Small molecules can potentially bind to a variety of bimolecular targets and whilst counter-screening against a wide variety of targets is feasible it can be rather expensive and probably only realistic for when a compound has been identified as of particular interest. For this reason there is considerable interest in building computational models to predict potential interactions. With the advent of large data sets of well annotated biological activity such as ChEMBL and BindingDB this has become possible.
These predictions may aid understanding of molecular mechanisms underlying the molecules bioactivity and predicting potential side effects or cross-reactivity.
Having worked wit Selcia on a number of projects I always keep an eye out for news on their work on Peptidyl-Prolyl cis-trans Isomerases (PPIase). These are very interesting class of enzymes whose principal function is to catalyse the cis-trans isomerisation of the X-Pro peptide bonds in polypeptide chains (where X is any amino acid). This transformation is thought to be a mechanism to modulate protein function.
PPIase enzyme targets are of increasing interest in drug discovery due to the extensive potential of small molecule inhibitors in a range of therapeutic areas, including infection, inflammation, cancer and neuroprotection.
Selcia have now expanded the range of Peptidyl-Prolyl cis-trans Isomerase (PPIase) assays they can offer.
The Open Source Malaria group are running a competition to develop a computational model that predicts which molecules will block the malaria parasite's ion pump, PfATP4.
PfATP4 is an important target for the development of new drugs for malaria. We are providing a dataset of actives and inactives. The challenge is to use the data to develop a model that allows us to (better) design compounds that will be active against that target.
The competition will close on 31st March 2017.
The details of the competition can be found here https://github.com/OpenSourceMalaria/OSMToDo_List/issues/421 and the video below gives more information
There is a Jupyter notebook that can be used to to access the information here http://www.macinchem.org/reviews/osm/osmipython.php or you can access the information in this google document https://docs.google.com/spreadsheets/d/1Rvy6OiM291d1GNcyT6eSwC3lSuJ1jaR7AJa8hgGsc/edit#gid=510297618, but remember the competition is a predictive model for series 4 only.
More details on Open Source Malaria
28th symposium on Medicinal Chemistry in Eastern England, Thursday 27th April 2017, The Fielder Centre, Hatfield, Hertfordshire, UK
Organised by RSC-BMCS (Royal Society of Chemistry – Biological and Medicinal Chemistry Sector)
09.00 Registration, refreshments and exhibition
Session chair: Adrian Hall, UCB
09.30 Opening remarks
Nicole Hamblin, GlaxoSmithKline
09.35 From phenotypic hit to a validated target for tuberculosis
Robert Bates, GlaxoSmithKline
10.10 Discovery of potent inhibitors of the lysophospholipase autotaxin
Prit Shah, Cancer Research Technology
10.45 Refreshments and exhibition
11.15 Development of Tesirine: a clinical antibody-drug conjugate pyrrolobenzodiazepine payload: medicinal chemistry at the frontier between small molecules and biologics
Arnaud Tiberghien, Spirogen
11.50 NMR conformational analysis in molecular design – case studies and impact
Martin Packer, AstraZeneca
12.25 Highly potent cell-penetrant inhibitors of the KEAP1-NRF2 protein-protein interaction via X-ray fragment screening
Charlotte Griffiths-Jones, Astex Pharmaceuticals
13.00 Lunch and exhibition
Session Chair: Simon Ward, University of Sussex
14:05 Selective on-target chemical probes of protein-protein interactions
Alessio Ciulli, University of Dundee
14.40 Solid state studies of a preclinical candidate in a CRO environment: the importance of de-risking early
Russell Scammell, Charles River
15.15 Refreshments and exhibition
15.45 Drug discovery case study
Tom Miller, Shire
16.20 Optimisation of a series of novel smoothened inhibitors
Matilda Bingham, RedX
16.55 Concluding remarks
I've been a tutor at the RSC MedChem School on a number of occasions and I can say this is an excellent opportunity for scientists new to drug discovery to benefit from an understanding of all aspects of the drug discovery process, from target and hit identification, through ADME and computational chemistry, to patents and safety studies.
The 2017 Medicinal Chemistry Residential School takes place 11 - 16 June, Loughborough UK, it is always very popular so well worth signing up early.
The 2017 Residential School will take place over 5 days and content is delivered by experts in the field from industry and academia. The programme includes lectures focusing on the fundamental principles of drug discovery, hands-on tutorials allowing delegates to put into practice what they have learnt and case histories from previous drug discovery projects. The programme will also include an evening lecture from a distinguished speaker. Throughout the week course tutors and speakers will be available for informal discussion and there will be plenty of opportunities to network with the broad range of academic and industrial researchers in attendance.
