Rajarshi Guha › Comments

J. Am. Chem. Soc. In Journal of the American Chemical Society (19 January 2013), doi:10.1021/ja309304m The identification of factors that promote ? cell proliferation could ultimately move type 1 diabetes treatment away from insulin injection therapy and toward a cure. We have performed high-throughput, cell-based screens using rodent ? cell lines to identify molecules that induce proliferation of ? cells. Herein we report the discovery and characterization of WS6, a novel small molecule that promotes ? cell proliferation in rodent and human primary islets. In the RIP-DTA mouse model of ? cell ablation, WS6 normalized blood glucose and induced concomitant increases in ? cell proliferation and ? cell number. Affinity pulldown and kinase profiling studies implicate Erb3 binding protein-1 and the I?B kinase pathway in the mechanism of action of WS6. Weijun Shen, Matthew Tremblay, Vishal Deshmukh, Weidong Wang, Christophe Filippi, George Harb, You-qing Zhang, Anwesh Kamireddy, Janine... - Rajarshi Guha

There's a reference to talks of length 5, 6 and 8 minutes. I'm a bit confused...? - Noel O'Boyle

thanks for catching it. should all be 8 min - Rajarshi Guha

RNA Biology, Vol. 10, No. 2., pp. 1-14 A Druz, YC Chen, R Guha, M Betenbaugh, SE Martin, J Shiloacch - Rajarshi Guha

Current Topics in Medicinal Chemistry (September 2012), pp. 1987-2001, doi:10.2174/156802612804910304 The Structure-Activity Relationships (SAR) landscape and activity cliffs concepts have their origins in medicinal chemistry and receptor-ligand interactions modelling. While intuitive, the definition of an activity cliff as a “pair of structurally similar compounds with large differences in potency“ is commonly recognized as ambiguous. This paper proposes a new and efficient method for identifying activity cliffs and visualization of activity landscapes. The activity cliffs definition could be improved to reflect not the cliff steepness alone, but also the rate of the change of the steepness. The method requires explicitly setting similarity and activity difference thresholds, but provides means to explore multiple thresholds and to visualize in a single map how the thresholds affect the activity cliff identification. The identification of the activity cliffs is addressed by... - Rajarshi Guha

Current Topics in Medicinal Chemistry (September 2012), pp. 1946-1956, doi:10.2174/156802612804910278 Numerical characterization of molecular structure is a first step in many computational analysis of chemical structure data. These numerical representations, termed descriptors, come in many forms, ranging from simple atom counts and invariants of the molecular graph to distribution of properties, such as charge, across a molecular surface. In this article we first present a broad categorization of descriptors and then describe applications and toolkits that can be employed to evaluate them. We highlight a number of issues surrounding molecular descriptor calculations such as versioning and reproducibility and describe how some toolkits have attempted to address these problems. Rajarshi Guha, Egon Willighagen - Rajarshi Guha

Nature, Vol. 493, No. 7433. (24 January 2013), pp. 473-475, doi:10.1038/493473a Chris Mattmann - Rajarshi Guha

Biotechniques, Vol. 49, No. 3. (2010), pp. 663-665 J Gorentstein, B Zack, JR Marszalek, A Bagchi, S Subramaniam, P Carroll, C Elbi - Rajarshi Guha

So that's what the fancy header in Elsevier journal articles cost! - Rajarshi Guha

Nature Chemical Biology, Vol. 2, No. 9. (18 August 2006), pp. 458-466, doi:10.1038/nchembio817 Combinatorial control of biological processes, in which redundancy and multifunctionality are the norm, fundamentally limits the therapeutic index that can be achieved by even the most potent and highly selective drugs. Thus, it will almost certainly be necessary to use new 'targeted' pharmaceuticals in combinations. Multicomponent drugs are standard in cytotoxic chemotherapy, but their development has required arduous empirical testing. However, experimentally validated numerical models should greatly aid in the formulation of new combination therapies, particularly those tailored to the needs of specific patients. This perspective focuses on opportunities and challenges inherent in the application of mathematical modeling and systems approaches to pharmacology, specifically with respect to the idea of achieving combinatorial selectivity through use of multicomponent drugs. Jonathan... - Rajarshi Guha

Cancer Discovery, Vol. 3, No. 1. (01 January 2013), pp. 52-67, doi:10.1158/2159-8290.CD-12-0408 Matthew Held, Casey Langdon, James Platt, Tisheeka Graham-Steed, Zongzhi Liu, Ashok Chakraborty, Antonella Bacchiocchi, Andrew Koo, Jonathan Haskins, Marcus Bosenberg, David Stern - Rajarshi Guha

J. Chem. Inf. Model. In Journal of Chemical Information and Modeling, Vol. 52, No. 4. (21 March 2012), pp. 867-881, doi:10.1021/ci200528d The aim of virtual screening (VS) is to identify bioactive compounds through computational means, by employing knowledge about the protein target (structure-based VS) or known bioactive ligands (ligand-based VS). In VS, a large number of molecules are ranked according to their likelihood to be bioactive compounds, with the aim to enrich the top fraction of the resulting list (which can be tested in bioassays afterward). At its core, VS attempts to improve the odds of identifying bioactive molecules by maximizing the true positive rate, that is, by ranking the truly active molecules as high as possible (and, correspondingly, the truly inactive ones as low as possible). In choosing the right approach, the researcher is faced with many questions: where does the optimal balance between efficiency and accuracy lie when evaluating a particular algorithm;... - Rajarshi Guha

