Meir Glick's Publications List

Construction of a 3D-shaped, natural product like fragment library by fragmentation and diversification of natural products.

2017-04-09T12:57:54Z

A fragment library consisting of 3D-shaped, natural product-like fragments was assembled. Library construction was mainly performed by natural product degradation and natural product diversification reactions and was complemented by the identification of 3D-shaped, natural product like fragments available from commercial sources. In addition, during the course of these studies, novel rearrangement...

Horst Prescher, Guido Koch, Tim Schuhmann, Peter Ertl, Alex Bussenault, Meir Glick, Ina Dix, Frank Petersen, Dimitrios E Lizos (2017) Bioorganic & medicinal chemistry 25: 3 921-925

Potent, Selective, and Orally Bioavailable Inhibitors of VPS34 Provide Chemical Tools to Modulate Autophagy in Vivo.

2017-04-09T12:57:54Z

Autophagy is a dynamic process that regulates lysosomal-dependent degradation of cellular components. Until recently the study of autophagy has been hampered by the lack of reliable pharmacological tools, but selective inhibitors are now available to modulate the PI 3-kinase VPS34, which is required for autophagy. Here we describe the discovery of potent and selective VPS34 inhibitors, their pharm...

Ayako Honda, Edmund Harrington, Ivan Cornella-Taracido, Pascal Furet, Mark S Knapp, Meir Glick, Ellen Triantafellow, William E Dowdle, Dmitri Wiedershain, Wieslawa Maniara, Christine Moore, Peter M Finan, Lawrence G Hamann, Brant Firestone, Leon O Murphy, Erin P Keaney (2016) ACS medicinal chemistry letters 7: 1 72-76

Public Domain HTS Fingerprints: Design and Evaluation of Compound Bioactivity Profiles from PubChem's Bioassay Repository.

2017-04-09T12:57:54Z

Molecular profiling efforts aim at characterizing the biological actions of small molecules by screening them in hundreds of different biochemical and/or cell-based assays. Together, these assays yield a rich data landscape of target-based and phenotypic effects of the tested compounds. However, submitting an entire compound library to a molecular profiling panel can easily become cost-prohibitive...

Kazi Yasin Helal, Mateusz Maciejewski, Elisabet Gregori-Puigjané, Meir Glick, Anne Mai Wassermann (2016) Journal of chemical information and modeling 56: 2 390-398

Dark chemical matter as a promising starting point for drug lead discovery.

2017-04-09T13:00:33Z

High-throughput screening (HTS) is an integral part of early drug discovery. Herein, we focused on those small molecules in a screening collection that have never shown biological activity despite having been exhaustively tested in HTS assays. These compounds are referred to as 'dark chemical matter' (DCM). We quantified DCM, validated it in quality control experiments, described its physicochemic...

Anne Mai Wassermann, Eugen Lounkine, Dominic Hoepfner, Gaelle Le Goff, Frederick J King, Christian Studer, John M Peltier, Melissa L Grippo, Vivian Prindle, Jianshi Tao, Ansgar Schuffenhauer, Iain M Wallace, Shanni Chen, Philipp Krastel, Amanda Cobos-Correa, Christian N Parker, John W Davies, Meir Glick (2015) Nature chemical biology 11: 12 958-966

Experimental design strategy: weak reinforcement leads to increased hit rates and enhanced chemical diversity.

2016-04-02T11:52:01Z

High Throughput Screening (HTS) is a common approach in life sciences to discover chemical matter that modulates a biological target or phenotype. However, low assay throughput, reagents cost, or a flowchart that can deal with only a limited number of hits may impair screening large numbers of compounds. In this case, a subset of compounds is assayed, and in silico models are utilized to aid in it...

Mateusz Maciejewski, Anne Mai Wassermann, Meir Glick, Eugen Lounkine (2015) Journal of chemical information and modeling 55: 5 956-962

The opportunities of mining historical and collective data in drug discovery.

2016-04-02T11:52:01Z

Vast amounts of bioactivity data have been generated for small molecules across public and corporate domains. Biological signatures, either derived from systematic profiling efforts or from existing historical assay data, have been successfully employed for small molecule mechanism-of-action elucidation, drug repositioning, hit expansion and screening subset design. This article reviews different ...

Anne Mai Wassermann, Eugen Lounkine, John W Davies, Meir Glick, L Miguel Camargo (2015) Drug discovery today 20: 4 422-434

Large scale meta-analysis of fragment-based screening campaigns: privileged fragments and complementary technologies.