I've added SkinSensDB to the Drug Discovery Resources page covering Chemistry and Biology Databases.
Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment….SkinSensDB has been constructed by curating data from published AOP-related assays. In addition to providing datasets for developing computational models, SkinSensDB is equipped with browsing and search tools which enable the assessment of new compounds for their skin sensitization potentials based on data from structurally similar compounds.
SkinSensDB: a curated database for skin sensitization assays DOI.
Fragment-based screening is now a well established methodology for the identification of leads for drug discovery and the aim of the 6th RSC-BMCS Fragment-based Drug Discovery meeting will be to continue the focus on case studies in Fragment-based Drug Discovery that have delivered compounds to late stage medicinal chemistry, preclinical or clinical programmes.
6th RSC-BMCS Fragment-based Drug Discovery meeting
Sunday to Tuesday, 5th to 7th March 2017
at Parkhotel Schönbrunn, Vienna, Austria
Full details and registration are online.
I know many groups in the UK have projects funded under Wellcome Trust (WT) "Seeding Drug Discovery" funding program, this program has been running successfully for many years but it was recently announced that there was to be a review of the WT funding activities. The results of the review are now available on the website http://dmtrk.net/2PXJ-E0XO-23KRZ4WBE/cr.aspx.
Key points are:-
In February 2017 Wellcome will be launching ‘Innovator Awards’ for proposals of up to £500k. One of the aims of this scheme will be to encourage people that do not currently work with us to apply - including translators and innovators from outside of the life and medical science community. We think this is important because new technology has the potential to transform biomedical science, as well as have significant applications to health.
We believe that in order to achieve greater impact on human health - we also need to focus on a smaller number of activities - something that we refer to as Flagships. An example of an existing Flagship is the Hilleman Laboratories – an R&D facility in New Delhi, dedicated to generating new vaccines. This is a joint venture between Wellcome and Merck, USA. We also consider our recently announced Wellcome Centres at Kings College, Dundee University and UCL as Flagships.
We will remain open to great ideas in any area. In our first year much of our support will focus on ideas and solutions involving mental health, neurological disorders and neglected tropical diseases, but these are not exclusive and other areas of particular interest will be announced in the future.
I have to say I delighted to see the focus on mental health and neglected tropical diseases, areas which I've tried to support.
The reproducibility of some target identification/validation studies has been questioned on several occasions and I've flagged up some of the concerns in the Target Validation section of the Drug Discovery Resources. A recent study, reported in Science 28 August 2015: Vol. 349 no. 6251 DOI looking at psychological science, attempted to replicate published work suggests that 39% of effects replicated the original result. Also Amgen, tried to replicate 53 'landmark' cancer studies and failed to replicate the original studies in all but six occasions, Nature 483, 531–533 (29 March 2012) DOI.
A while back a project was initiated to look at reproducibility in cancer, Science Forum: An open investigation of the reproducibility of cancer biology research DOI.
It is widely believed that research that builds upon previously published findings has reproduced the original work. However, it is rare for researchers to perform or publish direct replications of existing results. The Reproducibility Project: Cancer Biology is an open investigation of reproducibility in preclinical cancer biology research. We have identified 50 high impact cancer biology articles published in the period 2010-2012, and plan to replicate a subset of experimental results from each article. A Registered Report detailing the proposed experimental designs and protocols for each subset of experiments will be peer reviewed and published prior to data collection. The results of these experiments will then be published in a Replication Study. The resulting open methodology and dataset will provide evidence about the reproducibility of high-impact results, and an opportunity to identify predictors of reproducibility.
Well some of the early results are in and they make for pretty sobering if not unexpected reading, of the first 7 papers examined, 2 appear to reproduce the original finding to some extent, three show significant differences from the original studies. The results are published in eLife here and there is an editorial here DOI, and they make an important point.
if all the original studies were reproducible, not all of them would be found to be reproducible, just based on chance. The experiments in the Reproducibility Project are typically powered to have an 80% probability of reproducing something that is true.
The key question is of course, is the failure to reproduce these results due to methodological differences not apparent from the described experimental or whether the fundamental result is invalid. At the moment if you are planning to invest in a drug discovery project based on a single publication then Caveat emptor.