Identification of New Potent GPR119 Agonists by Combining Virtual Screening and Combinatorial Chemistry

Perspectives on current approaches to virtual screening in drug discovery

INTRODUCTION

For the past two decades, virtual screening (VS) has been an efficient hit finding approach for drug discovery. Today, billions of commercially accessible compounds are routinely screened, and many successful examples of VS have been reported. VS methods continue to evolve, including machine learning and physics-based methods.

AREAS COVERED

The authors examine recent examples of VS in drug discovery and discuss prospective hit finding results from the critical assessment of computational hit-finding experiments (CACHE) challenge. The authors also highlight the cost considerations and open-source options for conducting VS and examine chemical space coverage and library selections for VS.

EXPERT OPINION

The advancement of sophisticated VS approaches, including the use of machine learning techniques and increased computer resources as well as the ease of access to synthetically available chemical spaces, and commercial and open-source VS platforms allow for interrogating ultra-large libraries (ULL) of billions of molecules. An impressive number of prospective ULL VS campaigns have generated potent and structurally novel hits across many target classes. Nonetheless, many successful contemporary VS approaches still use considerably smaller focused libraries. This apparent dichotomy illustrates that VS is best conducted in a fit-for-purpose way choosing an appropriate chemical space. Better methods need to be developed to tackle more challenging targets.

Navigating large chemical spaces in early-phase drug discovery

The size of actionable chemical spaces is surging, owing to a variety of novel techniques, both computational and experimental. As a consequence, novel molecular matter is now at our fingertips that cannot and should not be neglected in early-phase drug discovery. Huge, combinatorial, make-on-demand chemical spaces with high probability of synthetic success rise exponentially in content, generative machine learning models go hand in hand with synthesis prediction, and DNA-encoded libraries offer new ways of hit structure discovery. These technologies enable to search for new chemical matter in a much broader and deeper manner with less effort and fewer financial resources. These transformational developments require new cheminformatics approaches to make huge chemical spaces searchable and analyzable with low resources, and with as little energy consumption as possible. Substantial progress has been made in the past years with respect to computation as well as organic synthesis. First examples of bioactive compounds resulting from the successful use of these novel technologies demonstrate their power to contribute to tomorrow's drug discovery programs. This article gives a compact overview of the state-of-the-art.

Exploration of Ultralarge Compound Collections for Drug Discovery

Designing new medicines more cheaply and quickly is tightly linked to the quest of exploring chemical space more widely and efficiently. Chemical space is monumentally large, but recent advances in computer software and hardware have enabled researchers to navigate virtual chemical spaces containing billions of chemical structures. This review specifically concerns collections of many millions or even billions of enumerated chemical structures as well as even larger chemical spaces that are not fully enumerated. We present examples of chemical libraries and spaces and the means used to construct them, and we discuss new technologies for searching huge libraries and for searching combinatorially in chemical space. We also cover space navigation techniques and consider new approaches to de novo drug design and the impact of the "autonomous laboratory" on synthesis of designed compounds. Finally, we summarize some other challenges and opportunities for the future.

Discovery of Roblitinib (FGF401) as a Reversible-Covalent Inhibitor of the Kinase Activity of Fibroblast Growth Factor Receptor 4

FGF19 signaling through the FGFR4/β-klotho receptor complex has been shown to be a key driver of growth and survival in a subset of hepatocellular carcinomas, making selective FGFR4 inhibition an attractive treatment opportunity. A kinome-wide sequence alignment highlighted a poorly conserved cysteine residue within the FGFR4 ATP-binding site at position 552, two positions beyond the gate-keeper residue. Several strategies for targeting this cysteine to identify FGFR4 selective inhibitor starting points are summarized which made use of both rational and unbiased screening approaches. The optimization of a 2-formylquinoline amide hit series is described in which the aldehyde makes a hemithioacetal reversible-covalent interaction with cysteine 552. Key challenges addressed during the optimization are improving the FGFR4 potency, metabolic stability, and solubility leading ultimately to the highly selective first-in-class clinical candidate roblitinib.

The next level in chemical space navigation: going far beyond enumerable compound libraries

Recent innovations have brought pharmacophore-driven methods for navigating virtual chemical spaces, the size of which can reach into the billions of molecules, to the fingertips of every chemist. There has been a paradigm shift in the underlying computational chemistry that drives chemical space search applications, incorporating intelligent reaction knowledge into their core so that they can readily deliver commercially available molecules as nearest neighbor hits from within giant virtual spaces. These vast resources enable medicinal chemists to execute rapid scaffold-hopping experiments, rapid hit expansion, and structure-activity relationship (SAR) exploitation in largely intellectual property (IP)-free territory and at unparalleled low cost.

