Flare API: A new playground for computational chemists and developers

Flare 2.0 comes with a full-featured Python API which enables both high-level access to scientific functionality and low-level access to the graphical user interface and internal processes. In addition to Flare methods, you will have access to RDKit, NumPy, SciPy, and to virtually any other Python module that can be pip-installed. RDKit molecules are treated just as native Flare molecules, and can be loaded interchangeably to Flare’s ligand table. This means that you can generate a virtual 2D library using RDKit reaction SMARTS and then turn it into a 3D library of field-enabled Cresset molecules without ever leaving the Flare environment.

Additionally, if you realize that you often use a certain Python script as part of your Flare workflow, you may decide to associate it to a custom control in the Flare ribbon user interface, be it a button, a menu, or a complex dialog with signals and callback functions (Figure 1).


Figure 1. An example of the custom controls that can be added to the Flare ribbon.
We have done our best to write a clear and easy-to-browse HTML documentation, but even more importantly we have come up with a number of sample scripts which cover a variety of use cases, in order to get you started as quickly as possible.

Python commands can be loaded and executed in Flare in a number of different ways, ranging from highest automation to highest interactivity.

For example, when you need to carry out a completely automated task, such as overnight preparation of a panel of proteins followed by docking of several ligand series, the most convenient option is to write a Python script that runs outside the Flare GUI, such that it can be distributed on a cluster via a queueing system for maximum performance. This use case is covered by the pyflare binary, which is effectively a Python interpreter just as the familiar python binary, slightly modified to play well with the rest of the Flare ecosystem (Figure 2).


Figure 2. Running a Flare Python script outside Flare using the pyflare interpreter.
If your goal is to run a simple Python one-liner to, for example, list all cysteine residues in a protein chain or to print the distance between a ligand atom and a couple of key residues in the active site, the embedded Python Console is probably the simplest and leanest option – run the command and examine its output in the text port (Figure 3).


Figure 3. Entering simple one-liners in the Python Console widget.
If you believe you will need to go through some iterations of a code-run-test-debug workflow on a somewhat more complex script, you will most likely choose the embedded Python Interpreter widget, which allows you to load a script, interactively edit it inside Flare and then save your modifications (Figure 4). Both the Python Console and the Interpreter come with a multi-tabbed interface that makes it possible to work on multiple Python snippets at the same time.


Figure 4. Loading and editing a script in the Python Interpreter widget.
If you are used to the highly interactive environment of Jupyter notebooks, then you are going to love the Python QtConsole embedded in Flare. This widget provides all the nifty Jupyter features, i.e., TAB completion, auto-indentation, syntax highlighting, context help, inline graphics, and more (Figure 5). Type Python commands, examine molecules, draw plots – all in the same window.


Figure 5. Visualizing text output and inline graphics in the Python QtConsole widget.
If you would rather prefer to use Jupyter Notebooks in the traditional way, i.e., multiple tabbed sessions inside your favorite browser, that’s entirely possible, too. You will even be able to look at ligands and proteins in 3D inside your notebook, including Cresset surfaces and field points (Figure 6).


Figure 6. Running a Flare workflow inside a Jupyter Notebook outside the Flare GUI application.
In summary, programmatic access to Flare methods is very appealing to computational chemists looking for ways to automate tasks or run complex workflows on multiple datasets. On the other hand, the possibility to extend the core functionality as well as the graphical user interface with own methods makes Flare the ideal playground for Python developers.

For academic researchers, Flare is an opportunity to make their science more broadly accessible through integration into a user-friendly environment, while corporate users will appreciate the possibility to augment Flare capabilities with in-house REST services and tools. The possibility to code in Python taking advantage of the highly interactive experience provided by the Jupyter QtConsole and Notebook is a further incentive to make Flare the environment of choice for computational chemistry workflows.

Request a free evaluation of Flare.

A sneak peek into Flare V2: A major advancement for structure-based design with Flare

Flare V2 is in the final rounds of testing, which means the release announcement is imminent. Ahead of the user group meeting, where we will be presenting this major advancement, this post takes a sneak peek at some of the new features in this version.

