Scaffold hopping with molecular field points: identification of a cholecystokinin-2 (CCK2) receptor pharmacophore and its use in the design of a prototypical series of pyrrole- and imidazole-based CCK2 antagonists

The combination of multi-approach studies to explore the potential therapeutic mechanisms of imidazole derivatives as an MCF-7 inhibitor in therapeutic strategies

Breast cancer covers a large area of research because of its prevalence and high frequency all over the world. This study is based on drug discovery against breast cancer from a series of imidazole derivatives. A 3D-QSAR and activity atlas model was developed by exploring the dataset computationally, using the machine learning process of Flare. The dataset of compounds was divided into active and inactive compounds according to their biological and structural similarity with the reference drug. The obtained PLS regression model provided an acceptable r ² = 0.81 and q² = 0.51. Protein-ligand interactions of active molecules were shown by molecular docking against six potential targets, namely, TTK, HER2, GR, NUDT5, MTHFS, and NQO2. Then, toxicity risk parameters were evaluated for hit compounds. Finally, after all these screening processes, compound C10 was recognized as the best-hit compound. This study identified a new inhibitor C10 against cancer and provided evidence-based knowledge to discover more analogs.

Iodine-Mediated Cyclization of Enamines to Imidazole-4-Carboxylic Derivatives with Sequential Removal of Nitrogen Atoms from TMSN3

An iodine-mediated oxidative [4+1] cyclization of enamines with TMSN₃ for the synthesis of 2,5-disubstituted imidazole-4-carboxylic derivatives has been developed. The mechanistic studies revealed that the reaction proceeds through a sequential removal of two nitrogen atoms from TMSN₃. The synthetic utility was further demonstrated with a gram-scale reaction and various derivatization transformations of the products.

CCK2R antagonists: from SAR to clinical trials

The widespread involvement of the cholecystokinin-2/gastrin receptor (CCK₂R) in multiple (patho)physiological processes has propelled extensive searches for nonpeptide small-molecule CCK₂R antagonists. For the past three decades, considerable research has yielded numerous chemically heterogeneous compounds. None of these entered into the clinic, mainly because of inadequate biological effects. However, it appears that the ultimate goal of a clinically useful CCK₂R antagonist is now just around the corner, with the most promising compounds, netazepide and nastorazepide, now in Phase II clinical trials. Here, we illustrate the structure-activity relationships (SARs) of stablished CCK₂R antagonists of various structural classes, and the most recent proof-of-concept studies where new applicabilities of CCK₂R antagonists as visualizing agents are presented.

Field template-based design and biological evaluation of new sphingosine kinase 1 inhibitors

Purpose

Sphingosine kinase 1 (SK1) is a protooncogenic enzyme expressed in many human tumours and is associated with chemoresistance and poor prognosis. It is a potent therapy target and its inhibition chemosensitises solid tumours. Despite recent advances in SK1 inhibitors synthesis and validation, their clinical safety and chemosensitising options are not well described. In this study, we have designed, synthesised and tested a new specific SK1 inhibitor with a low toxicity profile.

Methods

Field template molecular modelling was used for compound design. Lead compounds were tested in cell and mouse cancer models.

Results

Field template analysis of three known SK1 inhibitors, SKI-178, 12aa and SK1-I, was performed and compound screening identified six potential new SK1 inhibitors. SK1 activity assays in both cell-free and in vitro settings showed that two compounds were effective SK1 inhibitors. Compound SK-F has potently decreased cancer cell viability in vitro and sensitised mouse breast tumours to docetaxel (DTX) in vivo, without significant whole-body toxicity.

Conclusion

Through field template screening, we have identified a new SK1 inhibitor, SK-F, which demonstrated antitumour activity in vitro and in vivo without overt toxicity when combined with DTX.

Electronic supplementary material

The online version of this article (10.1007/s10549-018-4900-1) contains supplementary material, which is available to authorized users.

