{"title":"Issue Information ‐ Table of Content","authors":"","doi":"10.1002/prot.26122","DOIUrl":"https://doi.org/10.1002/prot.26122","url":null,"abstract":"","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84598135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenxue Zhou, Zhongjie Han, Zhixiang Wu, Weikang Gong, Shuang Yang, Lei Chen, Chunhua Li, Luke R. Vass, Katie M. Branscum, R. Bourret, Clay A. Foster, A. Mobeen, B. L. Puniya, Srinivasan Ramachandran, Krisztina Varga, Harish Vashisth, Ashutosh Prakash Dubey, Vijay Shankar Singh, Rajeev Mishra, Anil Kumar Tripathi, Arshad Hosseini, Nikolay V. Dokholyan, Jiaan Yang, Wen Xiang Cheng, Xiao Fei Zhao, Gang Wu, Shi Tong Sheng, Qiyue Hu
{"title":"Issue Information ‐ Forthcoming","authors":"Wenxue Zhou, Zhongjie Han, Zhixiang Wu, Weikang Gong, Shuang Yang, Lei Chen, Chunhua Li, Luke R. Vass, Katie M. Branscum, R. Bourret, Clay A. Foster, A. Mobeen, B. L. Puniya, Srinivasan Ramachandran, Krisztina Varga, Harish Vashisth, Ashutosh Prakash Dubey, Vijay Shankar Singh, Rajeev Mishra, Anil Kumar Tripathi, Arshad Hosseini, Nikolay V. Dokholyan, Jiaan Yang, Wen Xiang Cheng, Xiao Fei Zhao, Gang Wu, Shi Tong Sheng, Qiyue Hu","doi":"10.1002/prot.26119","DOIUrl":"https://doi.org/10.1002/prot.26119","url":null,"abstract":"","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"89 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81493191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Issue Information ‐ Table of Content","authors":"","doi":"10.1002/prot.26118","DOIUrl":"https://doi.org/10.1002/prot.26118","url":null,"abstract":"","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"186 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77033001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Issue Information ‐ Table of Content","authors":"","doi":"10.1002/prot.26114","DOIUrl":"https://doi.org/10.1002/prot.26114","url":null,"abstract":"","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84898996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenxue Zhou, Zhongjie Han, Zhixiang Wu, Weikang Gong, Shuang Yang, Lei Chen, Chunhua Li
The YTH domain of YTHDF3 belongs to a class of protein “readers” recognizing the N6‐methyladenosine (m6A) modification in mRNA. Although static crystal structure reveals m6A recognition by a conserved aromatic cage, the dynamic process in recognition and importance of aromatic cage residues are not completely clear. Here, molecular dynamics (MD) simulations are performed to explore the issues and negative selectivity of YTHDF3 toward unmethylated substrate. Our results reveal that there exist conformation selectivity and induced‐fit in YTHDF3 binding with m6A‐modified RNA, where recognition loop and loop6 play important roles in the specific recognition. m6A modification enhances the stability of YTHDF3 in complex with RNA. The methyl group of m6A, like a warhead, enters into the aromatic cage of YTHDF3, where Trp492 anchors the methyl group and constraints m6A, making m6A further stabilized by π–π stacking interactions from Trp438 and Trp497. In addition, the methylation enhances the hydrophobicity of adenosine, facilitating water molecules excluded out of the aromatic cage, which is another reason for the specific recognition and stronger intermolecular interaction. Finally, the comparative analyses of hydrogen bonds and binding free energy between the methylated and unmethylated complexes reveal the physical basis for the preferred recognition of m6A‐modified RNA by YTHDF3. This study sheds light on the mechanism by which YTHDF3 specifically recognizes m6A‐modified RNA and can provide important information for structure‐based drug design.
