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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.

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.

Melanoma is a harmful disease among all types of skin cancer. Genetic factors and the exposure of UV rays causes melanoma skin lesions. Early diagnosis is important to identify malignant melanomas to improve the patient prognosis. A biopsy is a traditional method which is painful and invasive when used for skin cancer detection. This method requires laboratory testing which is not very efficient and time-consuming to detect skin lesions. To solve the above issue, a computer aided diagnosis (CAD) for skin lesion detection is needed. In this article, we have developed a mobile application with the capabilities to segment skin lesions in dermoscopy images using a triangulation method and categorize them into malignant or bengin lesions through a supervised method which is convolution neural network (CNN). This mobile application will make the skin cancer detection non-invasive which does not require any laboratory testing, making the detection less time consuming and inexpensive with a detection accuracy of 81%.

Advancement in the field of biotechnology has opened a vast global market. The Indian biotechnology arena is promising for advance and pioneering growth with its immense growth potential which could play a significant role toward India's contribution to global industrial biotechnology. Today, India is one of the fastest-growing trillion-dollar economies in the world and the fifth largest overall, with a GDP (gross domestic product) of $2.94 trillion. Biotechnology (BT) and information technology (IT) are the key drivers contributing to this growth which constitutes approximately 5% of the country's total annual GDP. Indian biotechnology growth is fueled by bio-pharmaceutical, bio-industrial, bio-services, bio-agricultural, and bioinformatics, and among them, the bio-industrial area is one of the most promising and advanced. New approaches which Indian industrial biotechnology is exploring, include harnessing microorganisms for the production of value-added bioactive ingredients such as industrial enzymes, organic acids, bulk chemicals, and single-cell proteins, which have played a predominant role in the overall development of biotechnology after bio-pharmaceuticals. The above factors made India one of the world's top 12 destinations for biotechnology. In this article, we review the status of the biotechnological industry and its future perspective in context to the Indian market and its role in global economy.