Stabilizing Plasmodium falciparum Proteins for Small Molecule Drug Discovery
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Abstract
Early-stage drug discovery relies on the availability of stable protein for reliable biophysical characterization of ligand binding. However, many Plasmodium falciparum proteins are challenging to produce in heterologous systems, which limits their experimental utility. To address this, we tested whether ProteinMPNN-guided sequence design could generate stabilized surrogate constructs that retain wild-type-like structure and binding thermodynamics. Designs were generated with constraints to maintain conserved and binding-site residues for three therapeutically relevant targets: Pf BDP1-BRD, Pf BDP4-BRD, and Pf K13-KREP. The resulting constructs showed markedly increased thermal stability. Using Pf BDP1-BRD as a benchmark, isothermal titration calorimetry confirmed that the stabilized variants retained wild-type-like binding thermodynamics with a known ligand. Extending this approach to other targets, a Pf K13-KREP construct led to an apo structure with a binding pocket closely matching the wild type, and a stabilized Pf BDP4-BRD surrogate - a previously unstable target - enabled the identification of Pf BDP4-BRD binders and a 1.25 Å co-crystal structure with a newly found inhibitor. Our findings demonstrate that computationally stabilized surrogates are practical and effective tools for robust biophysics and structure-enabled drug discovery against otherwise challenging malaria proteins.
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Our findings demonstrate that computationally stabilized surrogates are practical and effective tools for robust biophysics and structure-enabled drug discovery against otherwise challenging malaria proteins.
Very interesting paper! I like that the authors looked at this problem that has been traditionally difficult to study in this way and attempted to use the tools available to bring it into the realm of something study-able!
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Our approach incorporated explicit constraints to preserve biological function, retaining evolutionarily conserved residues
I think this is a really important point, and I like that you showed conservation of binding thermodynamics for PfBDP1 with RMM23 as my biggest question throughout the manuscript was how you ensure that protein function is preserved when introducing this many sequence changes. These constraints seem like a strong step, as well as that control, but maybe still an important thing to keep in mind. For example, even if the binding pocket geometry is structurally conserved, mutations outside the pocket could still influence binding (e.g., through altered dynamics, stability of the fold, or long-range effects on binding energetics).
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First, standard AlphaFold2 predictions represent single energy minima and cannot capture the conformational ensembles or dynamic distributions that often govern experimental behavior, particularly for flexible regions and allosteric sites
This is really powerful as it's allowing you to study proteins that otherwise were not able to be studied in this way. But related to this idea that AF2 isn't capturing conformational ensembles, are you thinking about the effect that stabilizing the protein might have on your ability to study biologically relevant conformational dynamics of the protein?
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PfBDP1-BRD served as our benchmark, as we had previously characterized its structure and ligand interactions
I like that you included benchmark that you've previously characterized structurally and functionally, really nice control!
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Across redesigned constructs, mean pLDDT values were uniformly high (96.63 to 99.30)
It would be interesting to know what the pLDDT values are for the wild-type proteins as well if you ran them through your structure prediction tool, just to see if there is a significant change. Interesting thought that pLDDT alone doesn't distinguish between well-behaved proteins and non-well-behaved proteins!
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the most sequence-diverse candidates were selected for experimental validation
Why did you select the most sequence-diverse candidates? I could be wrong, but if the goal is just to stabilize the proteins while maintaining their other biological functions wouldn't you want to minimize changes? Also curious how many candidates you considered per protein and how many met the criteria before you selected the candidates you moved forward with.
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