Scaffold hopping

Classification of scaffold-hopping approaches

The general goal of drug discovery is to identify novel compounds that are active against a preselected biological target with acceptable pharmacological properties defined by marketed drugs. Scaffold hopping has been widely applied by medicinal chemists to discover equipotent compounds with novel backbones that have improved properties. In this article we classify scaffold hopping into four major categories, namely heterocycle replacements, ring opening or closure, peptidomimetics and topology-based hopping. We review the structural diversity of original and final scaffolds with respect to each category. We discuss the advantages and limitations of small, medium and large-step scaffold hopping. Finally, we summarize software that is frequently used to facilitate different kinds of scaffold-hopping methods.

Differentiation and visualization of diverse cellular phenotypic responses in primary high-content screening

High-throughput screening, based on subcellular imaging, has become a powerful tool in lead discovery. Through the generation of high-quality images, not only the specific target signal can be analyzed but also phenotypic changes of the whole cell are recorded. Yet analysis strategies for the exploration of high-content screening results, in a manner that is independent from predefined control phenotypes, are largely missing. The approach presented here is based on a well-established modeling technique, self-organizing maps (SOMs), which uses multiparametric results to group treatments that create similar morphological effects. This report describes a novel visualization of the SOM clustering by using an image of the cells from each node, with the most representative cell highlighted to deploy the phenotype described by each node. The approach has the potential to identify both expected hits and novel cellular phenotypes. Moreover, different chemotypes, which cause the same phenotypic effects, are identified, thus facilitating "scaffold hopping."

Chemical informatics: using molecular shape descriptors in structure-based drug design

The concept of molecular shape has been considered in various forms in the context of drug design. The following chapter details the application of molecular shape to the design of compound libraries for assessment of potential biological activity. Whilst the utility of shape descriptors is well documented in the area of ligand similarity, the use of shape descriptors is equally applicable to protein structures. Indeed, work has been published using various descriptors to compare proteins but little published where protein shape descriptors have been used to investigate ligand selectivity.

Pyridobenzothiazole derivatives as new chemotype targeting the HCV NS5B polymerase

Hepatitis C virus (HCV) infection has been recognized as the major cause of liver failure that can lead to hepatocellular carcinoma. Among all the HCV proteins, NS5B polymerase represents a leading target for drug discovery strategies. Herein, we describe our initial research efforts towards the identification of new chemotypes as allosteric NS5B inhibitors. In particular, the design, synthesis, in vitro anti-NS5B and in cellulo anti-HCV evaluation of a series of 1-oxo-1H-pyrido[2,1-b][1,3]benzothiazole-4-carboxylate derivatives are reported. Some of the newly synthesized compounds showed an IC(50) ranging from 11 to 23 μM, and molecular modeling and biochemical studies suggested that the thumb domain could be the target site for this new class of NS5B inhibitors.

Modeling of human prokineticin receptors: interactions with novel small-molecule binders and potential off-target drugs

BACKGROUND AND MOTIVATION

The Prokineticin receptor (PKR) 1 and 2 subtypes are novel members of family A GPCRs, which exhibit an unusually high degree of sequence similarity. Prokineticins (PKs), their cognate ligands, are small secreted proteins of ∼80 amino acids; however, non-peptidic low-molecular weight antagonists have also been identified. PKs and their receptors play important roles under various physiological conditions such as maintaining circadian rhythm and pain perception, as well as regulating angiogenesis and modulating immunity. Identifying binding sites for known antagonists and for additional potential binders will facilitate studying and regulating these novel receptors. Blocking PKRs may serve as a therapeutic tool for various diseases, including acute pain, inflammation and cancer.

METHODS AND RESULTS

Ligand-based pharmacophore models were derived from known antagonists, and virtual screening performed on the DrugBank dataset identified potential human PKR (hPKR) ligands with novel scaffolds. Interestingly, these included several HIV protease inhibitors for which endothelial cell dysfunction is a documented side effect. Our results suggest that the side effects might be due to inhibition of the PKR signaling pathway. Docking of known binders to a 3D homology model of hPKR1 is in agreement with the well-established canonical TM-bundle binding site of family A GPCRs. Furthermore, the docking results highlight residues that may form specific contacts with the ligands. These contacts provide structural explanation for the importance of several chemical features that were obtained from the structure-activity analysis of known binders. With the exception of a single loop residue that might be perused in the future for obtaining subtype-specific regulation, the results suggest an identical TM-bundle binding site for hPKR1 and hPKR2. In addition, analysis of the intracellular regions highlights variable regions that may provide subtype specificity.

