Human β-glucuronidase (HGUSB), a key lysosomal glycosyl hydrolase for the degradation pathway of glycosaminoglycans (GAGs), plays a crucial role in cell proliferation and inflammation, making it a promising target for novel therapeutic strategies including antibody-drug conjugates (ADCs) with β-glucuronic linkers. In this study, molecular docking and molecular dynamics (MD) simulations were performed to investigate the conformational stability of HGUSB in complex with different ligands, including substrates, inhibitors, and β-glucuronic linkers. Our rationale approach includes the evaluation of commercial substrates and a known inhibitor with different binding stoichiometries to identify the most favorable configuration and the most stable conformation of the enzyme. Based on the binding mechanism of HGUSB to these well-known ligands, the interaction with commercial linkers was evaluated, providing a structural determination of the recognition mechanism between the enzyme and ADCs. MD simulations on HGUSB::Linker complexes revealed that the maleimide-containing hydrophilic β-glucuronide, exhibited the most stable binding making it the best fitting linker among those analyzed in this study. Overall, this study identifies the optimal binding configuration of the HGUSB enzyme for investigating small molecule interactions and, despite the endogenous homotetrameric assembly, justifies the use of a simplified monomeric model for the study of larger macromolecular complexes, like linker analysis, ensuring an efficient and accurate computational approach. These findings lay the groundwork for a rationale optimization of β-glucuronic linker-based ADCs, offering new perspectives for targeted cancer therapies.
{"title":"In Silico Structural Analysis of Human β-Glucuronidase for Antibody-Drug Conjugates Optimization.","authors":"Giorgia Canini, Simona Saporiti, Crescenzo Coppa, Mara Rossi, Fabio Centola, Alessandro Arcovito","doi":"10.1002/prot.70077","DOIUrl":"10.1002/prot.70077","url":null,"abstract":"<p><p>Human β-glucuronidase (HGUSB), a key lysosomal glycosyl hydrolase for the degradation pathway of glycosaminoglycans (GAGs), plays a crucial role in cell proliferation and inflammation, making it a promising target for novel therapeutic strategies including antibody-drug conjugates (ADCs) with β-glucuronic linkers. In this study, molecular docking and molecular dynamics (MD) simulations were performed to investigate the conformational stability of HGUSB in complex with different ligands, including substrates, inhibitors, and β-glucuronic linkers. Our rationale approach includes the evaluation of commercial substrates and a known inhibitor with different binding stoichiometries to identify the most favorable configuration and the most stable conformation of the enzyme. Based on the binding mechanism of HGUSB to these well-known ligands, the interaction with commercial linkers was evaluated, providing a structural determination of the recognition mechanism between the enzyme and ADCs. MD simulations on HGUSB::Linker complexes revealed that the maleimide-containing hydrophilic β-glucuronide, exhibited the most stable binding making it the best fitting linker among those analyzed in this study. Overall, this study identifies the optimal binding configuration of the HGUSB enzyme for investigating small molecule interactions and, despite the endogenous homotetrameric assembly, justifies the use of a simplified monomeric model for the study of larger macromolecular complexes, like linker analysis, ensuring an efficient and accurate computational approach. These findings lay the groundwork for a rationale optimization of β-glucuronic linker-based ADCs, offering new perspectives for targeted cancer therapies.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"838-852"},"PeriodicalIF":2.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12865248/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145410874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Proteolysis Targeting Chimeras (PROTACs) represent a transformative approach to drug development by leveraging the intracellular ubiquitin-proteasome system (UPS) for the selective degradation of target proteins. A PROTAC molecule comprises three essential components: a ligand that binds to the E3 ubiquitin ligase, a ligand that targets the protein of interest, and a flexible linker that connects the two. This distinctive structure enables the PROTAC to simultaneously engage with both the target protein and the E3 ligase, facilitating their interaction. Such proximity initiates the ubiquitination of the target protein, marking it for recognition and subsequent degradation. In this study, we benchmark ternary complexes based on PROTACs using four recently employed predictive tools: Chai-1, AlphaFold2, AlphaFold3, and Protenix. Comparative analysis indicated that the ternary complexes predicted by the four prediction tools demonstrated satisfactory accuracy (Cα-RMSD < 10 Å). Among the evaluated tools, three-Chai-1, AlphaFold3, and Protenix-demonstrated superior performance in over half of the tests, while AlphaFold2 exhibited comparatively lower performance. However, significant challenges remained in accurately predicting the orientation of POI and the E3 ligase (Cα-RMSD < 10 Å when POI or E3 ligase were used as reference), as well as the position of the small molecule PROTAC (RMSD < 5 Å). By benchmarking these tools, we underscore recent advancements in protein structure prediction, enhance our understanding of the mechanisms underpinning PROTAC complexes, and provide a valuable reference for evaluating the binding conformations of other ternary complexes, as well as for the development of future predictive tools.
