Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments

Опубликована: Янв. 31, 2025

Small molecule ligands exhibit a diverse range of conformations in solution. Upon binding to target protein, this conformational diversity is generally reduced. However, can retain some degree flexibility even when bound receptor. In the Protein Data Bank (PDB), small number have been modeled with distinct alternative that are supported by X-ray crystallography density maps. vast majority structural models fit single ligand conformation, potentially ignoring underlying heterogeneity present sample. We previously developed qFit-ligand sample and select parsimonious ensemble consistent density. While approach indicated many populate conformations, limitations our sampling procedures often resulted non-physical could not model complex like macrocycles. Here, we introduce several improvements qFit-ligand, including use routines within RDKit for stochastic sampling. This new method greatly enriches low energy molecules further extended identify PanDDA-modified maps from high throughput fragment screening experiments. The version improves electron reduces torsional strain relative deposited conformer previous qFit-ligand. These advances enhance analysis residual ligand-bound structures, which provide important insights rational design therapeutic agents.

Язык: Английский

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Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments

Опубликована: Янв. 31, 2025

Small molecule ligands exhibit a diverse range of conformations in solution. Upon binding to target protein, this conformational diversity is generally reduced. However, can retain some degree flexibility even when bound receptor. In the Protein Data Bank (PDB), small number have been modeled with distinct alternative that are supported by X-ray crystallography density maps. vast majority structural models fit single ligand conformation, potentially ignoring underlying heterogeneity present sample. We previously developed qFit-ligand sample and select parsimonious ensemble consistent density. While approach indicated many populate conformations, limitations our sampling procedures often resulted non-physical could not model complex like macrocycles. Here, we introduce several improvements qFit-ligand, including use routines within RDKit for stochastic sampling. This new method greatly enriches low energy molecules further extended identify PanDDA-modified maps from high throughput fragment screening experiments. The version improves electron reduces torsional strain relative deposited conformer previous qFit-ligand. These advances enhance analysis residual ligand-bound structures, which provide important insights rational design therapeutic agents.

Язык: Английский

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Enhanced RNA replication and pathogenesis in recent SARS-CoV-2 variants harboring the L260F mutation in NSP6

PLoS Pathogens, Год журнала: 2025, Номер 21(3), С. e1013020 - e1013020

Опубликована: Март 31, 2025

The COVID-19 pandemic has been driven by SARS-CoV-2 variants with enhanced transmission and immune escape. Apart from extensive evolution in the Spike protein, non-Spike mutations are accumulating across entire viral genome their functional impact is not well understood. To address contribution of these mutations, we reconstructed genomes recent Omicron disabled expression (replicons) to systematically compare RNA replication capabilities independently Spike. We also used a single reference replicon complemented it various variant proteins quantify entry single-round infection assays. Viral were negatively correlated, suggesting that as evolve reduced functions under growing pressure on Spike, increases compensatory mechanism. identified multiple replication. NSP6 emerged hotspot distinct L260F mutation arising BQ.1.1 XBB.1.16 variants. Using mutant revertant clones, was validated enhance cells increase pathogenesis mice. Notably, this host lipid droplet content NSP6. Collectively, systematic analysis defined NSP6’s key role provides insight into evolutionary trajectories possible therapeutic implications.

Язык: Английский

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Identifying novel chemical matter against the Chikungunya virus nsP3 macrodomain through crystallographic fragment screening

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 23, 2024

Abstract Chikungunya virus (CHIKV) causes severe fever, rash and debilitating joint pain that can last for months 1,2 or even years. Millions of people have been infected with CHIKV, mostly in low middle-income countries, the continues to spread into new areas due geographical expansion its mosquito hosts. Its genome encodes a macrodomain, which functions as an ADP-ribosyl hydrolase, removing ADPr from viral host-cell proteins interfering innate immune response. Mutational studies shown CHIKV nsP3 macrodomain is necessary replication, making it potential target development antiviral therapeutics. We, therefore, performed high-throughput crystallographic fragment screen against yielding 109 hits covering ADPr-binding site two adjacent subsites are absent homologous SARS-CoV-2 but may be present other alphaviruses, such Venezuelan equine encephalitis (VEEV) eastern (EEEV). Finally, subset overlapping fragments was used manually design three merges adenine oxyanion subsites. The rich dataset chemical matter structural information discovered this publicly available starting point developing inhibitor.

Язык: Английский

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Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 23, 2024

ABSTRACT Small molecule ligands exhibit a diverse range of conformations in solution. Upon binding to target protein, this conformational diversity is generally reduced. However, can retain some degree flexibility even when bound receptor. In the Protein Data Bank (PDB), small number have been modeled with distinct alternative that are supported by X-ray crystallography density maps. vast majority structural models fit single ligand conformation, potentially ignoring underlying heterogeneity present sample. We previously developed qFit-ligand sample and select parsimonious ensemble consistent density. While approach indicated many populate conformations, limitations our sampling procedures often resulted non-physical could not model complex like macrocycles. Here, we introduce several improvements qFit-ligand, including use routines within RDKit for stochastic sampling. This new method greatly enriches low energy molecules further extended identify PanDDA-modified maps from high throughput fragment screening experiments. The version improves electron reduces torsional strain relative deposited conformer previous qFit-ligand. These advances enhance analysis residual ligand-bound structures, which provide important insights rational design therapeutic agents.

Язык: Английский

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