Journal: bioRxiv

Article Title: MCC950/CRID3 potently targets the NACHT domain of wildtype NLRP3 but not disease-associated mutants for inflammasome inhibition

doi: 10.1101/634493

Figure Lengend Snippet: (A-F) Wild type (A- B), Nlrp3 L351P/L351P (C-D) or Nlrp3 A350V/A350V (E-F) BMDMs that were transduced with a Cre-recombinase expressing lentiviral vector, were left unstimulated (Ctrl) or stimulated with LPS and then left untreated or treated with ATP or nigericin (Nig) in absence or presence of MCC950/CRID3. Supernatants was analyzed for IL-1β (A,C,E) and IL-18 (B,D,F) secretion. Graphs show mean ± s.d. of triplicate wells and represent three independent experiments.

Article Snippet: To induce lentivirus production, the lentiviral GFP.Cre empty vector (20781, Addgene) together with 2 nd generation packaging vector psPAX2 (12260, Addgene) and VSV-G-expressing envelope plasmid pCMV-VSV-G (8454, Addgene) were transfected into HEK293 T cells using jetPRIME transfection reagent (114-15, PolyPlus Transfect).

Techniques: Transduction, Expressing, Plasmid Preparation

Journal: Molecular Systems Biology

Article Title: AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

doi: 10.1038/s44320-024-00019-8

Figure Lengend Snippet: ( A ) Schematic overview of the LuTHy-BRET and LuTHy-LuC assays. X: Protein X, Y: Protein Y, D: NanoLuc donor, A: mCitrine acceptor, AB: antibody. ( B ) With the LuTHy assay, each protein pair X–Y can be tested in eight possible configurations (N- vs. C-terminal fusion for each protein), and proteins can be swapped from one tag to the other resulting in 16 quantitative scores for each protein pair, i.e., eight for LuTHy-BRET and eight for LuTHy-LuC. ( C ) Line plots showing the fraction of protein pairs that scored positive ( y axis) dependent on the quantitative interaction scores ( x axis) for 10 binary PPI assay versions. For each tested protein pair, the tagging configuration with the highest interaction score is used. For LuTHy all eight tagging configurations were tested, whereas for MN2H, VN2H, YN2H, GPCA, NanoBi four and for KISS, MAPPIT and SIMPL two tagging configurations were tested. Recovery rates at maximum specificity, i.e., where none of the protein pairs in the RRS scored positive (0%), are indicated. Note that in Choi et al (Choi et al, ) recovery rates at maximum specificity were calculated by using distinct cutoffs for each tagging configuration. ( D ) Line plots showing the fraction of protein pairs that scored positive ( y axis) dependent on the distribution of interaction scores, i.e., the mean of all interaction scores + n*(sd) ( x axis) for 10 binary PPI assay versions. Recovery rates at mean + 1 standard deviation are indicated. ( E ) Line plots showing the fraction of protein pairs that scored positive ( y axis) dependent on the distribution of interaction scores, i.e., the median of all interaction scores + n*(sd) ( x axis) for 10 binary PPI assays. Recovery rates at median + 1 standard deviation are indicated. LuTHy experiments from this study were repeated twice with n = 2, biological replicates, each containing n = 3 technical replicates; SIMPL from Yao et al (Yao et al, ); all other from Choi et al (Choi et al, ). Note that the SIMPL assay was benchmarked by Yao et al (Yao et al, ) against 88 positive proteins pairs derived from the hsPRS-v1 (Venkatesan et al, ) and as a random reference set against “88 protein pairs with baits and preys selected from the PRS but used in combinations determined computationally to have low probability of interaction” (Yao et al, ).

Article Snippet: For the mN2H assay, additional control plasmids (pDEST-N2H-F1-empty vector, Addgene #125551; pDEST-N2H-F2-empty vector, Addgene #125552) were used, as previously described (Choi et al, ).