{"title":"Benchmarking Deep Learning for PROTAC Ternary Complex Prediction.","authors":"Haoyu Chen, Fengjiao Wei, Jiajie Li, Zhuobin Shi, Shanshan Chen, Yu Fang, Shuxin Li, Xinru Gao, Lin Ju, Senbiao Fang, Ximing Xu","doi":"10.1002/prot.70117","DOIUrl":"https://doi.org/10.1002/prot.70117","url":null,"abstract":"<p><p>Proteolysis Targeting Chimeras (PROTACs) represent a transformative approach to drug development by leveraging the intracellular ubiquitin-proteasome system (UPS) for the selective degradation of target proteins. A PROTAC molecule comprises three essential components: a ligand that binds to the E3 ubiquitin ligase, a ligand that targets the protein of interest, and a flexible linker that connects the two. This distinctive structure enables the PROTAC to simultaneously engage with both the target protein and the E3 ligase, facilitating their interaction. Such proximity initiates the ubiquitination of the target protein, marking it for recognition and subsequent degradation. In this study, we benchmark ternary complexes based on PROTACs using four recently employed predictive tools: Chai-1, AlphaFold2, AlphaFold3, and Protenix. Comparative analysis indicated that the ternary complexes predicted by the four prediction tools demonstrated satisfactory accuracy (Cα-RMSD < 10 Å). Among the evaluated tools, three-Chai-1, AlphaFold3, and Protenix-demonstrated superior performance in over half of the tests, while AlphaFold2 exhibited comparatively lower performance. However, significant challenges remained in accurately predicting the orientation of POI and the E3 ligase (Cα-RMSD < 10 Å when POI or E3 ligase were used as reference), as well as the position of the small molecule PROTAC (RMSD < 5 Å). By benchmarking these tools, we underscore recent advancements in protein structure prediction, enhance our understanding of the mechanisms underpinning PROTAC complexes, and provide a valuable reference for evaluating the binding conformations of other ternary complexes, as well as for the development of future predictive tools.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146114974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-07-28DOI: 10.1002/prot.70027
Tanguy Scaillet, Élise Pierson, Marianne Fillet, Johan Wouters
Amino acid L-serine (L-Ser) is a precursor of various biomolecules, including other amino acids, glutathione, and nucleotides. The metabolism of this amino acid is crucial in diseases such as brucellosis. Previous studies have revealed that the enzymes involved in L-Ser biosynthesis are essential for Brucella replication, making them potential targets for the development of new drugs. Here, we focus on Brucella melitensis phosphoserine phosphatase (BmPSP), which catalyzes the dephosphorylation of phosphoserine in L-Ser. The enzyme is characterized through enzymatic and structural studies, leading to the discovery of its first crystallographic structures. The interactions of BmPSP with different ligands are also investigated. We demonstrate that the substitution of its Mg2+ cofactor with Ca2+ inhibits the enzyme and results in a slight movement of catalytic residues in the active site. Crystallographic structures of BmPSP in complex with substrate, reaction products, and substrate analogs are also detailed, revealing the interaction between these molecules and the active site residues. This structural study provides a better understanding of phosphoserine phosphatases, highlighting the involvement of two highly conserved residues in the mechanism of substrate entry into the active site.