2016-04-02T11:52:01Z

A first step in fragment-based drug discovery (FBDD) often entails a fragment-based screen (FBS) to identify fragment "hits." However, the integration of conflicting results from orthogonal screens remains a challenge. Here we present a meta-analysis of 35 fragment-based campaigns at Novartis, which employed a generic 1400-fragment library against diverse target families using various biophysical ...

Peter S Kutchukian, Anne Mai Wassermann, Mika K Lindvall, S Kirk Wright, Johannes Ottl, Jaison Jacob, Clemens Scheufler, Andreas Marzinzik, Natasja Brooijmans, Meir Glick (2015) Journal of biomolecular screening 20: 5 588-596

A screening pattern recognition method finds new and divergent targets for drugs and natural products.

2016-04-02T11:52:01Z

Computational target prediction methods using chemical descriptors have been applied exhaustively in drug discovery to elucidate the mechanisms-of-action (MOAs) of small molecules. To predict truly novel and unexpected small molecule-target interactions, compounds must be compared by means other than their chemical structure alone. Here we investigated predictions made by a method, HTS fingerprint...

Anne Mai Wassermann, Eugen Lounkine, Laszlo Urban, Steven Whitebread, Shanni Chen, Kevin Hughes, Hongqiu Guo, Elena Kutlina, Alexander Fekete, Martin Klumpp, Meir Glick (2014) ACS chemical biology 9: 7 1622-1631

Bioturbo similarity searching: combining chemical and biological similarity to discover structurally diverse bioactive molecules.

2016-04-02T11:52:01Z

Virtual screening using bioactivity profiles has become an integral part of currently applied hit finding methods in pharmaceutical industry. However, a significant drawback of this approach is that it is only applicable to compounds that have been biologically tested in the past and have sufficient activity annotations for meaningful profile comparisons. Although bioactivity data generated in pha...

Anne Mai Wassermann, Eugen Lounkine, Meir Glick (2013) Journal of chemical information and modeling 53: 3 692-703

Efficient search of chemical space: navigating from fragments to structurally diverse chemotypes.

2016-04-02T11:47:20Z

We introduce a novel strategy to sample bioactive chemical space, which follows-up on hits from fragment campaigns without the need for a crystal structure. Our results strongly suggest that screening a few hundred or thousand fragments can substantially improve the selection of small-molecule screening subsets. By combining fragment-based screening with virtual fragment linking and HTS fingerprin...

Anne Mai Wassermann, Peter S Kutchukian, Eugen Lounkine, Tiffany Luethi, Jacques Hamon, Michael T Bocker, Hasnain A Malik, Sandra W Cowan-Jacob, Meir Glick (2013) Journal of medicinal chemistry 56: 21 8879-8891

Biodiversity of small molecules--a new perspective in screening set selection.

2016-04-02T11:52:01Z

How is the 'diversity' of a compound set defined and how is the most appropriate compound subset identified for assay when screening the entire HTS deck is not an option? A common approach has so far been to cover as much of the chemical space as possible by screening a chemically diverse set of compounds. We show that, rather than chemical diversity, the biologic diversity of a compound library i...

Paula M Petrone, Anne Mai Wassermann, Eugen Lounkine, Peter Kutchukian, Benjamin Simms, Jeremy Jenkins, Paul Selzer, Meir Glick (2013) Drug discovery today 18: 13-14 674-680

Rethinking molecular similarity: comparing compounds on the basis of biological activity.

2016-04-02T11:52:01Z

Since the advent of high-throughput screening (HTS), there has been an urgent need for methods that facilitate the interrogation of large-scale chemical biology data to build a mode of action (MoA) hypothesis. This can be done either prior to the HTS by subset design of compounds with known MoA or post HTS by data annotation and mining. To enable this process, we developed a tool that compares com...

Paula M Petrone, Benjamin Simms, Florian Nigsch, Eugen Lounkine, Peter Kutchukian, Allen Cornett, Zhan Deng, John W Davies, Jeremy L Jenkins, Meir Glick (2012) ACS chemical biology 7: 8 1399-1409

Inside the mind of a medicinal chemist: the role of human bias in compound prioritization during drug discovery.

2016-04-02T11:52:01Z

Medicinal chemists' "intuition" is critical for success in modern drug discovery. Early in the discovery process, chemists select a subset of compounds for further research, often from many viable candidates. These decisions determine the success of a discovery campaign, and ultimately what kind of drugs are developed and marketed to the public. Surprisingly little is known about the cognitive asp...

