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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...

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Related Experiment Video

Updated: Jun 22, 2026

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

E-novo: an automated workflow for efficient structure-based lead optimization.

Bradley C Pearce1, David R Langley, Jia Kang

  • 1Bristol-Myers Squibb, Computer-Assisted Drug Design, 5 Research Parkway, Wallingford, Connecticut 06492, USA. bradley.pearce@bms.com

Journal of Chemical Information and Modeling
|June 26, 2009
PubMed
Summary
This summary is machine-generated.

The E-Novo protocol automates structure-based drug design for lead optimization. This computational tool rapidly assesses and scores potential drug compounds, accelerating the drug discovery process.

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Related Experiment Videos

Last Updated: Jun 22, 2026

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
08:35

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source

Published on: May 29, 2021

Synthesizing Amino Acids Modified with Reactive Carbonyls in Silico to Assess Structural Effects Using Molecular Dynamics Simulations
05:57

Synthesizing Amino Acids Modified with Reactive Carbonyls in Silico to Assess Structural Effects Using Molecular Dynamics Simulations

Published on: April 26, 2024

Area of Science:

  • Computational chemistry
  • Drug discovery
  • Structural biology

Background:

  • Structure-based drug design is crucial for optimizing lead compounds.
  • Existing computational tools can be complex and time-consuming.
  • There is a need for integrated, automated platforms for lead optimization.

Purpose of the Study:

  • To develop and validate an automated protocol, E-Novo, for structure-based lead optimization.
  • To create a user-friendly, all-in-one tool for rapid assessment of drug candidate libraries.
  • To improve the efficiency of the drug design process through computational methods.

Main Methods:

  • The E-Novo protocol was built using Pipeline Pilot and CHARMm components in Discovery Studio.
  • It involves scaffold generation, ligand enumeration, conformational sampling, and protein-ligand docking (CDOCKER).
  • A physics-based scoring function (MM/GBSA) was employed for final pose ranking.

Main Results:

  • The protocol was validated against diverse kinase and protease inhibitor datasets, showing good correlation with experimental binding affinities.
  • Performance was assessed using published crystal structures and an in-house dataset for Respiratory Syncytial Virus inhibitors.
  • Least squares analysis indicated reasonable validation of the protocol's predictions.

Conclusions:

  • E-Novo offers a convenient, automated solution for structure-based drug design and lead optimization.
  • The protocol enables rapid assessment and scoring of large ligand libraries.
  • It streamlines the early stages of drug discovery by integrating multiple computational steps.