RSC Medicinal Chemistry special FBDD issue

The Royal Society of Chemistry puts out RSC Med. Chem., and last year they asked David Rees (Astex), Anna Hirsch (Helmholtz Institute for Pharmaceutical Research Saarland), and me whether a special themed issue on FBDD would be useful for the community. Naturally we said yes, and the results have now been published. You can read our introduction here.

 

Unlike olden days, when special issues were bound between covers, this is a virtual special issue, with papers published over a period of several months. Indeed, we already wrote about two of them last year: one on combining DNA-encoded libraries (DEL) with FBLD and one on inhibitors of PRMT5/MTA. (Both of these were also topics at the CHI FBDD meeting earlier this month.) In the next few paragraphs we highlight the rest.

 

AstraZeneca has been doing FBDD since 2002, and has gained hard-won wisdom, some of which was shared in a 2016 review we wrote about here. After years of screening, their fragment library had started to deteriorate, so they rebuilt it entirely, as described by Simon Lucas and colleagues. Some of the starting fragments came from their previous library, but they also considered molecules from their larger collection. Rather than focusing on the rule of three, they developed their own multiparameter optimization function, “FragScore,” which incorporates logD_7.4, heavy atom count, number of rotatable bonds, and number of hydrogen bond donors. All compounds were inspected to make sure they would be synthetically tractable, and quality was assessed by SPR, NMR, redox activity, and solubility. The final set consists of 2741 fragments, with a subset of 1152 maximally diverse and attractive fragments for ligandability assessments or screening hard-to-make proteins. They also gathered 16,806 near neighbors for hit follow-up. So far the effort has paid off, with all four of the targets screened thus far yielding progressible hits. If you’re building or renovating a fragment library, you should read this paper.

 

Continuing on the theme of libraries, Bradley Doak, Martin Scanlon, and colleagues at Monash University describe their “MicroFrag” library, a set of 91 tiny (5-8 non-hydrogen atom) compounds similar to MiniFrags and FragLites. A crystallographic screen (at 1 M concentration!) of the MicroFrag library against the difficult E. coli target DsbA yielded a 52% hit rate, compared with a 2% hit rate with a conventional fragment library. Importantly, the MicroFrag screen identified the two main hot spots previously discovered from the conventional fragment library, along with ten others that may be less actionable. Interestingly, a crystallographic screen of 15 organic solvents at even higher concentrations (50-80%) was less informative: the primary hot spot did not distinguish itself from others. In the case of MicroFrags, not only did this hotspot bind the largest number of fragments, but all the molecular interactions seen for larger fragments were observed.

 

Fluorine NMR takes advantage of its own specialized library, the subject of a paper by Chojiro Kojima (Osaka University), Midori Takimoto-Kamimura (CBI Research Institute) and collaborators from several institutions. The researchers describe the construction of a 220-member library divided into pools of 10-21 compounds. This library was screened against four diverse proteins, yielding between 3 and 16 hits. The three hits against FKBP were characterized in more detail, including two-dimensional NMR and isothermal titration calorimetry. The researchers also discuss using ¹⁹F STD experiments to determine the binding mode of bound fragments.

 

Fluorine is not the only halogen of interest for library design. We’ve previously described the halogen-enriched fragment library (HEFLib, here and here), which consists of chlorine, bromine, and iodine-containing molecules. Frank Boeckler and collaborators at Eberhard Karls Universität Tübingen and the Max Planck Institute describe screening this library against the Y220C mutant of p53 in an expansion of work they first described back in 2012. Of 14 hits identified by thermal shift or STD NMR, ten confirmed by two-dimensional ¹H-¹⁵N-HSQC NMR. Four of these bound in the cleft created by the Y220C oncogenic mutation. Two other fragments turned out to be covalent binders, though they reacted with more than one cysteine residue. Although all the fragments have low affinities, they could potentially serve as starting points for optimization.