{"title":"Structural and Enzymological Characterization of Phosphoserine Phosphatase From Brucella melitensis.","authors":"Tanguy Scaillet, Élise Pierson, Marianne Fillet, Johan Wouters","doi":"10.1002/prot.70027","DOIUrl":"10.1002/prot.70027","url":null,"abstract":"<p><p>Amino acid L-serine (L-Ser) is a precursor of various biomolecules, including other amino acids, glutathione, and nucleotides. The metabolism of this amino acid is crucial in diseases such as brucellosis. Previous studies have revealed that the enzymes involved in L-Ser biosynthesis are essential for Brucella replication, making them potential targets for the development of new drugs. Here, we focus on Brucella melitensis phosphoserine phosphatase (BmPSP), which catalyzes the dephosphorylation of phosphoserine in L-Ser. The enzyme is characterized through enzymatic and structural studies, leading to the discovery of its first crystallographic structures. The interactions of BmPSP with different ligands are also investigated. We demonstrate that the substitution of its Mg<sup>2+</sup> cofactor with Ca<sup>2+</sup> inhibits the enzyme and results in a slight movement of catalytic residues in the active site. Crystallographic structures of BmPSP in complex with substrate, reaction products, and substrate analogs are also detailed, revealing the interaction between these molecules and the active site residues. This structural study provides a better understanding of phosphoserine phosphatases, highlighting the involvement of two highly conserved residues in the mechanism of substrate entry into the active site.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"502-514"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144735758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-09-21DOI: 10.1002/prot.70054
Nilvea Ramalho de Oliveira, Andrei Santos Siqueira, Paulo Sérgio Alves Bueno, Evonnildo Costa Gonçalves, Juliano Zanette
Metallothioneins (MTLs) are small, cysteine-rich proteins known for their ability to bind metal ions and exhibit flexible, disordered structures. The structural and functional characteristics of metallothionein I (MTL-1) from Caenorhabditis elegans were investigated, focusing on its behavior in both metal free (MTL-1 Apo) and metal-bond states with Zn2+, Cd2+, Cu2+, Hg2+, and Pb2+ divalent metal ions. Using molecular dynamics simulations and 3D modeling via AlphaFold, we characterized the flexibility and stability of MTL. The MTL-1 Apo form displayed high flexibility, aligning with its intrinsically disordered protein (IDP) nature, with 89.3% of its structure composed of coils, bends, and turns. Metal binding significantly enhanced the protein's stability, particularly with Zn2+, Cd2+, Cu2+, and Hg2+, reducing root mean square deviation (RMSD), root mean square fluctuation (RMSF), accessible surface area (SASA) and radius of gyration (R g) values, indicating structural compaction. Conversely, Pb2+ showed a weaker stabilizing effect, with a more dynamic and less stable structure. Structural analysis revealed that conserved cysteine residues coordinate the metal through strong thiolate interactions, with additional contributions from non-cysteine residues, such as Glu and Lys. The study underscores the importance of incorporating intrinsically disordered protein models in MD simulations to provide deeper insights into how metallothionein's flexibility and stability vary in response to different metal ions, offering a structural perspective on their biological interactions and behavior under diverse environmental conditions. While thermodynamic aspects were not directly assessed, the results reveal consistent conformation trends across different metal coordination states.