New coloring options

Completely rewritten surface generation code results in faster and better surfaces with quality options built in to the surface creation dialog. This is combined with new coloring options for new surfaces to give you more insights into your proteins and ligands.


Figure 1: (a) New surface coloring options in Flare V2, and (b) PDB code 4MBS with a hydrophobic surface colored yellow (hydrophobic) to blue (hydrophilic).

Improved Z-clipping

Making pictures is key to communicating your insights on protein-ligand binding. Flare V2 has major improvements to the Z-clipping to enable you to get the view that you want. In addition, to apply a specific clipping plane to an individual surface, you now have the option to exclude ligands from the clip altogether. This option makes a significant impact on pictures of binding sites that are completely buried.


Figure 2: PDB 1IKW showing the ability to selectively clip proteins. (a) Ligand clipping often makes it difficult to get the picture you want whereas (b) disabled ligand clipping in Flare V2 gives you more options to communicate key insights.

Figure 3: Flare V2 gives the option to clip individual surfaces independently of other objects. Here a clipping plane is added only to the electrostatic surface enabling the visualization of protein residues that are above the ligand in combination with a surface.

Other features contribute to a major advancement for Flare

The new protein surfaces are complemented by new options for ligand surfaces, the new storyboard panel to capture and replay key 3D insights and many new features for ligands. Taken together with the Python API this release of Flare is a major advancement in this innovative new application for structure-based design.

Find out more and get hands-on

Register for the up-coming user group meeting to find out more about Flare V2, network with existing users and receive free training at one of the hands-on workshops.

Request an evaluation.

Flare: Accessible structure-based design

Modern structure-based design encompasses hundreds of methods, advanced algorithms and diverse biological targets. Cresset has a long-standing reputation for easy to use applications in the ligand-based design sphere. In deciding to bring Flare™, a new structure-based design application, to the market we created a challenge – can structure-based design be made simple?

A balance of usability and flexibility

Usability and flexibility are such fundamental features of well-designed software that they are often only noticed when they are absent. Usability reduces frustration, reduces training overhead, and makes it easier to access the full potential of the software. However, users also want the flexibility to tweak experiments, perform complex workflows and customise their applications to work the way they do. These key ‘unspoken’ features have been part of the design process in building Flare from the very start.

Focus on design

Critical to any analysis is the use of your conclusions to change the future. In structure-based design this means using information on how ligands bind to proteins to influence the design of the next ligand. In Flare we have put ligands at the heart of the application. They are stored in their own table and have a dedicated tab menu. The table layout enables physico-chemical property data to be stored alongside each ligand or calculated for every new design. It enables you to organize your compounds (sorting ligands based on their properties) or split ligands into different groups (roles) so that you can break down larger datasets into manageable chunks.

Designing new ligands is easy using the simple ‘Edit a copy’ feature. This brings up the molecular editor where the ligand can be improved in the protein active site and in reference to other ligands. The combination makes it easy to design in 3D, gaining all the productivity benefits that this brings. Sequential edits give an iterative process where each new design can be analysed and used as the basis for the next design.

Accessible methods

Analysis of existing or newly designed ligands requires complex methods. From docking to a detailed energetic prediction of binding, structure-based design methods are all complex. The challenge here is to present complex methods in an accessible way that enables expert users to modify key parameters but is not daunting to the regular user. In Flare a standardised layout is used for all calculation dialogues and provide default settings that work well in most cases. Experts have the choice to take the defaults or progress to the Advanced Options to change the parameters to meet their needs.

Great pictures

Creating great pictures is central to structure-based design. It seems like no J. Med. Chem. Article is complete without at least one protein-ligand picture. Creating pictures in Flare is easy with control over every aspect of the 3D display straight from the Home tab menu. Add to these the ability to control the clipping planes of surfaces independently of atoms and bonds and control over the picture resolution and you have all the elements you need to make stunning pictures. Whether for internal presentations, print articles or large posters, Flare delivers the quality of picture that you need.

Free evaluation of Flare

The feedback that we have received on the usability of Flare has been very positive. In the next release, you will see even more usability features such as storyboards, improved ligand selection and enhancements to the drag and drop features. We want Flare to be the best structure-based design application you use, so share your experience with us.

