Source 1primary paper2024Nature Communications
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
Problem links
This item is explicitly described as a hit-finding robot intended to expedite drug discovery, making it one of the few candidates with direct automation relevance. It could plausibly reduce manual handling and improve throughput in chemistry workflows tied to molecule discovery.
This is the only candidate explicitly framed as a drug-discovery hit-finding method, which could help generate and prioritize molecules for downstream ADME/Tox evaluation. Its computational and assay-linked workflow also fits the need for improved predictive modeling more directly than the other items.
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 prioritizationmachine-learning-based fragment prioritizationstructural-environment similarity matchingstructural-environment similarity matchingstructure-based fragment seedingstructure-based fragment seedingTarget processes
recombinationselectionInput: Chemical
Implementation Constraints
cofactor dependency: cofactor requirement unknownencoding mode: genetically encodedimplementation constraint: context specific validationoperating role: builder
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
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
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
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
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)
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.
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.
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).
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).
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.
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.
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.
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.
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
2 sources8 linked approval claimsfirst-pass slug frase-bot
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:
application resultsupports
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:
method capabilitysupports
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:
method capabilitysupports
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:
method capabilitysupports
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:
method introductionsupports
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:
discovery claimsupports
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:
method applicationsupports
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:
method capabilitysupports
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.
Compared with CRISPR/Cas system
FRASE-bot and CRISPR/Cas system address a similar problem space because they share recombination, selection.
Shared frame: shared target processes: recombination, selection; same primary input modality: chemical
Strengths here: appears more independently replicated; looks easier to implement in practice.
Compared with FRASE
FRASE-bot and FRASE address a similar problem space because they share recombination, selection.
Shared frame: same top-level item type; shared target processes: recombination, selection; shared mechanisms: structural-environment similarity matching, structure-based fragment seeding; same primary input modality: chemical
Strengths here: appears more independently replicated; looks easier to implement in practice.
Compared with NCBI sequence screening for 2A/2A-like occurrence
FRASE-bot and NCBI sequence screening for 2A/2A-like occurrence address a similar problem space because they share recombination, selection.
Shared frame: same top-level item type; shared target processes: recombination, selection
Strengths here: appears more independently replicated; looks easier to implement in practice.
Ranked Citations
- 1.