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Related Concept Videos

Drug Discovery: Overview01:26

Drug Discovery: Overview

Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Synthetic Biology02:55

Synthetic Biology

Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
Golden rice
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Related Experiment Video

Updated: May 20, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
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A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English

Published on: April 3, 2026

PyRMD Studio: A Unified Suite for Next-Generation, AI-Powered Virtual Screening.

Benito Natale1, Muhammad Waqas1, Michele Roggia1

  • 1DiSTABiF, University of Campania Luigi Vanvitelli, Caserta 81100, Italy.

Journal of Chemical Information and Modeling
|May 19, 2026
PubMed
Summary
This summary is machine-generated.

PyRMD Studio simplifies artificial intelligence (AI) for drug discovery with a new graphical interface, making virtual screening (VS) accessible to nonexperts. It ensures reliable results through robust validation and offers faster screening speeds.

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Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
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Last Updated: May 20, 2026

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Published on: April 3, 2026

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07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Area of Science:

  • Computational chemistry
  • cheminformatics
  • drug discovery

Background:

  • Artificial intelligence (AI) is crucial for drug discovery but faces adoption barriers due to complex command-line tools and overfitting risks.
  • Existing virtual screening (VS) software often requires coding expertise and lacks rigorous validation, leading to unreliable results.

Purpose of the Study:

  • To introduce PyRMD Studio, an updated open-source VS software with a graphical user interface (GUI).
  • To enhance accessibility for nonexpert users in AI-driven drug discovery workflows.
  • To improve the reliability and efficiency of virtual screening.

Main Methods:

  • Development of a comprehensive GUI for Linux and Windows, enabling ligand-based and structure-based VS.
  • Implementation of a Butina clustering-based validation strategy to separate training and test sets, preventing data leakage.
  • Code optimization and vectorization for increased computational efficiency.

Main Results:

  • PyRMD Studio provides a user-friendly GUI, democratizing access to AI-powered VS for users without coding skills.
  • The Butina clustering validation strategy ensures reliable performance estimation by mitigating overfitting and data leakage.
  • Optimized code resulted in an approximate 3.3-fold increase in screening speed compared to the previous version.

Conclusions:

  • PyRMD Studio offers a streamlined and reliable toolkit for high-throughput virtual screening campaigns.
  • The software lowers the barrier to entry for AI in drug discovery, promoting wider adoption.
  • Enhanced accessibility, scientific rigor, and computational efficiency make PyRMD Studio a valuable resource for researchers.