Yael Marantz

PREDICT modeling and in‐silico screening for G‐protein coupled receptors

G‐protein coupled receptors (GPCRs) are a major group of drug targets for which only one x‐ray structure is known (the nondrugable rhodopsin), limiting the application of structure‐based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple ‘decoy’ conformations of the protein in order to find its most stable structure, culminating in a virtual receptor‐ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in‐silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9‐fold to 44‐fold better than random screening. Namely, the PREDICT models can be used to identify active small‐molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non‐GPCR targets. Proteins 2004.

VRX-03011, a novel 5-HT4 agonist, enhances memory and hippocampal acetylcholine efflux.

Recent evidence suggests that 5-hydroxytryptamine (5-HT)(4) receptor activity enhances cognition and provides neuroprotection. Here we report the effects of VRX-03011, a novel partial 5-HT(4) agonist, that is both potent (K(i) approximately 30 nM) and highly selective (K(i) > 5 microM for all other 5-HT receptors tested). In separate experiments, rats received VRX-03011 (0.1-10 mg/kg i.p.) 30 min prior to spontaneous alternation testing in a no-delay or a 30-s delay condition. VRX-03011 (1, 5 and 10 mg/kg, but not 0.1 mg/kg) significantly enhanced delayed spontaneous alternation performance while none of the doses enhanced performance in the no-delay test. VRX-03011 (1 and 5 mg/kg) concomitantly enhanced hippocampal acetylcholine output and delayed spontaneous alternation scores compared to that of vehicle controls, but had no effect on hippocampal acetylcholine release under a resting condition. Moreover, suboptimal doses of VRX-03011 and the acetylcholinesterase inhibitor galanthamine combined to enhance memory. VRX-03011 also regulated amyloid precursor protein (APP) metabolism by inducing a concentration-dependent increase in the non-amyloidogenic soluble form of APP (sAPPalpha) with an EC(50) approximately 1--10 nM. VRX-03011 had no effect on contractile properties in guinea pig ileum or colon preparations with an EC(50) > 10 microM and did not alter rat intestinal transit at doses up to 10 mg/kg. These findings suggest that VRX-03011 may represent a novel treatment for Alzheimers disease that reduces cognitive impairments and provides neuroprotection without gastrointestinal side effects.

Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, ~tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.

THE DYNAMIC FEATURE OF THE PROTON COLLECTING ANTENNA OF A PROTEIN SURFACE

The surface of a protein is a condense matrix of proton binding sites having wide range of pK values. In domains where proton uptake is a part of the catalytic cycle, the surface sites endow the region with special kinetic features which represents the ensemble properties of the proton binding sites. Low pK carboxylate can merge their Coulomb cages to form an extended proton trap, where the binding of a proton to one is rapidly followed by shuttling to another. Neutral pK moieties can act as a temporary proton reservoir which delay the proton at the site, enhancing the probability that upon dissociation it will be taken up by the other elements of the active site. These features had been experimentally identified in small model molecules, where detailed kinetic analysis was carried out. On the base of these measurements the dynamics of protonation of the proton entry sites of bacteriorhodopsin and cytochrome oxidase were investigated.

Biophysical aspects of intra-protein proton transfer.

The passage of proton trough proteins is common to all membranal energy conserving enzymes. While the routes differ among the various proteins, the mechanism of proton propagation is based on the same chemical-physical principles. The proton progresses through a sequence of dissociation association steps where the protein and water molecules function as a solvent that lowers the energy penalty associated with the generation of ions in the protein. The propagation of the proton in the protein is a random walk, between the temporary proton binding sites that make the conducting path, that is biased by the intra-protein electrostatic potential. Kinetic measurements of proton transfer reactions, in the sub-ns up to micros time frame, allow to monitor the dynamics of the partial reactions of an overall proton transfer through a protein.

G Protein-Coupled Receptors: Target-Based In Silico Screening

In silico (or virtual) screening has become a common practice in current computer-aided drug design efforts. However, application to hit discovery in the G Protein-Coupled Receptors (GPCRs) arena was until recently hampered by the paucity of crystal structures available for this important class of pharmaceutical targets, forcing practitioners in the field to rely on GPCR models derived either ab initio or through homology modeling approaches. In this work we describe the EPIX in silico screening workflow which consists of the following stages: (1) Target modeling; (2) Preparation of screening library; (3) Docking; (4) Binding mode selection; (5) Scoring; (6) Consensus scoring and (7) Selection of virtual hits. This workflow was applied to the virtual screening of 13 GPCRs (5 biogenic amine receptors, 5 peptide receptors, 1 lipid receptor, 1 purinergic receptor and 1 cannabinoid receptor). Hit rates vary between 4% and 21% with higher hit rates usually obtained for biogenic amines and lower hits rates for peptide receptors. These data are analyzed in the context of the available experimental information (i.e., mutational data), the model (i.e., binding site location, and type of interactions) and the screening library. Specific examples are discussed in more detail as well as the future directions and challenges of this approach to in silico screening.

