Protein Modeling

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Can InterPLM Decode the Hidden Language of Protein Modeling and Design AI?
ByAnchal Negi December 6, 2024October 22, 2026

The emergence of Protein Language Models (PLMs) is changing biological research for the better through efficient prediction of functional annotations and protein structures. However, the actual features and mechanisms of these models still largely remain unclear. This posed a critical question that sparked the curiosity of Elana Simon and James Zou, who are both researchers…

Read More Can InterPLM Decode the Hidden Language of Protein Modeling and Design AI?
AI | Bioinformatics | Neural Network | News | Paper Summary | Structural Biology | Tools | Trending

How ChemNet is Revolutionizing Protein-Small Molecule Conformational Modeling
ByDeotima Chakraborty September 30, 2024October 22, 2026

Modeling of protein-small molecule systems offers advantages in speed and generality for exploring interactions with small molecules in the folded state; the modeling of conformational heterogeneity in protein-small molecule systems is deemed an outstanding issue at the atomic level. Researchers from the University of Washington created a graph neural network named ChemNet that was taught…

Read More How ChemNet is Revolutionizing Protein-Small Molecule Conformational Modeling
AI | Bioinformatics | Molecular Dynamics | News | Structural Biology | Tools

Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension
ByAnshika Gupta June 6, 2024October 22, 2026

Acting as enzymes, structural elements, and molecular motors, proteins represent the molecular drive of biological systems, the elucidation of which relies on the explication of conformational transitions. In a recent study by Linköping University, Sweden, researchers got into the issue of protein conformational sampling, stating that there are limitations to current methods and that AFsample2…

Read More Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension
AI | Bioinformatics | Machine Learning | News | Paper Summary | PLM | Proteomics | Tools | Trending | Web Servers

No Coding Required! SaprotHub Brings Protein Modeling to Every Biologist
ByDeotima Chakraborty June 4, 2024October 22, 2026

Users without prior Machine Learning (ML) experience have difficulties when it comes to training and implementing deep learning models. Regardless of prior experience with machine learning, SaprotHub, introduced by the researchers of Westlake University, provides a simple platform for training, using, and exchanging protein models, encouraging cooperation among biologists. All it takes is a few…

Read More No Coding Required! SaprotHub Brings Protein Modeling to Every Biologist
AI | Bioinformatics | Computational Models | LLM | News | Paper Summary | Proteomics | Trending

Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis at Single Amino Acid Resolution
ByDeotima Chakraborty January 28, 2024October 22, 2026

The field of biological sequence analysis has lately benefited from the revolutionary changes brought about by the development of self-supervised deep language models for natural language processing tasks. Conventional models show significant effectiveness in a variety of applications. These models are mostly based on the Transformer and BERT architectures. However, the quadratic computational complexity O(L2)…

Read More Unveiling ProtHyena: A Fast and Efficient Protein Language Model for Analysis at Single Amino Acid Resolution
Bioinformatics | Machine Learning | News | Structural Biology | Tools | Trending

Genome-Scale Protein Structure and Function Prediction with High-Performance Computing Toolkit
ByDr. Tamanna Anwar January 23, 2022November 4, 2022

A group of scientists from the Department of Energy’s Oak Ridge National Laboratory (ORNL) and the Georgia Institute of Technology applied supercomputing and new deep learning technologies (Google’s DeepMind) to anticipate the structures and functions of an organism’s whole proteome. The deep learning-based algorithms developed by the team predict protein structure and function from DNA…

Read More Genome-Scale Protein Structure and Function Prediction with High-Performance Computing Toolkit
Bioinformatics | Machine Learning | News | Paper Summary | Structural Biology | Trending

Modeling Protein Fitness Using Evolutionary and Assay-Labeled Data
BySwati Yadav January 23, 2022November 2, 2023

Scientists from the University of California, Berkeley have developed a machine learning-based model that predicts protein fitness from the sequence. Protein fitness is a broad term that includes a wide range of protein properties, such as stability, enzyme activity, and ligand binding. Models of protein fitness based on machine learning typically learn from either unlabeled,…

Read More Modeling Protein Fitness Using Evolutionary and Assay-Labeled Data

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Protein Modeling

Predicting Multiple Conformations and Ensembles with AFsample2: An AlphaFold2 Extension

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