We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBE SCIENTIFIC, LLC

Download Mobile App




An Omics Approach for Predicting Mutations in Protein-Metal Binding Sites

By LabMedica International staff writers
Posted on 06 Jan 2020
A deep learning approach was developed that was able to predict how mutations in the metal-binding sites of metalloproteins were related to various diseases.

Metalloproteins play important roles in many biological processes. More...
Mutations at the metal-binding sites may functionally disrupt metalloproteins, initiating severe diseases; however, there has not been an effective approach for predicting such mutations.

In this regard, investigators at the University of Hong Kong (China) developed an “omics”-based deep learning approach to predict disease-associated mutations of the metal-binding sites in a protein. Omics (such fields as genomics, proteomics, etc.) aims at the collective characterization and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms.

The investigators began by integrating omics data from different databases to build a comprehensive computer training dataset. Statistical analysis of the collected data revealed that various metals had different disease associations. A mutation in zinc-binding sites had a major role in breast, liver, kidney, immune system, and prostate diseases. By contrast, mutations in calcium- and magnesium-binding sites were associated with muscular and immune system diseases, respectively. Mutations in iron-binding sites were associated with metabolic diseases. In addition, mutations of manganese- and copper-binding sites were associated with cardiovascular diseases, and copper-binding site mutations were also associated with nervous system diseases.

The investigators generated energy-based affinity grid maps and physiochemical features of the metal-binding pockets (obtained from different databases as spatial and sequential features) and subsequently incorporated these features into a multichannel convolutional neural network. After training the model, the multichannel convolutional neural network successfully predicted disease-associated mutations that occurred at the first and second coordination spheres of zinc-binding sites with an area under the curve of 0.90 and an accuracy of 0.82.

Senior author Dr. Hongzhe Sun, professor of bioinorganic chemistry at the University of Honk Kong, said, "Machine learning and AI play important roles in the current biological and chemical science. In my group we worked on metals in biology and medicine using integrative omics approach including metallomics and metalloproteomics, and we already produced a large amount of valuable data using in vivo/vitro experiments. We now develop an artificial intelligence approach based on deep learning to turn these raw data to valuable knowledge, leading to uncover secrets behind the diseases and to fight with them. I believe this novel deep learning approach can be used in other projects, which is undergoing in our laboratory."

The mettaloprotein binding site mutations paper was published in the December 9, 2019, online edition of the journal Nature Machine Intelligence.

Related Links:
University of Hong Kong


Gold Member
Veterinary Hematology Analyzer
Exigo H400
Serological Pipet Controller
PIPETBOY GENIUS
New
Host Response Immunoassay Test
MeMed BV
New
Silver Member
Quality Control Material
NATtrol Chlamydia trachomatis Positive Control
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








DIASOURCE (A Biovendor Company)

Channels

Hematology

view channel
Image: CitoCBC is the world first cartridge-based CBC to be granted CLIA Waived status by FDA (Photo courtesy of CytoChip)

Disposable Cartridge-Based Test Delivers Rapid and Accurate CBC Results

Complete Blood Count (CBC) is one of the most commonly ordered lab tests, crucial for diagnosing diseases, monitoring therapies, and conducting routine health screenings. However, more than 90% of physician... Read more

Immunology

view channel
Image: A simple blood test could replace surgical biopsies for early detecion of heart transplant rejection (Photo courtesy of Shutterstock)

Blood Test Detects Organ Rejection in Heart Transplant Patients

Following a heart transplant, patients are required to undergo surgical biopsies so that physicians can assess the possibility of organ rejection. Rejection happens when the recipient’s immune system identifies... Read more

Pathology

view channel
These images illustrate how precision oncology Organ Chips recapitulate individual patients’ responses to chemotherapy (Photo courtesy of Wyss Institute at Harvard University)

Cancer Chip Accurately Predicts Patient-Specific Chemotherapy Response

Esophageal adenocarcinoma (EAC), one of the two primary types of esophageal cancer, ranks as the sixth leading cause of cancer-related deaths worldwide and currently lacks effective targeted therapies.... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.