Chemical Lead Optimization Research Articles

On the Discovery and Development of Pimavanserin: A Novel Drug Candidate for Parkinson’s Psychosis

Parkinson’s disease psychosis (PDP) is a condition that may develop in up to 60 % of Parkinson’s patients, and is a major reason for nursing home placement for those affected. There are no FDA approved drugs for PDP but low doses of atypical anti-psychotic drugs (APDs) are commonly prescribed off-label. Only low-dose clozapine has shown efficacy in randomized controlled trials, but all APDs have black box warnings related to the increased mortality and morbidity when used in elderly demented patients. Using molecular pharmacological profiling of a large collection of marketed drugs, we discovered that potent inverse agonist activity against 5-HT2A serotonin receptors was a common feature of atypical APDs, especially the atypical APDs used to treat PDP. Since low-dose clozapine therapy selectively blocks this receptor, it was hypothesized that a highly selective 5-HT2A receptor inverse agonist might provide good symptom control in patients suffering from PDP, with a greatly improved safety and tolerability profile. A high throughput screening and subsequent chemical lead optimization campaign to develop potent, selective 5-HT2A receptor inverse agonists was launched, eventually resulting in the discovery of pimavanserin. Pimavanserin displays nanomolar potency as a 5-HT2A receptor inverse agonist, selectivity for 5-HT2A over 5-HT2C receptors, and no meaningful activity at any other G-protein coupled receptor. It demonstrated robust activity in preclinical models of schizophrenia and PDP, and did not worsen motoric symptoms, in contrast to the APDs tested. In a Phase III clinical trial, pimavanserin showed highly significant benefits in the primary endpoint, the scale for assessment of positive symptoms-PD, a scale adapted for use in PDP. In addition, improvements in all other efficacy endpoints, including physician’s clinical global impression, caregiver burden, night-time sleep quality and daytime wakefulness, were seen. Pimavanserin demonstrated good safety and tolerability and did not worsen motoric symptoms as assessed by the unified Parkinson’s disease rating scale parts II and III. An open-label extension study has further demonstrated that pimavanserin is safe and well-tolerated with long-term use. Pimavanserin may therefore offer a viable treatment option for patients suffering from PDP.

Discovery and optimization of Lu AF58801, a novel, selective and brain penetrant positive allosteric modulator of alpha-7 nicotinic acetylcholine receptors: Attenuation of subchronic phencyclidine (PCP)-induced cognitive deficits in rats following oral administration

In this Letter, we describe a chemical lead optimization campaign starting from a novel, weak α7 nicotinic acetylcholine receptor positive allosteric modulator (PAM) hit from a HTS screen. Exploration of the structure–activity relationships for α7 PAM potency, intrinsic hepatic clearance, the structure–property relationships for lipophilicity, and thermodynamic solubility, led to the identification of Lu AF58801: a potent, orally available, brain penetrant PAM of the α7 nicotinic acetylcholine receptor, showing efficacy in a novel object recognition task in rats treated subchronically with phencyclidine (PCP).

Discovery and optimization of a novel, selective and brain penetrant M1 positive allosteric modulator (PAM): the development of ML169, an MLPCN probe.

This Letter describes a chemical lead optimization campaign directed at VU0108370, a weak M(1) PAM hit with a novel chemical scaffold from a functional HTS screen within the MLPCN. An iterative parallel synthesis approach rapidly established SAR for this series and afforded VU0405652 (ML169), a potent, selective and brain penetrant M(1) PAM with an in vitro profile comparable to the prototypical M(1) PAM, BQCA, but with an improved brain to plasma ratio.

Discovery of molecular switches within the ADX-47273 mGlu5 PAM scaffold that modulate modes of pharmacology to afford potent mGlu5 NAMs, PAMs and partial antagonists

This Letter describes a chemical lead optimization campaign directed at a weak mGlu(5) NAM discovered while developing SAR for the mGlu(5) PAM, ADX-47273. An iterative parallel synthesis effort discovered multiple, subtle molecular switches that afford potent mGlu(5) NAMs, mGlu(5) PAMs as well as mGlu(5) partial antagonists.

Heterobiaryl and heterobiaryl ether derived M 5 positive allosteric modulators

This Letter describes a chemical lead optimization campaign directed at VU0238429, the first M 5-preferring positive allosteric modulator (PAM), discovered through analog work around VU0119498, a pan G q mAChR M 1, M 3, M 5 PAM. An iterative parallel synthesis approach was employed to incorporate basic heterocycles to improve physiochemical properties.

ChemInform Abstract: Chemical Lead Optimization of a Pan Gq mAChR M1, M3, M5 Positive Allosteric Modulator (PAM) Lead. Part 1. Development of the First Highly Selective M5 PAM (I).

AbstractChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.