Techniques: Standard Deviation, Derivative Assay

Journal: Molecular Systems Biology

Article Title: AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

doi: 10.1038/s44320-024-00019-8

Figure Lengend Snippet: ( A ) Receiver characteristic analysis comparing sensitivity and specificity between the five AFM-predicted structural models for PAE, ΔG and iA of the hsPRS-AF and hsRRS-AF. ( B ) Bar plots showing the fraction of hsPRS-AF and hsRRS-AF interactions with structures deposited in PDB that scored above classifier probabilities of 50%, 75% and 95% by AlphaFold-Multimer (i) by LuTHy (ii) or the mean recovery of N2H (MN2H, VN2H, YN2H), GPCA, KISS, MAPPIT and NanoBiT (iii). Data for the SIMPL assay was excluded for this analysis due to the different composition of the reference sets. LuTHy experiments from this study were repeated two times with n = 2, biological replicates, each containing n = 3 technical replicates; AFM was used to predict n = 5 structural models; all other from Choi et al (Choi et al, ). Bars and error bars in this figure represent mean values and standard error of the proportion, respectively.

Article Snippet: For the mN2H assay, additional control plasmids (pDEST-N2H-F1-empty vector, Addgene #125551; pDEST-N2H-F2-empty vector, Addgene #125552) were used, as previously described (Choi et al, ).

Techniques:

Journal: Molecular Systems Biology

Article Title: AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

doi: 10.1038/s44320-024-00019-8

Figure Lengend Snippet: ( A ) Venn diagrams showing the overlap between interactions recovered by LuTHy at >50%, >75% and >95% probabilities and interactions deposited in the IntAct database (Orchard et al, ). ( B ) Scatter plot showing normalized mN2H ratios ( y axis) of each of the eight SARS-CoV-2 interactions newly identified with LuTHy ( x axis). Average classifier probabilities obtained from the hsPRS-v2/hsRRS-v2 mN2H models are displayed as the size of the data points and as a colored grid in the background. ( C ) Scatter plot showing normalized mN2H ratios ( x axis) against classifier probabilities ( y axis) for the newly identified SARS-CoV-2 interactions selected for validation. ( D ) Bar plots showing the fraction (left y axis) and number (right y axis) of newly identified SARS-CoV-2 interactions selected for validation that scored above classifier probabilities of 50%, 75% or 95% with mN2H. Bars and error bars represent mean values and standard error of the proportion, respectively, with n = 3 biological replicates. ( E ) Heatmaps showing the mN2H classifier probabilities for the newly identified SARS-CoV-2 interactions selected for validation. ( F ) Boxplots showing predicted alignment error (PAE), solvation-free energy (ΔG) and interface area (iA) from AlphaFold-Multimer (AFM) predicted SARS-CoV-2-AF structures. Boxplots display the median, lower and upper hinges of the 25th and 75th percentiles and lower and upper whiskers extending from the hinges with 1.5× the interquartile range. Each dot represents one predicted structural model. ( G ) Scatter plot showing PAE ( x axis) against interface area ( y axis) for all SARS-CoV-2-AF (orange) protein pairs. Average classifier probability predicted by the 100 maSVM models trained by the hsPRS-AF and hsRRS-AF set (see Fig. ), is displayed as the size of the data points. Each point in the colored grid in the background displays the average classifier probabilities from the 100 maSVM models. ( H ) Scatter plot showing the ΔG ( x axis) for all five AFM-predicted structural SARS-CoV-2-AF models against the LuTHy-BRET determined binding strengths (BRET 50 , see Appendix Fig. S ). The respective log-transformed interface areas are indicated by the fill color of the data points. A linear regression fit through the data is shown and the Spearman correlation coefficient (R) and P value are indicated. ( I ) Barplot showing the fraction of AFM-predicted structures with 0–75%, 75–95% and >95% classification probability that have an experimentally reported structure deposited to the PDB (Berman et al, ) database. ( J , K ) Luminescence ( J ) and fluorescence ( K ) values from LuTHy-BRET donor saturation experiments, where constant amounts of NSP10-NL WT or K93E (Lys93Glu) are co-expressed with increasing amounts of mCitrine-NSP16 WT or D106K (Asp106Lys). Experiments with NSP10-NL WT and K93E were repeated two times, with n = 2, biological replicates, and each with n = 2 technical replicates; experiments with mCit-NSP16 WT and D106K were repeated four times, with n = 4, biological replicates, and each with two technical replicates, n = 2. Bars and error bars represent the mean and standard deviation, respectively.

