Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Amino acids

Amino acids

Amino acids are the monomers that comprise proteins. Each amino acid has the same fundamental structure, which consists of a central carbon atom, or the alpha (α) carbon, bonded to an amino group (NH2), a carboxyl group (COOH), and to a hydrogen atom. Every amino acid also has another atom or group of atoms bonded to the central atom known as the R group. There are 20 common amino acids present in proteins, each with a different R group. Variation in the amino acid sequence is responsible...

Molecular Models

Molecular Models

Physical models representing molecular architectures of chemical compounds play essential roles in understanding chemistry. The use of molecular models makes it easier to visualize the structures and shapes of atoms and molecules.

You might also read

Related Articles

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

Sort by

Same author

Combined Quantitative and Qualitative Statistical Analyses Improve Benzodiazepine Target Discovery in Label-free Affinity-Based Protein Profiling Data.

Journal of proteome research·2026

Same author

A Post-translational Histidine-Histidine Cross-Link Enhances Enzymatic Oxygen Reduction Activity with Greater pH Adaptability.

Journal of the American Chemical Society·2025

Same author

Best Practices in NMR Metabolomics: Current State.

Trends in analytical chemistry : TRAC·2025

Same author

Correction to "Advancing the Prediction of MS/MS Spectra Using Machine Learning".

Journal of the American Society for Mass Spectrometry·2025

Same author

Advancing the Prediction of MS/MS Spectra Using Machine Learning.

Journal of the American Society for Mass Spectrometry·2024

Same author

QC-GN<sup>2</sup>oMS<sup>2</sup>: a Graph Neural Net for High Resolution Mass Spectra Prediction.

Journal of chemical information and modeling·2024

Same journal

PSDTA: An Approach to Drug-Target Binding Affinity Prediction by Integrating Physicochemical and Structural Information to Reduce Feature Redundancy.

Journal of chemical information and modeling·2026

Same journal

M-JEPA: Predictive Self-Supervised Learning for Molecular Graphs with Scaffold-Shift Evaluation on Tox21.

Journal of chemical information and modeling·2026

Same journal

Advancing Biochemical Molecule Registration, Representation and Search for New Drug Modalities.

Journal of chemical information and modeling·2026

Same journal

A Unified Molecular Graph and Protein Language Model Framework for Predicting Human Drug-Hormone Receptor Interactions with Structure-Aware Validation.

Journal of chemical information and modeling·2026

Same journal

Intricate Role of Cholesterol in Membrane Fusion.

Journal of chemical information and modeling·2026

Same journal

tmGNN-XAI: An Explainable Graph Neural Network Tool for Predicting Electronic Properties of Transition Metal Complexes from SMILES.

Journal of chemical information and modeling·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 5, 2025

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Published on: April 26, 2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials.

Richard E Overstreet¹, Dennis G Thomas², John R Cort²

¹Physical Detection Systems and Deployment Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States.

Journal of Chemical Information and Modeling

|December 10, 2024

Summary

This summary is machine-generated.

We developed NCAP, a software tool that generates CHARMM-compatible parameters for noncanonical amino acids (ncAAs) from quantum chemical calculations. This facilitates accurate modeling of ncAA mutations in protein design.

More Related Videos

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Related Experiment Videos

Last Updated: Jun 5, 2025

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Author Spotlight: In Silico Creation and Impact of Carbonylated Amino Acids on Protein Structure and Function

Published on: April 26, 2024

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

Published on: January 26, 2024

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Curation of Computational Chemical Libraries Demonstrated with Alpha-Amino Acids

Published on: April 13, 2022

Area of Science:

Biochemistry
Computational Biology
Protein Engineering

Background:

Noncanonical amino acids (ncAAs) expand protein functionality but are challenging to model due to synthesis difficulties and limited structural data.
Accurate molecular potentials are crucial for predicting the effects of ncAA mutations in rational protein design.
Existing molecular potentials, like CHARMM, are primarily designed for canonical amino acids, requiring parametrization for ncAAs.

Purpose of the Study:

To introduce NCAP, a novel software package for generating CHARMM-compatible parameters for noncanonical amino acids (ncAAs).
To bridge the gap between quantum chemical calculations and CHARMM potential parameters for ncAAs.
To enable more accurate computational modeling of proteins containing ncAAs.

Main Methods:

Utilizing quantum chemical calculations to derive molecular potentials for ncAAs.
Developing the NCAP software to automatically recognize ncAA structures and generate CHARMM-compatible parameters.
Validating the generated parameters against canonical amino acid parameter sets.

Main Results:

NCAP successfully generates CHARMM-compatible parameters for ncAAs.
The software automates the process of parameter generation, overcoming limitations of current tools.
Validation demonstrates the accuracy and utility of NCAP-generated parameters.

Conclusions:

NCAP provides a critical tool for computational protein design involving noncanonical amino acids.
The software facilitates the accurate modeling of structural and functional perturbations introduced by ncAAs.
NCAP enhances the application of molecular dynamics simulations in protein engineering with novel amino acids.