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Helicases are essential motor enzymes that couple nucleoside-triphosphate hydrolysis with DNA or RNA strand unwinding. Helicases are integral to replication, transcription, splicing, and translation of the genome, play crucial roles in the proliferation of cancer cells and propagation of viral pathogens, and are implicated in neurodegenerative diseases. Despite their therapeutic potential, drug discovery efforts targeting helicases face significant challenges due to their dynamic enzymatic cycles, the transient nature of their conformational states, and the conservation of their active sites. Analysis of cocrystal structures of inhibitor-helicase complexes revealed four distinct mechanisms of inhibition: allosteric, ATP-competitive, RNA-competitive, and interfacial inhibitors. While these static X-ray structures reveal potential binding pockets that may support the development of selective drugs, the application of advanced techniques such as cryo-EM, single-molecule analysis, and computational modeling will be essential for understanding helicase dynamics and designing effective inhibitors.

Computational tools for structure-based drug design (SBDD) are widely used in drug discovery and can provide valuable insights to advance projects in an efficient and cost-effective manner. However, despite the importance of SBDD to the field, the underlying methodologies and techniques have many limitations. In particular, binding pose and activity predictions (P-AP) are still not consistently reliable. We strongly believe that a limiting factor is the lack of a widely accepted and established community benchmarking process that independently assesses the performance and drives the development of methods, similar to the CASP benchmarking challenge for protein structure prediction. Here, we provide an overview of P-AP, unblinded benchmarking data sets, and blinded benchmarking initiatives (concluded and ongoing) and offer a perspective on learnings and the future of the field. To accelerate a breakthrough on the development of novel P-AP methods, it is necessary for the community to establish and support a long-term benchmark challenge that provides nonbiased training/test/validation sets, a systematic independent validation, and a forum for scientific discussions.

Conflicting health messages negatively impact trust. Breast cancer screening (BCS) is one area of healthcare where conflicting messages are common. We examined whether women's healthcare system trust was impacted after exposure to information about harms and benefits of BCS. We enrolled 497 women into this study. Participants were administered a decision aid (DA) containing information about the harms and benefits of BCS and reported their healthcare system trust pre- and post-DA exposure. We observed a significant decrease in healthcare system trust from pre- to post-DA. This decrease in trust was associated with participants' perception that the message conflicted with their previously held beliefs and not the reactions it elicited. When people receive information about BCS that conflicts with past health messages, they may lose trust in the healthcare system. This underscores the importance of adopting consistent messages about BCS., Competing Interests: Declaration of conflicting interestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Target class-focused drug discovery has a strong track record in pharmaceutical research, yet public domain data indicate that many members of protein families remain unliganded. Here we present a systematic approach to scale up the discovery and characterization of small molecule ligands for the WD40 repeat (WDR) protein family. We developed a comprehensive suite of protocols for protein production, crystallography, and biophysical, biochemical, and cellular assays. A pilot hit-finding campaign using DNA-encoded chemical library selection followed by machine learning (DEL-ML) to predict ligands from virtual libraries yielded first-in-class, drug-like ligands for 7 of the 16 WDR domains screened, thus demonstrating the broader ligandability of WDRs. This study establishes a template for evaluation of protein family wide ligandability and provides an extensive resource of WDR protein biochemical and chemical tools, knowledge, and protocols to discover potential therapeutics for this highly disease-relevant, but underexplored target class.

We report an enantioselective protein affinity selection mass spectrometry screening approach (EAS-MS) that enables the detection of weak binders, informs about selectivity, and generates orthogonal confirmation of binding. After method development with control proteins, we screened 31 human proteins against a designed library of 8,210 chiral compounds. 16 binders to 12 targets, including many proteins predicted to be "challenging to ligand", were discovered and confirmed in orthogonal assays. 7 binders to 6 targets bound in an enantioselective manner, with K D s ranging from 3 to 20 μM. Binders for four targets (DDB1, WDR91, WDR55, and HAT1) were selected for in-depth characterization using X-ray crystallography. In all four cases, the mechanism for enantioselective selectivity was readily explained. EAS-MS can be used to identify and characterize selective and weakly-binding ligands for novel protein targets with unprecedented throughput and sensitivity., Competing Interests: COMPETING INTERESTS The authors declare no competing interests.

Critical Assessment of Computational Hit-Finding Experiments (CACHE) Challenges emerged as real-life stress tests for computational hit-finding strategies. In CACHE Challenge #1, 23 participants contributed their original workflows to identify small-molecule ligands for the WD40 repeat (WDR) of LRRK2, a promising Parkinson's target. We applied the FRASE-based hit-finding robot (FRASE-bot), a platform for interaction-based screening allowing a drastic reduction of the explorable chemical space and a concurrent detection of putative ligand-binding sites. In two screening rounds, 84 compounds were procured for experimental testing and 8 were confirmed to bind LRRK2-WDR with dissociation constants ( K d ) ranging from 3 to 41 μM. To investigate the functional effect of WDR ligands, they were tested for their ability to modify the LRRK2 activity markers in HEK293T cells. Two compounds showed statistically significant increases in the kinase activity of WT LRRK2, and two compounds affected the conformation and kinase activity of major LRRK2 mutants., Competing Interests: The authors declare no competing interests., (This journal is © The Royal Society of Chemistry.)