Catherine E. Peishoff

Thousands of chemical starting points for antimalarial lead identification

Malaria is a devastating infection caused by protozoa of the genus Plasmodium. Drug resistance is widespread, no new chemical class of antimalarials has been introduced into clinical practice since 1996 and there is a recent rise of parasite strains with reduced sensitivity to the newest drugs. We screened nearly 2 million compounds in GlaxoSmithKline’s chemical library for inhibitors of P. falciparum, of which 13,533 were confirmed to inhibit parasite growth by at least 80% at 2 µM concentration. More than 8,000 also showed potent activity against the multidrug resistant strain Dd2. Most (82%) compounds originate from internal company projects and are new to the malaria community. Analyses using historic assay data suggest several novel mechanisms of antimalarial action, such as inhibition of protein kinases and host–pathogen interaction related targets. Chemical structures and associated data are hereby made public to encourage additional drug lead identification efforts and further research into this disease.

CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma

The 2014 CSAR Benchmark Exercise was the last community-wide exercise that was conducted by the group at the University of Michigan, Ann Arbor. For this event, GlaxoSmithKline (GSK) donated unpublished crystal structures and affinity data from in-house projects. Three targets were used: tRNA (m1G37) methyltransferase (TrmD), Spleen Tyrosine Kinase (SYK), and Factor Xa (FXa). A particularly strong feature of the GSK data is its large size, which lends greater statistical significance to comparisons between different methods. In Phase 1 of the CSAR 2014 Exercise, participants were given several protein-ligand complexes and asked to identify the one near-native pose from among 200 decoys provided by CSAR. Though decoys were requested by the community, we found that they complicated our analysis. We could not discern whether poor predictions were failures of the chosen method or an incompatibility between the participants method and the setup protocol we used. This problem is inherent to decoys, and we strongly advise against their use. In Phase 2, participants had to dock and rank/score a set of small molecules given only the SMILES strings of the ligands and a protein structure with a different ligand bound. Overall, docking was a success for most participants, much better in Phase 2 than in Phase 1. However, scoring was a greater challenge. No particular approach to docking and scoring had an edge, and successful methods included empirical, knowledge-based, machine-learning, shape-fitting, and even those with solvation and entropy terms. Several groups were successful in ranking TrmD and/or SYK, but ranking FXa ligands was intractable for all participants. Methods that were able to dock well across all submitted systems include MDock,1 Glide-XP,2 PLANTS,3 Wilma,4 Gold,5 SMINA,6 Glide-XP2/PELE,7 FlexX,8 and MedusaDock.9 In fact, the submission based on Glide-XP2/PELE7 cross-docked all ligands to many crystal structures, and it was particularly impressive to see success across an ensemble of protein structures for multiple targets. For scoring/ranking, submissions that showed statistically significant achievement include MDock1 using ITScore1,10 with a flexible-ligand term,11 SMINA6 using Autodock-Vina,12,13 FlexX8 using HYDE,14 and Glide-XP2 using XP DockScore2 with and without ROCS15 shape similarity.16 Of course, these results are for only three protein targets, and many more systems need to be investigated to truly identify which approaches are more successful than others. Furthermore, our exercise is not a competition.

Refinement of a molecular model of angiotensin II (AII) employed in the discovery of potent nonpeptide antagonists

Abstract A novel conformational model of AII, Model II, had been employed previously in the design of potent benzylimidazole AII antagonists (J. Med. Chem. 1991, 34, 1514–1517). This paper considers this model in relation to the recently described potent AII analogs [hCys3,5]-AII, and [Sar1,hCys3,5,IIe8]-AII. Conformational analysis of Ac-S,S-cyclo-(hCys-Ala-hCys)-NH2 suggests a family of modified conformations for AII, Model III, which retains the topological arrangement of functional groups in Model II that had been employed in nonpeptide analog design.

Metal mediated protease inhibition: design and synthesis of inhibitors of the human cytomegalovirus (hCMV) protease.

A versatile synthetic route to a novel series of bis-imidazolemethanes designed to inhibit the hCMV protease has been developed and a series of potential metal binding inhibitors has been identified. In selectivity assays, the compounds were highly specific for CMV protease and showed no inhibition (IC50 > 100 microM) of other prototypical serine proteases such as trypsin, elastase, and chymotrypsin. Although the presence of free zinc ions was found to be an absolute requirement for the in vitro biological activity of this class of inhibitor, the potency of the inhibitors could not be improved beyond the micromolar level.

D and L-N-[(1-benzyl-1H-imidazol-5-yl)-alkyl]-amino acids as angiotensin II AT-1 antagonists

Abstract A series of D and L-N-[(1-benzyl-1H-imidazol-5-yl)-alkyl]-aromatic amino acids ( 2 to 9 ) and several achiral analogs ( 1,10,11 ) were found to be potent AII antagonists (nM range). Among chiral pairs the D isomer had the highest affinity for the binding site. A D-phenylalanine analog, 3 , was the most potent (IC 50 3.8 nM) and had activity in vivo similar to SK&F 108566 when given i.v. but was only marginally active when given i.d.

Molecular Biology of the Endothelin Receptors

Since the initial discovery of the endothelium-derived constricting factor, endothelin-1 (ET-1) (1) and determination of its peptidic nature (2), elucidation of the molecular details of the endothelin (ET) system has progressed rapidly via a multidisciplinary approach using the tools of biochemistry, chemistry, pharmacology, and molecular biology. Milestones in the development of this area include the isolation (3) and three-dimensional structure determination (4,5) of ET-1 and related peptides, the pharmacological characterization and molecular cloning of ET-receptor subtypes (6,7) which was followed by the development of potent peptide and nonpeptide antagonists (8–13), and, more recently, the disruption of the genes encoding ET-1, ET-3, and the ETB receptor subtype (14–16). Thus elucidation of the intricacies of the endothelin system has been the product of a truly molecular approach to pharmacology.

Peptide Mimetics as Adhesion Molecule Antagonists

As a class, drugs that modulate cell adhesion as a mechanism of action are in their infancy. Although several drugs are in clinical development as intravenous agents, none have reached the market. Even in this early period, however, the pursuit of adhesion molecule antagonists that may be administered orally has begun within the arena of platelet fibrinogen receptor antagonists (also called GPIIb/IIIa antagonists). As one of the more mature areas of antiadhesion, platelet fibrinogen receptor antagonists have advanced from the native protein fibrinogen to small potent inhibitory peptides, and more recently to potent semipeptide and nonpeptide antagonists. Although nonpeptide ligands to GPIIb/IIIa have been discovered through compound data-base screening, the path to non Peptides through peptide mimetics is also being avidly pursued. This chapter will focus on the development of an RGD peptide pharmacophore model for the design of novel nonpeptide mimetic ligands to GPIIb/IIIa. It will be instructive, however, to examine first the path that led to the discovery of small potent inhibitory peptide GPIIb/IIIa antagonists, focusing on the work at SmithKline Beecham.

Chapter 8:Docking Algorithms and Scoring Functions; State-of-the-Art and Current Limitations

The past three decades have seen an explosion in the amount of data required for structure-based design of pharmaceutically relevant molecules. This data expansion encompasses both an exponential increase in the number of available protein structures and an increase in the number of real and hypothe...