Multiparameter Optimization in CNS Drug Discovery: Design of Pyrimido[4,5-d]azepines as Potent 5-Hydroxytryptamine 2C (5-HT2C) Receptor Agonists with Exquisite Functional Selectivity over 5-HT2A and 5-HT2B Receptors
Abstract:A series of 4-substituted pyrimido[4,5-d]azepines that are potent, selective 5-HT2C receptor partial agonists is described. A rational medicinal chemistry design strategy to deliver CNS penetration coupled with SAR-based optimization of selectivity and agonist potency provided compounds with the desired balance of preclinical properties. Lead compounds 17 (PF-4479745) and 18 (PF-4522654) displayed robust pharmacology in a preclinical canine model of stress urinary incontinence (SUI) and no measurable functiona… Show more
“…The hierarchical GPCR modelling protocol (HGMP) has been developed to support GPCR SBDD programmes. HGMP has been successfully applied in GPCR drug discovery projects such as MCH-1R for obesity treatment [30], the orexin-1 and -2 receptors (OX 1 R and OX 2 R) for insomnia [31,32], the 5-HT 2C for the treatment of metabolic disorders [33,34] and in other confidential drug discovery programmes. Additionally, the HGMP technology was used in the solving of the two H 1 R crystals structures [4] bound to the second and third generation antihistamines: cetirizine and fexofenadine.…”
The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR–ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in ‘real-time’ and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allows ab initio approaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure–function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available.
“…The hierarchical GPCR modelling protocol (HGMP) has been developed to support GPCR SBDD programmes. HGMP has been successfully applied in GPCR drug discovery projects such as MCH-1R for obesity treatment [30], the orexin-1 and -2 receptors (OX 1 R and OX 2 R) for insomnia [31,32], the 5-HT 2C for the treatment of metabolic disorders [33,34] and in other confidential drug discovery programmes. Additionally, the HGMP technology was used in the solving of the two H 1 R crystals structures [4] bound to the second and third generation antihistamines: cetirizine and fexofenadine.…”
The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity and is essential for an efficient structure-based drug discovery (SBDD) process. Clearly, to begin SBDD, a structure is needed, and although there has been fantastic progress in solving G-protein-coupled receptor (GPCR) crystal structures, the process remains quite slow and is not currently feasible for every GPCR or GPCR–ligand complex. This situation significantly limits the ability of X-ray crystallography to impact the drug discovery process for GPCR targets in ‘real-time’ and hence there is still a need for other practical and cost-efficient alternatives. We present here an approach that integrates our previously described hierarchical GPCR modelling protocol (HGMP) and the fragment molecular orbital (FMO) quantum mechanics (QM) method to explore the interactions and selectivity of the human orexin-2 receptor (OX2R) and its recently discovered nonpeptidic agonists. HGMP generates a 3D model of GPCR structures and its complexes with small molecules by applying a set of computational methods. FMO allows ab initio approaches to be applied to systems that conventional QM methods would find challenging. The key advantage of FMO is that it can reveal information on the individual contribution and chemical nature of each residue and water molecule to the ligand binding that normally would be difficult to detect without QM. We illustrate how the combination of both techniques provides a practical and efficient approach that can be used to analyse the existing structure–function relationships (SAR) and to drive forward SBDD in a real-world example for which there is no crystal structure of the complex available.
“…Several recent structural publications have provided greater clarity on the binding modes and kinetics of existing drugs in both orthosteric sites, such as bronchodilator tiotropium binding to muscarinic M 3 receptor (Tautermann et al 2013 ), and allosteric binding sites, such as anti-viral maraviroc which acts as a negative allosteric modulator of chemokine receptor CCR 5 (Kruse et al 2012 ; Tan et al 2013 ). Provision of knowledge of this type should begin to assist in design of more subtype selective ligands, especially when combined with leading edge computational techniques such as homology modelling (Storer et al 2014 ) and molecular dynamic simulations.…”
Section: Challenges and Solutions For Gpcr Drug Discoverymentioning
confidence: 99%
“… Fig. 8 Modelling of binding and activation of 5-HT 2C (Storer et al 2014 ) receptor by pyrimido[4,5- d ]azepines …”
Section: Challenges and Solutions For Gpcr Drug Discoverymentioning
G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.
“…[25] A b 2 -adrenergic receptorb ased homology model has been generated and used to predict the possible binding modes of putative 5-HT 2C ligands to this receptor. [26] In our study,w eu sed the b 2 -AR structure in its inactive mode for generating ah omology model of 5-HT 2C in its inactive mode, while the active mode model was generated by combining the resolved structure of the 5-HT 2B and the b 2 -AR in its fully active state. [24] The bindingm odes of one of our best 5-HT 2c ligands, namely compound 16,t ot he receptors were predictedb yd ockings imulations, and the ligand was found to fit nicely into the active conformation of the 5-HT 2C homology model.T he binding is stabilized by the ion pair between the ligand'sa mmonium group and Asp134 on TM3 along with various p-p and hydrophobic interactions.…”
Section: Homologymodeling and Putativebindingpreference Of 2-phenylcymentioning
The serotonin 2C (5-HT2C) receptor has been identified as a potential drug target for the treatment of a variety of central nervous system (CNS) disorders, such as obesity, substance abuse, and schizophrenia. In this Viewpoint article, recent progress in developing selective 5-HT2C agonists for use in treating these disorders is summarized, including the work of our group. Challenges in this field and the possible future directions are described. Homology modeling as a method to predict the binding modes of 5-HT2C ligands to the receptor is also discussed. Compared to known ligands, the improved pharmacological profiles of the 2-phenylcyclopropylmethylamine-based 5-HT2C agonists make them preferred candidates for further studies.
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