Developmental expression of protein kinase C subspecies in rat brain-pituitary axis

We have examined the neonatal developmental expression of protein kinase C subspecies (PKCs) in rat brain, pituitary glands and cells by enzymatic activity assays, immunohistochemistry and Western blot analysis with type-specific antibodies. A very large increase (455%) was noticed in brain PKC activity during the first week of life with the particulate fraction (22% of total enzyme activity on day 1) increasing dramatically (900%) during the first week to 50% of enzyme activity. In contrast, the pituitary gland showed high activity on day 1 that decreased progressively to reach the lowest levels at 1 year of age. Paradoxically, the number of pituitary cells immunolabeled for PKC increases as a function of age. Western blot analysis showed only small changes in PKC alpha, PKC beta and PKC epsilon when brains from 6-day-old and 3-month-old female rats were compared, whereas PKC tau and PKC delta increased markedly during this period. On the other hand, brain PKC zeta decreased between 6 days and 3 months of age. Western blot analysis showed no major changes in pituitary PKC alpha, PKC beta and PKC zeta when 6-day-old and 3-month-old female rats were compared, while PKC tau was not detected. The major band of pituitary PKC delta (76 kDa) decreased markedly between 6 days and 3 months of age whereas the minor band (68 kDa) did not change.(ABSTRACT TRUNCATED AT 250 WORDS)

Benzofuran Derivatives as Potent, Orally Active S1P1 Receptor Agonists: A Preclinical Lead Molecule for MS

We have discovered novel benzofuran-based S1P1 agonists with excellent in vitro potency and selectivity. 1-((4-(5-Benzylbenzofuran-2-yl)-3-fluorophenyl)methyl) azetidine-3-carboxylic acid (18) is a potent S1P1 agonist with >1000× selectivity over S1P3. It demonstrated a good in vitro ADME profile and excellent oral bioavailability across species. Dosed orally at 0.3 mg/kg, 18 significantly reduced blood lymphocyte counts 24 h postdose and demonstrated efficacy in a mouse EAE model of relapsing MS.

G Protein Coupled Receptors - In Silico Drug Discovery and Design

In silico drug discovery is a complex process requiring flexibility and ingenuity in method selection and a careful validation of work protocols. GPCR in silico drug discovery poses additional challenges due to the paucity of crystallographic data. This paper starts by reviewing selected GPCR in silico screening programs reported in the literature, including both structure-based and ligand-based approaches. Particular emphasis is given to library design, binding mode selection, process validation and compound selection for biological testing. Following literature review, we provide insights into in silico methodologies and process workflows used at EPIX to drive over 20 highly successful screening and lead optimization programs performed since 2001. Applications of the various methodologies discussed are demonstrated by examples from recent programs that have not yet been published.

SeleX-CS : A New Consensus Scoring Algorithm for Hit Discovery and Lead Optimization

Identifying active compounds (hits) that bind to biological targets of pharmaceutical relevance is the cornerstone of drug design efforts. Structure based virtual screening, namely, the in silico evaluation of binding energies and geometries between a protein and its putative ligands, has emerged over the past few years as a promising approach in this field. The success of the method relies on the availability of reliable 3-dimensional (3D) structures of the target protein and its candidate ligands (the screening library), a reliable docking method that can fit the different ligands into the proteins binding site, and an accurate scoring function that can rank the resulting binding modes in accord with their binding affinities. This last requirement is arguably the most difficult to meet due to the complexity of the binding process. A potential solution to this so-called scoring problem is the usage of multiple scoring functions in an approach known as consensus scoring. Several consensus scoring methods were suggested in the literature and have generally demonstrated an improved ranking of screening libraries relative to individual scoring functions. Nevertheless, current consensus scoring strategies suffer from several shortcomings, in particular, strong dependence on the initial parameters and an incomplete treatment of inactive compounds. In this work we present a new consensus scoring algorithm (SeleX-Consensus Scoring abbreviated to SeleX-CS) specifically designed to address these limitations: (i) A subset of the initial set of the scoring functions is allowed to form the consensus score, and this subset is optimized via a Monte Carlo/Simulated Annealing procedure. (ii) Rank redundancy between the members of the screening library is removed. (iii) The method explicitly considers the presence of inactive compounds. The new algorithm was applied to the ranking of screening libraries targeting two G-protein coupled receptors (GPCR). Excellent enrichment factors were obtained in both cases: For the cannabinoid receptor 1 (CB1), SeleX-CS outperformed the best single score and afforded an enrichment factor of 41 at 1% of the screening library compared with the best single score value of 15 (GOLD_Fitness). For the chemokine receptor type 2 (CCR2) SeleX-CS afforded an enrichment factor of 72 (again at 1% of the screening library) once more outperforming any single score (enrichment factor of 20 by GSCORE). Moreover, SeleX-CS demonstrated success rates of 67% (CCR2) and 73% (CB1) when applied to ranking an external test set. In both cases, the new algorithm also afforded good derichment of inactive compounds (i.e., the ability to push inactive compounds to the bottom of the ranked library). The method was then extended to rank a lead optimization series targeting the Kv4.3 potassium ion channel, resulting in a Spearmans correlation coefficient, p = 0.63 (n = 40), between the SeleX-CS-based rank and the actual pKi values. These results suggest that SeleX-CS is a powerful method for ranking screening libraries in the lead discovery phase and also merits consideration as a lead optimization tool.