{"title":"Metal-Coordination Specificity and Structural Dynamics of C. elegans Metallothionein I: Insights From 3D Modeling and MD Simulations.","authors":"Nilvea Ramalho de Oliveira, Andrei Santos Siqueira, Paulo Sérgio Alves Bueno, Evonnildo Costa Gonçalves, Juliano Zanette","doi":"10.1002/prot.70054","DOIUrl":"10.1002/prot.70054","url":null,"abstract":"<p><p>Metallothioneins (MTLs) are small, cysteine-rich proteins known for their ability to bind metal ions and exhibit flexible, disordered structures. The structural and functional characteristics of metallothionein I (MTL-1) from Caenorhabditis elegans were investigated, focusing on its behavior in both metal free (MTL-1 Apo) and metal-bond states with Zn<sup>2+</sup>, Cd<sup>2+</sup>, Cu<sup>2+</sup>, Hg<sup>2+</sup>, and Pb<sup>2+</sup> divalent metal ions. Using molecular dynamics simulations and 3D modeling via AlphaFold, we characterized the flexibility and stability of MTL. The MTL-1 Apo form displayed high flexibility, aligning with its intrinsically disordered protein (IDP) nature, with 89.3% of its structure composed of coils, bends, and turns. Metal binding significantly enhanced the protein's stability, particularly with Zn<sup>2+</sup>, Cd<sup>2+</sup>, Cu<sup>2+</sup>, and Hg<sup>2+</sup>, reducing root mean square deviation (RMSD), root mean square fluctuation (RMSF), accessible surface area (SASA) and radius of gyration (R <sub>g</sub>) values, indicating structural compaction. Conversely, Pb<sup>2+</sup> showed a weaker stabilizing effect, with a more dynamic and less stable structure. Structural analysis revealed that conserved cysteine residues coordinate the metal through strong thiolate interactions, with additional contributions from non-cysteine residues, such as Glu and Lys. The study underscores the importance of incorporating intrinsically disordered protein models in MD simulations to provide deeper insights into how metallothionein's flexibility and stability vary in response to different metal ions, offering a structural perspective on their biological interactions and behavior under diverse environmental conditions. While thermodynamic aspects were not directly assessed, the results reveal consistent conformation trends across different metal coordination states.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"620-632"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12779199/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145115073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-08-28DOI: 10.1002/prot.70048
Bernardo Bonilauri
The exponential growth of biomedical and life sciences literature, including research on amyloid biology, has made it increasingly challenging to track new discoveries and gain a comprehensive understanding of the evolution of specific research fields. Advances in natural language models (NLM) and artificial intelligence (AI) approaches now enable large-scale analysis of scientific publications, uncovering hidden patterns and facilitating data-driven insights. Here, a two-dimensional mapping of the global amyloid research landscape is presented, using the transformer-based large language model PubMedBERT, in combination with t-SNE and Latent Dirichlet Allocation (LDA), to analyze more than 140 000 abstracts from the PubMed database. This analysis provides a comprehensive visualization of the amyloid field, capturing key trends such as the historical progression of amyloid research, the emergence of dominant subfields, the distribution of contributing authors and their respective countries, and the identification of latent research topics over time, including chemicals and small molecules. By integrating AI-driven text analysis with large-scale bibliometric data, this study offers a novel perspective on the evolution of amyloid research, facilitating a deeper interdisciplinary understanding. This work serves as a valuable interactive resource for researchers while highlighting the potential of machine learning-driven literature mapping in identifying knowledge gaps and guiding future investigations.
{"title":"The Evolving Landscape of Amyloid Research.","authors":"Bernardo Bonilauri","doi":"10.1002/prot.70048","DOIUrl":"10.1002/prot.70048","url":null,"abstract":"<p><p>The exponential growth of biomedical and life sciences literature, including research on amyloid biology, has made it increasingly challenging to track new discoveries and gain a comprehensive understanding of the evolution of specific research fields. Advances in natural language models (NLM) and artificial intelligence (AI) approaches now enable large-scale analysis of scientific publications, uncovering hidden patterns and facilitating data-driven insights. Here, a two-dimensional mapping of the global amyloid research landscape is presented, using the transformer-based large language model PubMedBERT, in combination with t-SNE and Latent Dirichlet