ASCC1 structures and bioinformatics reveal a novel helix-clasp-helix RNA-binding motif linked to a two-histidine phosphodiesterase

RNA sculpting by the primordial Helix-clasp-Helix-Strand-Loop (HcH-SL) motif enforces chemical recognition enabling diverse KH domain functions

In all domains of life, the ancient K homology (KH) domain superfamily is central to RNA processes including splicing, transcription, posttranscriptional gene regulation, signaling, and translation. Proteins with 1 to 15 KH domains bind single-strand (ss) RNA or DNA with base sequence specificity. Here, we examine over 40 KH domain experimental structures in complex with nucleic acid (NA) and define a novel Helix-clasp-Helix-Strand-Loop (HcH-SL) NA recognition motif binding 4 to 5 nucleotides using 10 to 18 residues. HcH-SL includes and extends the Gly-X-X-Gly (GXXG) signature sequence "clasp" that brings together two helices as an ∼90° helical corner. The first helix primarily provides side chain interactions to unstack and sculpt 2 to 3 bases on the 5' end for recognition of sequence and chemistry. The clasp and second helix amino dipole recognize a central phosphodiester. Following the helical corner, a beta strand and its loop extension recognize the two 3' nucleotides, primarily through main chain interactions. The HcH-SL structural motif forms a right-handed triangle and concave functional interface for NA interaction that unexpectedly splays four bound nucleotides into conformations matching RNA recognition motif (RRM) bound RNA structures. Evolutionary analyses and its ability to recognize base sequence and chemistry make HcH-SL a primordial NA binding motif distinguished by its binding mode from other NA structural recognition motifs: helix-turn-helix, helix-hairpin-helix, and beta strand RRM motifs. Combined results explain its vulnerability as a viral hijacking target and how mutations and expression defects lead to diverse diseases spanning cancer, cardiovascular, fragile X syndrome, neurodevelopmental disorders, and paraneoplastic disease.

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.