 

An ongoing debate is whether there is an advantage to screening more “three dimensional” fragments as opposed to planar aromatic fragments. If your taste tends towards the former, the synthetic chemistry can get tricky. According to an analysis we highlighted last year, the piperidine ring is the third most common scaffold found in drugs. Now, Peter O’Brien (University of York) and an international group of collaborators report efficient synthetic routes to all 20 cis- and trans-piperidines substituted with a methyl group and a methyl ester. A virtual library of 80 compounds in which the secondary amine is capped with simple substituents such as methyl or acetyl groups was found to be quite shapely, particularly compared with the disubstituted pyridyl starting materials. Moreover, the fragments are still reasonably sized, with no more than 15 non-hydrogen atoms and ClogP values < 2.

 

Machine learning is gaining prominence everywhere, not least in drug discovery. In 2021 we highlighted an “autoencoder” designed for constructing fragment libraries biased towards “privileged” fragments more likely to generate hits. However, the method required considerable programming savvy. Now Angelo Pugliese (BioAscent) and collaborators at the Beatson Institute have implemented their model in the open-source KNIME platform, making it accessible to a wider range of researchers. As an example they use the method to construct a GPCR-focused fragment library, with the structures of all the members provided in the supporting information.

 

On the subject of fragment libraries, please make sure to vote in our 6-question poll on library design (right side of page; you may need to scroll up).

 

Not all the papers in this special issue involve library design. Marko Hyvönen, David Spring, and collaborators at University of Cambridge and National University of Singapore describe allosteric inhibitors of the kinase CK2α, which has been implicated in cancer cell survival. We highlighted some of their work against this target in 2017, in which they used fragment linking to find high nanomolar inhibitors of the enzyme. In the new paper, the researchers describe additional fragment binders at the so-called αD pocket, distant from the ATP-binding site. Virtual screening for analogs led to a fragment with mid-micromolar activity in biochemical and cell assays, and fragment merging led to low micromolar inhibitors.

 

This is a nice collection of papers, and for those of you without easy literature access make sure to check them out soon: for the next six months all of them are free to read after free RSC registration. Enjoy!

A very useful list: common linkers and bioisosteric replacements

Last week’s post highlighted an example of fragment linking, which despite being less common than fragment growing can still be effective. But how do you choose the linker? We’ve previously written about the most common rings found in drugs. In a new Bioorg. Med. Chem. paper Peter Ertl and colleagues at Novartis tabulate the most common linkers found in bioactive molecules.

 

The researchers start by defining linkers “as moieties connecting 2 ring systems.” To focus on druglike molecules, linkers could contain no more than eight non-hydrogen atoms total and no more than five consecutive bonds between the two ring systems. This means that para-disubstituted phenyl or 1,4-disubstiuted butyl would both be considered in the analysis, but longer linkers such as this recent example would not.

 

Molecules were extracted from the databases ChEMBL and ZINC, yielding a total of 1686 unique linkers. Various descriptors were calculated for all, which in addition to size and length included the number of heteroatoms and electronic properties. Bioactivity data for molecules in ChEMBL was used to assess which replacements were most frequently tolerated. If one linker could be replaced by another without causing a drop in affinity (or inhibition, etc.), the two linkers were considered to be bioisosteres.

 

So, what are the most common linkers? A single methylene is the most common, followed by an amide bond. I was surprised that, of the 40 most common linkers, only five are rings: para-disubstituted phenyl, 1,4-piperzine, 1,4-piperidine, 1,2,4-oxadiazole, and meta-phenyl, in that order. Not coincidentally, phenyl rings, piperidines, and piperazines are also the most common rings found in drugs, according to an analysis last year.

 

Last year we highlighted a paper from the Ertl group that included a link to a “Ring Replacement Recommender,” which suggests bioisosteric replacements for any ring. Alas, there is no “Linker Replacement Recommender,” but the new paper does provide a “bioisosteric replacement network,” which is a full-page 10 x 15 grid with the 150 most common linkers arranged such that nearby linkers are likely to be bioisosteric. For example, para-phenyl is adjacent to 2,5-thiophene and quite some distance from sulfone. These make sense, but there are also less obvious examples: the table suggests that a 1,4-pyrazole makes a good replacement for a carbamate.