Chemical lead optimization of a pan G q mAChR M 1, M 3, M 5 positive allosteric modulator (PAM) lead. Part II: Development of a potent and highly selective M 1 PAM

This Letter describes a chemical lead optimization campaign directed at VU0119498, a pan G q mAChR M 1, M 3, M 5 positive allosteric modulator (PAM) with the goal of developing a selective M 1 PAM. An iterative library synthesis approach delivered a potent (M 1 EC 50 = 830 nM) and highly selective M 1 PAM (>30 μM vs M 2–M 5).

Chemical lead optimization of a pan G q mAChR M 1, M 3, M 5 positive allosteric modulator (PAM) lead. Part I: Development of the first highly selective M 5 PAM

This Letter describes a chemical lead optimization campaign directed at VU0238429, the first M 5-preferring positive allosteric modulator (PAM), discovered through analog work around VU0119498, a pan G q mAChR M 1, M 3, M 5 PAM. An iterative library synthesis approach delivered the first selective M 5 PAM (no activity at M 1–M 4 @ 30 μM), and an important tool compound to study the role of M 5 in the CNS.

From Structure–Activity to Structure–Selectivity Relationships: Quantitative Assessment, Selectivity Cliffs, and Key Compounds

The exploration of structure-activity relationships (SARs) in chemical lead optimization is mostly focused on activity against single targets. Because many active compounds have the potential to act against multiple targets, achieving a sufficient degree of target selectivity often becomes a major issue during optimization. Herein we report a data analysis approach to explore compound selectivity in a systematic and quantitative manner. Sets of compounds that are active against multiple targets provide a basis for exploring structure-selectivity relationships (SSRs). Compound similarity and selectivity data are analyzed with the aid of network-like similarity graphs (NSGs), which organize molecular networks on the basis of similarity relationships and SAR index (SARI) values. For this purpose, the SARI framework has been adapted to quantify SSRs. Using sets of compounds with differential activity against four cathepsin thiol proteases, we show that SSRs can be quantitatively described and categorized. Furthermore, local SSR environments are identified, the analysis of which provides insight into compound selectivity determinants at the molecular level. These environments often contain "selectivity cliffs" formed by pairs or groups of similar compounds with significantly different selectivity. Moreover, key compounds are identified that determine characteristic features of single-target SARs and dual-target SSRs. The comparison of compounds involved in the formation of selectivity cliffs often reveals chemical modifications that render compounds target selective.

Application of Combinatorial Chemistry Science on Modern Drug Discovery

The science that established combinatorial chemistry as important new discipline in the 1980s and 1990s has re-emerged and infiltrated every sub-discipline within modern drug discovery and has profound impact. The application of combinatorial chemistry science has revolutioned high-throughput screening paradigms, chemical lead optimization, library purification, and post-purification sample handling, as well as in vitro and in vivo drug metabolism and pharmacokinetic assays. Although no longer in the spotlight and heralded as the savior of the drug industry, “combinatorial chemistry” is alive and well; in fact, combinatorial chemistry science is more prevalent and wide-spread than ever before.