Allocation (LDA), to analyze more than 140 000 abstracts from the PubMed database. This analysis provides a comprehensive visualization of the amyloid field, capturing key trends such as the historical progression of amyloid research, the emergence of dominant subfields, the distribution of contributing authors and their respective countries, and the identification of latent research topics over time, including chemicals and small molecules. By integrating AI-driven text analysis with large-scale bibliometric data, this study offers a novel perspective on the evolution of amyloid research, facilitating a deeper interdisciplinary understanding. This work serves as a valuable interactive resource for researchers while highlighting the potential of machine learning-driven literature mapping in identifying knowledge gaps and guiding future investigations.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"660-671"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-09-11DOI: 10.1002/prot.70047
Olga E Chepikova, Victoria I Bunik, Ivan V Rodionov, Neonila V Gorokhovets, Andrey A Zamyatnin, Lyudmila V Savvateeva
Cysteine cathepsins have been suggested as attractive therapeutic targets due to their critical role in several pathologies. In particular, inhibitors of cysteine cathepsins reduce the viability of tumor cells. The present study uses enzyme kinetics to characterize the interaction of human cathepsins L and S with their peptide substrate acetyl-QLLR-7-amino-4-methylcoumarin (Ac-QLLR-AMC) and peptide inhibitors with anti-tumor activity: FFSFGGAL (CS-PEP1) and acetyl-PLVE-fluoromethyl-ketone (Ac-PLVE-fmk). Due to multiple cellular locations of cathepsins, our study is conducted under different pH conditions, simulating lysosomal and cytosolic environments (pH 4.6 and 6.5-7.0). Catalytic activities of both cathepsins are higher at pH 6.5-7.0 compared to pH 4.6. Affinities for the substrate or inhibitor CS-PEP1 are higher for cathepsin L than S independent of pH, but show different pH sensitivities, reciprocating different pI's of the cathepsins. Mixed inhibition by CS-PEP1 is demonstrated for both cathepsins. While preincubation of cathepsins with CS-PEP1 does not enhance the inhibition, Ac-PLVE-fmk inactivates both cathepsins in the preincubation medium. A strong increase in the inactivation rate is observed with increasing pH in the interval including pK a of the active site cysteine residues of cathepsins, in agreement with the irreversible modification by mono-fluoromethyl ketones of the catalytic thiolate anion. At pH 4.6, cathepsin L has a higher affinity for Ac-PLVE-fmk, but a slower rate of the irreversible modification compared to cathepsin S. Our findings highlight opportunities for differential targeting of L and S cathepsins by peptide inhibitors in different cellular compartments, providing directions for cathepsin- and location-specific drug design.
{"title":"Kinetic Characterization of Inhibition of Cathepsins L and S by Peptides With Anticancer Potential.","authors":"Olga E Chepikova, Victoria I Bunik, Ivan V Rodionov, Neonila V Gorokhovets, Andrey A Zamyatnin, Lyudmila V Savvateeva","doi":"10.1002/prot.70047","DOIUrl":"10.1002/prot.70047","url":null,"abstract":"<p><p>Cysteine cathepsins have been suggested as attractive therapeutic targets due to their critical role in several pathologies. In particular, inhibitors of cysteine cathepsins reduce the viability of tumor cells. The present study uses enzyme kinetics to characterize the interaction of human cathepsins L and S with their peptide substrate acetyl-QLLR-7-amino-4-methylcoumarin (Ac-QLLR-AMC) and peptide inhibitors with anti-tumor activity: FFSFGGAL (CS-PEP1) and acetyl-PLVE-fluoromethyl-ketone (Ac-PLVE-fmk). Due to multiple cellular locations of cathepsins, our study is conducted under different pH conditions, simulating lysosomal and cytosolic environments (pH 4.6 and 6.5-7.0). Catalytic activities of both cathepsins are higher at pH 6.5-7.0 compared to pH 4.6. Affinities for the substrate or inhibitor CS-PEP1 are higher for cathepsin L than S independent of pH, but show different pH sensitivities, reciprocating different pI's of the cathepsins. Mixed inhibition by CS-PEP1 is demonstrated for both cathepsins. While preincubation of cathepsins with CS-PEP1 does not enhance the inhibition, Ac-PLVE-fmk inactivates both cathepsins in the preincubation medium. A strong increase in the inactivation rate is observed with increasing pH in the interval including pK <sub>a</sub> of the active site cysteine residues of cathepsins, in agreement with the irreversible modification by mono-fluoromethyl ketones of the catalytic thiolate anion. At pH 4.6, cathepsin L has a higher affinity for Ac-PLVE-fmk, but a slower rate of the irreversible modification compared to cathepsin S. Our findings highlight opportunities for differential targeting of L and S cathepsins by peptide inhibitors in different cellular compartments, providing directions for cathepsin- and location-specific drug design.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"582-597"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145042463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-09-17DOI: 10.1002/prot.70055