Request a free evaluation of Flare to see for yourself just how accessible structure-based design is for computational, medicinal and synthetic chemists.

Proximagen enhances medicinal chemists’ toolkit with Flare for structure-based design

Cambridge, UK – 12 December 2017 – Cresset, innovative provider of software and contract research services for small molecule discovery and design, is pleased to announce that Proximagen, a drug discovery and development company, has licensed Flare.

“Flare will give our medicinal chemistry team rapid, hands-on access to structure-based design capabilities” says Dr Ed Savory, Head of Exploratory Research, Proximagen. “When combined with our use of Cresset’s Forge for SAR and design, and Spark for R-group exploration and scaffold hopping, our medicinal chemists have access to a wide range of easy to use modelling applications.”

“I’m delighted that Proximagen have chosen to enhance their toolkit by making Flare accessible to their medicinal chemists,” says Dr Tim Cheeseright, Director of Products, Cresset. “I’m confident that Flare will bring fresh insights into their protein-ligand analysis and design.”

Comparing ligand and protein electrostatics of Btk inhibitors

Abstract

Protein interaction potentials implemented in Flare,1 Cresset’s structure-based design software, were used to calculate a detailed map of the electrostatic character of the protein active site of Bruton’s tyrosine kinase2 (Btk). The interaction potential maps were compared to those of selected Btk ligands to get a detailed understanding of ligand binding and SAR. 3D-RISM analysis in Flare was applied to investigate the stability of the crystallographic water molecules populating the Btk active site.

Introduction

Bruton’s tyrosine kinase is a member of the Tec family of non-receptor tyrosine kinases. Recent literature findings2 indicate that Btk inhibition could be an attractive approach for the treatment of autoimmune diseases such as rheumatoid arthritis, a progressive autoimmune disease characterized by swelling and erosion of the joints.

The published X-ray crystal structure PDB:4ZLZ shows that the 4RV ligand interacts with the active site of Btk (Figure 1 – left) by making H-bond interactions with Glu475 and Met477 in the hinge region. The pyridyl ring is involved in a cation-pi interaction with Lys430, with the pyridyl nitrogen making a water-mediated interaction to the P-loop residues Phe413 and Gly414. The replacement of 4-methylpyridin-3-yl with small bicyclic heterocycles like indazole in 4L6 (PDB:4Z3V, Figure 1 – right), displacing the water molecule and making direct H-bond interactions with the P-loop, led to the discovery of ligands with improved potency towards Btk such as compounds 4L6, 1 and 2 (see Table 1).3


Figure 1. Left: X-ray crystal structure of 4RV (PDB:4ZLZ) in the active site of Btk making a water mediated hydrogen bond with the P-loop backbone. Right: X-ray crystal structure of 4L6 (PDB:4Z3V) making direct H-bond interactions with the P-loop backbone.

In this case study, we used the protein interaction potentials and the 3D-RISM method available in Flare to investigate the electrostatics of the active site of Btk and the stability of the crystallographic water molecules. This information was then used to understand the SAR of the molecules in Table 1.

Method

The 4ZLZ and 4Z3V ligand-protein complexes were downloaded from the Protein Data Bank into Flare, and carefully prepared using the Build Model4 tool from BioMolTech,5 to add hydrogen atoms, optimize hydrogen bonds, remove atomic clashes and assign optimal protonation states to the protein structures. Any truncated protein chains were capped as part of protein preparation.

The protein sequences were aligned in Flare using the COBALT6 multiple alignment tool and subsequently superimposed by means of a least squares fit of equivalent C.alpha carbon atoms.

Protein minimization

The active site of the prepared 4ZLZ and 4Z3V ligand-protein complexes was minimized in Flare using the XED force field7 and Normal conditions (gradient cutoff: 0.200 kcal/mol/Å, 2,000 maximum iterations). The ligand structures were included in the minimization of the active site.

3D-RISM analysis

The Reference Interaction Site Model (RISM) is a modern approach to solvation based on the Molecular Ornstein-Zernike equation.8 3D-RISM has seen increasing use as a method to investigate the location and stability of water molecules in a protein.

