Toolkit/FRASE-bot
FRASE-bot
Also known as: FRASE-based hit-finding robot
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
FRASE-bot is an in silico fragment-based hit-finding method for drug discovery against unconventional therapeutic targets. It mines thousands of 3D protein-ligand complex structures to build a fragment-in-structural-environment database, matches target protein environments to that database, and uses machine learning to prioritize seeded fragments as candidate binders.
Usefulness & Problems
Why this is useful
FRASE-bot is useful for structure-based hit finding when conventional target classes may be difficult to address, because it distills ligand-binding information from large numbers of known protein-ligand complex structures. In the reported application, it enabled identification of a small-molecule ligand for CIB1, with binding confirmed by TR-FRET.
Source:
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Source:
A neural network model is used to retain fragments with the highest likelihood of being native binders.
Source:
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
Source:
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
Problem solved
FRASE-bot addresses the problem of rapidly finding small-molecule starting points for unconventional therapeutic targets from structural information. Specifically, it provides a way to seed a target protein structure with ligand fragments by identifying similar structural environments in a database derived from known protein-ligand complexes.
Source:
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
machine-learning-based fragment prioritizationstructural-environment similarity matchingstructure-based fragment seedingTarget processes
recombinationselectionInput: Chemical
Implementation Constraints
Implementation requires 3D structures of protein-ligand complexes to construct the FRASE database and a target protein structure for structural-environment matching and fragment seeding. The reported validation used a TR-FRET assay to confirm binding of the identified CIB1 ligand, but the evidence does not specify software requirements, input formats, or experimental follow-up workflow details.
The supplied evidence documents one published application to CIB1, so validation breadth is limited. The evidence does not provide quantitative performance metrics, comparative benchmarking, model architecture details, or independent replication across multiple targets.
Validation
Supporting Sources
Ranked Claims
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
The identified small-molecule CIB1 ligand had binding confirmed in a TR-FRET assay.
a small-molecule CIB1 ligand (with binding confirmed in a TR-FRET assay)
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
Approval Evidence
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
Source:
FRASE-bot exploits big data and machine learning (ML) to distill 3D information relevant to the target protein from thousands of protein-ligand complexes to seed it with ligand fragments.
Source:
Applying FRASE-bot to CIB1 identified a small-molecule CIB1 ligand.
We apply FRASE-bot to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)... FRASE-based virtual screening identifies a small-molecule CIB1 ligand
Source:
A neural network model is used to retain seeded fragments with the highest likelihood of being native binders.
A neural network model is used to retain fragments with the highest likelihood of being native binders.
Source:
FRASE-bot mines 3D structures of ligand-protein complexes to create a database of fragments in structural environments.
FRASE-bot mines available 3D structures of ligand-protein complexes to create a database of FRAgments in Structural Environments (FRASE).
Source:
The FRASE database can be screened to identify structural environments similar to those in a target protein and seed the target structure with relevant ligand fragments.
The FRASE database can be screened to identify structural environments similar to those in the target protein and seed the target structure with relevant ligand fragments.
Source:
FRASE-bot is introduced as a hit-finding method intended to expedite drug discovery for unconventional therapeutic targets.
We introduce FRASE-based hit-finding robot (FRASE-bot), to expedite drug discovery for unconventional therapeutic targets.
Source:
FRASE-based virtual screening identified a small-molecule ligand for CIB1, described as the first such ligand in the abstract.
FRASE-based virtual screening identified the first small-molecule CIB1 ligand
Source:
FRASE-bot was applied to identify ligands for CIB1.
Here, FRASE-bot was applied to identify ligands for Calcium and Integrin Binding protein 1 (CIB1)
Source:
FRASE-bot uses big data and machine learning to distill target-relevant 3D information from thousands of protein-ligand complexes and seed a target protein with ligand fragments.
FRASE-bot exploits big data and machine learning (ML) to distill 3D information relevant to the target protein from thousands of protein-ligand complexes to seed it with ligand fragments.
Source:
Comparisons
Source-backed strengths
The method leverages large-scale 3D structural data from thousands of protein-ligand complexes and applies machine learning to prioritize fragments relevant to a target protein. Its reported utility includes successful application to CIB1, where it identified a small-molecule ligand and obtained binding confirmation in a TR-FRET assay.
Ranked Citations
- 1.