In the meantime, David Colquhoun has decided to make his distaste for altmetrics personal by discrediting the messanger. Since I have you guys to thank for increasing my awareness of classic derailing techniques, figured I'd point it out: https://twitter.com/david_c... - Heather Piwowar

+1 for CiTO. I dunno the best way to push it though, no tool yet that makes it easy. I think it'd have to be a tool that automatically classifies them when you submit a paper, and then authors are tasked to fix wrong ones. or other ideas? - Heather Piwowar

Drug Discovery Today, Vol. 17, No. 13-14. (July 2012), pp. 665-670, doi:10.1016/j.drudis.2012.01.015 The pharmaceutical industry is in the process of re-inventing its pipeline in an attempt to overcome its increasing phase II and III attrition rates. Here, we describe how systems pharmacology can be used as a risk assessment tool to alleviate this problem before bringing in larger investments. We propose that this translational research tool could provide a valuable, complementary addition to other emerging innovative approaches for target identification and validation in discovery and, ultimately, for aiding clinical trial optimization. Lourdes Cucurull-Sanchez, Karen Spink, Sterghios Moschos - Rajarshi Guha

Proceedings of the National Academy of Sciences (18 December 2012), doi:10.1073/pnas.1210419110 Combination chemotherapies have been a mainstay in the treatment of disseminated malignancies for almost 60 y, yet even successful regimens fail to cure many patients. Although their single-drug components are well studied, the mechanisms by which drugs work together in clinical combination regimens are poorly understood. Here, we combine RNAi-based functional signatures with complementary informatics tools to examine drug combinations. This approach seeks to bring to combination therapy what the knowledge of biochemical targets has brought to single-drug therapy and creates a statistical and experimental definition of “combination drug mechanisms of action.” We show that certain synergistic drug combinations may act as a more potent version of a single drug. Conversely, unlike these highly synergistic combinations, most drugs average extant single-drug variations in therapeutic response.... - Rajarshi Guha

Histochem Cell Buil, Vol. 133 (2010), pp. 477-480 Y Ohsaki, Y Shinohara, M Suzuki, T Fujimoto - Rajarshi Guha

Nucleic Acids Research, Vol. 41, No. D1. (01 January 2013), pp. D1137-D1143, doi:10.1093/nar/gks1059 The SwissBioisostere database (http://www.swissbioisostere.ch) contains information on molecular replacements and their performance in biochemical assays. It is meant to provide researchers in drug discovery projects with ideas for bioisosteric modifications of their current lead molecule, as well as to give interested scientists access to the details on particular molecular replacements. As of August 2012, the database contains 21 293 355 datapoints corresponding to 5 586 462 unique replacements that have been measured in 35 039 assays against 1948 molecular targets representing 30 target classes. The accessible data were created through detection of matched molecular pairs and mining bioactivity data in the ChEMBL database. The SwissBioisostere database is hosted by the Swiss Institute of Bioinformatics and available via a web-based interface. Matthias Wirth, Vincent Zoete, Olivier... - Rajarshi Guha

Drug Discovery Today, Vol. 17, No. 5-6. (March 2012), pp. 203-214, doi:10.1016/j.drudis.2012.02.002 Conventional drug discovery strategies are typically ‘target centric’ based on the selection of lead compounds with optimised ‘on-target’ potency and selectivity profiles. However, high-attrition rates are often the result of compensatory or redundant cancer mechanisms and the fact that tumours do not find it difficult to escape inhibition of a single pathway. In this article, we highlight two emerging and complimentary technologies; namely phenotypic imaging and post-translational pathway profiling, which when combined with relevant disease models can provide pharmacodiagnostic and drug combination strategies that predict and counteract inherent and adaptive drug resistance. The implementation of such approaches at early stages of the drug discovery process enables more informed decisions on candidate drug selection and how to maximise and predict efficacy before clinical development.... - Rajarshi Guha

Journal of Biomolecular Screening, Vol. 17, No. 9. (01 October 2012), pp. 1204-1210, doi:10.1177/1087057112458317 Cancer stem cells (CSCs) are resistant to standard cancer treatments and are likely responsible for cancer recurrence, but few therapies target this subpopulation. Due to the difficulty in propagating CSCs outside of the tumor environment, previous work identified CSC-like cells by inducing human breast epithelial cells into an epithelial-to-mesenchymal transdifferentiated state (HMLE_sh_ECad). A phenotypic screen was conducted against HMLE_sh_ECad with 300 718 compounds from the Molecular Libraries Small Molecule Repository to identify selective inhibitors of CSC growth. The screen yielded 2244 hits that were evaluated for toxicity and selectivity toward an isogenic control cell line. An acyl hydrazone scaffold emerged as a potent and selective scaffold targeting HMLE_sh_ECad. Fifty-three analogues were acquired and tested; compounds ranged in potency from 790 nM to... - Rajarshi Guha

