Welcome to our Winter 2013 newsletter.
Firstly, we would like to introduce our new website, which has been updated to reflect the changing face of pharmaceutical research, with the growth of open innovation, translational medicine and the increasing activity of academic and charitable institutions in all areas of drug discovery. The site contains much more information on how CompChem Solutions can work with various types of organisations.
We have collaborated on many projects with medicinal chemists, leading to successful achievement of project milestones and to successful grant funding. To help establish similarly valuable joint collaborations we have created an area of the website which has links to medicinal chemistry consultants who may be able to add value to your projects.
If you are a medicinal chemistry consultant and would like to be included in this section of our website, do get in touch.
Obviously, the collaboration between medicinal chemists and computational chemists is central to drug discovery, and our article below (authored by Dr Bill Harris of Drug Discovery Opinion) describes how the med chem./comp chem. unit can accelerate projects.
Continued methods development and published validation studies have helped position the Cresset tools at the leading edge of ligand-based modelling approaches. As such, CompChem Solutions has recently linked up with Cresset, and is now delighted to be able to offer the use of Cresset software for appropriate client projects, either alone or in combination with the wide range of other software tools avaliable to CompChem Solutions .
Just before going to press, we received the devastating news about Patrik Rydberg, who so kindly contributed an atricle about his SMARTCyp methodology for this newsletter a couple of weeks ago. Prior to joining Optibrium, Patrik had a highly successful academic career at the University of Copenhagen where he undertook pioneering research into prediction of metabolism. We are indebted to Patrik for his enormous contribution to the field of computational ADMET prediction, and our thoughts are with his family at this time. As a mark of respect for Patrik and his work, we would like to dedicate this edition of the newsletter to his memory.
At the RSC/SCI Medicinal Chemistry Symposium in September 2013, Susan Boyd presented a poster describing how properties of fragments active against protein-protein interaction targets were observed to differ from those of standard enzyme targets. This work is summarised below but is due to be published in full shortly in a review on Fragment-Based Drug Discovery and Protein-Protein Interactions, in the Journal of Research and Reports in Biochemistry.
Our news section describes the new Doctoral Training Centre being formed by a consortium of three universityes, and of course, don’t forget to check out our compilation of upcoming meetings which might be of interest to our readers, and some job opportunities which are currently advertised.
We would like to wish all of our readers a very happy Christmas and a successful 2014.
Do check out our new website though before you pack up for the holiday season!
– Accelerating Research
Bill Harris (Drug Discovery Opinion)
Computational sciences have long played an integral part in drug discovery, providing insights into accumulated data as well as new ideas and hypotheses for exploration and testing. Many computational tools, such as data visualisation and property calculation are now firmly embedded in medicinal chemistry activities. Examination of structure-activity and structure-property relationships are fundamental to the advancement of drug discovery projects, providing ideas to address potency, selectivity, drug-likeness and other properties required of the target drug.
Often, unexpected correlations can provide a fast-track to problem solving. For example, in one particular kinase inhibitor project, plasma protein binding (PPB) was an issue (whether PPB is ever really an issue is a separate discussion!). Whilst PPB did not correlate with cLogP of the compounds, it did correlate with cLogP of one substituent on the common template. This allowed manipulation of PPB without altering global properties of the molecules.
More specialised computational methods, such as virtual high-throughput screening, homology modelling, molecular modelling or de novo design, require the expertise of the computational chemist. Dialogue between medicinal and computational chemist can significantly influence the outcome of these activities. Insights from the medicinal chemist can be used to guide and modify the assumptions and parameters that underlie these methods, with beneficial consequences to the output.
The synergy between medicinal and computational chemistry is especially apparent in drug design. Whether suggestions for novel molecules are generated by software or by scientists developing new ideas by working with crystal structures or homology models, the cycle of ‘what ifs’ further refines ideas. A new molecular structure modelled into an active site may look a great fit, but further modification by scientists from both disciplines working together may improve properties such as synthetic tractability and physicochemical properties and also has the potential to address potential off-target liabilities.
CompChem Solutions has recently entered into an agreement with Cresset which enables CompChem Solutions to access Cresset’s field technology tools for our clients’ projects. Cresset offer some excellent tools for ligand-based modelling, including applications for molecular alignment, pharmacophore-type modelling and statistical data modelling which can be used in scaffold-hopping, lead-finding and lead-optimisation projects.