Conceptually, 3D-RISM is equivalent to running an infinite-time molecular dynamics simulation on the solvent (keeping the solute fixed), and then extracting the density of solvent particles. The output of a 3D-RISM calculation consists in a grid containing particle densities, one for oxygen and one for hydrogen atoms. A thermodynamic analysis then assigns a ΔG value to each position on the grid, representing the ‘happiness’ of a putative water molecule at that position of the grid relative to bulk water.

3D-RISM calculations in Flare use Cresset’s XED force field, which offers the advantage of incorporating both electronic anisotropy and a certain degree of polarizability, and accordingly improves the effectiveness of the method.

A 3D-RISM analysis was carried out on 4ZLZ and 4Z3V to investigate the stability of crystallographic water molecules surrounding the 4RV and 4L6 ligands bound to the active site of Btk.

The following conditions were used:

  • XED force field and charge method
  • 4Å grid spacing
  • 14Å grid external border width
  • Convergence tolerance: 10-8
  • Maximum number of iterations: 10,000
  • Total formal charge handling: neutralize with counterions.

Protein interaction potentials

Protein interaction potentials are an extension of Cresset molecular interaction potentials to proteins. Both are calculated using the XED force field. The approach is similar in principle to the calculation of ligand fields: the protein’s active site is flooded with probe atoms, and interaction potentials are calculated at each point. This method makes use of a distance-dependent dielectric function based on the work of Mehler,9 to better cope with the large number of charged groups in protein structures.

All the ligands in Table 1 belong to the same series as 4L6, so for this case study protein interaction potentials were only calculated and displayed for the active site of 4Z3V.

Ligand fields

To obtain a sensible pose for the ligands in Table 1, the corresponding 2D structures were docked into the ‘dry’ (i.e., not including crystallographic water molecules) active site of 4Z3V using the Lead Finder10 method implemented in Flare.

Cresset’s ligand fields were then calculated and compared to the 4Z3V protein interaction potentials, to investigate the SAR for the ligand series.

Results

3D-RISM analysis on 4ZLZ

At the end of a 3D-RISM run, a 3D-RISM water molecule chain is added to the protein structure. The water molecules in this chain occupy regions of high water density as predicted by 3D-RISM, and are colored according to the calculated ΔG for the whole water molecule, averaged over all orientations.

‘Happy’ water molecules (associated with a calculated negative ΔG) are colored in shades of green: these are water molecules which 3D-RISM predicts to be more stable in the protein than in bulk water, and hence more difficult to displace with a ligand.

‘Unhappy’ water molecules (associated with a calculated positive ΔG) are colored in shades of red: these are waters that are less stable relative to bulk water and hence more easily displaced by a ligand.

Figure 2 shows the results of the 3D-RISM calculation on 4ZLZ. The oxygen density surface (Figure 2 – left) clearly shows a region of localized water near the nitrogen of the pyridine, and the 3D-RISM localization algorithm (Figure 2 – right) suggests that a water molecule should exist in exactly the spot where it is seen in the crystal structure. The thermodynamic analysis indicates that this water molecule is neither particularly ‘happy’ nor particularly ‘unhappy’. This is consistent with the fact that this water molecule is displaceable (as proven by 4L6 and the other compounds in Table 1), but also indicates that the displacing group needs to have the correct electrostatics and shape to avoid losing affinity.

3D-RISM analysis on 4Z3V

The oxygen density surface for 4Z3V is shown in Figure 3 – left. The 3D-RISM localization algorithm correctly identifies the position of the majority of crystallographic water molecules surrounding the 4L6 ligand bound to the Btk active site: many of these water molecules are predicted to be ‘happy’. Accordingly, a selected subset of the stable water molecules was included in the calculation of protein interaction potentials for 4Z3V, as they were considered to be an integral part of the protein active site with respect to ligand binding.


Figure 2: 3D-RISM results on 4ZLZ. Left: oxygen isodensity surface at ρ=5. Right: localized 3D-RISM waters, colored by ΔG.


