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Related Concept Videos

Drug Discovery: Overview01:26

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Bioavailability is a critical factor in determining a drug's effectiveness. It refers to the proportion of a drug that enters the circulation when introduced into the body and is, as a result, able to have an active effect. Enhancing bioavailability is essential for drugs with poor solubility, as it can significantly impact their therapeutic efficacy. Various methods are employed to increase the solubility of drugs, thereby enhancing their bioavailability.Micronization and nanonization are...
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Drugs target macromolecules to modify ongoing cellular processes. Primary drug targets include receptors, ion channels, transporters, and enzymes.
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Related Experiment Video

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Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
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Structure-Based Drug Discovery Accelerated by Many-Core Devices.

Wei Feinstein, Michal Brylinski1

  • 1Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.

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Summary
This summary is machine-generated.

Modern drug discovery leverages computational approaches and genomic data. Heterogeneous systems with parallel accelerators like Intel Xeon Phi significantly speed up drug development by enhancing computational power for complex data processing.

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Area of Science:

  • Computational chemistry and bioinformatics
  • Genomic data analysis
  • High-performance computing in pharmaceutical research

Background:

  • Drug discovery increasingly relies on computational methods and vast genomic data.
  • Large-scale data processing necessitates advanced computing resources.
  • Heterogeneous systems offer petaflops of performance for scientific acceleration.

Purpose of the Study:

  • To review modern parallel accelerator architectures, focusing on Intel Xeon Phi.
  • To discuss parallel programming frameworks for many-core devices.
  • To demonstrate the acceleration of drug discovery algorithms using heterogeneous systems.

Main Methods:

  • Review of Intel Xeon Phi many-core architecture.
  • Discussion of parallel programming frameworks (OpenMP, OpenCL, MPI, HPX).
  • Analysis of code development for heterogeneous implementations.

Main Results:

  • Intel Xeon Phi offers massively parallel capabilities.
  • Heterogeneous implementations show advantages over serial computing.
  • Algorithms like eFindSite, BUDE, and biomolecular simulation force fields are accelerated.

Conclusions:

  • Heterogeneous systems with parallel accelerators are crucial for modern drug discovery.
  • Intel Xeon Phi and associated programming frameworks enable efficient processing of large datasets.
  • Accelerated algorithms significantly enhance hit identification, lead selection, and virtual screening.