Biology subjects

Biswas, N.

Publications and source records attributed to Biswas, N..

3 recordsLinked to original sources

bioRxiv2020

Leish-ExP: a database of exclusive proteins from Leishmania parasite

Leishmaniasis is a complex disease caused by different species of genus Leishmania, which affects millions of people spanning over 88 countries causing extensive mortality and morbidity. Leishmaniasis exists in three clinical forms; cutaneous, mucocutaneous and visceral. Anti-leishmanial therapy is one of the challenging fields due to the presence of wide range of Leishmania species and host response against the pathogenic infection. Clinical survey reveals toxicity of drugs and trial compounds causing death among patients and predominant resistance to different class of antimonials among the leishmaniasis patient. Identification of appropriate target protein is a primary and important phase of drug development and Leishmania is a suitable system for targeted drug development as it branched out quite early from the higher eukaryotes like human. With the advancement of genomic era and availability of whole genome sequences of Leishmania species, relevant information on their respective genes and proteins are now easily extracted. Hence, in the current study, to aid the targeted drug therapy, an exhaustive whole genome scale comparative sequence analysis was performed to identify genes/proteins exclusive to Leishmania. Subsequently, further filtration was employed to identify the individual Leishmania species specific gene/proteins. Among such proteins, a considerable number was found to have no recognizable structure and functions. Hence, efforts were taken to characterize these Leishmania exclusive gene/proteins via providing additional sequence, structure, localization and functional information. All the information about each of these Leishmania exclusive gene/proteins from five different Leishmania species has been systemically categorized and represented in the form a user-friendly database called Leish-ExP, which is freely available at http://www.hpppi.iicb.res.in/Leish-ex.

bioinformatics↗

bioRxiv2020

Analysis of Pan-Omics Data in Human Interactome Network (APODHIN)

Analysis of Pan-Omics Data in Human Interactome Network (APODHIN) is a platform for integrative analysis of transcriptomics, proteomics, genomics, and metabolomics data for identification of key molecular players and their interconnections exemplified in cancer scenario. APODHIN works on a meta-interactome networks consisting of human protein-protein interactions, miRNA-target gene regulatory interactions, and transcription factor-target gene regulatory relationships, respectively. In its first module, APODHIN maps proteins/genes/miRNAs from different omics data in its meta-interactome network and extracts the network of biomolecules that are differentially altered in the given scenario. Using this context specific, filtered interaction network, APODHIN identifies topologically important nodes (TINs) implementing graph theory based network topology analysis and further justifies their role via pathway and disease marker mapping. These TINs could be used as prospective diagnostic and/or prognostic biomarkers and/or potential therapeutic targets. In its second module, APODHIN attempts to identify cross pathway regulatory and protein-protein interaction (PPI) links connecting signaling proteins, transcription factors, and miRNAs to metabolic enzymes via utilization of single-omics and/or pan-omics data and implementation of mathematical modeling. Interconnections between regulatory components such as signaling proteins/TFs/miRNAs and metabolic pathways need to be elucidated more elaborately in order to understand the role of oncogene and tumor suppressors in regulation of metabolic reprogramming during cancer. APODHIN platform contains a web server component where users can upload single/multi omics data to identify TINs and cross-pathway links. Tabular, graphical and 3D network representations of the identified TINs and cross-pathway links are provided for better appreciation. Additionally, this platform also provides a database part where cancer specific, single and/or multi omics dataset centric meta-interactome networks, TINs, and cross-pathway links are provided for cervical, ovarian, and breast cancers, respectively. APODHIN platform is freely available at http://www.hpppi.iicb.res.in/APODHIN/home.html.

bioinformatics↗

bioRxiv2019

Novel sampling strategies and a coarse-grained score function for docking homomers, flexible heteromers, and oligosaccharides using Rosetta in CAPRI Rounds 37-45

CAPRI Rounds 37 through 45 introduced larger complexes, new macromolecules, and multi-stage assemblies. For these rounds, we used and expanded docking methods in Rosetta to model 23 target complexes. We successfully predicted 14 target complexes and recognized and refined near-native models generated by other groups for two further targets. Notably, for targets T110 and T136, we achieved the closest prediction of any CAPRI participant. We created several innovative approaches during these rounds. Since Round 39 (target 122), we have used the new RosettaDock 4.0, which has a revamped coarse-grained energy function and the ability to perform conformer selection during docking with hundreds of pre-generated protein backbones. Ten of the complexes had some degree of symmetry in their interactions, so we tested Rosetta SymDock, realized its shortcomings, and developed the next-generation symmetric docking protocol, SymDock2, which includes docking of multiple backbones and induced-fit refinement. Since the last CAPRI assessment, we also developed methods for modeling and designing carbohydrates in Rosetta, and we used them to successfully model oligosaccharide-protein complexes in Round 41. While the results were broadly encouraging, they also highlighted the pressing need to invest in (1) flexible docking algorithms with the ability to model loop and linker motions and in (2) new sampling and scoring methods for oligosaccharide-protein interactions.

biophysics↗