Unlocking the Full Potential
of Predictive Modeling for Precise hERG Activity Predictions
A Comprehensive Guide to Using the Pred-hERG App's Advanced Machine Learning Model for Reliable Results
NEWS
We are excited to introduce Pred-hERG 5.0, an innovative machine learning web application for predicting hERG blockage. This advanced tool offers enhanced accuracy, user-friendliness, and robustness to meet the needs of the global research community. Here are the key highlights of Pred-hERG 5.0:
Advanced Machine Learning
By harnessing the power of cutting-edge machine learning algorithms, we have taken significant strides in improving the accuracy of hERG blockage predictions. As a result, we are empowering researchers to make highly informed decisions with utmost confidence and precision.
Expansion of
Database
Our integrated database has expanded significantly,
now encompassing comprehensive information on over 14,364 compounds sourced from ChEMBL v30 database,
providing an extensive and diverse array of data points, enabling highly accurate and nuanced predictions.
Meticulous data curation
To ensure the utmost accuracy and reliability of our predictions,
we have implemented a rigorous data curation process,
that includes several crucial steps such as the removal of salts, mixtures,
inorganic and organometallic compounds, normalization of chemotypes,
as well as the elimination of duplicate entries.
Diverse Prediction
Models
Pred-hERG 5.0 introduces a robust framework consisting of three distinct models—classificatory,
multi-classificatory, and regression. These models have been optimized to accommodate a wide
range of prediction tasks, thereby making Pred-hERG 5.0 highly adaptable and versatile
for a wide range of research applications.
Improved prediction accuracy
Pred-hERG 5.0 sets a new standard in performance,
surpassing previous iterations and outshining other available tools.
With remarkable advancements in prediction accuracy rates,
this latest version enables unparalleled precision in hERG blockage predictions.
User-Centric Design
With a commitment to addressing the needs of our user community, we have redesigned the interface for
enhanced usability and intuitive navigation. By prioritizing user-friendliness,
we have made Pred-hERG more accessible to a diverse range of researchers,
students, and professionals, empowering them to leverage its powerful capabilities with ease and confidence.
Instructions
1
Draw a substance or Pasting a smiles String
The first step is to draw the chemical structure of the compound you want to evaluate using the drawing tool provided in the app.
Alternatively, you can paste a SMILES string of the compound into the drawer.
SMILES is a line notation that represents the molecular structure of a compound.
Once you have drawn or pasted the compound, you can review and edit it if necessary.
2
or uploading a csv or sdf file
Step 2: Uploading a CSV or SDF file. If you have a large number of compounds to evaluate, you can upload a CSV or SDF file containing the structures of the compounds.
The file size should not exceed 2 MB. If you are uploading a CSV file, please ensure that it has
a column with the name "SMILES" that contains the SMILES strings of the compounds. Only the first 10 SMILES will be considered in the evaluation.
3
hit the prediction button
After you have drawn or uploaded the compound(s), you can hit the Forecast button to initiate the evaluation process. The app will use a predictive model to analyze the compound(s) and provide a prediction of their hERG activity.
4
review the results
Once the evaluation process is complete, the app will display the results of the analysis.
The results will include a prediction of the compound's hERG activity, along with a confidence score.
You can review the results and use them to make informed decisions about the compound(s) you are evaluating.
Explore the Global Utilization of Pred-hERG
Delve into the worldwide usage of Pred-hERG through this interactive map, showcasing the diverse locations of its users across the globe.
Gain insights into the widespread adoption of Pred-hERG and its impact on various regions and communities.