Molecule of the Month

Bad news for cancer. The Bcl-2 (B-cell lymphoma 2) family of proteins is comprised of both pro-apoptotic and anti-apoptotic members that operate through a complex series of protein-protein interactions [1-3]. The pro-apoptotic proteins are categorized into two groups based on the number of Bcl homology (BH) domains: 1) those with 3 BH domains (BH1-BH3 such as Bax and Bak) and 2) those with a single BH domain (BH-3 only such as Bad, Bik, Puma, etc...). The prosurvival (anti-apoptotic) members contain four BH domains (BH1-BH4 such as Bcl-2, Bcl-xL, etc...). Overexpression of Bcl-2 and its closely related counterpart Bcl-xL affords a mechanism by which cancer cells suppress apoptotic signaling, confer a survival advantage and provide resistance to chemotherapy [1-3]. Recognizing that inhibition of Bcl-2 family members should specifically target the abnormal cell death pathway in the overexpressing cancer cells led Elmore and co-workers at Abbott labs to launch a drug discovery campaign aimed at developing small molecule protein-protein inhibitors of the Bcl-2 family [4-6]. Initial work centered on a class of potent biarylacylsulfonamide antagonists - outside the usual α-helical mimetics - and a lead compound which bound Bcl-xL with a Ki of 800 pM [4]. Despite effective cytotoxic activity with multiple cytotoxic agents and UV irradiation, this Bcl-xL antagonist had no single agent efficacy across a large panel of human tumor cell lines. Elmore and co-workers then reasoned that since this inhibitor was developed by structure-based design aimed at Bcl-xL, it was not surprising that it exhibited much lower affinity for Bcl-2 [5,6]. Since Bcl-2 overexpression is a major hallmark of many human cancers, the team sought to broaden their inhibitor profile to target both Bcl-xL and Bcl-2; interestingly, despite only 49% homology, the three-dimensional structures of Bcl-xL and Bcl-2 are similar. The researchers focused in on the largest structural distinction between the two - a different helical fold of the α3 helix [5]. The α3 helix borders one side of the hydrophobic binding groove, and there exists a wider groove for Bcl-2 than Bcl-xL and a deeper hydrophobic pocket within the groove for Bcl-2 than Bcl-xL. Based on this key structural difference, the team designed modified inhibitors to access this deep hydrophobic pocket in the floor of the groove and thereby increasing affinity for Bcl-2. Their strategy worked! A chemical lead optimization campaign along with structure-guided design resulted in the identification of a clincal candidate, ABT-737, the first dual, subnanomolar inhibitors of Bcl- 2 and Bcl-xL (Ki < 1 nM and < 0.5 nM, respectively) and with EC50s of 8 nM and 30 nM, respectively [5]. ABT-737 showed single agent efficacy against human follicular lymphoma cell lines that overexpress Bcl-2 and efficacy in a murine tumor xenograft model of lymphoma when given as either a single agent or in combination with etoposide. ABT-737 was also efficacious in two mice small cell lung carcinoma xenograft models known to be resistant to most cytotoxic agents. For example, ABT-737 administered i.p. at 75 mg/kg/day for 21 days in a H146 model caused complete regression of established xenografts and 58 days after cessation of therapy, the tumors did not grow back in 77% of the mice [5,6]. ABT-737 represents a significant advance in the discovery and development of small molecule protein-protein inhibitors and clinical data in human patients is eagerly awaited. REFERENCES [1] Cory, S.; Adams, J.M. The Bcl2 family: regulators of the cellular life-ordeath switch. Nat. Rev. Cancer 2002, 2, 647-656. [2] Borner, C. The Bcl2 protein family: sensor and checkpoints for life-or-death decisions. Mol. Immunol. 2003, 39, 615-647. [3] van Delft, M.F.; Huang, D.S.C. How the Bcl-2 family of proteins interact to regulate apoptosis. Cell. Res. 2006, 16, 203-213. [4] Wendt, M.D.; Shen, W.; Kunzer, A.; McClellan, W.J.; Bruncko, M.; Oost, T.K.; Ding, H.; Joseph, M. K.; Zhang, H.; Nimmer, P.M.; Ng, S.-C.; Shoemaker, A.R.; Petros, A.M.; Oleksijew, A.; Marsh, K.; Bauch, J.; Oltersdorf, T.; Belli, B.A.; Martineau, D.; Fesik, S.W.; Rosenberg, S. H.; Elmore, S.W. Discovery and structure-activity relationship of antagonists of B-Cell Lymphoma 2 Family Proteins with chemopotentiation activity in vitro and in vivo. J. Med. Chem. 2006, 49, 1165-1181.

Chemogenomics: drug discovery's panacea?

Chemogenomics aims towards the systematic identification of small molecules that interact with the products of the genome and modulate their biological function. This Opinion article summarizes the different knowledge-based chemogenomics strategies that are followed and outlines the challenges and opportunities that will impact drug discovery. Chemogenomics aims towards the systematic identification of small molecules that interact with the products of the genome and modulate their biological function. While historically the approach is based on efforts that systematically explore target gene families like kinases, today additional knowledge-based systematization principles are followed within early drug discovery projects which aim to biologically validate the targets and to identify starting points for chemical lead optimization. While the expectations of chemogenomics are very high, the reality of drug discovery is quite sobering with very high project attrition rates. This article summarizes the different knowledge-based chemogenomics strategies that are followed and outlines the challenges and potential opportunities that will impact drug discovery.

QSAR studies on some thiophene analogs as anti-inflammatory agents: enhancement of activity by electronic parameters and its utilization for chemical lead optimization

Small molecule heterocycle is an integral part of new drug discovery in anti-inflammatory research. In our previous papers we reported the synthesis of thiophene analogs substituted at the fifth position with α-oximino propionic ester moiety and the fact that such new chemical entities exhibit anti-inflammatory activity in male/female Sprague–Dawley rats. In this paper we report the quantitative structure activity relationship (QSAR) studies of a series of 43 thiophene analogs. The analogs when subjected to cluster analysis technique led to the formation of four homogeneous groups. The cluster analysis technique grouped the 2-anilino-5-substituted-4-methyl-thiophene-3-carboxylic acid methyl esters as one homogeneous group. The clusters were individually taken up for a Hansch type of QSAR study with 10 molecular descriptors. The QSAR equations generated were cross validated by the leave out one method. The studies gave an insight into the dominant role played by electronic properties like energy of the lowest unoccupied molecular orbital ( E LUMO) and dipole moment (dipole) in modulating the anti-inflammatory activity. From the QSAR studies a three point pharmacophore has been established for designing novel anti-inflammatory molecules.