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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

132
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...
132
Stability of Substituted Cyclohexanes02:30

Stability of Substituted Cyclohexanes

13.7K
This lesson discusses the stability of substituted cyclohexanes with a focus on energies of various conformers and the effect of 1,3-diaxial interactions.
The two chair conformations of cyclohexanes undergo rapid interconversion at room temperature. Both forms have identical energies and stabilities, each comprising equal amounts of the equilibrium mixture. Replacing a hydrogen atom with a functional group makes the two conformations energetically non-equivalent.
For example, in...
13.7K
Structures of Carboxylic Acid Derivatives01:28

Structures of Carboxylic Acid Derivatives

3.1K
Structure of Carboxylic Acid Derivatives
Carboxylic acid derivatives contain an acyl group attached to a heteroatom such as chlorine, oxygen, or nitrogen. The carbonyl carbon and oxygen are both sp2-hybridized with an unhybridized p orbital.
The three sp2 orbitals of the carbonyl carbon form three σ bonds, one each with the carbonyl oxygen, the α carbon, and the heteroatom, whereas the other two sp2 orbitals of the carbonyl oxygen are occupied by the lone pairs. Further, the...
3.1K
Combinatorial Gene Control02:33

Combinatorial Gene Control

8.7K
Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
8.7K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.7K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
11.7K
Structure of Conjugated Dienes01:16

Structure of Conjugated Dienes

6.1K
Introduction
Conjugated dienes are compounds characterized by the presence of alternating double and single bonds. In a conjugated system like 1,3-butadiene, the unhybridized 2p orbital on each carbon overlaps continuously, allowing the π electrons to be delocalized across the entire molecule. In contrast, this type of overlap does not occur in cumulated and isolated dienes, such as 2,3-pentadiene and 1,4-pentadiene, respectively. Instead, the π electrons remain localized between the double...
6.1K

You might also read

Related Articles

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

Sort by
Same author

PegaPlus─Interactive Machine Learning by Human Observation for Efficient Clustering and Analysis of Structure-Activity Data.

Journal of chemical information and modeling·2026
Same author

Enabling Automatic Generation of Protein-Ligand Complex Data Sets with Atomistic Detail.

Journal of chemical information and modeling·2026
Same author

Guiding Similarity Search in Chemical Fragment Spaces with Weighted Fingerprints.

Journal of chemical information and modeling·2026
Same author

ActivityFinder: Toward the Fully Automatic Integration of Structural and Binding Affinity Data.

Journal of chemical information and modeling·2026
Same author

A Benchmark Set of Bioactive Molecules for Diversity Analysis of Compound Libraries and Combinatorial Chemical Spaces.

Journal of chemical information and modeling·2025
Same author

A bottom-up approach to find lead compounds in expansive chemical spaces.

Communications chemistry·2025

Related Experiment Video

Updated: Oct 21, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.8K

Maximum Common Substructure Searching in Combinatorial Make-on-Demand Compound Spaces.

Robert Schmidt1, Raphael Klein2, Matthias Rarey1

  • 1Universität Hamburg, ZBH-Center for Bioinformatics, Bundesstraße 43, 20146 Hamburg, Germany.

Journal of Chemical Information and Modeling
|September 3, 2021
PubMed
Summary
This summary is machine-generated.

We developed SpaceMACS for precise chemical searches in large compound libraries. This tool enables efficient maximum common induced substructure (MCIS) searches, aiding drug discovery by finding available analogs quickly.

More Related Videos

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis
09:56

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis

Published on: September 6, 2019

7.0K
Synthesis of a Water-soluble Metal–Organic Complex Array
06:40

Synthesis of a Water-soluble Metal–Organic Complex Array

Published on: October 8, 2016

10.2K

Related Experiment Videos

Last Updated: Oct 21, 2025

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids
08:21

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

2.8K
Hierarchical and Programmable One-Pot Oligosaccharide Synthesis
09:56

Hierarchical and Programmable One-Pot Oligosaccharide Synthesis

Published on: September 6, 2019

7.0K
Synthesis of a Water-soluble Metal–Organic Complex Array
06:40

Synthesis of a Water-soluble Metal–Organic Complex Array

Published on: October 8, 2016

10.2K

Area of Science:

  • Computational Chemistry
  • Medicinal Chemistry
  • Drug Discovery

Background:

  • Commercial make-on-demand compound spaces are increasingly popular for drug discovery.
  • Existing search technologies like FTrees-FS and SpaceLight are limited in precise atomic-level structural feature searches.
  • There is a need for methods that can perform detailed substructure searches within large chemical fragment spaces.

Purpose of the Study:

  • To develop a novel method, SpaceMACS, for efficient and precise maximum common induced substructure (MCIS) similarity and substructure searches.
  • To enable the identification of specific structural features, even those spanning fragment borders, within large chemical spaces.
  • To provide access to the closest chemically available analogs for rational drug discovery from various compound sources.

Main Methods:

  • SpaceMACS extracts query substructures and matches them against fragments within the chemical space.
  • Partial results are combined to form complete compounds, enabling substructure identification across fragment boundaries.
  • The method was applied to three commercial fragment spaces, searching for analogs similar to a known glucosyltransferase binder.

Main Results:

  • SpaceMACS successfully identified almost all building blocks for known analogs and numerous additional compounds.
  • The tool demonstrated efficiency, finding structurally closest analogs within seconds to minutes.
  • It enables precise substructure searches that were previously not feasible in large combinatorial catalogs.

Conclusions:

  • SpaceMACS is a crucial tool for rational drug discovery, bridging the gap between compound design and commercially available analogs.
  • It significantly enhances the utility of make-on-demand combinatorial catalogs by allowing detailed structural queries.
  • The method provides rapid access to relevant chemical analogs, regardless of their origin (de novo design, AI generation, or manual drawing).