Peter S Kutchukian, Nadya Y Vasilyeva, Jordan Xu, Mika K Lindvall, Michael P Dillon, Meir Glick, John D Coley, Natasja Brooijmans (2012) PloS one 7: 11

Chemotography for multi-target SAR analysis in the context of biological pathways.

2016-04-02T11:52:01Z

The increasing amount of chemogenomics data, that is, activity measurements of many compounds across a variety of biological targets, allows for better understanding of pharmacology in a broad biological context. Rather than assessing activity at individual biological targets, today understanding of compound interaction with complex biological systems and molecular pathways is often sought in phen...

Eugen Lounkine, Peter Kutchukian, Paula Petrone, John W Davies, Meir Glick (2012) Bioorganic & medicinal chemistry 20: 18 5416-5427

From in silico target prediction to multi-target drug design: current databases, methods and applications.

2016-04-02T11:52:01Z

Given the tremendous growth of bioactivity databases, the use of computational tools to predict protein targets of small molecules has been gaining importance in recent years. Applications span a wide range, from the 'designed polypharmacology' of compounds to mode-of-action analysis. In this review, we firstly survey databases that can be used for ligand-based target prediction and which have gro...

Alexios Koutsoukas, Benjamin Simms, Johannes Kirchmair, Peter J Bond, Alan V Whitmore, Steven Zimmer, Malcolm P Young, Jeremy L Jenkins, Meir Glick, Robert C Glen, Andreas Bender (2011) Journal of proteomics 74: 12 2554-2574

Activity-aware clustering of high throughput screening data and elucidation of orthogonal structure-activity relationships.

2016-04-02T11:52:01Z

From a medicinal chemistry point of view, one of the primary goals of high throughput screening (HTS) hit list assessment is the identification of chemotypes with an informative structure-activity relationship (SAR). Such chemotypes may enable optimization of the primary potency, as well as selectivity and phamacokinetic properties. A common way to prioritize them is molecular clustering of the hi...

Eugen Lounkine, Florian Nigsch, Jeremy L Jenkins, Meir Glick (2011) Journal of chemical information and modeling 51: 12 3158-3168

Computational methods for early predictive safety assessment from biological and chemical data.

2016-04-02T11:52:01Z

The goal of early predictive safety assessment (PSA) is to keep compounds with detectable liabilities from progressing further in the pipeline. Such compounds jeopardize the core of pharmaceutical research and development and limit the timely delivery of innovative therapeutics to the patient. Computational methods are increasingly used to help understand observed data, generate new testable hypot...

Florian Nigsch, Eugen Lounkine, Patrick McCarren, Ben Cornett, Meir Glick, Kamal Azzaoui, Laszlo Urban, Philippe Marc, Arne Müller, Florian Hahne, David J Heard, Jeremy L Jenkins (2011) Expert opinion on drug metabolism & toxicology 7: 12 1497-1511

A lead discovery strategy driven by a comprehensive analysis of proteases in the peptide substrate space.

2011-04-01T19:13:04Z

We present here a comprehensive analysis of proteases in the peptide substrate space and demonstrate its applicability for lead discovery. Aligned octapeptide substrates of 498 proteases taken from the MEROPS peptidase database were used for the in silico analysis. A multiple-category naïve Bayes model, trained on the two-dimensional chemical features of the substrates, was able to classify the s...

Sai Chetan K Sukuru, Florian Nigsch, Jean Quancard, Martin Renatus, Rajiv Chopra, Natasja Brooijmans, Dmitri Mikhailov, Zhan Deng, Allen Cornett, Jeremy L Jenkins, Ulrich Hommel, John W Davies, Meir Glick (2010) Protein Sci 19: 11 2096-2109

Gaining Insight into Off-Target Mediated Effects of Drug Candidates with a Comprehensive Systems Chemical Biology Analysis.

2011-04-01T19:13:04Z

We present a workflow that leverages data from chemogenomics based target predictions with Systems Biology databases to better understand off-target related toxicities. By analyzing a set of compounds that share a common toxic phenotype and by comparing the pathways they affect with pathways modulated by nontoxic compounds we are able to establish links between pathways and particular adverse effe...

Josef Scheiber, Bin Chen, Mariusz Milik, Sai Chetan K Sukuru, Andreas Bender, Dmitri Mikhailov, Steven Whitebread, Jacques Hamon, Kamal Azzaoui, Laszlo Urban, Meir Glick, John W Davies, Jeremy L Jenkins (2009) J Chem Inf Model :

Use of ligand based models for protein domains to predict novel molecular targets and applications to triage affinity chromatography data.

