Optimization Campaign Research Articles

Design, Synthesis, and In Vitro Evaluation of Potential West Nile Virus Protease Inhibitors Based on the 1-Oxo-1,2,3,4-tetrahydroisoquinoline and 1-Oxo-1,2-dihydroisoquinoline Scaffolds

The 1-oxo-1, 2, 3, 4-tetrahydroisoquinoline and 1-Oxo-1, 2-dihydroisoquinoline scaffolds were utilized in the design and solution phase synthesis of focused libraries of compounds for screening against West Nile Virus (WNV) protease. Exploratory studies have led to the identification of a WNV protease inhibitor (a 1-oxo-1, 2-dihydroisoquinoline-based derivative, 12j) which could potentially serve as a launching pad for a hit-to-lead optimization campaign. The identified hit was devoid of any inhibitory activity toward a panel of mammalian serine proteases.

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.

Capsule performance optimization in the national ignition campaign

A capsule performance optimization campaign will be conducted at the National Ignition Facility [1] to substantially increase the probability of ignition. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

Optimal storage design for a multi-product plant: A non-convex MINLP formulation

We discuss a tank design problem for a multi product plant, in which the optimal cycle time and the optimal campaign size are unknown. A mixed-integer nonlinear programming (MINLP) formulation is presented, where non-convexities are due to the tank investment cost, storage cost, campaign setup cost and variable production rates. The objective of the optimization model is to minimize the sum of the production cost per ton per product produced. A continuous-time mathematical programming formulation is proposed and several extensions are discussed. The model is implemented in GAMS and computational results are reported for the two global MINLP solver BARON and LINDOGlobal as well as several nonlinear solvers available in GAMS.

Capsule performance optimization in the National Ignition Campaign

A capsule performance optimization campaign will be conducted at the National Ignition Facility [G. H. Miller et al., Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition by laser-driven hohlraums [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)]. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the OMEGA facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

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).

Abstract A211: Fragment-based drug discovery of the synthetic small molecule HSP90 inhibitor AT13387

Abstract Heat Shock Protein 90 (HSP90) is a member of a family of molecular chaperone proteins which directs the folding of polypeptides into functional configurations affecting stabilisation and activation. Many of these proteins are oncogenes regulating tumor cell growth, survival and apoptosis. This poster will focus on the screening and medicinal chemistry work that led to the identification of AT13387, a high affinity HSP90 inhibitor that is currently in clinical trials for the treatment of cancer. A fragment screening campaign was conducted against the N-terminal domain of HSP90 to detect very low molecular weight compounds (Molecular Weight <250 Da) that bound to the ATPase active site. The screening produced a small fragment which was co-crystallised with HSP90 and had an affinity of 790µM. Three iterations of structure-guided medicinal chemistry led to the identification of a lead compound with 0.5nM affinity for the enzyme, good cell activity and confirmed mechanism of action in cells. The fragment to lead optimisation increased affinity by over a million fold but resulted in a molecule that was only 6 heavy atoms larger than the fragment starting point. Such an efficient optimisation campaign is unprecedented in the field of fragment-based drug discovery. Subsequent lead optimisation focussed on the improvement of in vivo distribution properties via the addition of basic moieties to the lead molecule. These compounds showed encouraging in vivo pharmacology and biological profiles, and further medicinal chemistry work led to the discovery of AT13387, an inhibitor with sub-nanomolar affinity, prolonged duration of action and excellent in vivo anti-tumor efficacy. This poster represents first disclosure of the structure of AT13387 and illustrates how a fragment-based drug discovery approach can be efficiently used to discover compounds suitable for clinical testing in oncology. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A211.

Abstract A139: Discovery and biological profiling of potent fibroblast growth factor receptor (FGFR) kinase inhibitors derived from in silico design with in vivo antitumor activity against FGFR2-dependent human tumors