 

The next time you’re doing SAR, it may be worth consulting the bioisosteric replacement network for ideas.

What rings are found in drugs?

Recently we highlighted the “Ring Replacement Recommender,” which provides suggestions for how to improve affinity by replacing one ring with another. The recommendations are based on an analysis of hundreds of thousands of molecules. But what about the rings found in actual drugs? This is the focus of a J. Med. Chem. paper by Richard Taylor and collaborators at UCB and Bohicket Pharma Consulting.

 

The researchers examined FDA-approved and investigational drugs with disclosed structures as of January 2020. These were fragmented into component “ring systems” for analysis. (Ring systems include not just monocycles but fused rings, such as purine. For example, sotorasib consists of four ring systems: benzene, pyridine, piperazine, and pyrido[2,3-d]pyrimidin-2-one.) More than 90% of drugs contain at least one ring.

 

Approved drugs have just 378 unique ring systems in total – a small increase from when the researchers examined approved drugs in 2014. The phenyl ring is found 727 times, with pyridyl (86 examples) a distant second, followed by piperidine (76 examples) piperazine (65 examples) and cyclohexane (47 examples). After that the numbers drop off sharply, with pyrazine in 50^th place with just six examples and fluorene in 100^th place with three examples.

 

Investigational drugs at first appear to be more diverse, with 450 unique ring systems, 280 of which are not found in approved drugs. Of these 280, pyridazine is the most common, with nine examples, followed by oxetane, with seven, but things quickly become less common from there, with 271 of the ring systems found just once. In contrast, ring systems found in drugs are found in multiple compounds, and in fact two thirds of investigational drugs only contain previously used ring systems.

 

Many of the new ring systems are closely related to those found in approved drugs, with nearly half differing by at most two atoms. Perhaps because of this the overall properties of the ring systems are similar between approved and investigational drugs, with no significant differences in heteroatom ratio, percentage of sp³ centers, or number of rings per system.

 

What new opportunities exist? The researchers identified nearly half a million synthetically accessible ring systems and winnowed these down to 3902 ring systems that have similar heteroatom ratios to those found in drugs and differ by at most two atoms. This attempt to explore new chemical space is similar to earlier work from the same group (here) as well as that from others (here, here and here).

 

The researchers also examined growth vectors and combinations of rings, the latter by using graph theory. These analyses suggest that investigational drugs do have greater variety. In other words, even if the component rings are shared with approved drugs, they might be combined in new ways.

 

Whether certain ring systems are more likely to fail in the clinic was intentionally not addressed, due to the difficulty of assessing why the failures occurred. For example, drugs can fail for commercial reasons; a company may choose to drop a drug against a particular target rather than be tenth to market. And even when the failure is due to the science, it might not be an indictment of the drug itself. Verubecestat did lower β-amyloid levels in people as designed, but had no effect on Alzheimer’s disease.

 

This paper is a fun read, and it will likely provide ideas for scaffold hopping and library design. It is also a reminder of how much chemical space remains to be explored.

What to make first? A new “Ring Replacement Recommender” provides suggestions

So you’ve run a fragment screen, gotten some hits, and validated them. What then? Looking for in-house or commercial analogs is always a good idea, but if you’re serious about a project you’ll eventually need to do chemistry, for example replacing one ring with another (say, a pyridyl for a phenyl). The possibilities are almost endless, especially if you don’t know how your fragment binds. In a new Eur. J. Med. Chem. paper, Peter Ertl and colleagues at Novartis describe a “Ring Replacement Recommender” to rapidly improve biological activity.

 

To determine which replacements are likely to improve affinity, the researchers turned to ChEMBL, a database of more than 2 million molecules and associated biological activity extracted from tens of thousands of publications. From these, more than 68,000 chemical series were chosen for analysis. Each series had on average 16 members, and at least three. The biological activity of each member of a series was compared with other members of the same series. (Importantly, the researchers intentionally excluded anti-targets such as hERG and CYPs so the tool wouldn’t inadvertently improve binding to these.) Focusing only on ring replacements that were reported in at least five publications led to a set of 26,762 changes. Changes could be as modest as adding a methyl substituent or more elaborate such as changing a single aromatic ring to a fused aromatic-aliphatic ring system.

