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View article: Assigning the Stereochemistry of Natural Products by Machine Learning
Assigning the Stereochemistry of Natural Products by Machine Learning Open
Nature has settled for L-chirality for proteinogenic amino acids and D-chirality for the carbohydrate backbone of nucleotides. Here we asked the question whether stereochemical patterns might also exist among natural products (NPs) such th…
View article: Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology
Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology Open
To assess how much structural diversity remains unexploited in simple drug scaffolds, we investigated ring systems functionalized with amine handles. Starting from the ring systems database GDB-4c, we enumerated 1139 possible amines and di…
View article: Antimicrobial Peptide‐Peptoid Macrocycles from the Polymyxin B2 Chemical Space
Antimicrobial Peptide‐Peptoid Macrocycles from the Polymyxin B2 Chemical Space Open
Macrocycles have emerged as important new modalities in drug discovery. In the context of addressing the global threat of antimicrobial resistance, here we used a genetic algorithm as a computational tool to evolve peptide‐peptoid macrocyc…
View article: Antimicrobial Peptide‐Peptoid Macrocycles from the Polymyxin B2 Chemical Space
Antimicrobial Peptide‐Peptoid Macrocycles from the Polymyxin B2 Chemical Space Open
Macrocycles have emerged as important new modalities in drug discovery. In the context of addressing the global threat of antimicrobial resistance, here we used a genetic algorithm as a computational tool to evolve peptide‐peptoid macrocyc…
View article: ELECTRUM: an electron configuration-based universal metal fingerprint for transition metal compounds
ELECTRUM: an electron configuration-based universal metal fingerprint for transition metal compounds Open
ELECTRUM is a lightweight, electron-configuration-based fingerprint for transition-metal complexes. Validated on CSD-derived datasets, it captures structural diversity and enables ML to predict coordination numbers and oxidation states.
View article: Chemical Space for Peptide-based Antimicrobials
Chemical Space for Peptide-based Antimicrobials Open
Multidrug-resistant (MDR) bacteria represent a global public health threat, and antimicrobial peptides (AMPs), derived from naturally occurring linear or cyclic peptides, can provide the solution. However, most AMPs are sensitive to protea…
View article: ELECTRUM: An Electron Configuration-based Universal Metal Fingerprint for Transition Metal Compounds
ELECTRUM: An Electron Configuration-based Universal Metal Fingerprint for Transition Metal Compounds Open
Machine learning has experienced a drastic rise in interest and applications in all fields of chemistry, enabling researchers to leverage large chemical datasets to gain novel insights. The success of machine learning-driven projects in ch…
View article: Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers
Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers Open
Herein we report a virtual library of 1E+60 members, a common estimate for the total size of the drug‐like chemical space. The library is obtained from 100 commercially available peptide and peptoid building blocks assembled into linear or…
View article: Navigating a 1E+60 Chemical Space
Navigating a 1E+60 Chemical Space Open
Herein we report a virtual library of 1E+60 members, a common estimate for the total size of the drug-like chemical space. The library is obtained from 100 commercially available peptide and peptoid building blocks assembled into linear or…
View article: One chiral fingerprint to find them all
One chiral fingerprint to find them all Open
Molecular fingerprints are indispensable tools in cheminformatics. However, stereochemistry is generally not considered, which is problematic for large molecules which are almost all chiral. Herein we report MAP4C, a chiral version of our …
View article: MAP4C Code/Analysis/Plots
MAP4C Code/Analysis/Plots Open
All the code and datasets for the evaluation of the MAP4C fingerprint.
View article: Can Large Language Models Predict Antimicrobial Peptide Activity and Toxicity?
Can Large Language Models Predict Antimicrobial Peptide Activity and Toxicity? Open
Antimicrobial peptides (AMPs) are naturally occurring or designed peptides up to a few tens of amino acids which may help address the antimicrobial resistance crisis. However, their clinical development is limited by toxicity to human cell…
View article: Can large language models predict antimicrobial peptide activity and toxicity?
