Pathogen-sugar interactions revealed by universal saturation transfer analysis

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an "end-on" manner. uSTA-guided modeling and a high-resolution cryo-electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis

Integrative modelling of biomolecular complexes

In recent years the use of integrative, information-driven computational approaches for modelling the structure of biomolecules has been increasing in popularity. These are now recognised as a crucial complement to experimental structural biology techniques such as X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy and cryo-electron microscopy (cryo-EM). This trend can be credited to a few reasons such as the increased prominence of structures solved by cryo-EM, the improvements in proteomics approaches such as Crosslinking Mass Spectrometry (XL-MS), the drive to study systems of higher complexity in their native state and the maturation of many computational techniques combined with the wide-spread availability of information-driven integrative modelling platforms. In this review we highlight recent works that exemplify how the use of integrative and/or information-driven approaches and platforms can produce highly accurate structural models. These examples include systems which present many challenges when studied with traditional structural biology techniques such as flexible and dynamic macromolecular assemblies and membrane associated complexes. We also identify some key areas of interest for information-driven, integrative modelling and discuss how they relate to ongoing challenges in the fields of computational structural biology. These include the use of coarse-grained forcefields for biomolecular simulations – allowing for simulations across longer (time-) and bigger (size-dimension) scales –, the use of bioinformatics predictions to drive sampling and/or scoring in docking such as those derived from coevolution analysis, and finally the study of membrane and membrane-associated protein complexes

Integrative modelling of biomolecular complexes

In recent years the use of integrative, information-driven computational approaches for modelling the structure of biomolecules has been increasing in popularity. These are now recognised as a crucial complement to experimental structural biology techniques such as X-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy and cryo-electron microscopy (cryo-EM). This trend can be credited to a few reasons such as the increased prominence of structures solved by cryo-EM, the improvements in proteomics approaches such as Crosslinking Mass Spectrometry (XL-MS), the drive to study systems of higher complexity in their native state and the maturation of many computational techniques combined with the wide-spread availability of information-driven integrative modelling platforms. In this review we highlight recent works that exemplify how the use of integrative and/or information-driven approaches and platforms can produce highly accurate structural models. These examples include systems which present many challenges when studied with traditional structural biology techniques such as flexible and dynamic macromolecular assemblies and membrane associated complexes. We also identify some key areas of interest for information-driven, integrative modelling and discuss how they relate to ongoing challenges in the fields of computational structural biology. These include the use of coarse-grained forcefields for biomolecular simulations – allowing for simulations across longer (time-) and bigger (size-dimension) scales –, the use of bioinformatics predictions to drive sampling and/or scoring in docking such as those derived from coevolution analysis, and finally the study of membrane and membrane-associated protein complexes

A novel antifolate suppresses growth of FPGS-deficient cells and overcomes methotrexate resistance

Cancer cells make extensive use of the folate cycle to sustain increased anabolic metabolism. Multiple chemotherapeutic drugs interfere with the folate cycle, including methotrexate and 5-fluorouracil that are commonly applied for the treatment of leukemia and colorectal cancer (CRC), respectively. Despite high success rates, therapy-induced resistance causes relapse at later disease stages. Depletion of folylpolyglutamate synthetase (FPGS), which normally promotes intracellular accumulation and activity of natural folates and methotrexate, is linked to methotrexate and 5-fluorouracil resistance and its association with relapse illustrates the need for improved intervention strategies. Here, we describe a novel antifolate (C1) that, like methotrexate, potently inhibits dihydrofolate reductase and downstream one-carbon metabolism. Contrary to methotrexate, C1 displays optimal efficacy in FPGS-deficient contexts, due to decreased competition with intracellular folates for interaction with dihydrofolate reductase. We show that FPGS-deficient patient-derived CRC organoids display enhanced sensitivity to C1, whereas FPGS-high CRC organoids are more sensitive to methotrexate. Our results argue that polyglutamylation-independent antifolates can be applied to exert selective pressure on FPGS-deficient cells during chemotherapy, using a vulnerability created by polyglutamylation deficiency.NWO16083Molecular Physiolog