Syeda Sumayya Tariq, Urooj Qureshi, Mamona Mushtaq, Sajida Munsif, Mohammad Nur-E-Alam, Mohammed F Hawwal, Yan Wang, Zaheer Ul-Haq
Bromo-DragonFLY (BDF), a potent designer psychedelic drug with hallucinogenic properties, has recently emerged as a significant recreational substance. Named for its dragonfly-like molecular structure, BDF induces prolonged psychedelic effects, with hallucinations lasting several days. Clinical reports highlight severe toxicity, including confusion, tachycardia, hypertension, seizures, renal failure, and, in extreme cases, death. BDF acts as a potent agonist of the 5-HT2A serotonin receptor subtype, which mediates the behavioral and psychedelic effects of hallucinogens. Despite its increasing prevalence and associated clinical implications, the precise molecular mechanisms underlying BDF's interaction with 5-HT2A remain inadequately characterized, particularly from an in silico perspective. This study addresses this gap by employing a comprehensive in silico framework to investigate the molecular interactions of BDF with the 5-HT2A receptor. Molecular docking was used to identify binding sites, while all-atom molecular dynamics (MD) simulations provided insights into the stability of the protein-ligand complex, assessing deviations, local flexibility, and time-dependent gyration patterns. The results revealed stable and compact complex formation between BDF and 5-HT2A, characterized by minimal per-residue fluctuations and high hydrogen bond occupancy, suggesting a highly stable interaction as shown experimentally. Additionally, principal component analysis, leveraging machine learning algorithms, demonstrated consistent motion, while free energy profiles highlighted stable energy basins with minimal variations for the BDF-5-HT2A complex. These findings suggest strong binding affinities of BDF with the serotonin receptor, leading to highly stable complex formation. This study provides a foundational understanding of BDF's molecular interactions, offering critical insights into its role as a potent psychedelic agent and laying the groundwork for future investigations into the risks posed by novel designer drugs.
{"title":"In Silico Characterization of Bromo-DragonFLY Binding to the 5-HT<sub>2A</sub> Receptor: Molecular Insights Into a Potent Designer Psychedelic.","authors":"Syeda Sumayya Tariq, Urooj Qureshi, Mamona Mushtaq, Sajida Munsif, Mohammad Nur-E-Alam, Mohammed F Hawwal, Yan Wang, Zaheer Ul-Haq","doi":"10.1002/prot.70055","DOIUrl":"10.1002/prot.70055","url":null,"abstract":"<p><p>Bromo-DragonFLY (BDF), a potent designer psychedelic drug with hallucinogenic properties, has recently emerged as a significant recreational substance. Named for its dragonfly-like molecular structure, BDF induces prolonged psychedelic effects, with hallucinations lasting several days. Clinical reports highlight severe toxicity, including confusion, tachycardia, hypertension, seizures, renal failure, and, in extreme cases, death. BDF acts as a potent agonist of the 5-HT2A serotonin receptor subtype, which mediates the behavioral and psychedelic effects of hallucinogens. Despite its increasing prevalence and associated clinical implications, the precise molecular mechanisms underlying BDF's interaction with 5-HT2A remain inadequately characterized, particularly from an in silico perspective. This study addresses this gap by employing a comprehensive in silico framework to investigate the molecular interactions of BDF with the 5-HT<sub>2A</sub> receptor. Molecular docking was used to identify binding sites, while all-atom molecular dynamics (MD) simulations provided insights into the stability of the protein-ligand complex, assessing deviations, local flexibility, and time-dependent gyration patterns. The results revealed stable and compact complex formation between BDF and 5-HT<sub>2A</sub>, characterized by minimal per-residue fluctuations and high hydrogen bond occupancy, suggesting a highly stable interaction as shown experimentally. Additionally, principal component analysis, leveraging machine learning algorithms, demonstrated consistent motion, while free energy profiles highlighted stable energy basins with minimal variations for the BDF-5-HT<sub>2A</sub> complex. These findings suggest strong binding affinities of BDF with the serotonin receptor, leading to highly stable complex formation. This study provides a foundational understanding of BDF's molecular interactions, offering critical insights into its role as a potent psychedelic agent and laying the groundwork for future investigations into the risks posed by novel designer drugs.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"609-619"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145076829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-09-29DOI: 10.1002/prot.70036
