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 Concept Videos

Statgraphics01:10

Statgraphics

119
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
119
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

139
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
139
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
45
Fast Fourier Transform01:10

Fast Fourier Transform

286
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
286
Introduction to R01:11

Introduction to R

257
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
257
Manipulation and Analysis01:21

Manipulation and Analysis

22
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
22

You might also read

Related Articles

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

Sort by
Same author

DiffDock-Glide: A Hybrid Physics-Based and Data-Driven Approach to Molecular Docking.

Journal of chemical information and modeling·2026
Same author

Glide WS: Methodology and Initial Assessment of Performance for Docking Accuracy and Virtual Screening.

Journal of chemical theory and computation·2025
Same author

Design and synthesis of a chemically diverse, lead-like DNA-encoded library from sequential amide coupling.

RSC medicinal chemistry·2025
Same author

Harnessing Medicinal Chemical Intuition from Collective Intelligence.

Journal of medicinal chemistry·2025
Same author

Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN.

Nature communications·2024
Same author

Discovery of Clinical Candidate GLPG3970: A Potent and Selective Dual SIK2/SIK3 Inhibitor for the Treatment of Autoimmune and Inflammatory Diseases.

Journal of medicinal chemistry·2024
Same journal

Development of APH003─a Highly Potent, Selective, and Orally Bioavailable IRAK4 PROTAC Degrader for the Treatment of Inflammatory Diseases.

Journal of medicinal chemistry·2026
Same journal

Recent Advances in Targeting RNA Splicing Factors with Small Molecules.

Journal of medicinal chemistry·2026
Same journal

Structure-Guided Optimization of α-Conotoxins Yields Potent and Selective Inhibitors of the Human α6β4 nAChR for Nicotine Addiction.

Journal of medicinal chemistry·2026
Same journal

Antibody-Assisted Protection from Paraoxon and Nerve Agent Model Compounds.

Journal of medicinal chemistry·2026
Same journal

Photocage Prodrug Coupled with Injectable Hydrogel for Self-Amplified Photochemotherapy.

Journal of medicinal chemistry·2026
Same journal

GPX4-Targeting Phenolato Zr<sup>IV</sup> Complexes Induce Ferroptosis and Lysosome-Dependent Cell Death for Immunotherapy of Chemoresistant Cancer.

Journal of medicinal chemistry·2026
See all related articles

Related Experiment Video

Updated: Jun 13, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

500

Computational Hit Finding: An Industry Perspective.

Paraskevi Gkeka1, Fredrik Svensson2, Carlos Roca Magadán3

  • 1Integrated Drug Discovery, Molecular Design Sciences, Sanofi, Vitry-sur-Seine 91380, France.

Journal of Medicinal Chemistry
|May 20, 2025
PubMed
Summary
This summary is machine-generated.

Computational hit finding, including virtual screening, is rapidly evolving. New technologies like ultralarge libraries and AI are transforming drug discovery workflows, offering more efficient and cost-effective approaches.

More Related Videos

Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.1K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.8K

Related Experiment Videos

Last Updated: Jun 13, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

500
Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.1K
Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

12.8K

Area of Science:

  • Drug Discovery
  • Computational Chemistry

Background:

  • Virtual screening is a key computational method in drug discovery, complementing experimental approaches.
  • Innovation in virtual screening had slowed due to mature technologies and limited library sizes.
  • Recent advancements in computing power and AI are driving significant changes in the field.

Purpose of the Study:

  • To provide a guide from industry experts on the evolving landscape of computational hit finding.
  • To offer practical recommendations for developing effective virtual screening workflows.
  • To discuss strategies for risk mitigation, success criteria, and emerging technologies in drug discovery.

Main Methods:

  • Summarizing key aspects of the changing computational hit finding landscape.
  • Providing practical recommendations for building end-to-end screening workflows.
  • Discussing strategies for risk mitigation and defining success criteria.

Main Results:

  • The field of computational hit finding is undergoing a major transformation.
  • Emerging technologies like ultralarge virtual libraries and AI are enhancing screening capabilities.
  • Industry practitioners offer insights into optimizing workflows and navigating challenges.

Conclusions:

  • The integration of advanced computational tools is revolutionizing drug discovery pipelines.
  • Strategic implementation of new technologies can improve the efficiency and success of hit finding.
  • Continuous adaptation to emerging technologies is crucial for future drug discovery efforts.