Abstract Dysregulation of members of the FGFR tyrosine kinase family has been increasingly implicated in a number of human cancers, including gastric, breast, endometrial, and bladder carcinomas. A proprietary structure-based design paradigm was employed to identify inhibitors which favor a mode of binding that is distinct from the commonly described ATP competitive inhibitors. A molecular template was identified (ARQ 523) which, upon further modification, provided molecules that were shown to inhibit FGFR kinases in the low micromolar range, to bind to FGFR2 in an enantiomeric-specific fashion, to bind to unphosphorylated FGFR2 with a KD of 5 µM; and, after pre-incubation with inactive FGFR2, to prevent a fluorescent analogue of ATP from binding to the enzyme. We have designated this novel type of kinase inhibitor as “ATP-exclusionary” or “Type IV” to differentiate these inhibitors from extant molecules. Following a lead optimization campaign, biochemical potencies of 1 nM or less against FGFR kinases with corresponding increases in binding affinities to FGFR2 in biophysical assays were documented in several compounds in two distinct series. These compounds showed sub-micromolar activity in both FGFR2-dependent pharmacodynamic and cytotoxicity assays, and demonstrated a moderately high degree of selectivity across the human kinome. A representative compound showed marked FGFR2 pharmacodynamic suppression and corresponding growth inhibition in KATO III and SNU-16 human gastric carcinoma cells. In addition, growth of SNU-16 tumor xenografts in athymic mice was markedly suppressed (58% regression as compared to vehicle-treated controls) after daily intraperitoneal administration for 9 days. A paired Ba/F3 xenograft model was also employed, using both Ba/F3 cells transfected with either FGFR2 or the unrelated insulin receptor. Significant tumor growth inhibition (77% inhibition as compared to vehicle-treated controls) was observed in treated mice bearing FGFR2-transfected Ba/F3 tumors but not in the insulin receptor transfectants. In summary, we have achieved proof-of-principle of a structure-based kinase inhibitor design paradigm for the identification of a series of FGFR kinase inhibitors that exhibits a preference for the inactive form of the kinase and excludes ATP upon binding. One advanced lead molecule demonstrated the ability to exert profound anti-tumor effects against cancer cell lines in which FGFR2 is the dominant oncogenic driver. The opportunity now exists to significantly expand the number of new chemotypes available for drug discovery against disease-relevant kinases in oncology and in other therapeutic areas, since it is predicted that approximately half of the human kinome is amenable to this novel mode of inhibition. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A139.

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.

Novel sulfamoyl benzamides as selective CB2 agonists with improved in vitro metabolic stability

A lead optimization campaign in our previously reported sulfamoyl benzamide class of CB(2) agonists was conducted to improve the in vitro metabolic stability profile in this series while retaining high potency and selectivity for the CB(2) receptor. From this study, compound 14, N-(3,4-dimethyl-5-(morpholinosulfonyl)phenyl)-2,2-dimethylbutanamide, was identified as a potent and selective CB(2) agonist exhibiting moderate in vitro metabolic stability and oral bioavailability. Compound 14 demonstrated in vivo efficacy in a rat model of post-surgical pain.

A new delay-SIR model for pulse vaccination

This paper introduces a new model for disease outbreaks. This model describes the disease evolution through a system of nonlinear differential equations with distributed-delay. The main difference between classical SIR-model resides in the fact that the recovery rate of the population is expressed as a distributed-delay term modeling the time spent being sick by infected people. This model is identified to fit realistic measurements which shows the effectiveness of the model. Finally, we develop an optimal campaign vaccination strategy based on recent results on the impulsive control of time-delay systems.

The rise of fragment-based drug discovery

The search for new drugs is plagued by high attrition rates at all stages in research and development. Chemists have an opportunity to tackle this problem because attrition can be traced back, in part, to the quality of the chemical leads. Fragment-based drug discovery (FBDD) is a new approach, increasingly used in the pharmaceutical industry, for reducing attrition and providing leads for previously intractable biological targets. FBDD identifies low-molecular-weight ligands (∼150 Da) that bind to biologically important macromolecules. The three-dimensional experimental binding mode of these fragments is determined using X-ray crystallography or NMR spectroscopy, and is used to facilitate their optimization into potent molecules with drug-like properties. Compared with high-throughput-screening, the fragment approach requires fewer compounds to be screened, and, despite the lower initial potency of the screening hits, offers more efficient and fruitful optimization campaigns. Here, we review the rise of FBDD, including its application to discovering clinical candidates against targets for which other chemistry approaches have struggled.

A new marketing strategy map for direct marketing

Direct marketing is one of the most effective marketing methods with an aim to maximize the customer’s lifetime value. Many cost-sensitive learning methods which identify valuable customers to maximize expected profit have been proposed. However, current cost-sensitive methods for profit maximization do not identify how to control the defection probability while maximizing total profits over the customer’s lifetime. Unfortunately, optimal marketing actions to maximize profits often perform poorly in minimizing the defection probability due to a conflict between these two objectives. In this paper, we propose the sequential decision making method for profit maximization under the given defection probability in direct marketing. We adopt a Reinforcement Learning algorithm to determine the sequential optimal marketing actions. With this finding, we design a marketing strategy map which helps a marketing manager identify sequential optimal campaigns and the shortest paths toward desirable states. Ultimately, this strategy leads to the ideal design for more effective campaigns.