 

One would think that most changes would have little effect, as had previously been seen in the case of methyl additions. Indeed about 65% of the replacements caused shifts in potency of 2-fold or less, which is probably within experimental error. However, 2860 replacements of 245 rings improved affinity at least 2-fold (averaging 3.5-fold), with 223 cases yielding greater than ten-fold improvements.

 

Analyzing the data further, the researchers found 80 ring systems that frequently led to improvements in affinity, and they suggest these could be used as “universal” or privileged building blocks. Strikingly, 74 of these are aromatic, confirming work from Cohen we highlighted in 2020 that proteins may favor “flat” rather than shapely molecules.

 

The researchers also extracted 9515 drugs and clinical compounds from ChEMBL and examined the component fragments. Of the 80 ring systems in the universal set, 19 are found in 50 or more drugs, with another 37 found in at least 5 drugs. This set may be a particularly attractive go-to list.

 

Importantly, not only are all the replacements available in the Supporting Information, the researchers have created a handy and free online tool. Just click on a ring of interest and the Ring Replacement Recommender provides suggestions, along with the average fold improvement observed and the number of publications used for the calculation.

 

To see how well it works, I looked at a couple recent examples which entailed ring changes. The indole to indazole replacement used in the TLR7/8 work described last month was not suggested by the Recommender, though in that case the researchers had the benefit of a crystal structure. On the other hand, a cyclobutyl to phenyl substitution for SARS-CoV-2-3CLp was correctly predicted to be beneficial.

 

Of course, as we’ve said repeatedly, affinity is only part of the battle in drug discovery, and the researchers emphasize that their recommendations may not improve physicochemical or pharmacokinetic properties. But for the earliest stage of a program, and especially in the absence of other data, it’s worth giving the Recommender a try.

Fragments in the Clinic: Indeglitazar

Following up on the discussion of fragment-derived compounds that have made it into the clinic, the first 2009 issue of PNAS describes the discovery of indeglitazar, which I believe is the USAN name of Plexxikon’s PLX-204/PPM-204. Indeglitazar is a pan-agonist of the peroxisome proliferator-activated receptors (PPARs), and has been in clinical trials for treatment of type 2 diabetes.

Plexxikon’s version of fragment-based screening, “scaffold-based discovery,” entails screening several thousand small to medium sized fragments (150-350 Da) in a biochemical assay, followed by crystallographic analysis of active molecules. In the current case, the researchers screened their collection against PPAR alpha, gamma, and delta, looking for molecules that activated two or more. After the primary screen, 170 molecules were characterized crystallographically, and about a quarter produced at least one structure. The substituted indole fragment (below) showed very weak activity, but bound snugly in a large pocket with its NH positioned toward a second pocket. Structure-guided design led to the more potent phenyl sulfonamide shown in the middle of the figure, and synthesis of just 20 additional compounds resulted in indeglitazar, which activates PPARs alpha, gamma, and delta. Ligand efficiency remained fairly constant throughout optimization.



Indeglitazar is a full agonist of PPAR alpha but only a partial agonist of PPAR gamma and delta; this may provide a better side effect profile than full activators. The molecule shows impressive pharmaceutical properties (high oral bioavailability, long half-life, etc.) as well as promising activity in mouse and rat models of diabetes (lower blood glucose, insulin, total cholesterol, triglycerides, free fatty acids, etc.). In contrast to other PPAR agonists, which sometimes cause weight gain, indeglitazar also caused weight loss in rodent and primate models; the authors suggest this could be because it affects all three PPARs.

Although indeglitazar was advanced to phase 2 trials in collaboration with Wyeth, increasing concerns over the potential side effects of PPAR agonists have caused Wyeth to discontinue development of this compound for diabetes, and as of November of 2008 the molecule was available for licensing.

Nonetheless, this is an impressive story, and appears to be the first example of using fragment-based methods to discover an agonist, as opposed to an inhibitor.