Design and synthesis of inhibitors of noroviruses by scaffold hopping

A scaffold hopping strategy was employed to identify new chemotypes that inhibit noroviruses. The replacement of the cyclosulfamide scaffold by an array of heterocyclic scaffolds lead to the identification of additional series of compounds that possessed anti-norovirus activity in a cell-based replicon system.

Identifying compound-target associations by combining bioactivity profile similarity search and public databases mining

Molecular target identification is of central importance to drug discovery. Here, we developed a computational approach, named bioactivity profile similarity search (BASS), for associating targets to small molecules by using the known target annotations of related compounds from public databases. To evaluate BASS, a bioactivity profile database was constructed using 4296 compounds that were commonly tested in the US National Cancer Institute 60 human tumor cell line anticancer drug screen (NCI-60). Each compound was used as a query to search against the entire bioactivity profile database, and reference compounds with similar bioactivity profiles above a threshold of 0.75 were considered as neighbor compounds of the query. Potential targets were subsequently linked to the identified neighbor compounds by using the known targets of the query compound. About 45% of the predicted compound-target associations were successfully verified retrospectively, suggesting the possible application of BASS in identifying the targets of uncharacterized compounds and thus providing insight into the study of promiscuity and polypharmacology. Furthermore, BASS identified a significant fraction of structurally diverse compounds with similar bioactivities, indicating its feasibility of “scaffold hopping” in searching novel molecules against the target of interest.

Novel inhibitors of trihydroxynaphthalene reductase with antifungal activity identified by ligand-based and structure-based virtual screening

Curvularia lunata is a dark pigmented fungus that is the causative agent of several diseases in plants and in both immunodeficient and immunocompetent patients. 1,8-Dihydroxynaphthalene-melanin is found in the cell wall of C. lunata and is believed to be the important virulence factor of dematiaceous fungi. Trihydroxynaphthalene reductase is an enzyme of the 1,8-dihydroxynaphthalene-melanin biosynthetic pathway, and it thus represents an emerging target for the development of novel fungicides and antimycotics. In the present study, we describe novel inhibitors of trihydroxynaphthalene reductase from C. lunata. These inhibitors were identified by ligand-based three-dimensional similarity searching and docking to a homology-built model and by subsequent biochemical and antifungal evaluation. Discovery of competitive inhibitors with K(i) values in low micromolar and even nanomolar concentration range proves the aplicability of homology-built model of 3HNR for hit finding by virtual screening methods.

Discovery of new photoactivatable diaryltetrazoles for photoclick chemistry via 'scaffold hopping'

We report the discovery of two long-wavelength (365 nm) photoactivatable diaryltetrazoles through screening a small library of diaryltetrazoles that were designed using a 'scaffold hopping' strategy. A naphthalene-derived tetrazole showed excellent reactivity in the photoinduced cycloaddition reaction with methyl methacrylate under 365 nm photoirradiation in acetonitrile PBS buffer mixture. Besides, the brightly fluorescent pyrazoline cycloadducts that were formed further increase the potential utility of these new diaryltetrazoles as 'photoclick' reagents and as reporters in biological studies.

Effectiveness of 2D fingerprints for scaffold hopping

Background: It has been suggested that similarity searching using 2D fingerprints may not be suitable for scaffold hopping. Methods: This article reports a detailed evaluation of the effectiveness of six common types of 2D fingerprints when they are used for scaffold-hopping similarity searches of the Molecular Design Limited Drug Data Report database, World of Molecular Bioactivity database and Maximum Unbiased Validation database. Results: The results demonstrate that 2D fingerprints can be used for scaffold hopping, with novel scaffolds being identified in nearly every search that was carried out. The degree of enrichment depends on the structural diversity of the actives that are being sought, with the greatest enrichments often being obtained using the extended connectivity fingerprint encoding a circular substructure of diameter four bonds (ECFP4) fingerprint. Conclusion: 2D fingerprints provide a simple and computationally efficient way of identifying novel chemotypes in lead-discovery programs.

