{"id":15525,"date":"2024-06-13T14:00:00","date_gmt":"2024-06-13T08:30:00","guid":{"rendered":"https:\/\/cbirt.net\/staging\/?p=15525"},"modified":"2026-10-22T15:26:39","modified_gmt":"2026-10-22T09:56:39","slug":"bionemo-folds-the-human-proteome-a-fused-dataset-of-3d-protein-models-for-machine-learning-applications","status":"publish","type":"post","link":"https:\/\/cbirt.net\/staging\/bionemo-folds-the-human-proteome-a-fused-dataset-of-3d-protein-models-for-machine-learning-applications\/","title":{"rendered":"BioNeMo Folds the Human Proteome: A Fused Dataset of 3D Protein Models for Machine Learning Applications"},"content":{"rendered":"\n

In a recent scientific breakthrough, a team of researchers from NVIDIA and Innophore, USA, came up with a holistic dataset of the predicted protein folding for each member of the proteome of human beings (the complete set of molecules encoded by human genes), representing a great advancement in protein science.<\/em><\/p>\n\n\n\n

Introduction<\/h2>\n\n\n\n

Life has protein as its foundation material, thus participating in almost every biological process. Medical advancements, drug innovations, and even the discovery of novel materials require understanding their complex designs, in other words, the structure of these proteins. However, protein structure determination is usually complex.  In this study, scientists used modeling tools provided within NVIDIA\u2019s BioNeMo platform and homology modeling platform from Innophore\u2019s CavitomiX to create a reliable and accurate dataset.<\/p>\n\n\n\n

Creating a Vast Dataset by Combining Protein Structure Predict Techniques <\/h2>\n\n\n\n

There are more than 20,000 proteins in the human proteome, each having a unique three-dimensional structure that governs its function. Protein structures were conventionally determined by X-ray diffraction or cryo-electron microscopy, which are time-consuming and demanding techniques.<\/p>\n\n\n\n

This new dataset takes a different course of action. The researchers used advanced computational methods such as AlphaFold 2<\/a>, OpenFold<\/a>, and ESMFold<\/a> to predict protein structures using artificial intelligence (AI) algorithms and powerful computers based on the analysis of protein sequences.<\/p>\n\n\n\n

The dataset includes structures from different sources:<\/strong><\/p>\n\n\n\n

AI-predicted models:<\/strong> These are completely created by AI algorithms using amino acid sequence information for the proteins.<\/p>\n\n\n\n

Homology models: <\/strong>These are structured based on similar sequences with known proteins.<\/p>\n\n\n\n

By combining these techniques, the researchers were able to generate structural predictions<\/a> for over 42,000 human proteins. This represents the most comprehensive collection of human protein structures available to date.<\/p>\n\n\n\n

Revealing the Data: What is Inside the Dataset?<\/h2>\n\n\n\n

The dataset is full of treasures for researchers who want to learn about protein structure and function. It contains:<\/p>\n\n\n\n