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We describe the discovery and preclinical characterization of a potent and selective lysophosphatidic acid receptor 1 (LPAR1) antagonist with a direct-acting antifibrotic mechanism. 18a was initially identified as a potent non-carboxylic acid LPAR1 antagonist in an LPA-induced myocardin-related transcription factor A (MRTF-A) nuclear translocation assay. Modifications to the aromatic elements in the structure allowed for improvements in metabolic stability and the mitigation of GSH adduct formation, but in vitro to in vivo clearance disconnects were observed with several potent sulfonamides (e.g., 27b ) across preclinical species. Through modification of the sulfonamide, 42 ( GS-2278 ) emerged as a potent LPAR1 antagonist with a suitable in vitro profile and desirable pharmacokinetic properties for oral QD dosing. GS-2278 dose-dependently blocked LPA-induced histamine release and demonstrated efficacy in an interventional model of bleomycin-induced lung fibrosis. However, CNS-related toxicity was observed in dogs, and based on these findings, the clinical development of GS-2278 for IPF was halted.

Acute respiratory viral infections, such as pneumovirus and respiratory picornavirus infections, exacerbate disease in COPD and asthma patients. A research program targeting respiratory syncytial virus (RSV) led to the discovery of GS-7682 ( 1 ), a novel phosphoramidate prodrug of a 4'-CN-4-aza-7,9-dideazaadenosine C -nucleoside GS-646089 ( 2 ) with broad antiviral activity against RSV (EC 50 = 3-46 nM), human metapneumovirus (EC 50 = 210 nM), human rhinovirus (EC 50 = 54-61 nM), and enterovirus (EC 50 = 83-90 nM). Prodrug optimization for cellular potency and lung cell metabolism identified 5'-methyl [( S )-hydroxy(phenoxy)phosphoryl]-l-alaninate in combination with 2',3'-diisobutyrate promoieties as being optimal for high levels of intracellular triphosphate formation in vitro and in vivo . 1 demonstrated significant reductions of viral loads in the lower respiratory tract of RSV-infected African green monkeys when administered once daily via intratracheal nebulized aerosol. Together, these findings support additional evaluation of 1 and its analogues as potential therapeutics for pneumo- and picornaviruses.

Motivation: Noncoding RNAs (ncRNAs) express their functions by adopting molecular structures. Specifically, RNA secondary structures serve as a relatively stable intermediate step before tertiary structures, offering a reliable signature of molecular function. Consequently, within an RNA functional family, secondary structures are generally more evolutionarily conserved than sequences. Conversely, homologous RNA families grouped within an RNA clan share ancestors but typically exhibit structural differences. Inferring the evolution of RNA structures within RNA families and clans is crucial for gaining insights into functional adaptations over time and providing clues about the Ancient RNA World Hypothesis., Results: We introduce the median problem and the small parsimony problem for ncRNA families, where secondary structures are represented as leaf-labeled trees. We utilize the Robinson-Foulds (RF) tree distance, which corresponds to a specific edit distance between RNA trees, and a new metric called the Internal-Leafset (IL) distance. While the RF tree distance compares sets of leaves descending from internal nodes of two RNA trees, the IL distance compares the collection of leaf-children of internal nodes. The latter is better at capturing differences in structural elements of RNAs than the RF distance, which is more focused on base pairs. We also consider a more general tree edit distance that allows the mapping of base pairs that are not perfectly aligned. We study the theoretical complexity of the median problem and the small parsimony problem under the three distance metrics and various biologically relevant constraints, and we present polynomial-time maximum parsimony algorithms for solving some versions of the problems. Our algorithms are applied to ncRNA families from the RFAM database, illustrating their practical utility., Availability and Implementation: https://github.com/bmarchand/rna\_small\_parsimony., (© The Author(s) 2024. Published by Oxford University Press.)