Joseph A DePaolo-Boisvert, Karina Tuz, David D L Minh, Oscar X Juarez
The sodium-pumping ubiquinone oxidoreductase sodium pumping quinone reductase (NQR) is an important enzyme in the respiratory chain of multiple pathogenic gram-negative bacteria. NQR has been proposed as a viable antibiotic target due to its importance in supporting energy-consuming reactions and its absence in human cells. In this study, molecular dynamics simulations were conducted to characterize the interactions between the ubiquinone binding pocket of Vibrio cholerae NQR with its substrate analogue ubiquinone-4 and three potent inhibitors: HQNO, aurachin-D42, and korormicin-A. Through interaction fingerprinting, distance calculations, and clustering analysis, important binding motifs for each of these ligands were identified. Subunit B residues K54, F137, E144, V145, V155, E157, G158, F159, and F160 were frequently identified as establishing either hydrogen bonding interactions or hydrophobic interactions with these three ligands. The findings of this in silico study are interpreted in view of mutagenesis analyses previously published in the literature. The elucidation of important binding interactions associated with the inhibitors is critical as it informs structure-activity relationships, which are essential for the development of novel antibiotics targeting NQR.
{"title":"Molecular Dynamics Analysis of Inhibitor Binding Interactions in the Vibrio cholerae Respiratory Complex NQR.","authors":"Joseph A DePaolo-Boisvert, Karina Tuz, David D L Minh, Oscar X Juarez","doi":"10.1002/prot.70036","DOIUrl":"10.1002/prot.70036","url":null,"abstract":"<p><p>The sodium-pumping ubiquinone oxidoreductase sodium pumping quinone reductase (NQR) is an important enzyme in the respiratory chain of multiple pathogenic gram-negative bacteria. NQR has been proposed as a viable antibiotic target due to its importance in supporting energy-consuming reactions and its absence in human cells. In this study, molecular dynamics simulations were conducted to characterize the interactions between the ubiquinone binding pocket of Vibrio cholerae NQR with its substrate analogue ubiquinone-4 and three potent inhibitors: HQNO, aurachin-D42, and korormicin-A. Through interaction fingerprinting, distance calculations, and clustering analysis, important binding motifs for each of these ligands were identified. Subunit B residues K54, F137, E144, V145, V155, E157, G158, F159, and F160 were frequently identified as establishing either hydrogen bonding interactions or hydrophobic interactions with these three ligands. The findings of this in silico study are interpreted in view of mutagenesis analyses previously published in the literature. The elucidation of important binding interactions associated with the inhibitors is critical as it informs structure-activity relationships, which are essential for the development of novel antibiotics targeting NQR.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"649-659"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12779168/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-09-04DOI: 10.1002/prot.70046
Prabuddha Bhattacharya, Sumit Mittal
The mechanisms driving amyloid assembly have long intrigued structural biologists, as they offer insights into systemic fibrotic changes and the dynamic behavior of transthyretin (TTR) aggregation, crucial for developing amyloid-targeted therapies. In TTR-associated amyloidosis, amyloid fibrils form via destabilization of the tetramer into dimers and monomers. While many TTR mutations have been studied, the atomistic impact of multiple mutations on amyloid transthyretin (ATTR) self-assembly remains underexplored. To the best of our knowledge, this is the first computational analysis reporting the impact of the L110M mutation on ATTR peptide aggregation. Using triplicate 1 μs all-atom molecular dynamics (MD) simulations, totaling 18 μs, the conformational dynamics of cross-β amyloid fibrils in the ATTR(105-115) segment were examined for both wild-type and L110M mutant TTR. The L110M mutation consistently enhanced the β-sheet content in all oligomers, with increases of ~1%, ~5%, and ~4% over the wild-type in the 2-, 4-, and 8-peptide systems, respectively. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations revealed higher effective binding free energy for the L110M mutant, with residue M110 contributing significantly to stabilization. These results suggest that L110M modestly enhances conformational order and stability in the TTR peptide assemblies without major structural disruption, deepening our understanding of amyloidogenesis in TTR-related disorders.
