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Dec
30

Summary of collaborative publications in 2013.

Time for a brief end of year summary and some insights into various papers, reviews and commentaries I was involved in this year. I have probably missed a few papers that are either not in PubMed or come to mind readily so will likely add as I remember them.

What really struck me in a year in which papers and the publication process have had a huge role, is how some of the established publishers are still so incredibly slow in getting accepted papers to the ASAP stage. ACS win awards for being fast and I am also impressed by J Cheminform.

While not all the papers come from my work with CDD, there are a bolus on TB and a couple on Malaria through collaborations. Again, as in previous years while much of the TB work was obviously grant funded, many of the projects I have helped out on did not result in any grant funding directly to me, so count this as a donation to science..When you add it up at least 14 or so of the following papers involved my unfunded input. I probably would not have it any other way, however I would prefer it if it resulted in freely available papers.

The year was also busy for grant writing, with many written with others and we are starting to see the payoff for this. It’s been a long and winding year. Who knows what 2014 will have in store, but hopefully I will be writing fewer grants and try to get to some languishing projects sitting on ice. I hope I can enjoy it and I have a bit more time to invest in the kinds of scientific collaborations which make it all worthwhile. My wish is that I can spend more time on the rare diseases.

 A huge thank you to the many collaborators, co-authors and friends.

Progress in computational toxicology.

Ekins S.

J Pharmacol Toxicol Methods. 2013 Dec 19. pii: S1056-8719(13)00325-0. doi: 10.1016/j.vascn.2013.12.003. [Epub ahead of print]

PMID:24361690

Comments: This review started life as a book chapter which the editors wanted changing for their book and I had spent enough time on it already. I tried to include a bit of a summary of online tools for metabolism ADME/Tox predictions.

No activation of human PXR by hyperforin-related phloroglucinols.

Kandel BA, Ekins S, Leuner K, Thasler WE, Harteneck C, Zanger UM.

J Pharmacol Exp Ther. 2013 Nov 20. [Epub ahead of print]

PMID:24259679 Free Article

Comments: I really enjoyed this collaboration with a group I had not worked with before and was actively involved in PXR predictions and paper writing.

Fusing Dual-Event Data Sets for Mycobacterium tuberculosis Machine Learning Models and Their Evaluation.

Ekins S, Freundlich JS, Reynolds RC.

J Chem Inf Model. 2013 Nov 25;53(11):3054-63. doi: 10.1021/ci400480s. Epub 2013 Oct 30.

PMID:24144044

Comments: The most recent of the TB modeling papers – This one came out of comments on a grant with reviewers asking why we had not looked at other machine learning methods..This should serve as a handy demonstration of different methods with the datasets.

Combining Computational Methods for Hit to Lead Optimization in Mycobacterium Tuberculosis Drug Discovery.

Ekins S, Freundlich JS, Hobrath JV, Lucile White E, Reynolds RC.

Pharm Res. 2013 Oct 17. [Epub ahead of print]

PMID:24132686

Comments: The data for this was a ‘gift’ from Bob Reynolds and SRI which provided another continuation of the Bayesian models for TB and large scale testing. Although I was not involved in their ARRA grant, being given the opportunity to use the data and author the paper was a great opportunity.

Computational Models for Neglected Diseases: Gaps and Opportunities.

Ponder EL, Freundlich JS, Sarker M, Ekins S.

Pharm Res. 2013 Aug 30. [Epub ahead of print]

PMID:23990313

Comments: This commentary came out of an SBIR which was greatly expanded beyond the single neglected disease in that topic. It discusses where computational approaches have been used throughout the R&D process of many neglected diseases. I hope it stimulates more use of such approaches.

Multifaceted roles of ultra-rare and rare disease patients/parents in drug discovery.

Wood J, Sames L, Moore A, Ekins S.

Drug Discov Today. 2013 Nov;18(21-22):1043-51. doi: 10.1016/j.drudis.2013.08.006. Epub 2013 Aug 19.

PMID:23968993

Comments: Probably wins the prize for most rewarding review to write. It combines the voices of 3 rare disease advocates in one review. Having worked with these friends for well over a year It was time that they told their stories together. I just lightly edited really and added a little informatics.

