Source 1review2021Nature Reviews Drug Discovery
Toolkit/EvoMining
EvoMining
Taxonomy: Technique Branch / Method. Workflows sit above the mechanism and technique branches rather than replacing them.
Summary
The supplied web research summary identifies EvoMining as an evolutionary genome-mining approach that complements mainstream biosynthetic gene cluster search tools and supports discovery of hidden biosynthetic chemistry.
Usefulness & Problems
No literature-backed usefulness or problem-fit explainer has been materialized for this record yet.
Published Workflows
Objective: Accelerate natural product drug discovery by combining sequence-based prospecting, analytical dereplication, curated reference resources, and downstream structure elucidation or library-generation workflows.
Why it works: The supplied evidence suggests that combining genome mining, dereplication, curated databases, and structural analysis narrows discovery space and reduces rediscovery and interpretation bottlenecks.
biosynthetic gene cluster predictionmass-spectrometry-based dereplicationmolecular networkingreference-database-guided annotationstructure elucidationgenome miningmachine learningmass spectrometrymolecular networkingdatabase curationmetagenomic discovery
Stages
- 1.Genome mining and biosynthetic gene cluster prediction(in_silico_filter)
The supplied evidence presents genome mining as an enabling early discovery technology for identifying candidate natural product chemistry from sequence data.
Selection: Predicted biosynthetic gene clusters and candidate access to new natural-product chemical space
- 2.MS-based dereplication and molecular networking(counter_screen)
The supplied evidence frames dereplication as a way to filter known chemistry and organize analytical data before deeper investment.
- 3.Reference-database-guided annotation(secondary_characterization)
The supplied evidence identifies curated resources as useful for interpreting genome-mining and compound-discovery results.
Selection: Comparison against curated biosynthetic gene cluster and natural product knowledge bases
- 4.Structure elucidation follow-up(confirmatory_validation)
The supplied evidence highlights MicroED as a technology that can reduce structure elucidation bottlenecks in natural product discovery.
Selection: Resolve candidate structures for prioritized natural products
Taxonomy & Function
Primary hierarchy
Technique Branch
Method: A concrete computational method used to design, rank, or analyze an engineered system.
Mechanisms
evolutionary comparative genome miningTarget processes
No target processes tagged yet.
Validation
Cell-freeBacteriaMammalianMouseHumanTherapeuticIndep. Replication
Supporting Sources
Ranked Claims
antiSMASH, DeepBGC, and EvoMining are presented in the supplied evidence as genome-mining approaches relevant to biosynthetic gene cluster discovery in natural product research.
GNPS and DEREPLICATOR+ are presented in the supplied evidence as analytical and dereplication tools for mass-spectrometry-based natural product discovery.
MIBiG and The Natural Products Atlas are presented in the supplied evidence as curated reference resources that support interpretation and normalization in natural product discovery.
Approval Evidence
1 source1 linked approval claimfirst-pass slug evomining
The supplied web research summary identifies EvoMining as an evolutionary genome-mining approach that complements mainstream biosynthetic gene cluster search tools and supports discovery of hidden biosynthetic chemistry.
Source:
tool role summarysupports
antiSMASH, DeepBGC, and EvoMining are presented in the supplied evidence as genome-mining approaches relevant to biosynthetic gene cluster discovery in natural product research.
Source:
Comparisons
No literature-backed comparison notes have been materialized for this record yet.
Ranked Citations
- 1.