Multivalent fragments in the clinic: Muvalaplin

It’s been a couple years since Practical Fragments last updated our “fragments in the clinic” list. Before doing so it makes sense to highlight some of those we’ve missed. Let’s start with an open-access Nature paper from Laura Michael and collaborators at Lilly and Monash University published in 2024. Truth be told I’ve been waiting for a longer discovery paper, but I’ll go with what’s available now.

 

The researchers were interested in lipoprotein(a), or Lp(a), which has been linked to cardiovascular diseases. Lp(a) forms when low-density lipoprotein (LDL) binds to apolipoprotein(a), or apo(a). This is a two step process, in which the ten subtypes of so-called Kringle IV (K_IV) domains in apo(a) bind to lysine residues on LDL, followed by disulfide bond formation between apo(a) and LDL. Blocking the first step in this process should reduce levels of Lp(a).

 

Here's the only description of the initial screen: “Biochemical and biophysical compound screens using purified apo(a) K_IV7-8 protein identified interacting small molecules. Optimization of the initial binding molecules led to…LSN3353871.” Whatever the details, LSN3353871 is unequivocally a rule-of-three compliant fragment. It is also a very ligand-efficient binder with high nanomolar affinity for the K_IV8 domain. LSN3353871 disrupted the formation of Lp(a) in vitro at low micromolar levels and decreased levels of Lp(a) in cynomolgus monkeys when dosed orally.

 

As noted above, the apo(a) protein contains multiple K_IV domains, and a classic method for improving potency is by making dimeric ligands that can bind to two domains simultaneously. The researchers did just this in the form of LSN3441732, which binds to apo(a) and disrupts formation of Lp(a) in vitro at picomolar concentrations.

 

If dimeric ligands are better than monomeric ones, why not go for multimeric ligands? The trimeric molecule LY3473329, or muvalaplin, was synthesized and crystallographically shown to bind to three copies of K_IV8. It blocked formation of Lp(a) in vitro and reduced Lp(a) levels in cynomolgus monkeys.

 

Kringle domains are found not just in apo(a) but also in plasminogen, the zymogen form of plasmin, which is responsible for degrading blood clots. Fortunately, subtle differences between the Kringle domains in apo(a) and human plasminogen provide selectivity for the former protein, especially for multivalent ligands such as muvalaplin, and a phase 1 clinical study showed that Lp(a) could be lowered without affecting plasmin activity.

 

This is a nice application of applying fundamental multivalent principles to develop a potent molecule. It is also another example of a molecule that may not look like a drug but works like one: despite containing four basic nitrogen atoms, three carboxylic acid moieties, and sporting a molecular weight above 700 Da, muvalaplin is orally bioavailable. It is currently in a phase 3 trial in up to 10,450 patients. Cardiovascular disease is the leading cause of death in the developed world, and Practical Fragments wishes luck to everyone involved in these studies.

 

In the meantime, watch for more Practical Fragments posts on new entries to our fragments in the clinic list, which will be updated later this year.

xSAR: Crystallographic SAR from crude reactions

Last year we highlighted an example of crystallographic screening of crude reaction mixtures to find inhibitors against the oncology target PHIP(2). Of 957 molecules tested, 22 showed crystallographic binding in two different orientations: 19 in a “lateral” pose and 3 in a “diving” pose. In a new open-access Chem. Sci. article, Philip Biggin and collaborators at Diamond Light Source and University of Oxford try to extract information from both the binders and the non-binders using crystallographic structure-activity relationships, or xSAR.

 

Chemists often think about SAR in qualitative terms: a methyl group here improves affinity, a chlorine atom there reduces it. In xSAR, the researchers sought to take a more quantitative approach. They converted each molecule into “Morgan fingerprints,” a set of more than 2048 binary bits describing structural features such as atom type, hybridization, and connectivity to other atoms within a certain distance. Some bits were found in all binding compounds, and these were referred to as conserved binding bits (CBB), while conserved nonbinding bits (CNB) were found only in non-binding compounds. These bits were then used to calculate Positive and Negative Binding Scores (PBS and NBS); a compound with a PBS of 1 contains all the CBB. Since there were two separate binding modes, the researchers calculated PBS and NBS values for both lateral and diving poses individually as well as for all binders.

 

As the researchers note, false negatives are a likely issue in crude reaction screening for a variety of reasons. To hunt for these, the PBS and NBS values were calculated for all 957 molecules previoulsy tested. A set of 97 pure compounds having mostly high scores were acquired and tested crystallographically, yielding an additional 23 lateral binders and 3 diving binders, more than doubling the initial yield. PBS was particularly informative in this retrospective exercise to recover false negatives, outperforming both NBS as well as other methods such as Tanimoto similarity scores.

 

The researchers also used PBS and NBS scores to search prospectively for new binders in a virtual set of more than 1.7 billion compounds in the Enamine REAL database. After filtering for high PBS/NBS scoring compounds followed by docking, 93 compounds were acquired and tested crystallographically. Interestingly, this yielded a relatively low hit rate of 9 binders, 6 in the lateral pose and three in somewhat different poses. None of the new compounds bound in the diving pose, which the researchers suggest may be due to the small sample size used to calculate PBS and NBS for this binding mode.

 

The 93 new compounds were also tested for binding using grated-coupled interferometry (GCI), and 13 showed measurable affinity, with most better than 50 µM. Two even showed single-digit micromolar affinity, more than an order of magnitude better than the best compound from the screen we discussed last year, and with better ligand efficiencies too. Surprisingly, these two compounds were not hits in the crystallographic screen.

 

This is an interesting paper with a couple important lessons. First, despite the fact that affinity was not used in calculating PBS and NBS, these metrics were nonetheless useful for identifying molecules with better affinity than those in the original training set, arguing for their utility. But perhaps just as importantly, the molecules with the best affinity were missed by crystallographic screening. If anything, this observation only strengthens my conclusion last year that while “there is a strong case for using crystallography first for finding fragments, I am not yet convinced the same applies for optimizing fragments.”