Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Drug discovery and computational evolutionary analysis.

Joanna D Holbrook1, Philippe Sanseau

  • 1GlaxoSmithKline, Molecular Discovery Research, Bioinformatics Analysis, Stevenage SG1 2NY, United Kingdom.

Drug Discovery Today
|October 16, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Evaluating transportability of in vitro cellular models to in vivo human phenotypes using gene perturbation data.

Nature communications·2025
Same author

Simultaneous sequencing of genetic and epigenetic bases in DNA.

Nature biotechnology·2023
Same author

Hydroxymethylation profile of cell-free DNA is a biomarker for early colorectal cancer.

Scientific reports·2022
Same author

Epigenome-wide association study of sarcopenia: findings from the Hertfordshire Sarcopenia Study (HSS).

Journal of cachexia, sarcopenia and muscle·2021
Same author

Human non-CpG methylation patterns display both tissue-specific and inter-individual differences suggestive of underlying function.

Epigenetics·2021
Same author

Maternal dysglycaemia, changes in the infant's epigenome modified with a diet and physical activity intervention in pregnancy: Secondary analysis of a randomised control trial.

PLoS medicine·2020
Same journal

Inorganic nanoparticles for diagnostics, drug delivery and therapy for solid tumors.

Drug discovery today·2026
Same journal

HDAC11 as a potential therapeutic target for Alzheimer's disease.

Drug discovery today·2026
Same journal

From biologics to small-molecule modulators: The evolving landscape of interleukin-targeted therapeutics.

Drug discovery today·2026
Same journal

Targeting the GLP-1 receptor pathways for dual management of obesity and depression.

Drug discovery today·2026
Same journal

Chemical intervention strategies targeting MYC for cancer therapy.

Drug discovery today·2026
Same journal

How many protein pairs can we chemically target?

Drug discovery today·2026
See all related articles

Drug discovery faces high attrition due to challenges translating animal model findings to humans. Evolutionary analysis of sequence data can improve understanding of species-specific differences, aiding drug development.

Area of Science:

  • Computational Biology
  • Drug Discovery
  • Evolutionary Medicine

Background:

  • Drug discovery is characterized by high attrition rates.
  • Translating pre-clinical findings from animal models to human clinical trials presents a significant challenge.
  • Diverse species data are utilized throughout the drug discovery process.

Purpose of the Study:

  • To explore the application of advanced computational evolutionary analysis in drug discovery.
  • To leverage increasing sequence information for systematic evolutionary approaches.
  • To enhance the understanding of inter-species experimental discrepancies.

Main Methods:

  • Utilizing advanced computational evolutionary analysis techniques.
  • Applying systematic evolutionary approaches to drug discovery targets and pathways.

Related Experiment Videos

  • Analyzing sequence information across different species.

    • Main Results:

    • Computational evolutionary analysis offers a systematic approach to drug discovery targets.
    • Increased availability of sequence data facilitates evolutionary studies.
    • These analyses can elucidate experimental differences between species.

    Conclusions:

    • Evolutionary analysis holds potential to improve the translation of pre-clinical findings.
    • Understanding species-specific differences can reduce attrition in drug discovery.
    • This approach can enhance the efficiency and success rate of developing new therapeutics.