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staphylococcus aureus atcc 25923  (ATCC)
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ATCC staphylococcus aureus atcc 25923
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
Gram Negative, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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masterpure gram positive dna purification kit  (Biosearch Technologies Inc)
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
Masterpure Gram Positive Dna Purification Kit, supplied by Biosearch Technologies Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
Gram Bacteria Dna Auto Plate Kit, supplied by Taiwan Advanced Nanotech, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
Gram Negative Pathogen Klebsiella Pneumoniae, supplied by ATCC, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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masterpure gram positive dna purification kit  (Lucigen Corp)
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
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gram positive bacterium  (ATCC)
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically <t>relevant</t> <t>Gram-negative</t> (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.
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(A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically relevant Gram-negative (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.

Journal: bioRxiv

Article Title: Modification-aware AI enables terminal chemical modifications for peptide design and discovers potent antimicrobials

doi: 10.64898/2026.04.09.717597

Figure Lengend Snippet: (A) Heat map of minimum inhibitory concentrations (MICs, μmol[L −1 ) against 11 clinically relevant Gram-negative (–) and Gram-positive (+) pathogens, including antibiotic-resistant strains. Bacteria (10 5 CFU) were incubated with serial peptide dilutions (0–64 μmol□L −1 ) at 37□°C, and growth was quantified by OD 600 after 24 h. MIC values represent the mode of replicate measurements for each condition. Hemolytic (HC 50 ) and cytotoxic (CC 50 ) concentrations, defined as the peptide concentration causing 50% lysis of red blood cells or reduction in HEK293T cell viability, respectively. Values were obtained by nonlinear regression of dose-response curves. Data represent three independent experiments. (B) Prediction accuracies of models for predicting peptide toxicity, evaluated on a randomly selected 20% test set from the curated dataset. (C) Experimental validation of the toxicity predicted score as a counter-screening filter. Of the 81 peptides selected using a toxicity score threshold of 0.2, 97.5% were non-hemolytic based on HC 50 , 74.1% were non-cytotoxic based on CC 50 , and 71.6% were classified as non-toxic using the combined endpoint min(HC 50 , CC 50 ). Peptides with HC 50 or CC 50 values > 64 μmol L −1 (estimated by non-linear regression) were considered non-hemolytic or non-cytotoxic, respectively. (D) Heat map shows the percentage of secondary structure for each peptide calculated using the BeStSel algorithm. Ternary plot showing the secondary structure fraction for each of the selected peptides.

Article Snippet: We evaluated a set of synthesized peptide candidates comprising 120 peptide entries, representing 60 unique backbone sequences with distinct N-terminus (Free vs Acetyl) and C-terminus (Free vs Amide) states, against a panel spanning Gram-negative ( A. baumannii ATCC 19606, E. coli ATCC 11775, K. pneumoniae ATCC 13883, P. aeruginosa PAO1, S. enterica ATCC 9150, and S. enterica Typhimurium ATCC 700720) and Gram-positive species ( B. subtilis ATCC 23857, S. aureus ATCC 12600, L. monocytogenes ATCC 19111, E. faecalis ATCC 700802, and E. faecium ATCC 700221) ( Figure S5 ).

Techniques: Bacteria, Incubation, Concentration Assay, Lysis, Biomarker Discovery