Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting

Table_1_Lineage-level species distribution model to assess the impact of climate change on the habitat suitability of Boleophthalmus pectinirostris.docx

Global climate change has profound impacts on the habitats of marine organisms, and predicting the habitat changes of species under climate change conditions is crucial for species sustainability. Boleophthalmus pectinirostris is an intertidal fish species that holds significant ecological and economic value. To better protect and manage its resources, this study aimed to predict its current potential distribution and habitat changes under different climate scenarios in the future. This study firstly quantified the hypervolume niches of the three lineages (AE1, AE2, and AES lineages) and compared the niche differentiation among them. Furthermore, this study constructed species-level and lineage-level species distribution models (SDMs) to assess the impact of climate change on the habitat suitability of B. pectinirostris. The result of the niche differentiation assessment showed that there was marked differentiation in niches among the three lineages. The responses of different lineages to environmental variables were different, suggesting that lineage-level models may provide more accurate prediction results. According to the model predictions, the AES may have greater resilience to climate change and may experience habitat expansion in the future, while the AE1 and the AE2 may face habitat loss in some regions. Climate change-driven shifts in oceanic conditions were anticipated to affect the distribution and community structure of marine organisms. This study assessed the impact of climate change on the suitable habitat range of three lineages of B. pectinirostris using SDMs. Consistent with previous studies, the results of our study indicated that lineage-level SDMs may be more reliable than species-level SDMs for species with population differentiation in terms of the accuracy of predictions. In addition, considering the vulnerability of the AE1 and AE2 lineages to climate change, conserving these two lineages should be given a higher priority. The results of this study will provide important information for the future management and conservation of this species.</p

DataSheet_1_Lineage-level species distribution model to assess the impact of climate change on the habitat suitability of Boleophthalmus pectinirostris.docx

Global climate change has profound impacts on the habitats of marine organisms, and predicting the habitat changes of species under climate change conditions is crucial for species sustainability. Boleophthalmus pectinirostris is an intertidal fish species that holds significant ecological and economic value. To better protect and manage its resources, this study aimed to predict its current potential distribution and habitat changes under different climate scenarios in the future. This study firstly quantified the hypervolume niches of the three lineages (AE1, AE2, and AES lineages) and compared the niche differentiation among them. Furthermore, this study constructed species-level and lineage-level species distribution models (SDMs) to assess the impact of climate change on the habitat suitability of B. pectinirostris. The result of the niche differentiation assessment showed that there was marked differentiation in niches among the three lineages. The responses of different lineages to environmental variables were different, suggesting that lineage-level models may provide more accurate prediction results. According to the model predictions, the AES may have greater resilience to climate change and may experience habitat expansion in the future, while the AE1 and the AE2 may face habitat loss in some regions. Climate change-driven shifts in oceanic conditions were anticipated to affect the distribution and community structure of marine organisms. This study assessed the impact of climate change on the suitable habitat range of three lineages of B. pectinirostris using SDMs. Consistent with previous studies, the results of our study indicated that lineage-level SDMs may be more reliable than species-level SDMs for species with population differentiation in terms of the accuracy of predictions. In addition, considering the vulnerability of the AE1 and AE2 lineages to climate change, conserving these two lineages should be given a higher priority. The results of this study will provide important information for the future management and conservation of this species.</p

Table_2_Lineage-level species distribution model to assess the impact of climate change on the habitat suitability of Boleophthalmus pectinirostris.docx