Can large language models predict antimicrobial peptide activity and toxicity? Open
The large language models GPT-3 and GTP-3.5 were challenged to predict the activity and hemolysis of antimicrobial peptides from their sequence and compared to recurrent neural networks and support vector machines.
View article: One chiral fingerprint to find them all
One chiral fingerprint to find them all Open
Background: Molecular fingerprints are indispensable tools in cheminformatics. However, stereochemistry is generally not considered, which is problematic for large molecules which are almost all chiral. Results: Herein we report MAP4C, a c…
View article: MAP4C Code/Analysis/Plots
MAP4C Code/Analysis/Plots Open
All the code and datasets for the evaluation of the MAP4C fingerprint.
View article: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes
Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes Open
Rising antimicrobial resistance (AMR) and lack of innovation in the antibiotic pipeline necessitate novel approaches to discovering new drugs. Metal complexes have proven to be promising antimicrobial compounds, but the number of studied c…
View article: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes
Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes Open
Rising antimicrobial resistance (AMR) and lack of innovation in the antibiotic pipeline necessitate novel approaches to discovering new drugs. Metal complexes have proven to be promising antimicrobial compounds, but the number of studied c…
View article: Libraries generated in: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes
Libraries generated in: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes Open
Libraries generated in the manuscript: "Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes". The libraries can be generated locally by running the code provided on GitHub, but are also provided here free to…
View article: Libraries generated in: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes
Libraries generated in: Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes Open
Libraries generated in the manuscript: "Using Machine Learning to Predict the Antibacterial Activity of Ruthenium Complexes". The libraries can be generated locally by running the code provided on GitHub, but are also provided here free to…
View article: Exploring the Sequence Space of Antimicrobial Peptide Dendrimers
Exploring the Sequence Space of Antimicrobial Peptide Dendrimers Open
There is an urgent need to develop new antibacterial agents against multidrug resistant bacteria. Herein we report our investigation of antimicrobial peptide dendrimers (AMPDs) active against Gram‐negative bacteria, whose sequences were de…
View article: GPT-3 accurately predicts antimicrobial peptide activity and hemolysis
GPT-3 accurately predicts antimicrobial peptide activity and hemolysis Open
Antimicrobial peptides (AMPs) have gained significant attention in the field of drug discovery due to their potential therapeutic applications in the fight against antimicrobial resistance. Since rationally designing AMPs is notoriously di…
View article: Alchemical Analysis of FDA Approved Drugs
Alchemical Analysis of FDA Approved Drugs Open
Chemical space maps help visualize similarities within molecular sets. However, there are many different molecular similarity measures resulting in a confusing number of possible comparisons. To overcome this limitation, we exploit the fac…
View article: PMB Analogs
PMB Analogs Open
Raw dataset generated from the PDGA for the project: PMB analogs.
View article: PMB Analogs
PMB Analogs Open
Raw dataset generated from the PDGA for the project: PMB analogs.
View article: Alchemical analysis of FDA approved drugs
Alchemical analysis of FDA approved drugs Open
Reaction informatics is used to map the chemical space of drugs paired by similarity according to different molecular fingerprints.
View article: T25 Analogs: Virtual Library
T25 Analogs: Virtual Library Open
The virtual library containing approx. 50k peptide dendrimers
View article: T25 Analogs: Virtual Library
T25 Analogs: Virtual Library Open
The virtual library containing approx. 50k peptide dendrimers
View article: Machine Learning Guided Discovery of Non‐Hemolytic Membrane Disruptive Anticancer Peptides
Machine Learning Guided Discovery of Non‐Hemolytic Membrane Disruptive Anticancer Peptides Open
Most antimicrobial peptides (AMPs) and anticancer peptides (ACPs) fold into membrane disruptive cationic amphiphilic α‐helices, many of which are however also unpredictably hemolytic and toxic. Here we exploited the ability of recurrent ne…