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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Data are individual items of information obtained from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random...
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Virtual Work01:20

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Virtual work is a powerful method used to solve problems involving several connected rigid bodies. When the system is in equilibrium, virtual work is zero. This allows the calculation of the resulting forces when a system undergoes a virtual displacement. When attempting to analyze such a system, first, use a free-body diagram, where an independent coordinate represents the configuration of the links, and mark its deflected position resulting from the positive virtual displacement.
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Genetic Screens02:46

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Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
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G-quadruplex virtual drug screening: A review.

Robert C Monsen1, John O Trent2

  • 1Department of Biochemistry and Molecular Biology, University of Louisville, Louisville, KY, 40206, USA.

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Summary
This summary is machine-generated.

G-quadruplexes are crucial in biological processes and cancer. This review covers a decade of virtual drug discovery for G-quadruplexes, offering best practices for future campaigns.

Keywords:
DockingDrug discoveryG-quadruplexVirtual screening

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Area of Science:

  • Biochemistry and Bioinformatics
  • Drug Discovery and Medicinal Chemistry

Background:

  • G-quadruplexes (G4s) are increasingly recognized as key regulators of biological processes, including DNA replication, transcription, and splicing.
  • Their structural diversity and prevalence in cancer-associated gene promoters make them attractive targets for therapeutic intervention.
  • Existing atomic structures of DNA and RNA G-quadruplexes facilitate computational drug design.

Purpose of the Study:

  • To review virtual drug discovery approaches for G-quadruplexes over the past decade.
  • To introduce effective virtual screening platforms for G4 ligand identification.
  • To provide best practices for future G-quadruplex virtual screening (G4 VS) campaigns.

Main Methods:

  • Literature review of G-quadruplex virtual drug discovery campaigns.
  • Identification and categorization of relevant in silico screening platforms.
  • Analysis of successful and unsuccessful G4 VS strategies.

Main Results:

  • The past decade has seen significant advancements in computational methods for G-quadruplex drug discovery.
  • Various virtual screening platforms have been developed and applied to identify novel G4 stabilizing ligands.
  • Key structural features and screening parameters influencing campaign success have been identified.

Conclusions:

  • Virtual drug discovery is a powerful and evolving strategy for developing G-quadruplex-targeting therapeutics.
  • Standardized best practices are essential for optimizing future G4 VS campaigns and accelerating the discovery of novel drug candidates.
  • Continued integration of structural biology and computational chemistry will drive innovation in G-quadruplex-based drug development.