovery programs. To overcome these limitations, we recently demonstrated that the meta-structure approach provides an alternative route to rational lead identification in cases where no 3D structure information about the biological target is available. Combined with information-rich NMR data, this strategy provides valuable information for lead development programs. We demonstrate with several examples the feasibility of the combined NMR and meta-structure approach to devise a rational strategy for fragment evolution without resorting to highly resolved protein complex structures.     

Structural bioinformatic approaches to the discovery of new antimycobacterial drugs

Integrated bioinformatic approaches to drug discovery exploit computational techniques to examine the flow of information from genome to structure to function. Informatics is being be used to accelerate and rationalize the process of antimycobacterial drug discovery and design, with the immediate goals to identify viable drug targets and produce a set of critically evaluated protein target models and corresponding set of probable lead compounds. Bioinformatic approaches are being successfully applied in the selection and prioritization of putative mycobacterial drug target genes; computational modelling and x-ray structure validation of protein targets with drug lead compounds; simulated docking and virtual screening of potential lead compounds; and lead validation and optimization using structure-activity and structure-function relationships. By identifying active sites, characterizing patterns of conserved residues and, where relevant, predicting catalytic residues, bioinformatics provides information to aid the design of selective and efficacious pharmacophores. In this review, we describe selected recent progress in antimycobacterial drug design, illustrating the strengths and limitations of current structural bioinformatic approaches as tools in the fight against tuberculosis.     

Approaching Target Selectivity by De Novo Drug Design

ABSTRACT

Introduction: The development of drug candidates with a defined selectivity profile and a unique molecular structure is of fundamental interest for drug discovery. In contrast to the costly screening of large substance libraries, the targeted de novo design of a drug by using structural information of either the biological target and/or structure–activity relationship data of active modulators offers an efficient and intellectually appealing alternative.

Areas covered: This review provides an overview on the different techniques of de novo drug design (ligand-based drug design, structure-based drug design, and fragment-based drug design) and highlights successful examples of this targeted approach toward selective modulators of therapeutically relevant targets.

Expert opinion: De novo drug design has established itself as a very efficient method for the development of potent and selective modulators for a variety of different biological target classes. The ever-growing wealth of structural data on therapeutic targets will certainly further enhance the importance of de novo design for the drug discovery process in the future. However, a consistent use of the terminology of de novo drug design in the scientific literature should be sought.     

Re-discovering PDE3 inhibitors--new opportunities for a long neglected target

The PDE3 enzymes or "low Km cGMP-inhibited phosphodiesterases" have long been established as important mediators of cellular physiology, and synthetic PDE3 inhibitors have been critical to the delineation of the enzymes' roles. Yet despite decades of progress on the biology of these enzymes, the medicinal chemistry landscape relating to PDE3 inhibitors has remained essentially unchanged since the mid 1990's. Up until then the field was at the cutting edge of drug design; without the tools of molecular and structural biology, molecules of high potency were being achieved using logical pharmacophore models and lead modification. Yet virtually all the impetus went out of this area on the back of failures at the clinic and PDE3 as a therapeutic target largely fell out of favour. A decade later and with the "new" technologies of structural and molecular biology breathing new life into PDE3 research in general, PDE3 inhibitors are sought for target validation in an array of therapeutic applications. In this review, we examine the current state of PDE3 research; firstly we summarize the structural and functional properties of PDE3 enzymes with particular attention to the heterogeneity within this class of enzymes which differ markedly in expression, localisation and means of regulation across various tissue types. It is the structural and functional complexity of the PDE3 enzymes that underpins the re-emergence of PDE3s roles as targets for drug design. We then look at past clinical evaluation of PDE3 inhibitors that occurred without that information and which may have had a significant bearing on the outcome of those drug discovery efforts. Finally we look at current approaches to the design of PDE3 inhibitors which utilize that historic data but also incorporate new inputs from structural biology and combinatorial chemistry.     

Thermodynamic studies for drug design and screening

INTRODUCTION: A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. AREAS COVERED: This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 - 2011 using the Science Citation Index and PUBMED and the keywords listed below. EXPERT OPINION: The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development toward an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in the design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design.     

Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein-ligand binding interactions

Representing and understanding the three-dimensional (3D) structural information of protein-ligand complexes is a critical step in the rational drug discovery process. Traditional analysis methods are proving inadequate and inefficient in dealing with the massive amount of structural information being generated from X-ray crystallography, NMR, and in silico approaches such as structure-based docking experiments. Here, we present SIFt (structural interaction fingerprint), a novel method for representing and analyzing 3D protein-ligand binding interactions. Key to this approach is the generation of an interaction fingerprint that translates 3D structural binding information from a protein-ligand complex into a one-dimensional binary string. Each fingerprint represents the "structural interaction profile" of the complex that can be used to organize, analyze, and visualize the rich amount of information encoded in ligand-receptor complexes and also to assist database mining. We have applied SIFt to tackle three common tasks in structure-based drug design. The first involved the analysis and organization of a typical set of results generated from a docking study. Using SIFt, docking poses with similar binding modes were identified, clustered, and subsequently compared with conventional scoring function information. A second application of SIFt was to analyze approximately 90 known X-ray crystal structures of protein kinase-inhibitor complexes obtained from the Protein Databank. Using SIFt, we were able to organize the structures and reveal striking similarities and diversity between their small molecule binding interactions. Finally, we have shown how SIFt can be used as an effective molecular filter during the virtual chemical library screening process to select molecules with desirable binding mode(s) and/or desirable interaction patterns with the protein target. In summary, SIFt shows promise to fully leverage the wealth of information being generated in rational drug design.     

Small molecule crystallography in drug design

Crystal structures of small molecules (i.e. isolated ligands) are a source of valuable structural information helpful in the process of drug design (pharmacophore model elaborations, 3D QSAR, docking, and de novo design). Indeed, structural data obtained from small molecules crystallography can approach ligand-receptor binding by providing unique structural features both about the conformation (internal geometry) of the ligand (s) and about the intermolecular interaction potentially occurring within the active site of a target (enzyme/receptor). Small molecule crystal structure databases can also be used in three dimensional search to identify new drug candidates. Future development in small molecule crystallography (e.g. powder diffraction) should also provide original solutions to complex problems related to polymorphism.     

Homology modeling of G-protein-coupled receptors and implications in drug design

G-protein-coupled receptors (GPCRs) are considered therapeutically important due to their involvement in a variety of processes governing several cellular functions, and their tractability as drug targets. A large percentage of drugs on the market, and in development stages, target the super family of the GPCRs. The enormous interest in GPCR drug design is, however, limited by the scarcity of structural information. The only GPCR for which a three dimensional (3D) structure is reported is bovine rhodopsin and it belongs to class A of the GPCR family. As a result, there has been considerable interest in alternative techniques, for example, homology modeling of GPCRs, in order to derive useful three dimensional models of other proteins for use in structure-based drug design. However, homology modeling of GPCRs is not straightforward, and encounters several problems, owing to the availability of a single structural template, as well as the low degree of sequence homology between the template and target sequences. There are several key issues which need to be considered during every stage of GPCR homology modeling, in order to derive reasonable 3D models. Homology modeling of GPCRs has been utilized increasingly in the past few years and has been successful, not only in furthering the understanding of ligand-protein interactions, but also in the identification of new and potent ligands. Thus, with the lessons learned from past experiences and new developments, homology modeling in case of GPCRs can be harnessed for developing more reliable three dimensional models. This, in turn, will provide better tools to use in structure-based drug design leading to the identification of novel and potent GPCR ligands for several therapeutic indications.     

Many Approved Drugs Have Bioactive Analogs With Different Target Annotations

Close structural relationships between approved drugs and bioactive compounds were systematically assessed using matched molecular pairs. For structural analogs of drugs, target information was assembled from ChEMBL and compared to drug targets reported in DrugBank. For many drugs, multiple analogs were identified that were active against different targets. Some of these additional targets were closely related to known drug targets while others were not. Surprising discrepancies between reported drug targets and targets of close structural analogs were often observed. On one hand, the results suggest that hypotheses concerning alternative drug targets can often be formulated on the basis of close structural relationships to bioactive compounds that are easily detectable. It is conceivable that such obvious structure–target relationships are frequently not considered (or might be overlooked) when compounds are developed with a focus on a primary target and a few related (or undesired) ones. On the other hand, our findings also raise questions concerning database content and drug repositioning efforts.     

Recent kinase and kinase inhibitor X-ray structures: mechanisms of inhibition and selectivity insights

Recent years have seen an explosion in the number of publicly available x-ray crystal structures of protein kinases. These structures have provided a wealth of information on the regulatory mechanisms, conformational plasticity and drugability of this important family of enzymes. Drawing upon structural information, new insights into the development of protein kinase inhibitors are discussed including de-novo design, molecular templates for ATP competitive inhibitors and alternative mechanisms of inhibition. The highly conserved nature of the ATP binding site is of central concern to drug development and the concept of a selectivity profile has arisen with structure-based design emerging as a key tool for addressing the challenges of specificity. In addition, protein-ligand complexes, where the enzyme is in an inactive conformation, signify an alternate approach to protein kinase inhibition. The belief that an inactive kinase presents a less conserved target is reviewed using observations on the structural changes occurring during protein kinase regulation.     