Article Snippet: For the mN2H assay, additional control plasmids (pDEST-N2H-F1-empty vector, Addgene #125551; pDEST-N2H-F2-empty vector, Addgene #125552) were used, as previously described (Choi et al, ).

Techniques: Biomarker Discovery, Binding Assay, Transformation Assay, Fluorescence, Standard Deviation

Journal: Molecular Systems Biology

Article Title: AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

doi: 10.1038/s44320-024-00019-8

Figure Lengend Snippet: ( A ) Structures of the protein complexes analyzed in this study: LAMTOR (PDB: 6EHR), BRISC (PDB: 6H3C) and MIS12 (PDB: 5LSK). ( B ) Binary interaction approach to systematically map PPIs within distinct complexes. Every protein subunit from each complex was screened against every other one (all-by-all, 16 × 16 matrix). ( C – E ) Scatter plot showing ( C ) log-transformed and normalized in-cell mCitrine expression ( x axis) against normalized cBRET ratios ( y axis), ( D ) number of protein pairs ( x axis) against log-transformed and normalized cLuC ratios ( y axis) or ( E ) the number of protein pairs ( x axis) against the log-transformed and normalized mN2H ratios ( y axis) for all protein pairs of the LAMTOR (yellow), BRISC (blue) and MIS12 (green) complexes and inter-complex (magenta) protein pairs from all eight tagging configurations. Average classifier probabilities from the 50 maSVM models for LuTHy-BRET ( C ) and LuTHy-LuC ( D ) or 100 maSVM models for mN2H ( E ) are displayed as the size of the data points and as a colored grid in the background. ( F – H ) Scatter plot showing on the x axis the normalized ( F ) cBRET ratios, ( G ) cLuC ratios, or ( H ) mN2H ratios against classifier probabilities ( y axis) for protein pairs of the BRISC (blue), LAMTOR (yellow) and MIS12 (green) complexes and inter-complex (magenta) protein pairs from all eight tagging configurations. ( I – K ) Bar plots showing the fraction of protein pairs of the LAMTOR (yellow), BRISC (blue) and MIS12 (green) complexes and inter-complex protein pairs that scored above the classifier probabilities of 50%, 75% or 95% by ( I ) LuTHy-BRET, ( J ) LuTHy-LuC, and ( K ) mN2H. Only the highest classifier probability per tested tagging configuration is considered. ( L ) Tile plots showing the classifier probabilities for the Donor/F1 protein pairs ( x axis) against the Acceptor/F2 protein pairs ( y axis) for LuTHy-BRET (orange, left), LuTHy-LuC (purple, middle) and mN2H (green, right) for protein pairs above 75% or 95%. Only the highest classifier probability per tested tagging configuration is shown. LuTHy experiments were performed in HEK293 cells two times with n = 2 biological replicates, each containing n = 3 technical replicates. mN2H experiments were performed in HEK293T cells four times with n = 4 biological replicates and n = 1 technical replicate. Tiles of not expressed constructs are filled black and respective protein names are colored in red. Bars and error bars in this figure represent mean values and standard error of the proportion, respectively. .

Article Snippet: For the mN2H assay, additional control plasmids (pDEST-N2H-F1-empty vector, Addgene #125551; pDEST-N2H-F2-empty vector, Addgene #125552) were used, as previously described (Choi et al, ).

Techniques: Transformation Assay, Expressing, Construct