Global climate change has profound impacts on the habitats of marine organisms, and predicting the habitat changes of species under climate change conditions is crucial for species sustainability. Boleophthalmus pectinirostris is an intertidal fish species that holds significant ecological and economic value. To better protect and manage its resources, this study aimed to predict its current potential distribution and habitat changes under different climate scenarios in the future. This study firstly quantified the hypervolume niches of the three lineages (AE1, AE2, and AES lineages) and compared the niche differentiation among them. Furthermore, this study constructed species-level and lineage-level species distribution models (SDMs) to assess the impact of climate change on the habitat suitability of B. pectinirostris. The result of the niche differentiation assessment showed that there was marked differentiation in niches among the three lineages. The responses of different lineages to environmental variables were different, suggesting that lineage-level models may provide more accurate prediction results. According to the model predictions, the AES may have greater resilience to climate change and may experience habitat expansion in the future, while the AE1 and the AE2 may face habitat loss in some regions. Climate change-driven shifts in oceanic conditions were anticipated to affect the distribution and community structure of marine organisms. This study assessed the impact of climate change on the suitable habitat range of three lineages of B. pectinirostris using SDMs. Consistent with previous studies, the results of our study indicated that lineage-level SDMs may be more reliable than species-level SDMs for species with population differentiation in terms of the accuracy of predictions. In addition, considering the vulnerability of the AE1 and AE2 lineages to climate change, conserving these two lineages should be given a higher priority. The results of this study will provide important information for the future management and conservation of this species.</p

Positively Charged Donor–Acceptor Type Thieno[3,4‑<i>b</i>]pyrazine-Based Conjugated Polymer for Near-Infrared Light Triggered Rapid and Efficient Photothermal Therapy of Sterilization

Diseases caused by antibiotic-resistant pathogenic bacteria are seriously threatening human health. Therefore, the development of new antimicrobial materials and treatment strategies is urgently needed. Herein, we designed and synthesized a donor–acceptor (D-A) structured conjugated polymer Poly­(TP-T), which is functionalized with a positively charged side chain for selective contact with bacterial cells through electrostatic interaction for rapid and efficient near-infrared light-activated photothermal antimicrobial therapy. Under 808 nm laser irradiation, Poly­(TP-T)-based nanoparticles exhibit a high photothermal conversion efficiency of 48.7% and thus excellent and broad-spectrum antimicrobial activity with almost 100% inhibition ratio against both Gram-(+) bacteria (S. aureus) and Gram-(−) bacteria (E. coli) within a few minutes. This work broadens the range of photoactive materials that can be used for highly efficient antimicrobial phototherapy and offers insight into the relationship between the polymer structure and phototherapeutic performances

Specific Lipid Binding of Membrane Proteins in Detergent Micelles Characterized by NMR and Molecular Dynamics

Many membrane proteins bind specifically to lipids as an integral component of their structures. The ability of detergents to support lipid binding is thus an important consideration when solubilizing membrane proteins for structural studies. In particular, the zwitterionic phosphocholine (PC)-based detergents, which have been widely used in solution NMR studies of channels and transporters, are controversial because of their strong solubilization power and thus perceived as more denaturing than nonionic detergents such as the maltosides. Here, we investigate the ability of the mitochondrial ADP/ATP carrier (AAC) to specifically bind cardiolipin, a mitochondrial lipid important for the carrier function, in dodecylphosphocholine (DPC) micelles. We found that in DPC, the AAC specifically binds cardiolipin in a manner consistent with the bound cardiolipins found in the crystal structures of the AAC determined in <i>n</i>-decyl β-d-maltoside. Our results suggest that PC detergent is compatible with specific lipid binding and that PC detergent mixed with the relevant lipid represents a viable solubilization system for NMR studies of membrane proteins

DataSheet_1_High-quality chromosome-level genome assembly of Pacific cod, Gadus macrocephalus.docx

The full text of this article can be freely accessed on the publisher's website

Genotoxicity-Related Chemistry of Human Metabolites of Benzo[<i>ghi</i>]perylene (B[<i>ghi</i>]P) Investigated using Electro-Optical Arrays and DNA/Microsome Biocolloid Reactors with LC-MS/MS