Human immunodeficiency virus protease inhibitors interact with ATP binding cassette transporter 4/multidrug resistance protein 4: a basis for unanticipated enhanced cytotoxicity.

Fukuda Y, Takenaka K, Sparreboom A, Cheepala SB, Wu CP, Ekins S, Ambudkar SV, Schuetz JD.

Mol Pharmacol. 2013 Sep;84(3):361-71. doi: 10.1124/mol.113.086967. Epub 2013 Jun 17.

PMID:23775562

Comments: This paper has some modeling contributed and is my first collaboration with John’s group at St Jude Children’s Hospital.

Enhancing hit identification in Mycobacterium tuberculosis drug discovery using validated dual-event Bayesian models.

Ekins S, Reynolds RC, Franzblau SG, Wan B, Freundlich JS, Bunin BA.

PLoS One. 2013 May 7;8(5):e63240. doi: 10.1371/journal.pone.0063240. Print 2013.

PMID:23667592 Free PMC Article

Comments: See some of my earlier blogging in the year about getting this paper in PLOSONE. A companion paper to the earlier one in Chem Biol. Actually there were 3 papers that were in progress in parallel. The 3rd is in press at Tuberculosis and will be published in 2014.

Dispensing processes impact apparent biological activity as determined by computational and statistical analyses.

Ekins S, Olechno J, Williams AJ.

PLoS One. 2013 May 1;8(5):e62325. doi: 10.1371/journal.pone.0062325. Print 2013.

PMID:23658723 Free PMC Article

Comments: See earlier extensive blog posts on this paper. All the work was done in 2012. Lots of ideas to expand the work. Tried to reach out to others, but I sense this one will just have to wait.

Computational models for tuberculosis drug discovery.

Ekins S, Freundlich JS.

Methods Mol Biol. 2013;993:245-62. doi: 10.1007/978-1-62703-342-8_16. Review.

PMID:23568475

Comments: A review of the TB modeling work up until 2012.

The Collaborative Drug Discovery (CDD) database.

Ekins S, Bunin BA.

Methods Mol Biol. 2013;993:139-54. doi: 10.1007/978-1-62703-342-8_10.

PMID:23568469

Comments: A review of the CDD work up until 2012.

Novel yeast-based strategy unveils antagonist binding regions on the nuclear xenobiotic receptor PXR.

Li H, Redinbo MR, Venkatesh M, Ekins S, Chaudhry A, Bloch N, Negassa A, Mukherjee P, Kalpana G, Mani S.

J Biol Chem. 2013 May 10;288(19):13655-68. doi: 10.1074/jbc.M113.455485. Epub 2013 Mar 22.

PMID:23525103

Comments: My contribution to this was some modeling/ docking to try to rationalize the biological data. Back in 2008 we had some initial ideas there might be more binding regions on PXR.

Bayesian models leveraging bioactivity and cytotoxicity information for drug discovery.

Ekins S, Reynolds RC, Kim H, Koo MS, Ekonomidis M, Talaue M, Paget SD, Woolhiser LK, Lenaerts AJ, Bunin BA, Connell N, Freundlich JS.

Chem Biol. 2013 Mar 21;20(3):370-8. doi: 10.1016/j.chembiol.2013.01.011.

PMID:23521795

Comments: The first in the years crop of TB papers. Sprang from extensive work over preceding 2 years. And great collaboration with the Freundlich Lab.

TB Mobile: a mobile app for anti-tuberculosis molecules with known targets.

Ekins S, Clark AM, Sarker M.

J Cheminform. 2013 Mar 6;5(1):13. doi: 10.1186/1758-2946-5-13.

PMID:23497706 Free PMC Article

Comments: A new mobile app that was an idea that spring from an STTR, why not use the data differently.

Cross-reactivity studies and predictive modeling of “Bath Salts” and other amphetamine-type stimulants with amphetamine screening immunoassays.

Petrie M, Lynch KL, Ekins S, Chang JS, Goetz RJ, Wu AH, Krasowski MD.

Clin Toxicol (Phila). 2013 Feb;51(2):83-91. doi: 10.3109/15563650.2013.768344.

PMID:23387345

Comments: An extension of the similarity work to understand cross reactivity of immunoassays – this time collating bath salts. A very useful database in itself.

Structure-activity relationship for FDA approved drugs as inhibitors of the human sodium taurocholate cotransporting polypeptide (NTCP).

