Dataset Information

In situ crystal data-collection and ligand-screening system at SPring-8.

ABSTRACT: In situ diffraction data collection using crystallization plates has been utilized for macromolecules to evaluate crystal quality without requiring additional sample treatment such as cryocooling. Although it is difficult to collect complete data sets using this technique due to the mechanical limitation of crystal rotation, recent advances in methods for data collection from multiple crystals have overcome this issue. At SPring-8, an in situ diffraction measurement system was constructed consisting of a goniometer for a plate, an articulated robot and plate storage. Using this system, complete data sets were obtained utilizing the small-wedge measurement method. Combining this system with an acoustic liquid handler to prepare protein-ligand complex crystals by applying fragment compounds to trypsin crystals for in situ soaking, binding was confirmed for seven out of eight compounds. These results show that the system functioned properly to collect complete data for structural analysis and to expand the capability for ligand screening in combination with a liquid dispenser.

SUBMITTER: Okumura H

PROVIDER: S-EPMC9158660 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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In situ crystal data-collection and ligand-screening system at SPring-8.

Okumura Hideo H Sakai Naoki N Murakami Hironori H Mizuno Nobuhiro N Nakamura Yuki Y Ueno Go G Masunaga Takuya T Kawamura Takashi T Baba Seiki S Hasegawa Kazuya K Yamamoto Masaki M Kumasaka Takashi T

Acta crystallographica. Section F, Structural biology communications 20220527 Pt 6

In situ diffraction data collection using crystallization plates has been utilized for macromolecules to evaluate crystal quality without requiring additional sample treatment such as cryocooling. Although it is difficult to collect complete data sets using this technique due to the mechanical limitation of crystal rotation, recent advances in methods for data collection from multiple crystals have overcome this issue. At SPring-8, an in situ diffraction measurement system was constructed consis ...[more]

PMID: 35647681

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Project description:BackgroundThe American Society for Clinical Oncology recently launched the minimal common oncology data elements project to facilitate cancer data interoperability. However, clinical data are often unrecorded in an organized way, and converting them into a structured format can be time-consuming. Clinical Data Warehouse (CDW) is a database that consolidates data from different clinical sources. However, the clinical data extracted from this database include not only structured data but also natural language generated during clinical practice. Therefore, applying these data to a clinical study is challenging because they are unstructured, and unformatted to allow essential content to be found. This study determined how best to organize a huge amount of clinical data to evaluate the upper aerodigestive tract cancers' clinical features and outcomes, including cancer of the head and neck, esophagus, lung, thymus, and mesothelioma.MethodsThe Real-time autOmatically updated data warehOuse in healThcare (ROOT) uses six main regions to describe the journey of cancer patients. This study, developed an algorithm optimized for each disease category using natural language processing of unstructured data and data capture of structured data. Data from patients diagnosed at the Samsung Medical Center from 2008-2020 were used.ResultsComprehensive clinical data for 67,617 patients across six tumor types: 28,954 with non-small-cell lung cancer, 2,540 with small-cell lung cancer, 30,035 with head and neck cancer, 4,950 with esophageal cancer, 966 with thymic cancer, and 172 with mesothelioma were collected. Additionally, the results of a longitudinal molecular study, including epidermal growth factor receptor (EGFR) mutations, anaplastic lymphoma kinase (ALK) tests, and next-generation sequencing (NGS), were included. Scattered information was integrated and automatically built up to match the cohort, allowing users to capture the most updated test results and treatment outcomes.ConclusionsThis landmark study documented the successful construction of a real-time updating system for medical big data, based on the CDW program.

Dataset Information

In situ crystal data-collection and ligand-screening system at SPring-8.

Publications

In situ crystal data-collection and ligand-screening system at SPring-8.

Similar Datasets

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