Figure 3: 3D-RISM results on 4Z3V. Left: oxygen isodensity surface at ρ=5. Right: localized 3D-RISM waters, colored by ΔG.

Protein interaction potentials for 4Z3V

As shown in Figure 4, the protein interaction potentials of both the ‘dry’ (not including crystallographic water molecules) and ‘wet’ (including stable crystallographic water molecules lining the active site) active site of 4Z3V match the 4L6 ligand fields in a satisfactory manner.

In particular:

  • the electron-rich cinnoline ring sits in a region of positive interaction potential in the middle of the 4Z3V active site;
  • the 5,6 hydrogens of the cinnoline ring sit near an area of negative interaction potential corresponding to the carbonyl of Leu408;
  • the carbonyl and the NH2 of 3-carboxamide sit respectively within and nearby an area of positive and negative interaction potential corresponding to the backbone NH of Met477 and the backbone carbonyl of Glu475 in the hinge region of Btk, with which they form H-bonds;
  • the 4-amino group on the cinnoline ring also sits nearby an area of negative interaction potential, corresponding to the carbonyls of Met477 and Leu408;
  • the electron-rich 5-membered ring of indazole sits in an area of positive interaction potential corresponding to the protonated side chain of Lys430 (not shown) and the backbone NH of Phe413, with the NH-group pointing towards a negative area corresponding to the backbone carbonyl of Gly414 with which it forms an H-bond.

The inclusion of stable water molecules in the calculation of protein interaction potentials confirms this scenario. In this case though, the region of positive protein interaction potential in the middle of the 4Z3V active site is much larger and embraces most of the cinnoline-indazole ring system. This is indeed fully consistent with the negative ligand field surrounding the cinnoline-indazole ring system (Figure 4 – bottom).

Also, the 4-amino group on the cinnoline ring sits in an area of negative interaction potential which nicely matches the positive ligand field corresponding to this group.


Figure 4: 4L6 superimposed to the protein interaction potentials of 4Z3V. Top-left: ‘dry’ active site, not including crystallographic water molecules. Top-right: ‘wet’ active site including stable water molecules. Bottom: Ligand fields for 4L6. Protein interaction potentials shown at isolevel = 3; ligand fields shown at isolevel = 2.

SAR of Btk inhibitors

A comparison of ligand fields with the protein interaction potentials for the active site of Btk provides some useful insight into the SAR of compounds in Table 1.

Compound 1

Compound 1 (pIC50 8.7) is one of the two most potent compounds in this data series,3 carrying a -OMe side chain on the indazole ring and a fluorine in position 5 of the cinnoline ring. The binding mode of 1 (Figure 5) is similar to that of 4L6. The compound makes H-bond interactions with Glu475 and Met477 in the hinge region, a cation-pi interaction with Lys430 (not shown), and H-bond interactions with the backbone of P-loop residues Phe413 and Gly414.

The fluorine group sits in a relatively large pocket close to a water molecule which it possibly displaces. The CH3 of the OMe group sits in an area of negative interaction potential.


Figure 5: Left: compound 1 (pIC50 = 8.7) superimposed to the protein interaction potentials for the active site of 4Z3V at isolevel = 3. Right: ligand fields for compound 1 at isolevel = 2.

Compound 2

Compound 2 is also one of the most active compounds in the data series3. Quite interestingly though, the NH on the indazole does not make an H-bond with Gly414, as it is turned on the other side, possibly making an
H-bond interaction with a nearby water molecule.


Figure 6: Compound 2 (pIC50 = 8.7) superimposed to the protein interaction potentials for the active site of 4Z3V at isolevel = 3.

Compounds 3 and 4

The good activity (pIC50=8.4) of compound 3 confirms that an H-bond donor on the bicyclic system is not an essential feature for a Btk ligand to reach good levels of activity. Quite interestingly, compound 4 (pIC50=7.7) is structurally very similar to 3, but significantly less active. The comparison of the ligand fields for these two compounds with the protein interaction potentials of the active site of 4Z3V provides a possible explanation, as shown in Figure 7. While for both compounds (Figure 7 – middle column) the negative ligand field shows a good complementarity with the positive interaction potential of the backbone NH of Phe413, the positive ligand field of 4 (Figure 7 – right column) does not match the negative interaction potential generated by the backbone carbonyl of Gly414.

