Introducing Andy Smith, Discovery Services Scientist

The last time I worked for Cresset I ended up being outsourced to a customer – but it was all part of the service! I’m delighted to be back at Cresset Discovery Services to work on a new set of customer projects. Here’s a brief overview of my computational chemistry journey so far.

An early sniff at GPCRs

I was introduced to computational chemistry when I stayed on at Warwick for a research MSc. The project was an SAR analysis of bell pepper odorants predicting the structural and electronic features that are important for olfactory recognition. My sponsor, Ernest Pollack, was getting very excited about proteins called GPCRs, which had just been identified as the receptors responsible for smell, and could possibly be the largest collection of proteins yet found. Meanwhile, I moved on to a PhD using quantum mechanics to investigate the Heck reaction.

Working closely with synthetic chemists

In 2001 I joined Proteus (later Protherics, then Tularik), who had a history with Factor Xa and already had a licensing agreement with Lilly for LY517717 established. After the takeover by Tularik the focus moved onto kinases which were difficult for our in-house software to model accurately. It was here that, with help from Mick Knaggs, I moved back into ligand-based design. I started homology modeling to augment the range of targets available for the in-house structure-based design methods and to expand the range of target we could work on using ligand-based design tools.

A narrow focus on structure-based design

I joined Sterix/Ipsen in 2004. Sterix had three areas of research: tubulin, hydroxysteroid dehydrogenase and dual aromatase-sulfatase inhibitors. Frustratingly, our work on these projects was limited to structure-based design, due to the fact that the group had made a large investment in the GOLD docking package from CCDC.

Back to the full range of computational chemistry methods

Upon moving to Peakdale Molecular in 2006 I worked on a range of diverse and interesting projects using a wide range of computational chemistry methods, including structure-based, ligand-based, ADMET predictions, homology modeling, molecular dynamics, quantum mechanics, cheminformatics, bioinformatics, library design, diversity and similarity analysis. The diversity of the projects meant I quickly learned to adapt to customer priorities, selecting the most appropriate method for the best possible modeling solution, whilst maintaining value for money.

It was here that I first used Cresset software. Torch (then FieldAlign) and Forge (then FieldTemplater) provided intuitive and visually informative methods for analyzing molecules which were understandable to our customers. These applications offered very useful methods of treating molecules which were different from other approaches I’d used before; both tools gave a more insightful understanding of ligand similarities and a deeper understanding of the features driving activity across a wide range of chemotypes and targets.

My first move to Cresset

Redx were working closely with Cresset, but were unsure how much support they would need, so in 2013 I took on the joint role of computational chemist at Redx and application scientist at Cresset.

Redx had fully functional medicinal chemistry projects in anti-infectives, oncology and crop protection, with large repositories of data. The established computational methods from Cresset Discovery Services showed the potential of computational chemistry and was the reason for Redx wanting to bring computational chemistry in-house. I provided the computational chemistry component and established a close working relationship with the medicinal chemistry teams.

Spark, Cresset’s scaffold hopping and R-group exploration application was integral to the development of a patent busting portfolio. As the company matured, Spark was used for backup series generation and to prevent the same patent busting approach to be applied to our own patents.

As an application scientist at Cresset, I carried out a very preliminary investigation of protein fields to determine whether we could transfer the Cresset methodology from ligands to proteins. It’s very gratifying to see the evolution of this early work brought to market in Flare, which provides fresh insights into structure-based design by integrating cutting edge approaches in an accessible and flexible user interface.

Outsourced to a customer

I joined Redx full time when it became clear that they needed more computational support. Working closely with Cresset software support, synthetic chemists were trained on Forge, a powerful ligand-focused workbench for SAR and design, and were encouraged to undertake general computational chemistry project related tasks. This freed up my time to provide more in-depth investigations to several key problems on projects.

A significant success was a compound that was sold to LOXO Oncology for $40 million. The computational work for this project was originally outsourced to Cresset Discovery Services. The compound was developed in 5 years and is a testament to the quality science undertaken at Redx.

In fact, the Redx CEO at the time was so impressed with the contribution of Cresset Discovery Services that he wrote:

“Cresset is a valuable partner in our drug discovery programs. Their deep knowledge of computational chemistry and its application to drug discovery is enabling us to progress multiple projects across a wide range of target classes very quickly and cost-effectively.

“Cresset has consistently delivered insightful support to our drug discovery efforts. In our experience, their knowledge, responsiveness and collaborative approach have set them apart from their competitors.”

 Dr Neil Murray, CEO, Redx Pharma, UK

Back to Cresset Discovery Services

I was delighted when I heard that Cresset Discovery Services was looking for a computational chemist to join the team. I’m very pleased to be back to working on a wide range of challenges on varied customer projects and putting my skills to use in the real world of modeling.

Contact us for a free confidential discussion to see how Cresset Discovery Services can work alongside your chemists to solve problems, provide fresh ideas, remove roadblocks and add direction and insight to you project. If you’re based near Alderley Park and would like to meet for a confidential chat, get in touch as I’m based at the BioHub part-time.