Dong Z, Ekins S, Polli JE.

Mol Pharm. 2013 Mar 4;10(3):1008-19. doi: 10.1021/mp300453k. Epub 2013 Feb 12.

PMID:23339484

Comments: A continuation of the long collaboration with the Polli lab, as we use the modeling alongside the in vitro work to find new substrates and inhibitors for various transporters of clinical importance. Always great to work with the different students who have an interest in the work.

Novel diaryl ureas with efficacy in a mouse model of malaria.

Anderson JW, Sarantakis D, Terpinski J, Kumar TR, Tsai HC, Kuo M, Ager AL, Jacobs WR Jr, Schiehser GA, Ekins S, Sacchettini JC, Jacobus DP, Fidock DA, Freundlich JS.

Bioorg Med Chem Lett. 2013 Feb 15;23(4):1022-5. doi: 10.1016/j.bmcl.2012.12.022. Epub 2012 Dec 20.

PMID:23313245 Free PMC Article

Comments: A multigroup collaboration with Joel, my contribution was a little pharmacophore work.

Drug transporters on arachnoid barrier cells contribute to the blood-cerebrospinal fluid barrier.

Yasuda K, Cline C, Vogel P, Onciu M, Fatima S, Sorrentino BP, Thirumaran RK, Ekins S, Urade Y, Fujimori K, Schuetz EG.

Drug Metab Dispos. 2013 Apr;41(4):923-31. doi: 10.1124/dmd.112.050344. Epub 2013 Jan 8.

PMID:23298861

Comments: This paper amazingly hopped from journal to journal before finding a home at DMD. Very surprising because I think it will be high impact. My modeling work was cut out thanks to reviewers comments, which is a real shame because we have a nice story showing how pharmacophores were used to select fluorescent probes. I am very grateful to remain on the paper and really enjoy working with Erin’s group. I always learn something new when working with them.

Discovery of novel antimalarial compounds enabled by QSAR-based virtual screening.

Zhang L, Fourches D, Sedykh A, Zhu H, Golbraikh A, Ekins S, Clark J, Connelly MC, Sigal M, Hodges D, Guiguemde A, Guy RK, Tropsha A.

J Chem Inf Model. 2013 Feb 25;53(2):475-92. doi: 10.1021/ci300421n. Epub 2013 Jan 23.

PMID:23252936

Comments: This took a few years (4-5) to see daylight as the work progressed. Initially I just provided some malaria datasets and advice and then paper edits. A nice companion paper to go alongside all the TB papers. Really should do more with the malaria data we have in CDD. Watch out 2014!

Challenges and recommendations for obtaining chemical structures of industry-provided repurposing candidates.

Southan C, Williams AJ, Ekins S.

Drug Discov Today. 2013 Jan;18(1-2):58-70. doi: 10.1016/j.drudis.2012.11.005. Epub 2012 Nov 15. Review.

PMID:23159359

Comments: A review / paper heavily driven by Chris and Tony. I managed to tag along. Really amazing to see how difficult it is to find structures for published molecules. Eye popping!

Four disruptive strategies for removing drug discovery bottlenecks.

Ekins S, Waller CL, Bradley MP, Clark AM, Williams AJ.

Drug Discov Today. 2013 Mar;18(5-6):265-71. doi: 10.1016/j.drudis.2012.10.007. Epub 2012 Oct 23.

PMID:23098820

Comments: A review with a well told gestation– made it to daylight in 2013.

Incorporating Green Chemistry Concepts into Mobile Chemistry Applications and Their Potential Uses, ACS Sustainable Chem. Eng., 2013, 1 (1), pp 8–13. DOI: 10.1021/sc3000509

Ekins S, Clark AM and Williams AJ

Comments: Another paper with a well told story made it into the first issue of a new ACS journal and they made it free!

Cheminformatics workflows using mobile apps

Chem-Bio Informatics Journal, Vol.13, pp.1-18(2013)

Alex M. Clark, Antony J. Williams, Sean Ekins

Comments: Taking the idea of how we could use apps in a pipeline and putting the early ideas out there. A not so crazy idea to try to get a bit more exposure in the east for the apps, Alex paid to make the paper free. I also had long wanted to put a paper in the journal for which I am on the editorial board.

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