Impact of recombinant DNA technology and protein engineering on structure-based drug design: case studies of HIV-1 and HCMV proteases

Structure-based drug design is an organized, multidisciplinary endeavor undertaken by scientists from many different scientific fields. The success of structure-based drug design was only made possible by advances in structure biology that provides the three-dimensional structure of the drug design target with which small molecular chemical ligands interact. Visualization of the conformation and interactions of a small molecule ligand bound to the protein target in the co-crystal structure of the protein:ligand complex enables the design of new chemical compounds with improved binding affinity and specificity. With the advances in molecular biology, lab automation, and computational science, genomic data have now become available for the human genome, as well as various other organisms. The pharmaceutical industry is currently putting forth tremendous effort in the area of functional genomics and structural genomics in attempts to decipher functions and structures of protein encoded by genes, with the ultimate goal of identifying novel targets for drug discovery and development. This chapter discusses the significant impact made by recombinant DNA technology and protein engineering on structural biology and, more specifically, on structure-based drug design.     

The structure of inosine 5'-monophosphate dehydrogenase and the design of novel inhibitors

The enzyme IMPDH is a homotetramer of approximately 55 kDa subunits and consists of a (beta/alpha)(8) barrel core domain and a smaller subdomain. The active site has binding pockets for the two substrates IMP and NAD. The enzymatic reaction of oxidation of IMP to XMP proceeds through a covalent mechanism involving an active site cysteine residue.This enzyme is a target for immunosuppressive agents because it catalyzes a key step in purine nucleotide biosynthesis which is important for the proliferation of lymphocytes. Several X-ray structures of inhibitors bound to IMPDH have been published. The uncompetitive IMPDH inhibitor MPA is the active metabolite of the immunosuppressive agent mycophenolate mofetil (CellCept(R)) which is approved for the prevention of acute rejection after kidney and heart transplantation. The bicyclic ring system of MPA packs underneath the hypoxanthine ring of XMP*, thereby trapping this covalent intermediate of the enzymatic reaction. Ribavirin monophosphate, the active metabolite of the antiviral agent ribavirin, is a substrate mimic of IMP. The structure of the two inhibitors 6-Cl-IMP and SAD binding in the IMP and NAD pockets of IMPDH, respectively, gives information for the binding mode of the di-nucleotide cofactor to the enzyme.At Vertex Pharmaceuticals a structure-based drug design program for the design of IMPDH inhibitors was initiated. Several new lead compound classes unrelated to other IMPDH inhibitors were found. Integrating structural information into an iterative drug-design process led to the design of VX-497. VX-497 is a potent uncompetitive enzyme inhibitor of IMPDH. The phenyl-oxazole moiety of the molecule packs underneath XMP*, analogous to MPA. VX-497 also makes several new interactions that are not observed in the binding of MPA. VX-497 is a potent immunosuppressive agent in vitro and in vivo. A Phase I clinical trial has been successfully concluded and the compound is currently in Phase II trials in psoriasis and hepatitis C. The rapid progress from initiation of the drug design program to a compound entering clinical trials illustrates the power of structure-based drug design to accelerate the drug discovery process.The structural information on IMPDH has also significantly increased our knowledge about the mechanistic details of this fascinating enzyme.     

The hunt for antimitotic agents: an overview of structure-based design strategies

ABSTRACT

Introduction: Structure-based drug discovery offers a rational approach for the design and development of novel anti-mitotic agents which target specific proteins involved in mitosis. This strategy has paved the way for development of a new generation of chemotypes which selectively interfere with the target proteins. The interference of these anti-mitotic targets implicated in diverse stages of mitotic cell cycle progression culminates in cancer cell apoptosis.

Areas covered: This review covers the various mitotic inhibitors developed against validated mitotic checkpoint protein targets using structure-based design and optimization strategies. The protein-ligand interactions and the insights gained from these studies, culminating in the development of more potent and selective inhibitors, have been presented.

Expert opinion: The advent of structure-based drug design coupled with advances in X-ray crystallography has revolutionized the discovery of candidate lead molecules. The structural insights gleaned from the co-complex protein-drug interactions have provided a new dimension in the design of anti-mitotic molecules to develop drugs with a higher selectivity and specificity profile. Targeting non-catalytic domains has provided an alternate approach to address cross-reactivity and broad selectivity among kinase inhibitors. The elucidation of structures of emerging mitotic drug targets has opened avenues for the design of inhibitors that target cancer.     