2011-04-01T19:13:04Z

The elucidation of drug targets is important both to optimize desired compound action and to understand drug side-effects. In this study, we created statistical models which link chemical substructures of ligands to protein domains in a probabilistic manner and employ the model to triage the results of affinity chromatography experiments. By annotating targets with their InterPro domains, general ...

Andreas Bender, Dmitri Mikhailov, Meir Glick, Josef Scheiber, John W Davies, Stephen Cleaver, Stephen Marshall, John A Tallarico, Edmund Harrington, Ivan Cornella-Taracido, Jeremy L Jenkins (2009) J Proteome Res 8: 5 2575-2585

How similar are similarity searching methods? A principal component analysis of molecular descriptor space.

2011-04-01T19:13:04Z

Different molecular descriptors capture different aspects of molecular structures, but this effect has not yet been quantified systematically on a large scale. In this work, we calculate the similarity of 37 descriptors by repeatedly selecting query compounds and ranking the rest of the database. Euclidean distances between the rank-ordering of different descriptors are calculated to determine des...

Andreas Bender, Jeremy L Jenkins, Josef Scheiber, Sai Chetan K Sukuru, Meir Glick, John W Davies (2009) J Chem Inf Model 49: 1 108-119

Mapping adverse drug reactions in chemical space.

2011-04-01T19:13:04Z

We present a novel method to better investigate adverse drug reactions in chemical space. By integrating data sources about adverse drug reactions of drugs with an established cheminformatics modeling method, we generate a data set that is then visualized with a systems biology tool. Thereby new insights into undesired drug effects are gained. In this work, we present a global analysis linking che...

Josef Scheiber, Jeremy L Jenkins, Sai Chetan K Sukuru, Andreas Bender, Dmitri Mikhailov, Mariusz Milik, Kamal Azzaoui, Steven Whitebread, Jacques Hamon, Laszlo Urban, Meir Glick, John W Davies (2009) J Med Chem 52: 9 3103-3107

Plate-based diversity selection based on empirical HTS data to enhance the number of hits and their chemical diversity.

2011-04-01T19:13:04Z

Typically, screening collections of pharmaceutical companies contain more than a million compounds today. However, for certain high-throughput screening (HTS) campaigns, constraints posed by the assay throughput and/or the reagent costs make it impractical to screen the entire deck. Therefore, it is desirable to effectively screen subsets of the collection based on a hypothesis or a diversity sele...

Sai Chetan K Sukuru, Jeremy L Jenkins, Rohan E J Beckwith, Josef Scheiber, Andreas Bender, Dmitri Mikhailov, John W Davies, Meir Glick (2009) J Biomol Screen 14: 6 690-699

Gaining insight into off-target mediated effects of drug candidates with a comprehensive systems chemical biology analysis.

2011-04-01T19:13:04Z

"Virtual fragment linking": an approach to identify potent binders from low affinity fragment hits.

2011-04-01T19:13:04Z

In this work we explore the possibilities of using fragment-based screening data to prioritize compounds from a full HTS library, a method we call virtual fragment linking (VFL). The ability of VFL to identify compounds of nanomolar potency based on micromolar fragment binding data was tested on 75 target classes from the WOMBAT database and succeeded in 57 cases. Further, the method was demonstra...

Thomas J Crisman, Andreas Bender, Mariusz Milik, Jeremy L Jenkins, Josef Scheiber, Sai Chetan K Sukuru, Jasna Fejzo, Ulrich Hommel, John W Davies, Meir Glick (2008) J Med Chem 51: 8 2481-2491

Which aspects of HTS are empirically correlated with downstream success?

2011-04-01T19:13:04Z

High-throughput screening (HTS) is a well-established hit-finding approach used in the pharmaceutical industry. In this article, recent experience at Novartis with respect to factors influencing the success of HTS campaigns is discussed. An inherent measure of HTS quality could be defined by the assay Z and Z' factors, the number of hits and their biological potencies; however, such measures of qu...

Andreas Bender, Dejan Bojanic, John W Davies, Thomas J Crisman, Dmitri Mikhailov, Josef Scheiber, Jeremy L Jenkins, Zhan Deng, W Adam G Hill, Maxim Popov, Edgar Jacoby, Meir Glick (2008) Curr Opin Drug Discov Devel 11: 3 327-337

Computational design and crystal structure of an enhanced affinity mutant human CD8 alphaalpha coreceptor.