For both compounds, the methyl group in position 7 of the cinnoline ring plays the same role of the methyl on the indazole ring of 4L6 in ensuring that the ligands achieve the correct conformation in the active site.


Figure 7: Compounds 3 and 4 superimposed to the protein interaction potentials for the active site of 4Z3V at isolevel = 3. Ligand fields shown at isolevel = 4.
Middle: positive interaction potentials superimposed to negative ligand fields.
Right: negative interaction potentials superimposed to positive ligand fields.

Conclusions

Protein interaction potentials and ligand fields, as implemented in Flare, are a powerful way of understanding the electrostatics of ligand-protein interactions. The inclusion of stable water molecules following a 3D-RISM analysis dramatically improves the precision of the method for the characterization of protein active sites. The information gained from protein interaction potentials can be used to inform ligand design, compare related proteins to identify selectivity opportunities, and understand SAR trends and ligand binding from the protein’s perspective.

References and links

1. http://www.cresset-group.com/products/flare/
2. C.R. Smith et al., J. Med. Chem. 2015, 58, 5437−5444
3. US patent 2015/0038510
4. V. Stroganov et al., Proteins 2011, 79(9), 2693-2710
5. https://www.biomoltech.com/
6. https://www.ncbi.nlm.nih.gov/tools/cobalt/re_cobalt.cgi
7. J.G. Vinter, J. Comput.-Aided Mol. Des. 1994, 8, 653-668
8. R. Skyner et. al., Phys. Chem. Chem. Phys. 2015, 17(9), 6174
9. E. L. Mehler, The Lorentz-Debye-Sack theory and dielectric screening of electrostatic effects in proteins and nucleic acids, in Molecular Electrostatic Potentials: Concepts and Applications, Theoretical and Computational Chemistry Vol. 3, 1996
10. O. V. Stroganov et al., J. Chem. Inf. Model. 2008, 48(12), 2371-2385

Cresset releases Flare: Powerful structure-based design application with outstanding new methods for protein-ligand systems

Cambridge, UK – 29 June 2017 – Cresset, innovative provider of software and contract research services for small molecule discovery and design, announces the release of Flare, an intuitive desktop application that provides outstanding new methods for understanding protein-ligand systems. Flare enhances Cresset’s existing excellent product range focused on ligand-based design, and becomes their first product explicitly designed to support structure-based design.

“Cresset has been pushing the boundaries of ligand-based design for many years,” says Dr Robert Scoffin, CEO of Cresset. “Flare introduces structure-based design into our portfolio, giving companies access to outstanding new methods for investigating protein-ligand systems.”

Computational, medicinal and synthetic chemists working on small molecule design and optimization will use Flare to:

  • Gain vital knowledge ofprotein and ligand electrostatics to improve new molecule design
  • Compare electrostatic patterns across a protein family to design more selective ligands
  • Design new molecules anddock them to a protein target
  • Minimizeprotein-ligand complexes to achieve the optimal interaction for each compound
  • Calculate the location andstability of water molecules in a protein to guide compound design.

“Flare represents the next generation of structure based design applications,” says Dr Tim Cheeseright, Director of Products. “It has a modern, intuitive interface and is easily configured to enable cloud-based calculations, making excellent science immediately available to all users whatever their experience level.”

Users will benefit from:

  • Simple drag and drop to import/export molecules to the desktop or other compatible applications
  • Ready access to powerful tools through a modern ‘ribbon bar’ interface
  • Simple yet powerful selection capabilities and cutting-edge display options producing highly insightful molecular graphics.

“Flare integrates cutting edge approaches from Cresset with significant open source and commercial methods,” explains Dr Mark Mackey, CSO. “Throughout the product development we have worked alongside users from major pharmaceutical and biotech companies to ensure that we deliver the best science in the most intuitive format.”

Flare can be evaluated free of charge.

Download press release.