Thermodynamic studies for drug design and screening

Introduction: A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions.

Areas covered: This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 – 2011 using the Science Citation Index and PUBMED and the keywords listed below.

Expert opinion: The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development toward an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in the design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design.     

Structural biology and drug discovery

In the past few years macromolecular crystallography has become a standard technique used by many pharmaceutical and biotechnology companies. This methodology offers details of protein-ligand interactions at levels of resolution virtually unmatched by any other technique, and this approach holds the promise of novel, more effective, safer and cheaper drugs. Although crystallography remains a laborious and rather expensive technique, remarkable advances in structure determination and structure based drug design (SBDD) have been made in recent years. This process has been aided by recent technological innovations such as high-throughput crystallization, high performance synchrotron beamlines, and new methods in structural bioinformatics and computational chemistry prompted by the structural genomics effort. As a consequence of the increased availability of structural data, the use of structure-based information has expanded from simple protein-ligand interaction analysis to include other aspects of the drug discovery process like target selection and initial lead discovery that used to be almost the exclusive property of biology and chemistry. This review will cover recent examples to illustrate how macromolecular crystallography has evolved and how structural information is now being used in the different stages of the drug discovery process. Advantages and shortcomings of the methodology will also be discussed.     

Utilizing peptide structures as keys for unlocking challenging targets

Three-dimensional structures of protein targets have proven to be extremely valuable for modern drug design and discovery. For cases where the structure of the protein is unattainable, such as G-protein coupled receptors (GPCRs), structural information on active ligands is still useful and helpful for deciphering the geometrical and chemical features of the active site. Peptides, constructed from easy-to-form amide backbones and featuring variable side-chains, have an inherent advantage in generating rapid quantitative structure-activity relationships (QSAR). Given the fact that peptides are natural ligands for many protein targets, structural investigation of a series of related peptides, typically carried out via nuclear magnetic resonance (NMR), can result in an accurate pharmacophore model. Such a model can be used for virtual screening, and to assist design of second-generation peptidomimetics with improved properties and design of non-peptidic leads. In this article, we will review examples in which a structural approach utilizing peptide ligands was employed to obtain a better understanding of the target active site. We will focus on cases where such information supplied guidance toward the discovery of small molecule ligands.     

MD studies on neuraminidase for probing binding pose of its inhibitors

Influenzal neuraminidase (NA) has proven to be potential drug target in designing anti-influenza drugs. The active site residues of group-1 and group-2 NA exhibit similarities, such that as structure-based drug design on group-2 NA has given potential anti-influenza drugs showing activity against group-1 as well as group-2 NA. The 150 (Gly147 to Asp151)-loop of NA has been reported to be the cause for the structural differences in the group-1 and group-2 NA enzymes. A cavity arises from an open conformation of the 150 loop which closes upon ligand binding has been reported for group-1 NA. Also recent studies have illustrated that mutation not only causes variation in the active site geometry but also changes the binding orientation of the NA inhibitors. To understand and examine the dynamic nature of ligand binding to NA, we have performed molecular dynamics simulations on NA. The docking study for the reported influenza inhibitors has been performed on averaged structure obtained from three minimum energy conformations of molecular dynamics (MD) trajectory. These results were compared with docking studies done on reported crystal structure of NA (PDB ID 3B7E). The information obtained from these studies can be used for the rational design of novel NA inhibitors.     

Targeting of AMP-activated protein kinase: prospects for computer-aided drug design

Introduction: Dysregulation of energy homeostasis has been implicated in a number of human chronic diseases including diabetes, obesity, cancer, and inflammation. Given the functional attributes as a central regulator of energy homeostasis, AMP-activated protein kinase (AMPK) is emerging as a therapeutic target for these diseases, and lines of evidence have highlighted the need for rational and robust screening systems for identifying specific AMPK modulators with a therapeutic potential for preventing and/or curing these diseases.

Areas covered: Here, the authors review the recent advances in the understanding of three-dimensional structures of AMPK in relationship with the regulatory mechanisms, potentials of AMPK as a therapeutic target in human chronic diseases, and prospects of computer-based drug design for AMPK.

Expert opinion: Accumulating information of AMPK structure has provided us with deep insight into the molecular basis underlying the regulatory mechanisms, and further discloses several structural domains, which can be served for a target site for computer-based drug design. Molecular docking and simulations provides useful information about the binding sites between potent drugs and AMPK as well as a rational screening format to discover isoform-specific AMPK modulators. For these reasons, the authors suggest that computer-aided virtual screening methods hold promise as a rational approach for discovering more specific AMPK modulators.