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Protein Modifications in the RER

Protein Modifications in the RER

Modification of secretory and transmembrane proteins entering the rough ER begins in the ER lumen. These modifications aid in protein folding and stabilize the acquired tertiary structure. Protein modifications in the rough ER co-occur at different stages of protein folding.
Broadly, these modifications can be categorized into four main categories — glycosylation, formation of disulfide bonds, assembly of protein subunits, and specific proteolytic cleavages like removal of signal...

Cotranslational Protein Translocation

Cotranslational Protein Translocation

Translocation of proteins across membranes is an ancient process that occurs even in bacteria and archaebacteria. In fact, the components of the translocation machinery are still conserved between prokaryotes and eukaryotes.
Sec61 channel partners for cotranslational translocation
During cotranslational translocation, the Sec61 channel partners with the signal recognition particle (SRP), the signal recognition particle receptor (SR), and the ribosomes to transport the nascent polypeptide chain...

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...

Translocation of Proteins into the Mitochondria

Translocation of Proteins into the Mitochondria

Mitochondrial precursors are translocated to the internal subcompartments via independent mechanisms involving distinct protein machineries called translocases.
Sorting of outer membrane proteins:
Mitochondrial outer membrane proteins are of two types: the transmembrane, beta-barrel porins, and the membrane-anchored, alpha-helical proteins. Beta-barrel porin precursors are translocated by the TOM complex and inserted into the outer mitochondrial membrane by the SAM complex. In contrast,...

Tagging and Fusion Proteins

Tagging and Fusion Proteins

Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...

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Related Experiment Video

Updated: Jun 6, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

LMPTMSite: A Platform for PTM Site Prediction in Proteins Leveraging Transformer-Based Protein Language Models.

Pawel Pratyush¹, Suresh Pokharel¹, Hamid D Ismail^1,2

¹Computer Science Department, Rochester Institute of Technology, Rochester, NY, USA.

Methods in Molecular Biology (Clifton, N.J.)

|November 22, 2024

Summary

We developed LMPTMSite, a platform using advanced language models to accurately predict protein post-translational modification sites, like S-nitrosylation and succinylation, offering a faster alternative to traditional methods.

Keywords:

CPU runtime Deep learning Natural language processing Post-translational modification (PTM)Protein language models RAM usage S-nitrosylation Succinylation Transformer Tricarboxylic acid (TCA) cycle

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Last Updated: Jun 6, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

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Published on: November 3, 2011

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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Published on: May 22, 2018

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

Area of Science:

Biochemistry
Computational Biology
Bioinformatics

Background:

Protein post-translational modifications (PTMs) are crucial for regulating protein function and biological systems.
Experimental methods for identifying PTM sites, such as mass spectrometry, are often time-consuming and costly.
Machine learning and deep learning present efficient alternatives for PTM site prediction.

Purpose of the Study:

To introduce the LMPTMSite platform for predicting protein S-nitrosylation and succinylation sites.
To detail the transformer-based protein language model (pLM) approaches, pLMSNOSite and LMSuccSite.
To evaluate the performance and efficiency of these novel prediction tools.

Main Methods:

Utilized transformer-based protein language models (pLMs) for sequence encoding.
Developed deep learning architectures for predicting S-nitrosylation (pLMSNOSite) and succinylation (LMSuccSite) sites.
Analyzed computational resource usage (CPU, RAM) and compared efficacy against state-of-the-art tools.

Main Results:

Demonstrated superior efficacy of pLMSNOSite and LMSuccSite compared to existing methods.
Provided analysis of runtime and memory usage, showing scalability with input sequence length.
Successfully applied LMSuccSite to predict succinylation sites in TCA cycle proteins, showcasing practical utility.

Conclusions:

The LMPTMSite platform, featuring pLMSNOSite and LMSuccSite, offers a powerful and efficient solution for PTM site prediction.
These tools significantly advance the characterization of protein modifications, aiding biological system research.
LMPTMSite is freely available as a web server and standalone packages for broad accessibility.