Molecular design towards Protein-Protein Interaction inhibitors

In December 2016 I attended the SCI Protein-Protein Interaction symposium. Armed with Cresset’s powerful ligand centric molecular modeling suite Forge, and an embryonic version of our new structure-based design application, Flare, I was keen to see what could usefully be done with PPI’s.

Prof. Richard Baylis (University of Leeds, UK) presented new data on the interaction of N-MYC with Aurora A. N-MYC is a disordered multi-domain protein with a host of interaction partners. Dysregulation of N-MYC has been linked to a range of cancers. N-MYC is short lived in-vivo and its usual fate is to be ubiquitinylated and degraded. Binding with Aurora A protects N-MYC from this process allowing its various tumorogenic affects to persist. The Baylis group provided the first x-ray evidence showing how N-MYC interacts at an allosteric site of Aurora A which stabilises an active conformation of the Kinase (figure 1).


Figure 1: Aurora A kinase with N-MYC – light green (left), and detail of the N-MYC short helical domain 74-89 (right).
Baylis suggested that DFG-out inhibitors of Aurora A provide distortions of the kinase that would prevent MYC binding, conversely, inhibition with ATP competitive inhibitors would not. Evidence of potential beneficial effects of the former type of kinase inhibitor, but not the latter, may be explained by this fact and led to the suggestion that this may be an effective therapeutic strategy for some types of cancer such as neuroblastoma.

An alternative computational strategy, which occurred to Cresset at the time, was to employ a structure-based approach; to furnish molecular designs that could directly prevent this protein-protein interaction. For this purpose, an initial analysis of the surface interaction, including both electrostatic and lipophilic hot-spots, would be vital.

During the talk, I used Flare to quickly download the relevant PDB file (5G1X) and to load the protein coordinates directly into the application. An automated protein prep protocol (build-model) was used to refine the pdb structure before generating the surface interaction maps, using Cressets proprietary XED force field (figure 2).


Figure 2: (A) Positive protein electrostatic isopotential surface of Aurora (left), negative protein electrostatic isopotential surface (center), and neutral isopotential surface with some key residues of N-MYC (right).
These isopotential maps show discrete positive (red), negative (blue) and neutral (yellow) surface regions that represent key interactions sites between N-MYC and Aurora A which allowed the assignment of the N-MYC residues on which to focus. The N-MYC protein was similarly used to generate and visualise the complimentary fields – as the other component half of the PPI (figure 3).


Figure 3: Negative protein electrostatic isopotential surface of N-MYC short helical region (left), and positive protein electrostatic isopotential surface of the same (right).
In keeping with other known PPI’s such as the MDM2 system, in the short helical domain (N-MYC 74-89) residues Met81 and Trp77 were identified as key lipophilic contacts. Much of the rest of the helix is largely for structural integrity and for stabilising solvent except for the NH of Trp77 and Glu84, which provide additional polar contacts, the latter capping an adjacent helix from Aurora. Further along the N-MYC peptide, towards the N-terminus, Pro74-Pro75 motif (figure 1) marks a change in sec. structure leading to another lipophilic contact Val61 and another polar contact Ser64 (not shown).

We can exploit this information to generate chemical starting points, once each important set of residues is identified and mapped. Thus, from the 3D shape and detailed electrostatic information we can conduct de-novo design experiments to furnish ideas for synthesis, or use virtual screening (Blaze) to search for commercial compounds to purchase and test.

Since the distance between the two main hot spot regions was not ideal (27 Ang. Val61 to Trp77) and although linking them might have been possible using a fragment linking or growing technique e.g., using Spark (Using Cresset’s Spark to grow and link distant fragment hits with sensible chemistry), we chose to tackle them independently with a de-novo design technique. I used the key residues Pro75, Trp77, Glu80, Met81 and Glu84 from the short helical domain as a molecular reference. We used this reference to score our molecular ideas against, and to optimize them via iterative ‘molecular design > alignment > scoring’ cycles in Forge. This powerful technique scores 3D shape, electrostatics and protein steric clashes whilst simultaneously calculating and/or filtering in-silico physiochemical properties. This method as described is limited only by the imagination of the user. In conjunction with Spark as the idea generator however, the limit is set only by the availability of appropriate fragments in the Spark databases – which is a substantial resource.

