ArticleChemistry (Weinheim an der Bergstrasse, Germany)2022
Type S Non-Ribosomal Peptide Synthetases for the Rapid Generation of Tailormade Peptide Libraries.
Article in Chemistry (Weinheim an der Bergstrasse, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- A Practical Guideline to Engineering Nonribosomal Peptide Synthetases.Methods in molecular biology (Clifton, N.J.) · 2023Guideline
- Generative AI designs functional thiolation domains for reprogramming non-ribosomal peptide synthetases.Nature communications · 2026Article
- High-Throughput Engineering and Modification of Non-Ribosomal Peptide Synthetases Based on Golden Gate Assembly.Angewandte Chemie (International ed. in English) · 2025Article
- High-throughput reprogramming of an NRPS condensation domain.Nature chemical biology · 2024Article
- Guidelines for Optimizing Type S Nonribosomal Peptide Synthetases.ACS synthetic biology · 2023Article
- Dynamics and mechanistic interpretations of nonribosomal peptide synthetase cyclization domains.Current opinion in chemical biology · 2023Review
- Type S Non-Ribosomal Peptide Synthetases for the Rapid Generation of Tailormade Peptide Libraries.Chemistry (Weinheim an der Bergstrasse, Germany) · 2022Article
- Complex peptide natural products: Biosynthetic principles, challenges and opportunities for pathway engineering.Synthetic and systems biotechnology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Bacterial natural products in general, and non-ribosomally synthesized peptides in particular, are structurally diverse and provide us with a broad range of pharmaceutically relevant bioactivities. Yet, traditional natural product research suffers from rediscovering the same scaffolds and has been stigmatized as inefficient, time-, labour- and cost-intensive. Combinatorial chemistry, on the other hand, can produce new molecules in greater numbers, cheaper and in less time than traditional natural product discovery, but also fails to meet current medical needs due to the limited biologically relevant chemical space that can be addressed. Consequently, methods for the high throughput generation of new natural products would offer a new approach to identifying novel bioactive chemical entities for the hit to lead phase of drug discovery programs. As a follow-up to our previously published proof-of-principle study on generating bipartite type S non-ribosomal peptide synthetases (NRPSs), we now envisaged the de novo generation of non-ribosomal peptides (NRPs) on an unreached scale. Using synthetic zippers, we split NRPSs in up to three subunits and rapidly generated different bi- and tripartite NRPS libraries to produce 49 peptides, peptide derivatives, and de novo peptides at good titres up to 145 mg L
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.