Methods for Virtual Screening of GPCR Targets: Approaches and Challenges

Virtual screening (VS) has become an integral part of the drug discovery process and is a valuable tool for finding novel chemical starting points for GPCR targets. Ligand-based VS makes use of biochemical data for known, active compounds and has been applied successfully to many diverse GPCRs. Recent progress in GPCR X-ray crystallography has made it possible to incorporate detailed structural information into the VS process. This chapter outlines the latest VS techniques along with examples that highlight successful applications of these methods. Best practices for increasing the likelihood of VS success, as well as ongoing challenges, are also discussed.

Core chemotype diversification in the HIV-1 entry inhibitor class using field-based bioisosteric replacement

Demand remains for new inhibitors of HIV-1 replication and the inhibition of HIV-1 entry is an extremely attractive therapeutic approach. Using field-based bioisosteric replacements, we have further extended the chemotypes available for development in the HIV-1 entry inhibitor class. Moreover, using field-based disparity analysis of the compounds, 3D structure-activity relationships were derived that will be useful in the further development of these inhibitors towards clinical utility.

Discovery and optimization of novel small-molecule HIV-1 entry inhibitors using field-based virtual screening and bioisosteric replacement

With the emergence of drug-resistant strains and the cumulative toxicities associated with current therapies, demand remains for new inhibitors of HIV-1 replication. The inhibition of HIV-1 entry is an attractive, yet underexploited therapeutic approach with implications for salvage and preexposure prophylactic regimens, as well as topical microbicides. Using the combination of a field-derived bioactive conformation template to perform virtual screening and iterative bioisosteric replacements, coupled with in silico predictions of absorption, distribution, metabolism, and excretion, we have identified new leads for HIV-1 entry inhibitors.

Molecular fields in ligand discovery

The discovery of novel biologically active small molecules is now a technologically and economically viable proposition for academic and small biotechnology laboratories wishing to build on their biological research into target proteins. Such small molecules may be useful reagents for further biological research or may form the basis for early-stage drug discovery. The availability of specialized virtual screening software to filter large molecular libraries into manageable numbers of compounds for biological assays is the driving force for finding novel ligands. The main focus of this chapter is the basis and use of molecular field methods to assess the interactions that may be made by small molecules. Molecular field based measures of capability and similarity of interaction may be used to discover novel ligands and expand ligand series for potential use as future therapies.

Molecular field technology applied to virtual screening and finding the bioactive conformation

Virtual screening is being applied to reduce the high-throughput screening bottleneck in many pharmaceutical companies and to reduce compound wastage. Cresset's ligand-based virtual screening technology using molecular fields can facilitate rapid identification of novel chemotypes from biologically testing only 200 - 1000 compounds. Four molecular fields calculated using the interaction of different probe atoms with the ligand are sufficient to describe how a ligand binds to its protein. Compounds with similar fields to known active ligands are predicted to have a high probability of showing similar activity. As binding is related to field similarity, this property has been exploited further to predict the bioactive conformation of small sets of structurally diverse active ligands starting from the two-dimensional structures alone without knowledge of the target site structure.

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.

LigMatch: a multiple structure-based ligand matching method for 3D virtual screening

We have developed a new virtual screening (VS) method called LigMatch and evaluated its performance on 13 protein targets using a filtered and clustered version of the directory of useful decoys (DUD). The method uses 3D structural comparison to a crystallographically determined ligand in a bioactive 'template' conformation, using a geometric hashing method, in order to prioritize each database compound. We show that LigMatch outperforms several other widely used VS methods on the 13 DUD targets. We go on to demonstrate that improved VS performance can be gained from using multiple, structurally diverse templates rather than a single template ligand for a particular protein target. In this case, a 2D fingerprint-based method is used to select a ligand template from a set of known bioactive conformations. Furthermore, we show that LigMatch performs well even in the absence of 2D similarity to the template ligands, thereby demonstrating its robustness with respect to purely 2D methods and its potential for scaffold hopping.