De novo design: balancing novelty and confined chemical space

IMPORTANCE OF THE FIELD

De novo drug design serves as a tool for the discovery of new ligands for macromolecular targets as well as optimization of known ligands. Recently developed tools aim to address the multi-objective nature of drug design in an unprecedented manner.

AREAS COVERED IN THIS REVIEW

This article discusses recent advances in de novo drug design programs and accessory programs used to evaluate compounds post-generation.

WHAT THE READER WILL GAIN

The reader is introduced to the challenges inherent in de novo drug design and will become familiar with current trends in de novo design. Furthermore, the reader will be better prepared to assess the value of a tool, and be equipped to design more elegant tools in the future.

TAKE HOME MESSAGE

De novo drug design can assist in the efficient discovery of new compounds with a high affinity for a given target. The inclusion of existing chemoinformatic methods with current structure-based de novo design tools provides a means of enhancing the therapeutic value of these generated compounds.

Bioisosteric Replacement and Scaffold Hopping in Lead Generation and Optimization

Bioisosteric replacement and scaffold hopping are twin methods used in drug design to improve the synthetic accessibility, potency and drug like properties of a compound and to move into novel chemical space. Bioisosteric replacement involves swapping functional groups of a molecule with other functional groups that have similar biological properties. Scaffold hopping is the replacement of the core framework of a molecule with another scaffold that will improve the properties of the molecule or to find similar potent compounds that exist in novel chemical space. This review outlines the key concepts, importance and challenges of both methods using examples and comparisons of techniques available for finding bioisosteric replacements and scaffold hops. There are many methods available for bioisosteric replacement and scaffold hopping, all with their own advantages and disadvantages. Drug design projects would benefit from a combination of these methods to retrieve diverse and complimentary results. Continuing progress in these fields will allow further validation of both methods as well as the accumulation of knowledge on bioisosteres and possible scaffold replacements.

Drug discovery: phosphinolactone, in vivo bioisostere of the lactol group

In drug discovery, structural modifications over the lead molecule are often crucial for the development of a drug. Herein, we reported the first in vivo bioisosteric effect of phosphinolactone function in relation to the lactol group constituting the bioactive molecule: Hydroxybupropion. The preparation of phosphinolactone analogues and their antidepressant evaluation towards forced swimming test in mice showed that biological activity was regained and even strengthen.

Similarity searching using 2D structural fingerprints

This chapter reviews the use of molecular fingerprints for chemical similarity searching. The fingerprints encode the presence of 2D substructural fragments in a molecule, and the similarity between a pair of molecules is a function of the number of fragments that they have in common. Although this provides a very simple way of estimating the degree of structural similarity between two molecules, it has been found to provide an effective and an efficient tool for searching large chemical databases. The review describes the historical development of similarity searching since it was first described in the mid-1980s, reviews the many different coefficients, representations, and weightings that can be combined to form a similarity measure, describes quantitative measures of the effectiveness of similarity searching, and concludes by looking at current developments based on the use of data fusion and machine learning techniques.

Novel 3-aminopyrazole inhibitors of MK-2 discovered by scaffold hopping strategy

New, selective 3-aminopyrazole based MK2-inhibitors were discovered by scaffold hopping strategy. The new derivatives proved to inhibit intracellular phosphorylation of hsp27 as well as LPS-induced TNFalpha release in cells. In addition, selected derivative 14e also inhibited LPS-induced TNFalpha release in vivo.

Using Tversky similarity searches for core hopping: finding the needles in the haystack

The combination of Daylight fingerprints and the Tversky coefficient is a powerful method for performing core hopping, that is, scaffold (or lead) hopping where the main structural difference between the query and bioactive target molecule is located in the central core of the molecular structure. However, a major disadvantage of this approach is the fact that a large number of false positives (in the context of core hopping) are retrieved. The tool we have developed and which is described here can be used to postprocess the hits from Daylight Tversky similarity searches by fragmenting the molecules and subsequently annotating them in a way that assists the users in removing false positives and enables them to better focus on molecules of interest. To validate our approach, we have selected four biological targets for which scaffold hopping examples have been reported. We present results from searches in databases containing published activity data and the subsequent analysis of the hits aimed at establishing the potential of our approach.

Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models

Monoamine Oxidase B interaction with known ligands was investigated using combined pharmacophore and structure based modeling approach. The docking results suggested that the pharmacophore and docking models are in good agreement and are used to identify the selective MAO-B inhibitors. The best model, Hypo2 consists of three pharmacophore features, i.e., one hydrogen bond acceptor, one hydrogen bond donor and one ring aromatic. The Hypo2 model was used to screen an in-house database of 80,000 molecules and have resulted in 5500 compounds. Docking studies were performed, subsequently, on the cluster representatives of 530 hits from 5500 compounds. Based on the structural novelty and selectivity index, we have suggested 15 selective MAO-B inhibitors for further synthesis and pharmacological screening.

Virtual screening to successfully identify novel janus kinase 3 inhibitors: a sequential focused screening approach

In an effort to identify novel Janus kinase 3 inhibitors, a sequential focused screening approach was adopted to search our in-house chemical database. By biologically testing only 79 selected compounds, we successfully identified 19 compounds showing IC 50 < 20 microM, with four of them in the nanomolar range. Particularly, a 3,5-disubstituted pyrazolo[4,3- d]pyrimidine scaffold emerged as a promising candidate for further lead optimization. With the advantages of efficiency and flexibility, this approach may be utilized to identify leads for other therapeutic targets.

ParaFrag--an approach for surface-based similarity comparison of molecular fragments

A frequent task in computer-aided drug design is to identify novel chemotypes similar in activity but structurally different to a given reference structure. Here we report the development of a novel method for atom-independent similarity comparison of molecular fragments (substructures of drug-like molecules). The fragments are characterized by their local surface properties coded in the form of 3D pharmacophores. As surface properties, we used the electrostatic potential (MEP), the local ionization energy (IE(L)), local electron affinity (EA(L)) and local polarizability (POL) calculated on isodensity surfaces. A molecular fragment can then be represented by a minimal set of extremes for each surface property. We defined a tolerance sphere for each of these extremes, thus allowing us to assess the similarity of fragments in an analogous manner to classical pharmacophore comparison. As a first application of this method we focused on comparing rigid fragments suitable for scaffold hopping. A retrospective analysis of successful scaffold hopping reported for Factor Xa inhibitors [Wood MR et al (2006) J Med Chem 49:1231] showed that our method performs well where atom-based similarity metrics fail.

New directions in library design and analysis

The high costs associated with high-throughput screening (HTS) coupled with the limited coverage and bias of current screening collections is such that diversity analysis continues to be an important criterion in lead generation. Whereas early approaches to diversity analysis were based on traditional descriptors such as two-dimensional fingerprints a recent emphasis has been on assessing scaffold coverage to ensure that a variety of different chemotypes are represented. Moreover, whether designing diverse or focused libraries, it is widely recognised that designs should aim to achieve a balance in a number of different properties and multiobjective optimisation provides an effective way of achieving such designs.

Discovery of a novel indole series of EP1 receptor antagonists by scaffold hopping

We describe the medicinal chemistry approach that generated a novel indole series of EP(1) receptor antagonists. The SAR of this new template was evaluated and culminated in the identification of compound 12g which demonstrated in vivo efficacy in a preclinical model of inflammatory pain.

Ultrafast shape recognition for similarity search in molecular databases

Molecular databases are routinely screened for compounds that most closely resemble a molecule of known biological activity to provide novel drug leads. It is widely believed that three-dimensional molecular shape is the most discriminating pattern for biological activity as it is directly related to the steep repulsive part of the interaction potential between the drug-like molecule and its macromolecular target. However, efficient comparison of molecular shape is currently a challenge. Here, we show that a new approach based on moments of distance distributions is able to recognize molecular shape at least three orders of magnitude faster than current methodologies. Such an ultrafast method permits the identification of similarly shaped compounds within the largest molecular databases. In addition, the problematic requirement of aligning molecules for comparison is circumvented, as the proposed distributions are independent of molecular orientation. Our methodology could be also adapted to tackle similar hard problems in other fields, such as designing content-based Internet search engines for three-dimensional geometrical objects or performing fast similarity comparisons between proteins. From a broader perspective, we anticipate that ultrafast pattern recognition will soon become not only useful, but also essential to address the data explosion currently experienced in most scientific disciplines.