{"title":"Specific recognition between YTHDF3 and m6A‐modified RNA: An all‐atom molecular dynamics simulation study","authors":"Wenxue Zhou, Zhongjie Han, Zhixiang Wu, Weikang Gong, Shuang Yang, Lei Chen, Chunhua Li","doi":"10.1002/prot.26389","DOIUrl":"https://doi.org/10.1002/prot.26389","url":null,"abstract":"The YTH domain of YTHDF3 belongs to a class of protein “readers” recognizing the N6‐methyladenosine (m6A) modification in mRNA. Although static crystal structure reveals m6A recognition by a conserved aromatic cage, the dynamic process in recognition and importance of aromatic cage residues are not completely clear. Here, molecular dynamics (MD) simulations are performed to explore the issues and negative selectivity of YTHDF3 toward unmethylated substrate. Our results reveal that there exist conformation selectivity and induced‐fit in YTHDF3 binding with m6A‐modified RNA, where recognition loop and loop6 play important roles in the specific recognition. m6A modification enhances the stability of YTHDF3 in complex with RNA. The methyl group of m6A, like a warhead, enters into the aromatic cage of YTHDF3, where Trp492 anchors the methyl group and constraints m6A, making m6A further stabilized by π–π stacking interactions from Trp438 and Trp497. In addition, the methylation enhances the hydrophobicity of adenosine, facilitating water molecules excluded out of the aromatic cage, which is another reason for the specific recognition and stronger intermolecular interaction. Finally, the comparative analyses of hydrogen bonds and binding free energy between the methylated and unmethylated complexes reveal the physical basis for the preferred recognition of m6A‐modified RNA by YTHDF3. This study sheds light on the mechanism by which YTHDF3 specifically recognizes m6A‐modified RNA and can provide important information for structure‐based drug design.","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"83 5 1","pages":"1965 - 1972"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79749544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nuclear factor kappa B (NF‐κB) signaling is the master regulator of inflammatory pathways; therefore, its regulation has been the subject of investigation since last two decades. Multiple models have been published that describes the dynamics of NF‐κB activity by stimulated activation and feedback loops. However, there is also paramount evidence of the critical role of posttranslational modifications (PTMs) in the regulation of NF‐κB pathway. With the premise that PTMs present alternate routes for activation or repression of the NF‐κB pathway, we have developed a model including all PTMs known so far describing the system behavior. We present a pathway network model consisting of 171 proteins forming 315 molecular species and consisting of 482 reactions that describe the NF‐κB activity regulation in totality. The overexpression or knockdown of interacting molecular partners that regulate NF‐κB transcriptional activity by PTMs is used to infer the dynamics of NF‐κB activity and offers qualitative agreement between model predictions and the experimental results heuristically. Finally, we have demonstrated an instance of NF‐κB constitutive activation through positive upregulation of cytokines (the stimuli) and IKK complex (NF‐κB activator), the characteristic features in several cancer types and metabolic disorders, and its reversal by employing combinatorial activation of PPARG, PIAS3, and P50‐homodimer. For the first time, we have presented a NF‐κB model that includes transcriptional regulation by PTMs and presented a theoretical strategy for the reversal of NF‐κB constitutive activation. The presented model would be important in understanding the NF‐κB system, and the described method can be used for other pathways as well.
{"title":"A computational approach to investigate constitutive activation of NF‐κB","authors":"A. Mobeen, B. L. Puniya, S. Ramachandran","doi":"10.1002/prot.26388","DOIUrl":"https://doi.org/10.1002/prot.26388","url":null,"abstract":"Nuclear factor kappa B (NF‐κB) signaling is the master regulator of inflammatory pathways; therefore, its regulation has been the subject of investigation since last two decades. Multiple models have been published that describes the dynamics of NF‐κB activity by stimulated activation and feedback loops. However, there is also paramount evidence of the critical role of posttranslational modifications (PTMs) in the regulation of NF‐κB pathway. With the premise that PTMs present alternate routes for activation or repression of the NF‐κB pathway, we have developed a model including all PTMs known so far describing the system behavior. We present a pathway network model consisting of 171 proteins forming 315 molecular species and consisting of 482 reactions that describe the NF‐κB activity regulation in totality. The overexpression or knockdown of interacting molecular partners that regulate NF‐κB transcriptional activity by PTMs is used to infer the dynamics of NF‐κB activity and offers qualitative agreement between model predictions and the experimental results heuristically. Finally, we have demonstrated an instance of NF‐κB constitutive activation through positive upregulation of cytokines (the stimuli) and IKK complex (NF‐κB activator), the characteristic features in several cancer types and metabolic disorders, and its reversal by employing combinatorial activation of PPARG, PIAS3, and P50‐homodimer. For the first time, we have presented a NF‐κB model that includes transcriptional regulation by PTMs and presented a theoretical strategy for the reversal of NF‐κB constitutive activation. The presented model would be important in understanding the NF‐κB system, and the described method can be used for other pathways as well.","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"5 1","pages":"1944 - 1964"},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72817067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Designing peptides for protein–protein interaction inhibition is of significant interest in computer‐aided drug design. Such inhibitory peptides could mimic and compete with the binding of the partner protein to the inhibition target. Experimental peptide design is a laborious, time consuming, and expensive multi‐step process. Therefore, in silico peptide design can be beneficial for achieving this task. We present a novel algorithm, Pep–Whisperer, which aims to design inhibitory peptides for protein–protein interaction. The desirable peptides would have a relatively high predicted binding affinity to the target protein in a given protein–protein complex. The algorithm outputs linear peptides which are based on an initial template. The template could either be a peptide which is retrieved from the interaction site, or a patch of nonconsecutive amino acids from the protein–protein interface which is completed to a linear peptide by short polyalanine linkers. In addition, the algorithm takes into consideration the conservation of the amino acids in the ligand‐protein binding site by using evolutionary information for choosing the preferred amino acids in each position of the designed peptide. Our algorithm was able to design peptides with high predicted binding affinity to the target protein. The method is fully automated and available as a web server at http://bioinfo3d.cs.tau.ac.il/PepWhisperer/.
