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

Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Predicting Reaction Outcomes02:24

Predicting Reaction Outcomes

Kinetics describes the rate and path by which a reaction occurs. In contrast, thermodynamics deals with state functions and describes the properties, behavior, and components of a system. It is not concerned with the path taken by the process and cannot address the rate at which a reaction occurs. Although it does provide information about what can happen during a reaction process, it does not describe the detailed steps of what appears on an atomic or a molecular level. On the other hand,...
Predicting Products: Substitution vs. Elimination02:52

Predicting Products: Substitution vs. Elimination

When a nucleophile and an alkyl halide react, nucleophilic substitution and β-elimination reactions compete to generate products.
The following factors can influence the mechanisms competing against each other:
Predicting Molecular Geometry02:27

Predicting Molecular Geometry

VSEPR Theory for Determination of Electron Pair Geometries
Predicting Products: SN1 vs. SN202:27

Predicting Products: SN1 vs. SN2

Nucleophilic substitution reactions of alkyl halides can proceed via an SN1 or an SN2 mechanism. While in SN2 reactions, the nucleophile attacks the substrate simultaneously as the leaving group departs, in SN1 reactions, the substrate first dissociates to give the carbocation intermediate. Various factors such as the structure of the substrate, the strength of the nucleophile, and the nature of the solvent promote one mechanism over the other.
With increased substitution on the alkyl halide,...

You might also read

Related Articles

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

Sort by
Same author

The Binding of Protein l-Isoaspartyl Methyltransferase (PIMT) to Tubulin and Disruption of Microtubule Assembly Leading to Tumor Regression.

Biochemistry·2025
Same author

Abundance of Glycine-mediated O···C=O, N-H···N, and C<sup>α</sup>-H···O Interactions in Homo- and Hetero-oligomeric Protein Complexes.

Biochemistry·2025
Same author

On the abundance and importance of AXXXA sequence motifs in globular proteins and their involvement in C<sub>β</sub>C<sub>β</sub> interaction.

Journal of structural biology·2024
Same author

Adenosine dialdehyde, a methyltransferase inhibitor, induces colorectal cancer cells apoptosis by regulating PIMT:p53 interaction.

Biochemical and biophysical research communications·2023
Same author

On the pathway of the formation of secondary structures in proteins.

Proteins·2023
Same author

The Role of Protein-<i>L</i>-isoaspartyl Methyltransferase (PIMT) in the Suppression of Toxicity of the Oligomeric Form of Aβ42, in Addition to the Inhibition of Its Fibrillization.

ACS chemical neuroscience·2023

Related Experiment Video

Updated: Jun 6, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Prediction of active site cleft using support vector machines.

Shrihari Sonavane1, Pinak Chakrabarti

  • 1Department of Biochemistry and Bioinformatics Centre, Bose Institute, P-1/12 CIT Scheme VIIM, Kolkata 700 054, India.

Journal of Chemical Information and Modeling
|November 18, 2010
PubMed
Summary

This study introduces a new computational method to accurately identify and rank protein binding sites. The approach enhances prediction accuracy for catalytic sites, improving drug discovery potential.

More Related Videos

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine
08:27

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Jun 6, 2026

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions
06:50

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Published on: January 26, 2024

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine
08:27

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Area of Science:

  • Computational biology
  • Structural bioinformatics
  • Protein structure analysis

Background:

  • Existing computational tools detect protein clefts but require improved ranking and catalytic site prediction accuracy.
  • Accurate identification of protein binding and catalytic sites is crucial for drug design and understanding protein function.

Purpose of the Study:

  • To develop and validate an improved computational method for recognizing and ranking active site clefts in protein 3D structures.
  • To enhance the accuracy of predicting catalytic sites by incorporating novel descriptors.

Main Methods:

  • Support Vector Machine (SVM) approach applied for active site cleft recognition and ranking.
  • Utilized protein centroid distance, sequence entropy of lining residues, and volume as key descriptors.
  • Tested performance on both ligand-bound and unbound protein structures.

Main Results:

  • The SVM method achieved 73% accuracy in predicting the correct active site cleft at rank one.
  • Accuracy increased to 94% (bound) and 90% (unbound) when considering the top three ranks.
  • The new method shows improved binding site cleft ranking compared to CASTp and is comparable to Fpocket.

Conclusions:

  • The combination of distance from centroid, sequence entropy, and volume significantly improves catalytic site prediction.
  • The SVM-based approach offers a valuable complementary tool for protein binding site analysis.
  • Despite a small training dataset, the results are promising for practical application in structural bioinformatics.