Similarity in drugs: reflections on analogue design

A survey of novel small-molecule therapeutics reveals that the majority of them result from analogue design and that their market value represents two-thirds of all small-molecule sales. In natural science, the term analogue, derived from the Latin and Greek analogia, has always been used to describe structural and functional similarity. Extended to drugs, this definition implies that the analogue of an existing drug molecule shares structural and pharmacological similarities with the original compound. Formally, this definition allows the establishment of three categories of drug analogues: analogues possessing chemical and pharmacological similarities (direct analogues); analogues possessing structural similarities only (structural analogues); and chemically different compounds displaying similar pharmacological properties (functional analogues).

Ultrafast shape recognition to search compound databases for similar molecular shapes

Finding a set of molecules, which closely resemble a given lead molecule, from a database containing potentially billions of chemical structures is an important but daunting problem. Similar molecular shapes are particularly important, given that in biology small organic molecules frequently act by binding into a defined and complex site on a macromolecule. Here, we present a new method for molecular shape comparison, named ultrafast shape recognition (USR), capable of screening billions of compounds for similar shapes using a single computer and without the need of aligning the molecules before testing for similarity. Despite its extremely fast comparison rate, USR will be shown to be highly accurate at describing, and hence comparing, molecular shapes.

Scaffold selection and scaffold hopping in lead generation: a medicinal chemistry perspective

Hit selection and lead generation are crucial for the success of the resource-demanding lead-optimization phase in drug discovery, and represent a major research area of medicinal chemistry today. Ligand-binding efficiency, ligand complexity, ligand-target profile complementarity and chemical tractability are important parameters in hit selection. As synthesis and assay throughput improve, a large number of analogs based on the same scaffold can be rapidly synthesized and tested. Consequently, more chemistry resources could be devoted to scaffold modifications to expand the candidate pool in lead generation. Most recently discovered druggable targets are promiscuous toward lipophilic ligands, and the hydrophobic portions of hit compounds should be preferentially modified in analog and scaffold design.

Identification of target-specific bioisosteric fragments from ligand–protein crystallographic data

Bioisosteres are functional groups or atoms that are structurally different but that can form similar intermolecular interactions. Potential bioisosteres were identified here from analysing the X-ray crystallographic structures for sets of different ligands complexed with a fixed protein. The protein was used to align the ligands with each other, and then pairs of ligands compared to identify substructural features with high volume overlap that occurred in approximately the same region of geometric space. The resulting pairs of substructural features can suggest potential bioisosteric replacements for use in lead-optimisation studies. Experiments with 12 sets of ligand-protein complexes from the Protein Data Bank demonstrate the effectiveness of the procedure.

Hierarchical Strategy for Identifying Active Chemotype Classes in Compound Databases

A general methodology is presented for analyzing patterns of activity in compound databases, which is based on the use of structural chemotypes and provides a focused, hierarchical classification of active compounds. Each node in the hierarchical tree corresponds to a specific chemotype and is labeled by a unique code or identifier. All chemotypes at a given level of the hierarchy define equivalence classes, and those of higher structural resolution have a strict parent-child (i.e. subset) relationship to those of lower resolution. Active chemotypes contain a relatively high proportion of actives and are characterized through the use of enrichment plots. These plots show the relationship of occupancy to activity enrichment for a set of chemotypes at a given level of structural resolution. Paths through the hierarchy from chemotypes of lower to those of higher structural resolution (e.g. reduced cyclic system skeletons --> cyclic system skeletons --> cyclic systems --> complete molecules) are unique. Unique paths in the hierarchy that only pass through active chemotypes are called chains or paths of actives. These chains provide links for identifying structurally related active compounds at increasing levels of structural resolution. Analysis of actives can also be carried out at any specific level of structural resolution deemed appropriate by the investigator. Chemotype codes can be used to search compound databases for new molecules possessing these codes or sets of hierarchically related codes. An example, based on the NCI AIDS database, is presented that illustrates the general approach and provides a more detailed description of several interesting classes of active chemotypes and their inter-relationships.