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Tiwari, K.

Publications and source records attributed to Tiwari, K..

3 recordsLinked to original sources

Ab initio modelling of an essential mammalian protein: Transcription Termination Factor 1 (TTF1)

Transcription Termination Factor 1 (TTF1) is an essential mammalian protein that regulates cellular transcription, replication fork arrest, DNA damage repair, chromatin remodelling etc. TTF1 interacts with numerous cellular proteins to regulate various cellular phenomena, and plays a crucial role in maintaining normal cellular physiology, dysregulation of which has been reported towards cancerous transformation of the cells. However, despite its key role in cellular physiology, the complete structure of human TTF1 has not been elucidated to date, either experimentally or computationally. Hence, understanding the structure of human TTF1 becomes highly important for studying its functions and interactions with other cellular factors. Therefore, the aim of this study was to construct the complete structure of human TTF1 protein, using molecular modelling approaches. Owing to the lack of suitable homologues in the PDB, the complete structure of human TTF1 was constructed using ab initio modelling. The structural stability was determined using molecular dynamics (MD) simulations in explicit solvent, and trajectory analyses. The representative structure of human TTF1 was obtained by trajectory clustering, and the central residues were determined by centrality analyses of the residue interaction network of TTF1. Two residue clusters, in the oligomerisation domain and C-terminal domain, were determined to be central to the structural stability of human TTF1. To the best of our knowledge, this study is the first to report the complete structure of human TTF1, and the results obtained herein will provide structural insights for future research in cancer biology and related studies. Author SummaryThe transcription termination factor 1 (TTF1) is an essential multifunctional mammalian protein which plays important role in regulating important cellular process like transcription, replication, DNA damage repair, chromatin remodelling etc. and its dysregulation leads to various cancers. Despite its being such an important factor, the complete structure of human TTF1 has not been determined to date, either using experimental techniques or computationally. Therefore, the aim of this study was to construct the complete structure of human TTF1 using computational modelling. In this study the complete structure of human TTF1 was constructed by ab initio modelling using iTasser. The stability of this model was determined by 200 ns molecular dynamics (MD) simulations. The representative conformation of human TTF1 was further determined by clustering the simulation trajectory and the residues that are central to the stability of this structure were identified. The results demonstrate the presence of two residue clusters in human TTF1, one in the oligomerisation domain and other in the C-terminal domain, which were found to be crucial for the structural stability of this protein. Hence, the results of this study will aid future studies in this field towards engineering this important protein for further biochemistry and cell biology research.

bioinformatics↗

High efficiency excitation energy transfer in biohybrid quantum dot-bacterial reaction center nanoconjugates

Reaction centers (RCs) are the pivotal component of natural photosystems, converting solar energy into the potential difference between separated electrons and holes that is used to power much of biology. RCs from anoxygenic purple photosynthetic bacteria such as Rhodobacter sphaeroides only weakly absorb much of the visible region of the solar spectrum which limits their overall light-harvesting capacity. For in vitro applications such as bio-hybrid photodevices this deficiency can be addressed by effectively coupling RCs with synthetic lightharvesting materials. Here, we studied the time scale and efficiency of Forster resonance energy transfer (FRET) in a nanoconjugate assembled from a synthetic quantum dot (QD) antenna and a tailored RC engineered to be fluorescent. Time-correlated single photon counting spectroscopy of biohybrid conjugates enabled the direct determination of FRET from QDs to attached RCs on a time scale of 26.6 {+/-} 0.1 ns and with a high efficiency of 0.75 {+/-} 0.01.

biophysics↗

Reproducibility in systems biology modelling

The reproducibility crisis has emerged as an important concern across many fields of science including life science, since many published results failed to reproduce. Systems biology modelling, which involves mathematical representation of biological processes to study complex system behaviour, was expected to be least affected by this crisis. While lack of reproducibility of experimental results and computational analysis could be a repercussion of several compounded factors, it was not fully understood why systems biology models with well-defined mathematical expressions fail to reproduce and how prevalent it is. Hence, we systematically attempted to reproduce 455 kinetic models of biological processes published in peer-reviewed research articles from 152 journals; which is collectively a work of about 1400 scientists from 49 countries. Our investigation revealed that about half (49%) of the models could not be reproduced using the information provided in the published manuscripts. With further effort, an additional 12% of the models could be reproduced either by empirical correction or support from authors. The other 37% remained non-reproducible models due to missing parameter values, missing initial concentration, inconsistent model structure, or a combination of these factors. Among the corresponding authors of the non-reproducible model we contacted, less than 30% responded. Our analysis revealed that models published in journals across several fields of life science failed to reproduce, revealing a common problem in the peer-review process. Hence, we propose an 8-point reproducibility scorecard that can be used by authors, reviewers and journal editors to assess each model and address the reproducibility crisis.

systems biology↗