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Related Concept Videos

Cryo-electron Microscopy01:28

Cryo-electron Microscopy

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Conventional electron microscopy (EM) involves dehydration, fixation, and staining of biological samples, which distorts the native state of biological molecules and results in several artifacts. Also, the high-energy electron beam damages the sample and makes it difficult to obtain high-resolution images. These issues can be addressed using cryo-EM, which uses frozen samples and gentler electron beams. The technique was developed by Jacques Dubochet, Joachim Frank, and Richard Henderson, for...
3.3K

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Optimizing Sample Preparation for Cryogenic Electron Microscopy
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GoToCloud optimization of cloud computing environment for accelerating cryo-EM structure-based drug design.

Toshio Moriya1, Yusuke Yamada2,3, Misato Yamamoto2

  • 1Structural Biology Research Center, Photon Factory, Institute of Materials Structure Science, High Energy Accelerator Research Organization (KEK), Tsukuba, Japan. toshio.moriya@kek.jp.

Communications Biology
|October 14, 2024
PubMed
Summary
This summary is machine-generated.

GoToCloud is a new cloud platform that accelerates Cryo-EM data analysis for drug design. It optimizes computing resources, reducing costs and processing time for structure-based drug design (SBDD).

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Area of Science:

  • Biophysics
  • Structural Biology
  • Computational Biology

Background:

  • Cryogenic electron microscopy (Cryo-EM) provides atomic-resolution 3D structures essential for structure-based drug design (SBDD).
  • Current Cryo-EM data analysis is a bottleneck, limiting throughput for SBDD due to rapid technological advancements.
  • Achieving sufficient throughput for SBDD remains a challenge in Cryo-EM research.

Purpose of the Study:

  • To introduce GoToCloud, a cloud-computing platform designed for advanced Cryo-EM data analysis and management.
  • To demonstrate how GoToCloud can optimize computing resources and reduce costs in Cryo-EM workflows.
  • To highlight the potential of GoToCloud in accelerating SBDD using Cryo-EM data.

Main Methods:

  • Development of GoToCloud, a cloud-based platform for Cryo-EM data analysis.
  • Implementation of resource optimization by selecting appropriate parallel processing settings for each step.
  • Conducting benchmark tests to evaluate the impact of computing hardware and target resolution on performance.

Main Results:

  • GoToCloud enables optimization of computing resources and cost reduction through tailored parallel processing.
  • Benchmark tests confirmed that parallel computing settings significantly impact processing time and cost-effectiveness.
  • The choice of computational hardware and desired resolution critically influence Cryo-EM data processing efficiency.

Conclusions:

  • GoToCloud offers a promising solution for accelerating Cryo-EM data analysis and SBDD.
  • Optimizing cloud computing environments is crucial for enhancing the efficiency of Cryo-EM workflows.
  • The platform facilitates cost-effective and time-efficient structure determination for drug discovery.