Modeling ‘big’: Applying the XED force field to biologics

Cresset is well known for powerful and accurate ligand-centric modeling, and Flare has established our methods for protein-ligand interactions. Work on GPCR modeling and viruses demonstrates the effectiveness and potential of Cresset technology for protein-protein interactions. Here I discuss the successes and challenges of modeling ‘big’ – applying Cresset’s XED force field to biologics.

Adventures in protein modeling: GPCRs

In 2014 Dr Andy Vinter, Cresset founder, reported on GPCR modeling exercises using the XED force field1, where ligand poses were exhaustively explored together with full complex minimizations to provide qualitative or quantitative analyses with binding estimates for agonist v antagonists. Although this was a huge modeling challenge, the approach provided fascinating new insights into GPCR behaviour that are in keeping with more recent literature. In particular, Brian Kobilka (joint winner of the 2012 Nobel Chemistry Prize) published a paper in 2016 showcasing the use of specific nanobody binding to the intracellular side of the GPCR to probe the long-range influence of ligands at the extracellular side2. He provided evidence supporting the hypothesis that GPCRs are likely partitioned between different states by differential stabilization of the full complexes in response to ligands. Our modeling findings concur in that the subtleties of these interactions extend beyond direct local binding interaction events and are propagated at distance across the full protein complex.

A matter of scale

Long-distance effects are not unusual in the realm of protein-protein interactions yet are beyond the scope of traditional molecular mechanics – from an accuracy point of view. From a sheer scaling point of view, the number of atoms involved means they are also beyond the scope of quantum mechanics. QMMM methods are also sometimes a poor compromise as these are discontinuous and focus on the local binding event.

Interestingly, this is where the XED force field has a nice sweet spot; accuracy approaching that of QM, but speed and the ability to map larger numbers of atoms >30,000, which is highly appropriate for the analysis of protein ligand and protein-protein systems. We can do this accurately and consistently through deployment of careful protein preparation and minimization workflows on protein systems.

Example: Influenza virus

The Centre for Pathogen Evolution at The University of Cambridge3 is involved in mapping data ultimately for the potential prediction of vaccine escape mutations of the influenza virus.

Hemagglutinin virus protein is the receptor that recognises mammalian cell surface glycans as an essential route to host cell entry. The ability of the virus to recognise sialic acid containing glycans is essential to this process and residues that contribute to its recognition represent those which are consequently difficult to mutate without compromising the virus. Antibodies which are directed to this site (Figure 1 left and middle) are less likely to suffer from viable virus mutations than others 4,5 (Figure 1 right).


Figure 1: Left: Influenza H3N2 hemagglutinin with the electrostatics of the core recognition element sialic acid from PDB 5VTQ. Middle: overlapping monoclonal antibody (blue tube) recognition site with electrostatics from key residues from PDB 2VIR. Right: a non-overlapping monoclonal antibody from PDB 5W42.

Optimizing biologics using 3D electrostatic shape and complementarity

In vogue, directed degradation mechanisms (PROTACS)/antibodies/vaccines, i.e., biologics, are example therapeutic paradigms which involve subclasses of these protein–protein interactions rather than the classical small molecule drug – protein target interactions. Modeling them is a significant challenge faced by many organizations charged with producing an array of diversely targeted therapeutics, because it is where a lot of what remains (the ‘higher hanging fruit’) happens to be.

The biologics industry may have slightly different criteria for cycling through an optimization, but ultimately similar schemes to those operating in the pharmaceutical industry still apply. There is an equivalent of traditional medicinal chemistry drug discovery workflows – involving SAR analysis, design, synthesis and test cycles. For antibodies, as for small molecules, target affinity, solubility, aggregation are key initial concerns. Mouse to human transformation is a uniquely biologics issue (unless we are talking in vivo models) as is the means of controlling SAR. For proteins it is all in the manipulation of the amino acid sequence, protein loop conformational preference, by single or multiple residue mutation. Incidentally, conventional sequence similarity metrics are not a useful measure of a residues relative potential for interaction with ligands or proteins in active sites (despite often being the tool of choice for analyzing protein data), as they were derived from natural mutation propensity and that consequence on maintenance of protein architecture.

Ultimately, the mechanism of target engagement, the molecular recognition event, is through electrostatic and shape complementarity and is fundamentally the same 3D phenomenon that applies to small molecules. Cresset scientists have an outstanding track record of working on electrostatic and shape complementarity and have successfully applied these skills to protein-protein interactions.

In the last 12 months, Cresset Discovery Services has completed work on viral vaccine modeling and biologics modeling which have proved highly useful for clients. We matched observed binding events with calculated binding enthalpy trends and predicting a-priori the observed pattern of protein binding or unwanted peptide binding suppression. This has been done using WT or mutant proteins that we have successfully taken through analysis, modeling/design and client testing cycles. As you would expect, client confidentiality prevents us disclosing further details, but contact us for a free confidential discussion.