2011-04-01T19:13:52Z

Human CD8 is a T cell coreceptor, which binds to pHLA I and plays a pivotal role in the activation of cytotoxic T lymphocytes. Soluble recombinant CD8 alphaalpha has been shown to antagonize T cell activation, both in vitro and in vivo. However, because of a very low affinity for pHLA I, high concentrations of soluble CD8 alphaalpha are required for efficient inhibition. Based upon our knowledge o...

David K Cole, Pierre J Rizkallah, Jonathan M Boulter, Malkit Sami, Anne-lise Vuidepot, Meir Glick, Feng Gao, John I Bell, Bent K Jakobsen, George F Gao (2007) Proteins 67: 1 65-74

Flexible 3D pharmacophores as descriptors of dynamic biological space.

2011-04-01T19:13:52Z

Development of a pharmacophore hypothesis related to small-molecule activity is pivotal to chemical optimization of a series, since it defines features beneficial or detrimental to activity. Although crystal structures may provide detailed 3D interaction information for one molecule with its receptor, docking a different ligand to that model often leads to unreliable results due to protein flexibi...

James H Nettles, Jeremy L Jenkins, Chris Williams, Alex M Clark, Andreas Bender, Zhan Deng, John W Davies, Meir Glick (2007) J Mol Graph Model 26: 3 622-633

Enhanced immunogenicity of CTL antigens through mutation of the CD8 binding MHC class I invariant region.

2011-04-01T19:13:52Z

CD8(+) cytotoxic T lymphocytes (CTL) are key determinants of immunity to intracellular pathogens and neoplastic cells. Recognition of specific antigens in the form of peptide-MHC class I complexes (pMHCI) presented on the target cell surface is mediated by T cell receptor (TCR) engagement. The CD8 coreceptor binds to invariant domains of pMHCI and facilitates antigen recognition. Here, we investig...

Linda Wooldridge, Anna Lissina, Jonathan Vernazza, Emma Gostick, Bruno Laugel, Sarah L Hutchinson, Fareed Mirza, P Rod Dunbar, Jonathan M Boulter, Meir Glick, Vincenzo Cerundolo, Hugo A van den Berg, David A Price, Andrew K Sewell (2007) Eur J Immunol 37: 5 1323-1333

Understanding false positives in reporter gene assays: in silico chemogenomics approaches to prioritize cell-based HTS data.

2011-04-01T19:13:52Z

High throughput screening (HTS) data is often noisy, containing both false positives and negatives. Thus, careful triaging and prioritization of the primary hit list can save time and money by identifying potential false positives before incurring the expense of followup. Of particular concern are cell-based reporter gene assays (RGAs) where the number of hits may be prohibitively high to be scrut...

Thomas J Crisman, Christian N Parker, Jeremy L Jenkins, Josef Scheiber, Mathis Thoma, Zhao Bin Kang, Richard Kim, Andreas Bender, James H Nettles, John W Davies, Meir Glick (2007) J Chem Inf Model 47: 4 1319-1327

Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure.

2011-04-01T19:13:52Z

Preclinical Safety Pharmacology (PSP) attempts to anticipate adverse drug reactions (ADRs) during early phases of drug discovery by testing compounds in simple, in vitro binding assays (that is, preclinical profiling). The selection of PSP targets is based largely on circumstantial evidence of their contribution to known clinical ADRs, inferred from findings in clinical trials, animal experiments,...

Andreas Bender, Josef Scheiber, Meir Glick, John W Davies, Kamal Azzaoui, Jacques Hamon, Laszlo Urban, Steven Whitebread, Jeremy L Jenkins (2007) ChemMedChem 2: 6 861-873

"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection.

2011-04-01T19:13:52Z

This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per pla...

Thomas J Crisman, Jeremy L Jenkins, Christian N Parker, W Adam G Hill, Andreas Bender, Zhan Deng, James H Nettles, John W Davies, Meir Glick (2007) J Biomol Screen 12: 3 320-327

Streamlining lead discovery by aligning in silico and high-throughput screening.

2011-04-01T19:13:52Z

Lead discovery in the pharmaceutical environment is largely an industrial-scale process in which it is typical to screen 1-5 million compounds in a matter of weeks using High Throughput Screening (HTS). This process is a very costly endeavor. Typically a HTS campaign of 1 million compounds will cost anywhere from $500000 to $1000000. There is consequently a great deal of pressure to maximize the r...