Automated Planar Electrode Electrophysiology in Drug Discovery: Examples of the Use of QPatch in Basic Characterization and High Content Screening on Nav, KCa2.3, and Kv11.1 Channels

Planar chip technology has strongly facilitated the progress towards fully automated electrophysiological systems that, in contrast to the traditional patch clamp technology, have the capability of parallel compound testing. The throughput has been increased from testing below 10 compounds per day to a realized capacity approaching high throughput levels. Many pharmaceutical companies have implemented automated planar chip electrophysiology in their drug discovery process, particularly at the levels of lead optimization, secondary screening and safety testing, whereas primary screening is generally not performed. In this review, we briefly discuss the technology and give examples from selected NeuroSearch ion channel programs, where one of the systems, the QPatch, has been evaluated for use in lead optimization and primary screening campaigns, where high information content was a requirement.

Structure−Activity Studies on a Series of a 2-Aminopyrimidine-Containing Histamine H4 Receptor Ligands

A series of 2-aminopyrimidines was synthesized as ligands of the histamine H4 receptor (H4R). Working in part from a pyrimidine hit that was identified in an HTS campaign, SAR studies were carried out to optimize the potency, which led to compound 3, 4- tert-butyl-6-(4-methylpiperazin-1-yl)pyrimidin-2-ylamine. We further studied this compound by systematically modifying the core pyrimidine moiety, the methylpiperazine at position 4, the NH2 at position 2, and positions 5 and 6 of the pyrimidine ring. The pyrimidine 6 position benefited the most from this optimization, especially in analogs in which the 6- tert-butyl was replaced with aromatic and secondary amine moieties. The highlight of the optimization campaign was compound 4, 4-[2-amino-6-(4-methylpiperazin-1-yl)pyrimidin-4-yl]benzonitrile, which was potent in vitro and was active as an anti-inflammatory agent in an animal model and had antinociceptive activity in a pain model, which supports the potential of H 4R antagonists in pain.

SPECIAL INTEREST POLITICS AND INTELLECTUAL PROPERTY RIGHTS: AN ECONOMIC ANALYSIS OF STRENGTHENING PATENT PROTECTION IN THE PHARMACEUTICAL INDUSTRY

Since the 1980s, the pharmaceutical industry has benefited substantially from a series of policy changes that have strengthened the patent protection for brand‐name drugs as a result of the industry's political influence. This paper incorporates special interest politics into a quality‐ladder model to analyze the policy‐makers' tradeoff between the socially optimal patent length and campaign contributions. The welfare analysis suggests that the presence of a pharmaceutical lobby distorting patent protection is socially undesirable in a closed‐economy setting but may improve social welfare in a multi‐country setting, which features an additional efficiency tradeoff between monopolistic distortion and international free riding on innovations.

2-(3-Aryl-3-oxopropen-1-yl)-9-tert-butyl-paullones: A New Antileishmanial Chemotype

A screening program directed to find new agents against Leishmania donovani, the parasite causing visceral leishmaniasis, revealed that paullones attenuate the proliferation of axenic amastigotes. Because these structures were not active in a test system involving infected macrophages, a structure optimization campaign was carried out. Concomitant introduction of an unsaturated side chain into the 2-position and a tert-butyl substituent into the 9-position of the parent scaffold led to compounds inhibiting also parasites dwelling in macrophages. By inclusion of the so elaborated scaffold into a chalcone substructure, the toxicity against uninfected host cells was significantly reduced. For the synthesis of this new compound class, a novel modification of the Heck-type palladium-catalyzed C,C-cross coupling strategy was used, employing a ketone Mannich base as precursor for the alkene reactant. The so-prepared compounds exhibited improved antileishmanial activity both on axenic amastigotes (GI50 < 1 microM) as well as on parasites in infected macrophages.

A New Delay-SIR Model for Pulse Vaccination

This paper introduces a new model for disease outbreaks. This model describes the disease evolution through a system of nonlinear differential equations with distributed-delay. The main difference between classical SIR-model resides in the fact that the recovery rate of the population is expressed as a distributed-delay term modeling the time spent being sick by infected people. This model is identified to fit realistic measurements which shows the effectiveness of the model. Finally, we develop an optimal campaign vaccination strategy based on recent results on the impulsive control of time-delay systems.

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.

Enhancement of chemical rules for predicting compound reactivity towards protein thiol groups

Non-specific chemical modification of protein thiol groups continues to be a significant source of false positive hits from high-throughput screening campaigns and can even plague certain protein targets and chemical series well into lead optimization. While experimental tools exist to assess the risk and promiscuity associated with the chemical reactivity of existing compounds, computational tools are desired that can reliably identify substructures that are associated with chemical reactivity to aid in triage of HTS hit lists, external compound purchases, and library design. Here we describe a Bayesian classification model derived from more than 8,800 compounds that have been experimentally assessed for their potential to covalently modify protein targets. The resulting model can be implemented in the large-scale assessment of compound libraries for purchase or design. In addition, the individual substructures identified as highly reactive in the model can be used as look-up tables to guide chemists during hit-to-lead and lead optimization campaigns.