Cresset software calculates and compares the molecular field characteristics of chemical compounds. Cresset’s field technology uses the surface properties of molecules to evaluate their activities and properties, rather than relying on 2D structure similarity, which enables Cresset’s users to find more interesting, novel and relevant results than other methods. This field technology provides a structure independent way of hit-finding, lead switching and lead optimization in drug discovery and other chemistry-based research projects. Cresset’s field technologies have been successfully applied to a very wide range of target classes on over 100 projects for major pharmaceutical and biotechnology companies.
Contact us for more information on how CompChem Solutions can help your project with the assistance of Cresset’s field-based technology.
Fragments for Protein-Protein Interactions
At the recent RSC/SCI Medicinal Chemistry Syposium in September 2013, Susan Boyd presented a poster on Design of Fragment Libraries for Targeting Protein-Protein Interactions (PPI), co-authored by colleagues from SARomics and Cancer Research Technology. As part of a review article which will shortly be submitted to Research and Reports in Biochemistry the poster describes some research conducted by Susan and her co-authors which explores whether fragment hits against PPI targets differ in any significant way from fragment hits against more standard enzyme targets.
Datasets of around 100 fragment hits against PPI targets (courtesy of L Vidler & N Brown, ICR, London) and 100 fragment hits against non-PPI targets (GC Ferenczy & GM Keresu, J Med Chem, 56, 2478-2486, 2013) were compiled and the properties of the datasets compared.
The results of the study suggest that the PPI fragment hits tend to be a little larger and more lipophilic than the non-PPI fragment hits, but despite this their Lipophilic Ligand Efficiency (LLE) is very similar indeed to the non-PPI fragment hits, indicating that the PPI fragment hits are often more active against their target than the non-PPI fragments. This may be due to the fragments seeking out hotspots on the protein-protein interface.
Interestingly the frequency of occurrence of both acidic groups and basic groups in the PPI fragment set was around double the rate seen in the non-PPI fragment set, and the minimum hydrophobic proportion of the PPI fragments is 46% compared with only 17% for the non-PPI fragments.
So in summary, the study would suggest that when designing a fragment library for a PPI target, it may be helpful to guide the selection towards fragments which are a little larger, more lipophilic and which contain more acidic/basic functionality than is usual in standard fragment sets.
Do look out for our full review article when it is published in the Journal of Research and Reports in Biochemistry.
Prediction of Cytochrome P450 Mediated Metabolism using SMARTCyp and StarDrop
Patrik Rydberg, Optibrium Ltd
75% of all drugs are metabolized by enzymes belonging to the cytochrome P450 family. To predict where metabolism will occur on a compound during this process, there are several prediction models available, both free (e.g. SMARTCyp) and commercial (e.g. StarDrop).
In principle, to predict which sites on a molecule that are most likely to be oxidized by a P450 enzyme, we need to calculate the reactivity of each atom and the likelihood that the molecule will bind in an orientation that puts this atom close to the heme group at the bottom of the active site, where the chemical reactions take place.
Before joining Optibrium, I was employed at the University of Copenhagen where I developed SMARTCyp, a model depending only on 2D structures and fragment matching. This assigns reactivity to a potential site of metabolism by matching fragments against a library for which highly accurate transition state energies have been precomputed, using density functional theory; a site’s accessibility is determined using a few simple 2D descriptors and 2D pharmacophores. StarDrop, on the other hand, computes the reactivities on-the-fly using semiempirical AM1 calculations and uses more extensive descriptors to assess the accessibilities. While the advantage of SMARTCyp is its speed and robustness, the advantages of StarDrop are that substituent effects are properly handled and that changes within a chemical series can be followed by doing a calculation for each compound (SMARTCyp will often assign the same scores to atoms in similar compounds).
The current research at Optibrium involves taking the best parts of SMARTCyp and integrating these into StarDrop, as well as extending the P450 models in StarDrop to additional P450 isoforms. A common limitation of most metabolism prediction models is that they only predict which site will be oxidized and not what metabolite will be formed. While the rules for predicting the metabolites formed by metabolism at a site are straightforward in the majority of cases, we are interested in exploring the mechanisms that give rise to less common products, particularly the formation of reactive metabolites. We are researching the possibility to extend StarDrop with such models, as well as methods for predicting which isoforms will contribute to the metabolism of a compound.
News – Doctoral Training Centre
EPSRC has just announced funding for a Centre for Doctoral Training in Theory and Modelling in Chemical Sciences (TMCS), formed as a tripartite consortium of the Universities of Oxford, Bristol and Southampton. A key aim of TMCS is active engagement with the wider national community in theoretical and computational chemistry.
