Browsing by Author "Shen, Bairong"

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    Identification of Intrinsic Disorder in Complexes from the Protein Data Bank
    (ACS Publications, 2020-07-14) Zhou, Jianhong; Oldfield, Christopher J.; Yan, Wenying; Shen, Bairong; Dunker, A.Keith; Biochemistry and Molecular Biology, School of Medicine
    Background: Intrinsically disordered proteins or regions (IDPs or IDRs) lack stable structures in solution, yet often fold upon binding with partners. IDPs or IDRs are highly abundant in all proteomes and represent a significant modification of sequence → structure → function paradigm. The Protein Data Bank (PDB) includes complexes containing disordered segments bound to globular proteins, but the molecular mechanisms of such binding interactions remain largely unknown. Results: In this study, we present the results of various disorder predictions on a nonredundant set of PDB complexes. In contrast to their structural appearances, many PDB proteins were predicted to be disordered when separated from their binding partners. These predicted-to-be-disordered proteins were observed to form structures depending upon various factors, including heterogroup binding, protein/DNA/RNA binding, disulfide bonds, and ion binding. Conclusions: This study collects many examples of disorder-to-order transition in IDP complex formation, thus revealing the unusual structure–function relationships of IDPs and providing an additional support for the newly proposed paradigm of the sequence → IDP/IDR ensemble → function.
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    Impacts of biomedical hashtag-based Twitter campaign: #DHPSP utilization for promotion of open innovation in digital health, patient safety, and personalized medicine
    (Elsevier, 2021) Kletecka-Pulker, Maria; Mondal, Himel; Wang, Dongdong; Parra, R. Gonzalo; Maigoro, Abdulkadir Yusif; Lee, Soojin; Garg, Tushar; Mulholland, Eoghan J.; Devkota, Hari Prasad; Konwar, Bikramjit; Patnaik, Sourav S.; Lordan, Ronan; Nawaz, Faisal A.; Tsagkaris, Christos; Rayan, Rehab A.; Louka, Anna Maria; De, Ronita; Badhe, Pravin; Schaden, Eva; Willschke, Harald; Maleczek, Mathias; Boyina, Hemanth Kumar; Khalid, Garba M.; Uddin, Md. Sahab; Sanusi; Khan, Johra; Odimegwu, Joy I.; Yeung, Andy Wai Kan; Akram, Faizan; Sai, Chandragiri Siva; Bucher, Sherri; Paswan, Shravan Kumar; Singla, Rajeev K.; Shen, Bairong; Di Lonardo, Sara; Tosevska, Anela; Simal-Gandara, Jesus; Zec, Manja; González-Burgos, Elena; Habijan, Marija; Battino, Maurizio; Giampieri, Francesca; Tikhonov, Aleksei; Cianciosi, Danila; Forbes-Hernandez, Tamara Y.; Quiles, José L.; Mezzetti, Bruno; Babiaka, Smith B.; Ahmed, Mosa E. O.; Piccard, Paula; Urquiza, Mágali S.; Depew, Jennifer R.; Schultz, Fabien; Sur, Daniel; Pai, Sandeep R.; Găman, Mihnea-Alexandru; Cenanovic, Merisa; Tzvetkov, Nikolay T.; Tripathi, Surya Kant; Kharat, Kiran R.; Garcia-Sosa, Alfonso T.; Sieber, Simon; Atanasov, Atanas G.; Pediatrics, School of Medicine
    The open innovation hub Digital Health and Patient Safety Platform (DHPSP) was recently established with the purpose to invigorate collaborative scientific research and the development of new digital products and personalized solutions aiming to improve human health and patient safety. In this study, we evaluated the effectiveness of a Twitter-based campaign centered on using the hashtag #DHPSP to promote the visibility of the DHPSP initiative. Thus, tweets containing #DHPSP were monitored for five weeks for the period 20.10.2020–24.11.2020 and were analyzed with Symplur Signals (social media analytics tool). In the study period, a total of 11,005 tweets containing #DHPSP were posted by 3020 Twitter users, generating 151,984,378 impressions. Analysis of the healthcare stakeholder-identity of the Twitter users who used #DHPSP revealed that the most of participating user accounts belonged to individuals or doctors, with the top three user locations being the United States (501 users), the United Kingdom (155 users), and India (121 users). Analysis of co-occurring hashtags and the full text of the posted tweets further revealed that the major themes of attention in the #DHPSP Twitter-community were related to the coronavirus disease 2019 (COVID-19), medicine and health, digital health technologies, and science communication in general. Overall, these results indicate that the #DHPSP initiative achieved high visibility and engaged a large body of Twitter users interested in the DHPSP focus area. Moreover, the conducted campaign resulted in an increase of DHPSP member enrollments and website visitors, and new scientific collaborations were formed. Thus, Twitter campaigns centered on a dedicated hashtag prove to be a highly efficient tool for visibility-promotion, which could be successfully utilized by healthcare-related open innovation platforms or initiatives.
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    Intrinsically disordered domains: Sequence ➔ disorder ➔ function relationships
    (Wiley, 2019-07-12) Zhou, Jianhong; Oldfield, Christopher J.; Yan, Wenying; Shen, Bairong; Dunker, A. Keith; Biochemistry and Molecular Biology, School of Medicine
    Disordered domains are long regions of intrinsic disorder that ideally have conserved sequences, conserved disorder, and conserved functions. These domains were first noticed in protein–protein interactions that are distinct from the interactions between two structured domains and the interactions between structured domains and linear motifs or molecular recognition features (MoRFs). So far, disordered domains have not been systematically characterized. Here, we present a bioinformatics investigation of the sequence–disorder–function relationships for a set of probable disordered domains (PDDs) identified from the Pfam database. All the Pfam seed proteins from those domains with at least one PDD sequence were collected. Most often, if a set contains one PDD sequence, then all members of the set are PDDs or nearly so. However, many seed sets have sequence collections that exhibit diverse proportions of predicted disorder and structure, thus giving the completely unexpected result that conserved sequences can vary substantially in predicted disorder and structure. In addition to the induction of structure by binding to protein partners, disordered domains are also induced to form structure by disulfide bond formation, by ion binding, and by complex formation with RNA or DNA. The two new findings, (a) that conserved sequences can vary substantially in their predicted disorder content and (b) that homologues from a single domain can evolve from structure to disorder (or vice versa), enrich our understanding of the sequence ➔ disorder ensemble ➔ function paradigm.