Structure and biological activity of endogenous and synthetic agonists of GPR119

A G-protein-coupled receptor, GPR119, is a promising pharmacological target for a new class of hypoglycaemic drugs with an original mechanism of action, namely, increase in the glucose-dependent incretin and insulin secretion. In 2005, the first ligands were found and in the subsequent years, a large number of GPR119 agonists were synthesized in laboratories in various countries; the safest and most promising agonists have entered phase I and II clinical trials as agents for the treatment of type 2 diabetes mellitus and obesity. The review describes the major endogenous GPR119 agonists and the main trends in the design and modification of synthetic structures for increasing the hypoglycaemic activity. The data on synthetic agonists are arranged according to the type of the central core of the molecules.

The bibliography includes 104 references.

G Protein-Coupled Receptor 119 (GPR119) Agonists for the Treatment of Diabetes: Recent Progress and Prevailing Challenges

In this Perspective, recent advances and challenges in the development of GPR119 agonists as new oral antidiabetic drugs will be discussed. Such agonists are expected to exhibit a low risk to induce hypoglycemia as well as to have a beneficial impact on body weight. Many pharmaceutical companies have been active in the search for GPR119 agonists, making it a highly competitive area in the industrial environment. Several GPR119 agonists have been entered into clinical studies, but many have failed either in phase I or II and none has progressed beyond phase II. Herein we describe the strategies chosen by the different medicinal chemistry teams in academia and the pharmaceutical industry to improve potency, physicochemical properties, pharmacokinetics, and the safety profile of GPR119 agonists in the discovery phase in order to improve the odds for successful development.

Copper Nitrate Mediated Regioselective [2+2+1] Cyclization of Alkynes with Alkenes: A Cascade Approach to Δ(2)-Isoxazolines

An efficient method for the regioselective synthesis of pharmacologically relevant polysubstituted Δ(2)-isoxazolines is based on the copper-mediated direct transformation of simple terminal alkynes and alkenes. The overall process involves the formation of four chemical bonds with inexpensive and readily available copper nitrate trihydrate as a novel precursor of nitrile oxides. The reaction can be easily handled and proceeds under mild conditions.

Construction of C(sp2)–S and C(sp2)–Se bonds via a silver(i)-mediated coupling reaction of heterocyclic ketene aminals with diaryl dichalcogenides

A novel Ag(i)-mediated direct coupling reaction using HKAs and diaryl dichalcogenides for the construction of C(sp²)–chalcogenide bonds is reported. The transformation leads to a variety of α-arylthio and α-phenylselanyl HKAs with high regioselectivity and excellent yields.

A categorical structure-activity relationship analysis of GPR119 ligands

The categorical structure-activity relationship (cat-SAR) expert system has been successfully used in the analysis of chemical compounds that cause toxicity. Herein we describe the use of this fragment-based approach to model ligands for the G protein-coupled receptor 119 (GPR119). Using compounds that are known GPR119 agonists and compounds that we have confirmed experimentally that are not GPR119 agonists, four distinct cat-SAR models were developed. Using a leave-one-out validation routine, the best GPR119 model had an overall concordance of 99%, a sensitivity of 99%, and a specificity of 100%. Our findings from the in-depth fragment analysis of several known GPR119 agonists were consistent with previously reported GPR119 structure-activity relationship (SAR) analyses. Overall, while our results indicate that we have developed a highly predictive cat-SAR model that can be potentially used to rapidly screen for prospective GPR119 ligands, the applicability domain must be taken into consideration. Moreover, our study demonstrates for the first time that the cat-SAR expert system can be used to model G protein-coupled receptor ligands, many of which are important therapeutic agents.

GPR119 agonists: a promising approach for T2DM treatment? A SWOT analysis of GPR119

Ever since its advent as a promising therapeutic target for type 2 diabetes mellitus (T2DM), G-protein-coupled receptor 119 (GPR119) has received much interest from the pharmaceutical industry. This interest peaked in June 2010, when Sanofi-Aventis agreed to pay Metabolex (Cymabay Therapeutics) US$375 million for MBX-2982, which was a representative orally active GPR119 agonist. However, Sanofi-Aventis opted to terminate the deal in May 2011 and another leading GPR119 agonist, GSK1292263, had a loss of efficacy during its clinical trial. In this review, I discuss the pros and cons of GPR119 through a strengths, weaknesses, opportunities, and threats (SWOT) analysis and propose development strategies for the eventual success of a GPR119 agonist development program.

Conformational restriction in a series of GPR119 agonists: differences in pharmacology between mouse and human

A series of conformationally restricted GPR119 agonists were prepared based around a 3,8-diazabicyclo[3.2.1]octane scaffold. Examples were found to have markedly different pharmacology in mouse and human despite similar levels of binding to the receptor. This highlights the large effects on GPCR phamacology that can result from small structural changes in the ligand, together with inter-species differences between receptors.