John W Davies, Meir Glick, Jeremy L Jenkins (2006) Curr Opin Chem Biol 10: 4 343-351

"Bayes affinity fingerprints" improve retrieval rates in virtual screening and define orthogonal bioactivity space: when are multitarget drugs a feasible concept?

2011-04-01T19:13:52Z

Conventional similarity searching of molecules compares single (or multiple) active query structures to each other in a relative framework, by means of a structural descriptor and a similarity measure. While this often works well, depending on the target, we show here that retrieval rates can be improved considerably by incorporating an external framework describing ligand bioactivity space for co...

Andreas Bender, Jeremy L Jenkins, Meir Glick, Zhan Deng, James H Nettles, John W Davies (2006) J Chem Inf Model 46: 6 2445-2456

Bridging chemical and biological space: "target fishing" using 2D and 3D molecular descriptors.

2011-04-01T19:13:52Z

Bridging chemical and biological space is the key to drug discovery and development. Typically, cheminformatics methods operate under the assumption that similar chemicals have similar biological activity. Ideally then, one could predict a drug's biological function(s) given only its chemical structure by similarity searching in libraries of compounds with known activities. In practice, effectivel...

James H Nettles, Jeremy L Jenkins, Andreas Bender, Zhan Deng, John W Davies, Meir Glick (2006) J Med Chem 49: 23 6802-6810

Prediction of biological targets for compounds using multiple-category Bayesian models trained on chemogenomics databases.

2011-04-01T19:13:52Z

Target identification is a critical step following the discovery of small molecules that elicit a biological phenotype. The present work seeks to provide an in silico correlate of experimental target fishing technologies in order to rapidly fish out potential targets for compounds on the basis of chemical structure alone. A multiple-category Laplacian-modified naïve Bayesian model was trained on ...

Nidhi, Meir Glick, John W Davies, Jeremy L Jenkins (2006) J Chem Inf Model 46: 3 1124-1133

Enrichment of high-throughput screening data with increasing levels of noise using support vector machines, recursive partitioning, and laplacian-modified naive bayesian classifiers.

2011-04-01T19:14:56Z

High-throughput screening (HTS) plays a pivotal role in lead discovery for the pharmaceutical industry. In tandem, cheminformatics approaches are employed to increase the probability of the identification of novel biologically active compounds by mining the HTS data. HTS data is notoriously noisy, and therefore, the selection of the optimal data mining method is important for the success of such a...

Meir Glick, Jeremy L Jenkins, James H Nettles, Hamilton Hitchings, John W Davies (2006) J Chem Inf Model 46: 1 193-200

Crystallization and preliminary X-ray structural studies of a high-affinity CD8alphaalpha co-receptor to pMHC.

2011-04-01T19:14:56Z

The class I CD8 positive T-cell response is involved in a number of conditions in which artificial down-regulation and control would be therapeutically beneficial. Such conditions include a number of autoimmune diseases and graft rejection in transplant patients. Although the CD8 T-cell response is dominated by the TCR-pMHC interaction, activation of T cells is in most cases also dependent on a nu...

David K Cole, Pierre J Rizkallah, Malkit Sami, Nikolai M Lissin, Feng Gao, John I Bell, Jonathan M Boulter, Meir Glick, Anne Lise Vuidepot, Bent K Jakobsen, George F Gao (2005) Acta Crystallogr Sect F Struct Biol Cryst Commun 61: Pt 3 285-287

Interaction between the CD8 coreceptor and major histocompatibility complex class I stabilizes T cell receptor-antigen complexes at the cell surface.

2011-04-01T19:14:56Z

The off-rate (k(off)) of the T cell receptor (TCR)/peptide-major histocompatibility complex class I (pMHCI) interaction, and hence its half-life, is the principal kinetic feature that determines the biological outcome of TCR ligation. However, it is unclear whether the CD8 coreceptor, which binds pMHCI at a distinct site, influences this parameter. Although biophysical studies with soluble protein...

Linda Wooldridge, Hugo A van den Berg, Meir Glick, Emma Gostick, Bruno Laugel, Sarah L Hutchinson, Anita Milicic, Jason M Brenchley, Daniel C Douek, David A Price, Andrew K Sewell (2005) J Biol Chem 280: 30 27491-27501

Enrichment of extremely noisy high-throughput screening data using a naïve Bayes classifier.