De novo molecular modeling and biophysical characterization of Manduca sexta eclosion hormone

Eclosion hormone (EH) is an integral component in the cascade regulating the behaviors culminating in emergence of an insect from its old exoskeleton. Little is known regarding the EH solution structure; consequently, we utilized a computational approach to generate a hypothetical structure for Manduca sexta EH. The de novo algorithm exploited the restricted conformational space of disulfide bonds (Cys14-Cys38, Cys18-Cys34, and Cys21-Cys49) and predicted secondary structure elements to generate a thermodynamically stable structure characterized by 55% helical content, an unstructured N-terminus, a helical C-terminus, and a solvent-exposed loop containing Trp28 and Phe29. Both the strain and pseudo energies of the predicted peptide compare favorably with those of known structures. The 62-amino acid peptide was synthesized, folded, assayed for activity, and structurally characterized to confirm the validity of the model. The helical content is supported by circular dichroism and hydrogen-deuterium exchange mass spectrometry. Fluorescence emission spectra and acrylamide quenching are consistent with the solvent exposure predicted for Trp28, which is shielded by Phe29. Furthermore, thermodynamically stable conformations that deviated only slightly from the predicted Manduca EH structure were generated in silico for the Bombyx mori and Drosophila melanogaster EHs, indicating that the conformation is not species-dependent. In addition, the biological activities of known mutants and deletion peptides were rationalized with the predicted Manduca EH structure, and we found that, on the basis of sequence conservation, functionally important residues map to two conserved hydrophobic clusters incorporating the C-terminus and the first loop.

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.

Rationalizing the activities of diverse cholecystokinin 2 receptor antagonists using molecular field points

Cholecystokinin 2 receptor antagonists encompass a wide range of structures. This makes them unsuitable candidates for existing 3D-QSAR methods and has led us to develop an alternative approach to account for their observed biological activities. A diverse set of 21 antagonists was subjected to a novel molecular field-based similarity analysis. The hypothesis is that compounds with similar field patterns will bind at the same target site regardless of their underlying structure. This initial report demonstrates a linear correlation between ligand similarity and biological activity for this challenging data set. A model generated with three molecules was used to predict the activity of 18 test compounds, with different chemotypes, with a root-mean-square error of 0.68 pKB units. The ability to automatically derive a molecular alignment without knowledge of the protein structure represents an improvement over existing pharmacophore methods and makes the method particularly suitable for scaffold-hopping.

Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR

This chapter discusses recent developments in some of the areas that exploit the molecular similarity principle, novel approaches to capture molecular properties by the use of novel descriptors, focuses on a crucial aspect of computational models-their validity, and discusses additional ways to examine data available, such as those from high-throughput screening (HTS) campaigns and to gain more knowledge from this data. The chapter also presents some of the recent applications of methods discussed focusing on the successes of virtual screening applications, database clustering and comparisons (such as drug- and in-house-likeness), and the recent large-scale validations of docking and scoring programs. While a great number of descriptors and modeling methods has been proposed until today, the recent trend toward proper model validation is very much appreciated. Although some of their limitations are surely because of underlying principles and limitations of fundamental concepts, others will certainly be eliminated in the future.

Streamlining lead discovery by aligning in silico and high-throughput screening

Lead discovery in the pharmaceutical environment is largely an industrial-scale process in which it is typical to screen 1-5 million compounds in a matter of weeks using High Throughput Screening (HTS). This process is a very costly endeavor. Typically a HTS campaign of 1 million compounds will cost anywhere from $500000 to $1000000. There is consequently a great deal of pressure to maximize the return on investment by finding fast and more effective ways to screen. A panacea that has emerged over the past few years to help address this issue is in silico screening. In silico screening is now incorporated in all areas of lead discovery; from target identification and library design, to hit analysis and compound profiling. However, as lead discovery has evolved over the past few years, so has the role of in silico screening.

Computational chemistry-driven decision making in lead generation

Novel starting points for drug discovery projects are generally found either by screening large collections of compounds or smaller more-focused libraries. Ideally, hundreds or even thousands of actives are initially found, and these need to be reduced to a handful of promising lead series. In several sequential steps, many actives are dropped and only some are followed up. Computational chemistry tools are used in this context to predict properties, cluster hits, design focused libraries and search for close analogues to explore the potential of hit series. At the end of hit-to-lead, the project must commit to one, or preferably a few, lead series that will be refined during lead optimization and hopefully produce a drug candidate. Striving for the best possible decision is crucial because choosing the wrong series is a costly one-way street.