{"title":"Pep–Whisperer: Inhibitory peptide design","authors":"N. Hurwitz, D. Zaidman, H. Wolfson","doi":"10.1002/prot.26384","DOIUrl":"https://doi.org/10.1002/prot.26384","url":null,"abstract":"Designing peptides for protein–protein interaction inhibition is of significant interest in computer‐aided drug design. Such inhibitory peptides could mimic and compete with the binding of the partner protein to the inhibition target. Experimental peptide design is a laborious, time consuming, and expensive multi‐step process. Therefore, in silico peptide design can be beneficial for achieving this task. We present a novel algorithm, Pep–Whisperer, which aims to design inhibitory peptides for protein–protein interaction. The desirable peptides would have a relatively high predicted binding affinity to the target protein in a given protein–protein complex. The algorithm outputs linear peptides which are based on an initial template. The template could either be a peptide which is retrieved from the interaction site, or a patch of nonconsecutive amino acids from the protein–protein interface which is completed to a linear peptide by short polyalanine linkers. In addition, the algorithm takes into consideration the conservation of the amino acids in the ligand‐protein binding site by using evolutionary information for choosing the preferred amino acids in each position of the designed peptide. Our algorithm was able to design peptides with high predicted binding affinity to the target protein. The method is fully automated and available as a web server at http://bioinfo3d.cs.tau.ac.il/PepWhisperer/.","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"28 1","pages":"1886 - 1895"},"PeriodicalIF":0.0,"publicationDate":"2022-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87067526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ekta Pathak, A. Dubey, V. Singh, Rajeev Mishra, A. Tripathi
In Azospirillum brasilense, an extra‐cytoplasmic function σ factor (RpoE10) shows the characteristic 119 amino acid long C‐terminal extension found in ECF41‐type σ factors, which possesses three conserved motifs (WLPEP, DGGGR, and NPDKV), one in the linker region between the σ2 and σ4, and the other two in the SnoaL_2 domain of the C‐terminal extension. Here, we have described the role of the two conserved motifs in the SnoaL_2 domain of RpoE10 in the inhibition and activation of its activity, respectively. Truncation of the distal part of the C‐terminal sequence of the RpoE10 (including NPDKV but excluding the DGGGR motif) results in its promoter's activation suggesting autoregulation. Further truncation of the C‐terminal sequence up to its proximal part, including NPDKV and DGGGR motif, abolished promoter activation. Replacement of NPDKV motif with NAAAV in RpoE10 increased its ability to activate its promoter, whereas replacement of DGGGR motif led to reduced promoter activation. We have explored the dynamic modulation of σ2 ‐σ4 domains and the relevant molecular interactions mediated by the two conserved motifs of the SnoaL2 domain using molecular dynamics simulation. The analysis enabled us to explain that the NPDKV motif located distally in the C‐terminus negatively impacts transcriptional activation. In contrast, the DGGGR motif found proximally of the C‐terminal extension is required to activate RpoE10.