2011-04-01T19:14:56Z

The noise level of a high-throughput screening (HTS) experiment depends on various factors such as the quality and robustness of the assay itself and the quality of the robotic platform. Screening of compound mixtures is noisier than screening single compounds per well. A classification model based on naïve Bayes (NB) may be used to enrich such data. The authors studied the ability of the NB clas...

Meir Glick, Anthony E Klon, Pierre Acklin, John W Davies (2004) J Biomol Screen 9: 1 32-36

A 3D similarity method for scaffold hopping from known drugs or natural ligands to new chemotypes.

2011-04-01T19:14:56Z

A primary goal of 3D similarity searching is to find compounds with similar bioactivity to a reference ligand but with different chemotypes, i.e., "scaffold hopping". However, an adequate description of chemical structures in 3D conformational space is difficult due to the high-dimensionality of the problem. We present an automated method that simplifies flexible 3D chemical descriptions in which ...

Jeremy L Jenkins, Meir Glick, John W Davies (2004) J Med Chem 47: 25 6144-6159

Finding more needles in the haystack: A simple and efficient method for improving high-throughput docking results.

2011-04-01T19:14:56Z

The technology underpinning high-throughput docking (HTD) has developed over the past few years to where it has become a vital tool in modern drug discovery. Although the performance of various docking algorithms is adequate, the ability to accurately and consistently rank compounds using a scoring function remains problematic. We show that by employing a simple machine learning method (naïve Bay...

Anthony E Klon, Meir Glick, Mathis Thoma, Pierre Acklin, John W Davies (2004) J Med Chem 47: 11 2743-2749

Combination of a naive Bayes classifier with consensus scoring improves enrichment of high-throughput docking results.

2011-04-01T19:14:56Z

We have previously shown that a machine learning technique can improve the enrichment of high-throughput docking (HTD) results. In the previous cases studied, however, the application of a naive Bayes classifier failed to improve enrichment for instances where HTD alone was unable to generate an acceptable enrichment. We present here a protocol to rescue poor docking results a priori using a combi...

Anthony E Klon, Meir Glick, John W Davies (2004) J Med Chem 47: 18 4356-4359

Application of machine learning to improve the results of high-throughput docking against the HIV-1 protease.

2011-04-01T19:14:56Z

We have previously reported that the application of a Laplacian-modified naive Bayesian (NB) classifier may be used to improve the ranking of known inhibitors from a random database of compounds after High-Throughput Docking (HTD). The method relies upon the frequency of substructural features among the active and inactive compounds from 2D fingerprint information of the compounds. Here we present...

Anthony E Klon, Meir Glick, John W Davies (2004) J Chem Inf Comput Sci 44: 6 2216-2224

Refined structure of bovine carboxypeptidase A at 1.25 A resolution.

2011-04-01T19:15:35Z

The crystal structure of the bovine zinc metalloproteinase carboxypeptidase A (CPA) has been refined to 1.25 A resolution based on room-temperature X-ray synchrotron data. The significantly improved structure of CPA at this resolution (anisotropic temperature factors, R factor = 10.4%, R(free) = 14.5%) allowed the modelling of conformational disorders of side chains, improved the description of th...

Alexandra Kilshtain-Vardi, Meir Glick, Harry M Greenblatt, Amiram Goldblum, Gil Shoham (2003) Acta Crystallogr D Biol Crystallogr 59: Pt 2 323-333

The CD8 T cell coreceptor exhibits disproportionate biological activity at extremely low binding affinities.

2011-04-01T19:14:56Z

T lymphocytes recognize peptides presented in the context of major histocompatibility complex (MHC) molecules on the surface of antigen presenting cells. Recognition specificity is determined by the alphabeta T cell receptor (TCR). The T lymphocyte surface glycoproteins CD8 and CD4 enhance T cell antigen recognition by binding to MHC class I and class II molecules, respectively. Biophysical measur...

Sarah L Hutchinson, Linda Wooldridge, Sabrina Tafuro, Bruno Laugel, Meir Glick, Jonathan M Boulter, Bent K Jakobsen, David A Price, Andrew K Sewell (2003) J Biol Chem 278: 27 24285-24293

Stable, soluble T-cell receptor molecules for crystallization and therapeutics.

2011-04-01T19:14:56Z

Antibody and T-cell receptors (TCRs) are the primary recognition molecules of the adaptive immune system. Antibodies have been extensively characterized and are being developed for a large number of therapeutic applications. This has been possible because of the ability to manufacture stable, soluble, monoclonal antibodies which retain the antigen specificity of B cells. Unlike antibodies, TCRs ar...