why no web service? - Andrew Lang

Thanks Rajarshi - I emailed him and he said 100+ is rejected - Andrew Lang

Nat Genet, Vol. 38, No. 4. (19 April 2006), pp. 489-494, doi:10.1038/ng1755 Multidrug treatments are increasingly important in medicine and for probing biological systems1, 2, 3, 4, 5, 6. Although many studies have focused on interactions between specific drugs, little is known about the system properties of a full drug interaction network6. Like their genetic counterparts, two drugs may have no interaction, or they may interact synergistically or antagonistically to increase or suppress their individual effects. Here we use a sensitive bioluminescence technique7, 8 to provide quantitative measurements of pairwise interactions among 21 antibiotics that affect growth rate in Escherichia coli. We find that the drug interaction network possesses a special property: it can be separated into classes of drugs such that any two classes interact either purely synergistically or purely antagonistically. These classes correspond directly to the cellular functions affected by the drugs. This... - Rajarshi Guha

Impressive work! - Rajarshi Guha

Nat Chem Biol, Vol. 8, No. 11. (November 2012), pp. 905-912, doi:10.1038/nchembio.1085 Georg Winter, Uwe Rix, Scott Carlson, Karoline Gleixner, Florian Grebien, Manuela Gridling, André Müller, Florian Breitwieser, Martin Bilban, Jacques Colinge, Peter Valent, Keiryn Bennett, Forest White, Giulio Superti-Furga - Rajarshi Guha

J. Med. Chem. In Journal of Medicinal Chemistry, Vol. 55, No. 16. (13 July 2012), pp. 7054-7060, doi:10.1021/jm300671m Reprofiling of existing drugs to treat conditions not originally targeted is an attractive means of addressing the problem of a decreasing stream of approved drugs. To determine if 3D shape similarity can be used to rationalize an otherwise serendipitous process, we employed 3D shape-based virtual screening to reprofile existing FDA-approved drugs. The study was conducted in two phases. First, multiple histamine H1 receptor antagonists were identified to be used as query molecules, and these were compared to a database of approved drugs. Second, the hits were ranked according to 3D similarity and the top drugs evaluated in a cell-based assay. The virtual screening methodology proved highly successful, as 13 of 23 top drugs tested selectively inhibited histamine-induced calcium release with the best being chlorprothixene (IC50 1 nM). Finally, we confirmed that the... - Rajarshi Guha

thanks. heh, at least it mistakes me for a famous person - Rajarshi Guha

(1 Oct 2012) Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. The network approach not only gives a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. Here we give a comprehensive assessment of the analytical tools of network topology and dynamics. We summarize the current knowledge and the state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets. We show how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as... - Rajarshi Guha

so wait for the old guard to retire before real progress is made? #openaccess - Rajarshi Guha

Annals of Oncology (07 February 2012), doi:10.1093/annonc/mdr608 Background: Clinical trials evaluating drug combinations are often stimulated by claims of synergistic interactions in preclinical models. Overuse or misuse of the term synergy could lead to poorly designed clinical studies. A Ocana, E Amir, C Yeung, B Seruga, IF Tannock - Rajarshi Guha

Concurrency Computat.: Pract. Exper. (2012), pp. n/a-n/a, doi:10.1002/cpe.2926 Virtual molecular docking is a computational method used in computer-aided drug discovery that calculates the binding affinity of a small molecule drug candidate to a target protein. High-throughput virtual screenings calculate the binding affinities for a large number of molecules at once and ranks potential drug candidates to greatly reduces the time and cost of suggesting new potential pharmaceuticals. This high-throughput screening is a task parallel process and therefore well-suited for distributed computing. In this study, we use the open source Hadoop framework implementing the MapReduce paradigm for distributed computing on a cloud platform and the widely used molecular docking program, AutoDock. The initial implementation of AutoDockCloud showed a speed-up of 450 on Kandinsky, a cloud computer located at Oak Ridge National Laboratory. Further modifications show promise for a greater speed-up of... - Rajarshi Guha

+1 for awesome title :-) - Noel O'Boyle

Sure. - Noel O'Boyle

Future medicinal chemistry, Vol. 3, No. 4. (March 2011), pp. 425-436, doi:10.4155/fmc.10.293 Bioisosteric replacements are commonly understood to be replacements of groups of atoms in bioactive compounds that retain their specific activity and retain, or further improve, compound potency. Such chemical modifications are of high interest in medicinal chemistry and are often considered in compound exploration and optimization. We have applied the matched molecular pair formalism to carry out a large-scale data mining study to identify bioisosteres in publicly available active compounds with similar potency. Our data mining effort has identified a set of 96 nonredundant bioisosteric replacements, approximately half of which were previously unobserved. However, a number of replacements commonly considered to be bioisosteric did not meet our extended bioisostere selection criteria, which included high frequency of occurrence, limited potency alterations and activity across different target... - Rajarshi Guha