TMCS will provide integrated, in-depth training across the full spectrum of contemporary theoretical and computational chemistry, with emphasis on the core activities of fundamental theory, software development, and application to contemporary research challenges; and with opportunities to engage with our industrial partners. Further details may be found on the TMCS website, http://www.tmcs.ac.uk . Training will follow a 1+3 model, with all year-1 students based in Oxford, and awarded an MSc at the end of year-1.
Up to 4 funded places each year will be open to students applying to undertake the year-1 CDT training at Oxford before proceeding to a PhD in a University *other than* Oxford, Bristol or Southampton. There will be *no cost* either to your student or your institution: TMCS will provide the year-1 funding to train students, who will receive an Oxford MSc upon successful completion of the course. Our onlyrequirement is that such students should have an offer of funding to undertake a subsequent PhD in your University (and we emphasise thatthey will not be permitted to undertake their PhD in a TMCS consortium University).
It is hoped that this scheme will prove attractive to colleagues across the UK, and that institutions will encourage their excellent students to applyto TMCS for their year-1 training. Further details, includinginformation for students on how to apply, can be found on the TMCS website above. If you have further questions you would like to ask, please feel free to telephone David Logan (01865 275418) or to send an e-mail to any of the following:
David Logan (Oxford) firstname.lastname@example.org
Fred Manby (Bristol) email@example.com
Jon Essex (Southampton) J.W.Essex@soton.ac.uk
Multiscale Modelling of Condensed Phase and Biological Systems, 7th-9th January 2014 Manchester, UK, http://www.ccpbiosim.ac.uk/multiscale2014
SMR Reducing Attrition through Early Assessment of Drug Safety, 13th March 2014, London, https://www.smr.org.uk/smr/Meetings/20140313/default.asp
UK QSAR & Chemoinformatics Group Spring Meeting 2014, Lilly, Date TBC
SCI Towards New Therapeutics for Diseases of the Developing World, 11th-13th May 2014, Madrid, Spain, https://www.soci.org/Events/Display-Event.aspx?EventCode=FCHEM138
SCI Kinase 2014: past, present and beyond, 19th-20th May 2014, Babraham Campus Cambridge, https://www.soci.org/Events/Display-Event.aspx?EventCode=FCHEM139
20th EuroQSAR, 31st Aug – 4th Sept 2014, St Petersburg, Russia, http://www.ldorganisation.com/v2/produits.php?langue=english&cle_menus=1238915734
The above list is not exhaustive, but constitutes a set of meetings which may be of interest to computational chemists & chemoinformaticians. If you have an upcoming meeting you’d like us to include in our spring newsletter please contact Susan Boyd via firstname.lastname@example.org
Computer-Aided Design Experts, Molplex Pharmaceuticals, Alderley Edge, Cheshire, http://www.molplex.com/index.php/about-molplex/careers/2-uncategorised/33-computational-chemist-cheminformatics-cadd
Scientific Services Manager, Chemical Computing Group Inc, https://www.chemcomp.com/AboutCCG-Careers_Scientific_Services_Manager_SSM13.htm
Application Scientist, Chemical Computing Group Inc, Cambridge (UK), https://www.chemcomp.com/AboutCCG-Careers_Application_Scientist_SS14.htm
Solutions Consultant, Accelrys Inc, Cambridge (UK), https://www5.ultirecruit.com/ACC1007/JobBoard/JobDetails.aspx?__ID=*CB5E83F45A2EB353
Research Associate, University of Manchester, http://www.jobs.ac.uk/job/AHQ897/research-associate/?utm_source=Indeed&utm_medium=organic&utm_campaign=Indeed. Closing date 15th December 2013
PhD studentship at the School of Chemistry and the Manchester Institute of Biotechnology (MIB) with supervisor Prof Popelier, University of Manchester. More details and on how to apply on http://www.chemistry.manchester.ac.uk/our-research/studentships/details/?theID=164
A fully funded PhD studentship in molecular modelling and chemical biology of the malaria M1 aminopeptidase is available at Queen’s University Belfast with supervisors Dr. Irina Tikhonova (computational aspects) and Prof. John Dalton (mutagenesis). The closing date for the application is January 31st 2014. The start date is October 2014, http://go.qub.ac.uk/pgapply & email@example.com
The above list is not exhaustive, but constitutes a set of positions which may be of interest to computational chemists & chemoinformaticians. CompChem Solutions takes no responsibility for the accuracy of any listing above or the availability of the positions. If you have a vacancy you’d like us to include in our spring newsletter please contact Susan Boyd via firstname.lastname@example.org