Jonathan M Boulter, Meir Glick, Penio T Todorov, Emma Baston, Malkit Sami, Pierre Rizkallah, Bent K Jakobsen (2003) Protein Eng 16: 9 707-711

Pattern recognition and massively distributed computing.

2011-04-01T19:15:35Z

A feature of Peter Kollman's research was his exploitation of the latest computational techniques to devise novel applications of the free energy perturbation method. He would certainly have seized upon the opportunities offered by massively distributed computing. Here we describe the use of over a million personal computers to perform virtual screening of 3.5 billion druglike molecules against pr...

E Keith Davies, Meir Glick, Karl N Harrison, W Graham Richards (2002) J Comput Chem 23: 16 1544-1550

Docking of flexible molecules using multiscale ligand representations.

2011-04-01T19:15:35Z

Structural genomics will yield an immense number of protein three-dimensional structures in the near future. Automated theoretical methodologies are needed to exploit this information and are likely to play a pivotal role in drug discovery. Here, we present a fully automated, efficient docking methodology that does not require any a priori knowledge about the location of the binding site or functi...

Meir Glick, Guy H Grant, W Graham Richards (2002) J Med Chem 45: 21 4639-4646

A stochastic algorithm for global optimization and for best populations: a test case of side chains in proteins.

2011-04-01T19:15:36Z

The problem of global optimization is pivotal in a variety of scientific fields. Here, we present a robust stochastic search method that is able to find the global minimum for a given cost function, as well as, in most cases, any number of best solutions for very large combinatorial "explosive" systems. The algorithm iteratively eliminates variable values that contribute consistently to the highes...

Meir Glick, Anwar Rayan, Amiram Goldblum (2002) Proc Natl Acad Sci U S A 99: 2 703-708

Pinpointing anthrax-toxin inhibitors.

2011-04-01T19:15:35Z

Meir Glick, Guy H Grant, W Graham Richards (2002) Nat Biotechnol 20: 2 118-119

Identification of ligand binding sites on proteins using a multi-scale approach.

2011-04-01T19:15:35Z

Identification of a ligand binding site on a protein is pivotal to drug discovery. To date, no reliable and computationally feasible general approach to this problem has been published. Here we present an automated efficient method for determining binding sites on proteins for potential ligands without any a priori knowledge. Our method is based upon the multiscale concept where we deal with a hie...

Meir Glick, Daniel D Robinson, Guy H Grant, W Graham Richards (2002) J Am Chem Soc 124: 10 2337-2344

Novel CD8+ T cell antagonists based on beta 2-microglobulin.

2011-04-01T19:15:35Z

The CD8 coreceptor of cytotoxic T lymphocytes binds to a conserved region of major histocompatibility complex class I molecules during recognition of peptide-major histocompatibility complex (MHC) class I antigens on the surface of target cells. This event is central to the activation of cytotoxic T lymphocyte (CTL) effector functions. The contribution of the MHC complex class I light chain, beta(...

Meir Glick, David A Price, Anne-Lise Vuidepot, Torben B Andersen, Sarah L Hutchinson, Bruno Laugel, Andrew K Sewell, Jonathan M Boulter, P Rod Dunbar, Vincenzo Cerundolo, Annette Oxenius, John I Bell, W Graham Richards, Bent K Jakobsen (2002) J Biol Chem 277: 23 20840-20846

A novel energy-based stochastic method for positioning polar protons in protein structures from X-rays.

2011-04-01T19:38:08Z

A novel automated method for the optimal placement of polar hydrogens in a protein structure is presented. The algorithm adds initially, to a protein data bank file of the protein, nonrotatable hydrogens such as peptide backbone hydrogens according to geometric considerations. Then, water protons and polar side chain protons of lysine, serine, threonine, tyrosine, aspartic acid, glutamic acid, and...

M Glick, A Goldblum (2000) Proteins 38: 3 273-287

US 2005/0114035 A1 Method for binding site identification

2011-12-31T20:36:13Z

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7,329,731 Soluble T cell receptor

2011-04-01T19:35:33Z

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7,763,718 Soluble T cell receptors

2011-04-01T19:35:51Z

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7,666,604 Modified soluble T cell receptor

2011-04-01T19:34:03Z

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7,569,664 Single chain recombinant T cell receptors

2011-04-01T19:34:36Z

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7,425,339 CD8alpha mutants

2011-04-01T19:35:03Z

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