References

  1. Applying the XED molecular mechanics force field to the binding mechanism of GPCRs
  2. Allosteric nanobodies reveal the dynamic range and diverse mechanisms of G-protein-coupled receptor activation, Kobilka et al, Naturevolume 535, pages448–452 (21 July 2016)
  3. https://www.pathogenevolution.zoo.cam.ac.uk/
  4. Substitutions Near the Receptor Binding Site Determine Major Antigenic Change During Influenza Virus Evolution, David F. Burke, Derek J. Smith et al, Science 22 Nov 2013:
    342, Issue 6161, pp. 976-979
  5. Diversity of Functionally Permissive Sequences in the Receptor-Binding Site of Influenza Hemagglutinin, Nicholas C. Wu Jia Xie Tianqing Zheng, Corwin M. Nycholat, Geramie Grande, James C. Paulson Richard A. Lerner and Ian A. Wilson, Host & Microbe 21, 742–753, June 14, 2017

Parkinson’s Virtual Biotech secures further funding for novel gene transcription modulators project

Following excellent progress in this drug discovery project that we announced in March, I am delighted that our unique software, virtual screening capabilities and highly experienced team have contributed to Parkinson’s UK securing further funding for the novel gene transcription modulators collaboration we are working on along with Selcia.

We look forward to continuing to deliver molecular modeling support for the next phase of this important project.

Using services to evaluate software

Evaluating new computational chemistry software requires a significant investment of time. No matter how helpful the sales team is, nor how many demonstrations you have seen, what really counts are the results you get when you try the software out on your own project data. And this is what takes the time.

An innovative alternative to running in-house evaluations is to commission a short services project from Cresset Discovery Services (CDS). We are experienced in carrying out projects using customer data so that you can free up your time to evaluate the results.

Try before you buy

Recently, a small pharmaceutical company took up this option with CDS. They had their own computational chemistry group and their own field based software that they used for virtual screening, docking and other tasks. Cresset software was of interest to them, but they weren’t going to buy it without trying it and they couldn’t spare the people to carry out a full evaluation. So they commissioned a trial project with CDS.

The computational group prepared a protein-ligand binding interaction and asked CDS to run a virtual screen on it. Rather than just go ahead and run the screen, the first step for us was to check the preparatory work. Based on this, we were able to suggest that they optimize the conformation slightly based on evidence from crystallography. This helped to refine the search, which maximized the success of the screen.

After reviewing the results they bought Blaze for virtual screening, plus remote access to our server, enabling them to use Blaze Cloud for remote virtual screens.

Outsource an on-site evaluation

Another company that didn’t have time to evaluate software themselves also wanted us to do a services evaluation project. However, in this case they didn’t want their discovery data to leave their site. As a result, CDS arranged for one of our consultants to carry out the work at the customer site.

Again, the customer was very happy with the results and actually went on to buy the full range of Cresset software to use in-house.

Services projects include software licenses

During all CDS projects we give customers a license to the molecular modeling environment Torch and other Cresset software as relevant. This enables them to see and manipulate the project data and molecules in an ideal environment. It makes it easy to communicate and explain the results and also gives them the chance to try out other options.

If you would like to run an evaluation project for any software you are considering purchasing, contact us for a confidential discussion.

 

Martin

Dr Martin Slater

Director, Cresset Discovery Services

An incredibly cost effective way of finding a chemical starting point

Many customers engage Cresset Discovery Services (CDS) to find a chemical starting point for their project. The input could be a competitor compound, a peptide, or a compound that is unsuitable for development for toxicity or patent reasons. Cresset computational methods are an extremely cost effective way of identifying promising candidate compounds.

Identifying a patentable chemical starting point

A pharmaceutical company was working on a particular target, but the only activity they had found was from a competitor compound. They engaged CDS to find an alternative chemical starting point for their project.

The first step was to generate a binding hypothesis for the competitor compound. This was used as input to a virtual screen in order to identify other compounds with a strong likelihood of having similar activity.

This short and efficient project resulted in a chemical starting point for the customer’s project. The final chosen compound was highly active, was different to the competitor compound and was patentable.

Virtual screening to find different chemotypes

As part of a longer ongoing contractual agreement, a customer purchased flexible service days from CDS and used them on this project over a 12 month period.

The customer was working on a novel ion channel target and they knew of two competitor compounds. CDS aligned the compounds and generated a number of alternative alignment hypotheses. We then carried out a virtual screen on the most diverse of the permutations, leading to 30 different chemotypes, which the customer was able to pursue. This resulted in a promising, patentable chemical starting point for their project.

“Our methods are an incredibly cost effective way to identify promising candidate compounds. For less than $25k for the actual computational chemistry work, plus the same again for the procurement and initial testing, our client had a promising, patentable chemical starting point for their project.”
Dr Martin Slater, Director of Cresset Discovery Services
 

Identifying drug-like chemotypes from a peptide starting point

Another customer had identified a series of peptides that block the aggregation of β-amyloid. They engaged Cresset to identify drug-like chemotypes to mimic this activity. See the full case study: A novel series of non-peptide small molecules for protein-protein interactions.

 

Contact us to find out how we can help you find a starting point for your project.