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Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
A limited set of protein domains often duplicate and recombine during evolution. These domains can be organized in different combinations to...

Conserved Binding Sites

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...

Conservation of Protein Domains

Conservation of Protein Domains

Protein Families

Protein Families

Protein families are groups of homologous proteins; that is, they have similarities in amino acid sequences and three-dimensional structures. Protein families usually occur because of gene duplication, where an additional copy of a gene is inserted into the genome of an organism. Mutations that change the amino acids but still allow the protein to be properly synthesized, will lead to new protein family members. If these new proteins contain similar amino acids in key...

Leaky Scanning

Leaky Scanning

During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA. Marilyn Kozak discovered that the sequence RCCAUGG (where R...

Ligand Binding Sites

Ligand Binding Sites

Proteins are dynamic macromolecules that carry out a wide variety of essential processes; however, the activities of most proteins depend on their interactions with other molecules or ions, known as ligands.
Protein-ligand interactions are quite specific; even though numerous potential ligands surround a cellular protein at any given time, only a particular ligand can bind to that protein. Moreover, a ligand binds only to a dedicated area on the surface of the protein, known as the...

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Related Experiment Video

Updated: May 30, 2025

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

Interpretable adenylation domain specificity prediction using protein language models.

Abhinav K Adduri¹, Andrew T McNutt², Caleb N Ellington¹

¹Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.

Biorxiv : the Preprint Server for Biology

|January 27, 2025

Summary

This summary is machine-generated.

We developed MASPR, a machine learning tool, to predict natural product structures from microbial genomes. This method accelerates the discovery of novel antibiotics, antifungals, and anticancer compounds.

Keywords:

Drug Discovery Generative Modeling Machine Learning Natural Products Protein Language Models

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Last Updated: May 30, 2025

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

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Published on: January 26, 2024

A Protocol for Computer-Based Protein Structure and Function Prediction

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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Area of Science:

Biochemistry
Computational Biology
Genomics

Background:

Natural products like non-ribosomal peptides (NRPs) and polyketides (PKs) are vital drug sources.
Traditional discovery methods are slow and often rediscover known compounds.
Genome mining offers a high-throughput approach to identify novel natural products.

Purpose of the Study:

To develop a machine learning method for predicting substrate specificities of adenylation (A) domains involved in NRP and NRP-PK biosynthesis.
To create an efficient algorithm for predicting hybrid NRP-PK natural product structures from genomic data.
To identify potential biosynthetic gene clusters for orphan natural products.

Main Methods:

Utilized protein language models to develop MASPR for accurate A-domain substrate specificity prediction.
Implemented MASPR for zero-shot classification, predicting novel substrates.
Developed Seq2Hybrid algorithm integrating MASPR to predict hybrid NRP-PK structures from microbial genomes.

Main Results:

MASPR demonstrated superior accuracy and generalization compared to existing methods.
MASPR successfully predicted substrates not present in its training data.
Seq2Hybrid enabled the proposal of biosynthetic gene clusters for orphan natural products Octaminomycin A, Dityromycin, SW-163B, and JBIR-39.

Conclusions:

MASPR provides an accurate and interpretable approach for A-domain substrate prediction.
Seq2Hybrid accelerates the discovery of novel hybrid NRP-PK natural products.
This genome mining strategy enhances the identification of valuable bioactive compounds.