{"title":"Effect of L110M Mutation on the Structure and Stability of ATTR(105-115) Peptide Assembly: A Computational Study.","authors":"Prabuddha Bhattacharya, Sumit Mittal","doi":"10.1002/prot.70046","DOIUrl":"10.1002/prot.70046","url":null,"abstract":"<p><p>The mechanisms driving amyloid assembly have long intrigued structural biologists, as they offer insights into systemic fibrotic changes and the dynamic behavior of transthyretin (TTR) aggregation, crucial for developing amyloid-targeted therapies. In TTR-associated amyloidosis, amyloid fibrils form via destabilization of the tetramer into dimers and monomers. While many TTR mutations have been studied, the atomistic impact of multiple mutations on amyloid transthyretin (ATTR) self-assembly remains underexplored. To the best of our knowledge, this is the first computational analysis reporting the impact of the L110M mutation on ATTR peptide aggregation. Using triplicate 1 μs all-atom molecular dynamics (MD) simulations, totaling 18 μs, the conformational dynamics of cross-β amyloid fibrils in the ATTR(105-115) segment were examined for both wild-type and L110M mutant TTR. The L110M mutation consistently enhanced the β-sheet content in all oligomers, with increases of ~1%, ~5%, and ~4% over the wild-type in the 2-, 4-, and 8-peptide systems, respectively. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations revealed higher effective binding free energy for the L110M mutant, with residue M110 contributing significantly to stabilization. These results suggest that L110M modestly enhances conformational order and stability in the TTR peptide assemblies without major structural disruption, deepening our understanding of amyloidogenesis in TTR-related disorders.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"570-581"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144994772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-02-01Epub Date: 2025-08-28DOI: 10.1002/prot.70041
Jayapriya Venkatesan, Durba Roy
Kinetics of intramolecular disulphide pairing in a six-cysteine containing plant toxin peptide cycloviolacin O1 (CyO1) having a cyclic backbone and a cyclic cystine knot (CCK) is studied using a Hidden Markov Model (HMM) created from molecular dynamics simulation trajectories. Starting from a fully reduced form of CyO1 (peptide-D), the kinetic model is created to track the peptide's evolution to a native-like state (peptide-N) where all three correct pairs of S-S linkages are most likely to be observed. The structural evolution and fluctuation of peptide-D through many partially folded S-S intermediates and the associated propensity, along with the timescale of formation of a single or simultaneously two or three S-S pairs, is studied using this Markov chain. The phenomenon of intramolecular S-S pairing, as observed in proteins and peptides, is fast, with a computed rate constant of ~106 s-1 in line with experimental observations in the bacterial disulphide bond redox protein DsbD. Rate networks and transition path theory analysis are used to find the most probable pathway for peptide-D to evolve into peptide-N.
{"title":"Markovian Timescales of Intramolecular Disulfide Pairing in Cyclotides.","authors":"Jayapriya Venkatesan, Durba Roy","doi":"10.1002/prot.70041","DOIUrl":"10.1002/prot.70041","url":null,"abstract":"<p><p>Kinetics of intramolecular disulphide pairing in a six-cysteine containing plant toxin peptide cycloviolacin O1 (CyO1) having a cyclic backbone and a cyclic cystine knot (CCK) is studied using a Hidden Markov Model (HMM) created from molecular dynamics simulation trajectories. Starting from a fully reduced form of CyO1 (peptide-D), the kinetic model is created to track the peptide's evolution to a native-like state (peptide-N) where all three correct pairs of S-S linkages are most likely to be observed. The structural evolution and fluctuation of peptide-D through many partially folded S-S intermediates and the associated propensity, along with the timescale of formation of a single or simultaneously two or three S-S pairs, is studied using this Markov chain. The phenomenon of intramolecular S-S pairing, as observed in proteins and peptides, is fast, with a computed rate constant of ~10<sup>6</sup> s<sup>-1</sup> in line with experimental observations in the bacterial disulphide bond redox protein DsbD. Rate networks and transition path theory analysis are used to find the most probable pathway for peptide-D to evolve into peptide-N.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"558-569"},"PeriodicalIF":2.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144980251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}