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Raval, S.

Publications and source records attributed to Raval, S..

3 recordsLinked to original sources

Seed-Guided De Novo Design Expands the Structural Diversity of Antitoxin Protein Binders

De novo design of protein binders targeting extended, multi-site interaction surfaces remains difficult for current generative methods, which often produce limited structural diversity and predominantly helical topologies. Here, we advance diffusion-based binder design by guiding protein backbone generation through "seeds," which are PDB-derived fragments selected for geometric complementarity to the target surface. To test this approach, we computationally generated seed-guided binders of the bacterial toxin RelE. RelB, the native antitoxin of RelE, engages two distinct interfaces with high surface complementarity, making it an appropriate test case. Seed-guided RFdiffusion produced backbones with substantially higher structural diversity and more target contacts than RFdiffusion alone. Experimental screening of 1,402 designs in a high-throughput bacterial survival assay identified multiple functional binders, including variants with nanomolar to low-micromolar affinity and one design with RelE neutralization comparable to RelBpep. Computational structure prediction and mutational analyses support that the designed interfaces rely on seed-derived contacts and adopt binding modes distinct from RelB. Molecular dynamics simulations and hydrogen-deuterium exchange experiments further suggest that one high-affinity design undergoes a conformational change upon binding. Notably, successful designs exhibited reduced cross-reactivity to RelE orthologs compared with RelBpep, suggesting that the extensive interfaces generated through seed-guided design can enable enhanced selectivity. These results establish motif scaffolding of surface-complementing seeds as an effective strategy for overcoming current limitations of de novo generative models, enabling the design of proteins that can engage challenging interface sites.

bioengineering↗

Genetic landscape of DNMT3A R882H reveals mechanism of aberrant oligomerization

DNA methyltransferase 3A (DNMT3A) is a de novo DNA methyltransferase that is recurrently mutated in hematological malignancies and developmental disorders. The most prevalent mutation, R882H, compromises DNMT3A activity in a dominant-negative manner, but its precise biochemical mechanism has been debated. Here, we use paired deep mutational scanning of the wild-type and R882H-mutant proteins to systematically identify mutations on a massively parallel scale that modify DNMT3A activity by suppressing, phenocopying, or selectively rescuing the dominant-negative effect of R882H. By leveraging the mutational depth and unbiased nature of the paired genetic landscapes, we uncover two distinct mechanisms that can rescue DNMT3AR882H activity, providing novel insights into the function of the R882 hotspot. First, by analyzing the effects of combinatorial mutations in the target recognition domain (TRD), we reveal that its crosstalk with the ADD regulatory domain modulates DNMT3A DNA binding and enzymatic activity, partially compensating for R882H-induced loss-of-function. Second, pairwise analysis of variant effects across the two genetic backgrounds supports the notion that R882H promotes aberrant macro-oligomerization of DNMT3A via its central dimerization interface, which accounts for its dominant-negative effect. Critically, we show that the R882 position exhibits a distinct dominant-negative signature in the genetic landscape, where positively charged residues at this position safeguard against aberrant macro-oligomerization. By performing hydrogen-deuterium exchange mass spectrometry (HDX-MS) on DNMT3A mutants, we show that R882H dramatically alters the protein dynamics of DNMT3A, rigidifying its central dimerization interface to promote oligomerization. Our data support a new model in which R882H removes the critical function of R882, where the arginine attenuates the pre-organization of the interface and subsequent oligomerization at a supramolecular assembly hotspot1. Altogether, we map the genetic landscape underpinning the DNMT3AR882H hotspot mutation, illuminating the unexpected molecular mechanism of macro-oligomerization that drives its dominant-negative effect.

biochemistry↗

Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology

We developed a hydrogen/deuterium exchange workflow coupled to tandem mass spectrometry (HX-MS2) that supports the acquisition of peptide fragment ions alongside their peptide precursors. The approach enables true auto-validation of HX data by mining a rich set of deuterated fragments, generated by collisional-induced dissociation (CID), to simultaneously confirm the peptide ID and authenticate MS1-based deuteration calculations. The high redundancy provided by the fragments supports a confidence assessment of deuterium calculations using a combinatorial strategy. The approach requires data-independent acquisition (DIA) methods that are available on most MS platforms, making the switch to HX-MS2 straightforward. Importantly, we find that HX-DIA enables a proteomics-grade approach and wide-spread applications. Considerable time is saved through auto-validation and complex samples can now be characterized and at higher throughput. We illustrate these advantages in a drug binding analysis of the ultra-large protein kinase DNA-PKcs, isolated directly from mammalian cells.

biochemistry↗