{"title":"Deciphering the role of the two conserved motifs of the ECF41 family σ factor in the autoregulation of its own promoter in Azospirillum brasilense Sp245","authors":"Ekta Pathak, A. Dubey, V. Singh, Rajeev Mishra, A. Tripathi","doi":"10.1002/prot.26387","DOIUrl":"https://doi.org/10.1002/prot.26387","url":null,"abstract":"In Azospirillum brasilense, an extra‐cytoplasmic function σ factor (RpoE10) shows the characteristic 119 amino acid long C‐terminal extension found in ECF41‐type σ factors, which possesses three conserved motifs (WLPEP, DGGGR, and NPDKV), one in the linker region between the σ2 and σ4, and the other two in the SnoaL_2 domain of the C‐terminal extension. Here, we have described the role of the two conserved motifs in the SnoaL_2 domain of RpoE10 in the inhibition and activation of its activity, respectively. Truncation of the distal part of the C‐terminal sequence of the RpoE10 (including NPDKV but excluding the DGGGR motif) results in its promoter's activation suggesting autoregulation. Further truncation of the C‐terminal sequence up to its proximal part, including NPDKV and DGGGR motif, abolished promoter activation. Replacement of NPDKV motif with NAAAV in RpoE10 increased its ability to activate its promoter, whereas replacement of DGGGR motif led to reduced promoter activation. We have explored the dynamic modulation of σ2 ‐σ4 domains and the relevant molecular interactions mediated by the two conserved motifs of the SnoaL2 domain using molecular dynamics simulation. The analysis enabled us to explain that the NPDKV motif located distally in the C‐terminus negatively impacts transcriptional activation. In contrast, the DGGGR motif found proximally of the C‐terminal extension is required to activate RpoE10.","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"6 1","pages":"1926 - 1943"},"PeriodicalIF":0.0,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90110733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. M. Gomari, N. Rostami, Davood Rabiei Faradonbeh, H. R. Asemaneh, G. Esmailnia, S. Arab, M. Farsimadan, Arshad Hosseini, N. Dokholyan
The binding of therapeutics to human serum albumin (HSA), which is an abundant protein in plasma poses a major challenge in drug discovery. Although HSA has several binding pockets, the binding site I on D2 and binding site II on D3 are the main binding pockets of HSA. To date, a few experiments have been conducted to examine the effects of the potential of hydrogen (pH) changes on HSA attributes. In the present investigation, the effect of acidic (pH 7.1) and basic states (pH 7.7) on HSA structure and its drug binding potency were examined in comparison with the physiological state (pH 7.4). For this purpose, molecular dynamics (MD), free energy landscape (FEL), principal component analysis (PCA), probability distribution function (PDF), tunnel‐cavity investigation, secondary structure analysis, docking study, and free energy investigation were employed to investigate the effect of pH changes on the structural characteristics of HSA at the atomic level. The results obtained from this study revealed the significant effect of pH alterations on the secondary and tertiary structure of HSA. In addition, HSA stability and its drug binding ability can be severely affected following pH changes. Given that pH change frequently occurs in various diseases such as cancer, diabetes, and kidney failure, therefore, pharmaceutical companies should allocate specific consideration to this subject throughout their drug design experiments.
{"title":"Evaluation of pH change effects on the HSA folding and its drug binding characteristics, a computational biology investigation","authors":"M. M. Gomari, N. Rostami, Davood Rabiei Faradonbeh, H. R. Asemaneh, G. Esmailnia, S. Arab, M. Farsimadan, Arshad Hosseini, N. Dokholyan","doi":"10.1002/prot.26386","DOIUrl":"https://doi.org/10.1002/prot.26386","url":null,"abstract":"The binding of therapeutics to human serum albumin (HSA), which is an abundant protein in plasma poses a major challenge in drug discovery. Although HSA has several binding pockets, the binding site I on D2 and binding site II on D3 are the main binding pockets of HSA. To date, a few experiments have been conducted to examine the effects of the potential of hydrogen (pH) changes on HSA attributes. In the present investigation, the effect of acidic (pH 7.1) and basic states (pH 7.7) on HSA structure and its drug binding potency were examined in comparison with the physiological state (pH 7.4). For this purpose, molecular dynamics (MD), free energy landscape (FEL), principal component analysis (PCA), probability distribution function (PDF), tunnel‐cavity investigation, secondary structure analysis, docking study, and free energy investigation were employed to investigate the effect of pH changes on the structural characteristics of HSA at the atomic level. The results obtained from this study revealed the significant effect of pH alterations on the secondary and tertiary structure of HSA. In addition, HSA stability and its drug binding ability can be severely affected following pH changes. Given that pH change frequently occurs in various diseases such as cancer, diabetes, and kidney failure, therefore, pharmaceutical companies should allocate specific consideration to this subject throughout their drug design experiments.","PeriodicalId":20789,"journal":{"name":"Proteins: Structure","volume":"8 1","pages":"1908 - 1925"},"PeriodicalIF":0.0,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88841911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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