Later, when we returned, we also ran a virtual screening test on this system using the Blaze demo server. Results of this quick virtual screen against a sub-set of the ChEMBL database are shown below (figure 4).


Figure 4: Forge ‘tile view‘ of example diverse 2D output results of the virtual screen using the Blaze Demo server against a sub-set of ChEMBL (left) and 3D alignments of two of these (pink and green sticks) against the reference N-MYC peptide (blue lines) bound to Aurora A (Forge screenshot).
Although some of the Blaze examples retrieved were interesting, very good considering that this was a very small set <200k compound DB, it appears that good shape score and field score were not generally observed simultaneously. The ‘new’ addition of ‘pharmacophoric atom features in Blaze’ ensured we retrieved some of the key contacts such as the indole H-bond. However, we felt that design was probably the best way to address achieving the precise set of contacts we were looking to mimic.  Afterwards, I expanded on the ‘initial’ de-novo design ideas and provided around 20 further designs which had more reasonable properties and synthetic tractability (figure 5).

A powerful combination of cutting edge ligand and structure-based modeling

Figure 5: Flare screenshot of the structure of an initial idea (left) superimposed on N-MYC hot spot residues, plus its calculated properties, and (right) a space filling model of a further example with superior properties, improved fit, better synthetic tractability and … an IP position.Although this is only a thought experiment (until the point at which any of these molecular designs are synthesized and tested) this illustrates how the powerful combination of both ligand centric and structure-based techniques in Flare, Forge, and perhaps also Spark, could be used to generate specific ideas that address the types of challenges presented by PPI’s or fragment enabled drug discovery projects. This is not untypical, in terms of a portfolio of tasks we might suggest to Cresset Discovery Services clients.

Download an evaluation of Flare, Forge, Spark and Blaze, or contact us to find out how Cresset Discovery Services can enhance your project with insightful and creative delivery of powerful molecular modeling.

Flare release imminent

New insights for structure-based design, thanks to our testers

With the release of Flare imminent, I would like to thank all our dedicated alpha and beta testers for their time and patience. Your work has been invaluable to directing the final stages of development and smoothing out workflows before the full release.

Throughout the development of Flare we have worked closely with users to ensure that we concentrate on the capabilities that are most important to you. We trust that Flare will add great value to your work, repaying the time and effort you have put in to its development.

Flare is a new product for us, moving into new scientific space, and has been many years in the making. Extensive scientific testing and benchmarking have been carried out on our own in-house methods and on those we have brought in from our scientific partners. We are completely committed to giving you the best science in the most usable form to push your projects forward and to fit in with your workflows.

The finishing touches are now being completed in advance of release which is scheduled for next week.

Request an evaluation of Flare.

Victrix CMCC chooses Cresset’s software for consulting projects to give insight into molecular activity

Welwyn Garden City, UK – 27 June 2013 – Cresset, innovative provider of chemistry software and services, announces that under a new agreement, Victrix CMCC will use Cresset’s software for their computational chemistry consulting projects. Cresset’s Spark, Forge and Torch software will help Victrix clients carry out structure-based drug design projects and to build predictive 3D SAR models for lead identification.

“Victrix is very pleased to be able to offer our clients access to Cresset’s software,” says Dr Adam Kallel, CSO of Victrix.  “Cresset’s field based software significantly expands our ability to help clients with programmes that have little or no structural information.”

Dr Kallel adds, “I have been a believer in field based methodology since I began work in the pharmaceutical industry and I was an early adopter of the Cresset technology.  I believe the XED force field that underlies Cresset’s software provides the ability to model molecules and their molecular fields in a way that is as close to high level quantum mechanics as possible, giving valuable insights into structure reactivity relationships. I strongly recommend its use and am very pleased to provide this functionality to Victrix clients.”

“We are delighted that Victrix has chosen to use Cresset’s software for their consulting projects,” says Dr Robert Scoffin, CEO of Cresset.  “Our field based approach of using 3D electrostatics and shape to understand molecular function is particularly valuable when there is no information available about the protein target.  We look forward to Victrix clients experiencing the difference our software will make to their research.”