Protease inhibitors (PIs) remain an important component of antiretroviral therapy for the treatment of HIV-1 infection due to their high genetic barrier to resistance development. Nevertheless, the two most commonly prescribed HIV PIs, atazanavir and darunavir, still require co-administration with a pharmacokinetic boosting agent to maintain sufficient drug plasma levels which can lead to undesirable drug-drug interactions. Herein, we describe GS-9770, a novel investigational non-peptidomimetic HIV PI with unboosted once-daily oral dosing potential due to improvements in its metabolic stability and its pharmacokinetic properties in preclinical animal species. This compound demonstrates potent inhibitory activity and high on-target selectivity for recombinant HIV-1 protease versus other aspartic proteases tested. In cell culture, GS-9770 inhibits Gag polyprotein cleavage and shows nanomolar anti-HIV-1 potency in primary human cells permissive to HIV-1 infection and against a broad range of HIV subtypes. GS-9770 demonstrates an improved resistance profile against a panel of patient-derived HIV-1 isolates with resistance to atazanavir and darunavir. In resistance selection experiments, GS-9770 prevented the emergence of breakthrough HIV-1 variants at all fixed drug concentrations tested and required multiple protease substitutions to enable outgrowth of virus exposed to escalating concentrations of GS-9770. This compound also remained fully active against viruses resistant to drugs from other antiviral classes and showed no in vitro antagonism when combined pairwise with drugs from other antiretroviral classes. Collectively, these preclinical data identify GS-9770 as a potent, non-peptidomimetic once-daily oral HIV PI with potential to overcome the persistent requirement for pharmacological boosting with this class of antiretroviral agents., Competing Interests: All authors were employed and compensated by Gilead Sciences and may be shareholders of the company.

Motivation: Many bioinformatics problems can be approached as optimization or controlled sampling tasks, and solved exactly and efficiently using Dynamic Programming (DP). However, such exact methods are typically tailored towards specific settings, complex to develop, and hard to implement and adapt to problem variations., Methods: We introduce the Infrared framework to overcome such hindrances for a large class of problems. Its underlying paradigm is tailored toward problems that can be declaratively formalized as sparse feature networks, a generalization of constraint networks. Classic Boolean constraints specify a search space, consisting of putative solutions whose evaluation is performed through a combination of features. Problems are then solved using generic cluster tree elimination algorithms over a tree decomposition of the feature network. Their overall complexities are linear on the number of variables, and only exponential in the treewidth of the feature network. For sparse feature networks, associated with low to moderate treewidths, these algorithms allow to find optimal solutions, or generate controlled samples, with practical empirical efficiency., Results: Implementing these methods, the Infrared software allows Python programmers to rapidly develop exact optimization and sampling applications based on a tree decomposition-based efficient processing. Instead of directly coding specialized algorithms, problems are declaratively modeled as sets of variables over finite domains, whose dependencies are captured by constraints and functions. Such models are then automatically solved by generic DP algorithms. To illustrate the applicability of Infrared in bioinformatics and guide new users, we model and discuss variants of bioinformatics applications. We provide reimplementations and extensions of methods for RNA design, RNA sequence-structure alignment, parsimony-driven inference of ancestral traits in phylogenetic trees/networks, and design of coding sequences. Moreover, we demonstrate multidimensional Boltzmann sampling. These applications of the framework-together with our novel results-underline the practical relevance of Infrared. Remarkably, the achieved complexities are typically equivalent to the ones of specialized algorithms and implementations., Availability: Infrared is available at https://amibio.gitlabpages.inria.fr/Infrared with extensive documentation, including various usage examples and API reference; it can be installed using Conda or from source., (© 2024. The Author(s).)

The Diaprepes root weevil (DRW), Diaprepes abbreviatus, is a broadly polyphagous invasive pest of agriculture in the southern United States and the Caribbean. Its genome was sequenced, assembled, and annotated to study genomic correlates of specialized plant-feeding and invasiveness and to facilitate the development of new methods for DRW control. The 1.69 Gb D. abbreviatus genome assembly was distributed across 653 contigs, with an N50 of 7.8 Mb and the largest contig of 62 Mb. Most of the genome was comprised of repetitive sequences, with 66.17% in transposable elements, 5.75% in macrosatellites, and 2.06% in microsatellites. Most expected orthologous genes were present and fully assembled, with 99.5% of BUSCO genes present and 1.5% duplicated. One hundred and nine contigs (27.19 Mb) were identified as putative fragments of the X and Y sex chromosomes, and homology assessment with other beetle X chromosomes indicated a possible sex chromosome turnover event. Genome annotation identified 18,412 genes, including 43 putative horizontally transferred (HT) loci. Notably, 258 genes were identified from gene families known to encode plant cell wall degrading enzymes and invertases, including carbohydrate esterases, polysaccharide lyases, and glycoside hydrolases (GH). GH genes were unusually numerous, with 239 putative genes representing 19 GH families. Interestingly, several other beetle species with large numbers of GH genes are (like D. abbreviatus) successful invasive pests of agriculture or forestry., (© The Author(s) 2023. Published by Oxford University Press on behalf of The American Genetic Association. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)