There is limited and sometimes contradictory information about the genotoxicity of the polycyclic aromatic hydrocarbon benzo­[<i>ghi</i>]­perylene (B­[<i>ghi</i>]­P). Using recently developed metabolic toxicity screening arrays and a biocolloid reactor-LC-MS/MS approach, both featuring films of DNA and human metabolic enzymes, we demonstrated the relatively low reactivity of metabolically activated B­[<i>ghi</i>]P toward DNA. Electro-optical toxicity screening arrays showed that B­[<i>ghi</i>]P metabolites damage DNA at a 3-fold lower rate than benzo­[<i>a</i>]­pyrene (B­[<i>a</i>]­P), whose metabolites have a strong and well-understood propensity for DNA damage. Metabolic studies using magnetic bead biocolloid reactors coated with microsomal enzymes in 96-well plates showed that cyt P450s 1A1 and 1B1 provide high activity for B­[<i>ghi</i>]P and B­[<i>a</i>]P conversion. Consistent with published results, the major metabolism of B­[<i>ghi</i>]P involved oxidations at 3,4 and 11,12 positions, leading to the formation of B­[<i>ghi</i>]P 3,4-oxide and B­[<i>ghi</i>]P 3,4,11,12-bisoxide. B­[<i>ghi</i>]P 3,4-oxide was synthesized and reacted with deoxyadenosine at N6 and N7 positions and with deoxyguanosine at the N2 position. B­[<i>ghi</i>]P 3,4-oxide is hydrolytically unstable and transforms into the 3,4-diol or converts to 3- or 4-hydroxy B­[<i>ghi</i>]­P. LC-MS/MS of reaction products from the magnetic biocolloid reactor particles coated with DNA and human enzymes revealed for the first time that a major DNA adduct results from the reaction between B­[<i>ghi</i>]P 3,4,11,12-bisoxide and deoxyguanosine. Results also demonstrated 5-fold lower formation rates of the major DNA adduct for B­[<i>ghi</i>]P metabolites compared to B­[<i>a</i>]­P. Overall, results from both the electro-optical array and biocolloid reactor-LC-MS/MS consistently suggest a lower human genotoxicity profile of B­[<i>ghi</i>]P than B­[<i>a</i>]­P

Mutagenic Bypass of an Oxidized Abasic Lesion-Induced DNA Interstrand Cross-Link Analogue by Human Translesion Synthesis DNA Polymerases

5′-(2-Phosphoryl-1,4-dioxobutane) (DOB) is an oxidized abasic site that is produced by several antitumor agents and γ-radiolysis. DOB reacts reversibly with a dA opposite the 3′-adjacent nucleotide to form DNA interstrand cross-links (ICLs), genotoxic DNA lesions that can block DNA replication and transcription. Translesion synthesis (TLS) is an important step in several ICL repair pathways to bypass unhooked intermediates generated by endonucleolytic incision. The instability of DOB-ICLs has made it difficult to learn about their TLS-mediated repair capability and mutagenic potential. We recently developed a method for chemically synthesizing oligonucleotides containing a modified DOB-ICL analogue. Herein, we examined the capabilities of several highly relevant eukaryotic TLS DNA polymerases (pols), including human pol η, pol κ, pol ι, pol ν, REV1, and yeast pol ζ, to bypass this DOB-ICL analogue. The prelesion, translesion, and postlesion replication efficiency and fidelity were examined. Pol η showed moderate bypass activity when encountering the DOB-ICL, giving major products one or two nucleotides beyond the cross-linked template nucleotide. In contrast, DNA synthesis by the other pols was stalled at the position before the cross-linked nucleotide. Steady-state kinetic data and liquid chromatography–mass spectrometry sequencing of primer extension products by pol η unambiguously revealed that pol η-mediated bypass is highly error-prone. Together, our study provides the first set of <i>in vitro</i> evidence that the DOB-ICL is a replication-blocking and highly miscoding lesion. Compared to several other TLS pols examined, pol η is likely to contribute to the TLS-mediated repair of the DOB-ICL <i>in vivo</i>