Current in silico proteomics require the trifecta analysis, namely, prediction, validation, and functional assessment of a modeled protein. The main drawback of this endeavor is the lack of a single protocol that utilizes a proper set of benchmarked open-source tools to predict a protein’s structure and function accurately. The present study rectifies this drawback through the design and development of such a protocol. The protocol begins with the characterization of a novel coding sequence to identify the expressed protein. It then recognizes and isolates evolutionarily conserved sequence motifs through phylogenetics. The next step is to predict the protein’s secondary structure, followed by the prediction, refinement, and validation of its three-dimensional tertiary structure. These steps enable the functional analysis of the macromolecule through protein docking, which facilitates the identification of the protein’s active site. Each of these steps is crucial for the complete characterization of the protein under study. We have dubbed this process the trifecta analysis. In this study, we have proven the effectiveness of our protocol using the cystatin C and AChE proteins. Beginning with just their sequences, we have characterized both proteins’ structures and functions, including identifying the cystatin C protein’s seven-residue active site and the AChE protein’s active-site gorge via protein–protein and protein–ligand docking, respectively. This process will greatly benefit new and experienced scientists alike in obtaining a strong understanding of the trifecta analysis, resulting in a domino effect that could expand drug development.

The relative lack of marine venom could be attributed to the difficulty in dealing with venomous marine animals. Moreover, the venom of marine animals consists of various bioactive molecules, many of which are proteins with unique properties. In this study, we investigated the potential toxic proteins of jellyfish collected for ligand screening to understand the mechanism of the toxic effects of jellyfish. Since taxonomic identification is problematic due to the lack of proper keys, we conducted morphological and molecular mitochondrial DNA sequencing from COI and ITS regions. The venom extract from nematocysts found along the bell margins was used for protein characterization using SDS-gel electrophoresis and nano-liquid chromatography-tandem mass spectrometry. Ligand screening for the most potent toxin and antibacterial and cytotoxicity assays were carried out. The phylogenetic tree showed distinct clustering from other Catostylus sp. The proteomic analysis revealed venom with many bioactive proteins. Only 13 venom proteins were identified with molecular weights ranging from 4318 to 184,923 Da, exhibiting the venom’s complexity. The overall toxin protein composition of Catostylus sp. venom was dominated by potassium channel toxin alpha-KTx. Molecular docking of toxin alpha-KTx 1.13 revealed high specificity towards the human voltage-gated potassium channel Kv3 with a high fitness score and a minimum energy barrier of −17.9 kcal/mol. Disc diffusion and cytotoxicity assays revealed potent antibacterial activity against Klebsiella pneumoniae with no cytotoxicity. Further studies on detailed characterization and therapeutic potentials are warranted.

The Sambar is one of the largest deer species distributed mainly in Asia, and it has been listed as a vulnerable species. Taxonomy based on morphological characterization has been the gold standard method used to identify the Sambar deer species. Yet, morphological identification is challenging and requires expertise. To conduct species identification and taxonomic decisions, we performed the molecular identification of R. unicolor found in Sri Lanka using DNA barcodes, COI, and Cyt b to compare the Sri Lankan R. unicolor with the Indian R. unicolor and other R. unicolor subspecies. We obtained mitochondrial DNA sequences from COI and Cyt b from blood samples collected from the wet zone in Sri Lanka. A phylogenetic tree was constructed based on the Bayesian analyses using MrBayes 3.2.7. Molecular dating was implemented in Bayesian Evolutionary Analysis Sampling Trees (BEAST v1.8.2) on the concatenated sequence using a log-normal relaxed clock and Yule species tree prior, with four categories. The results showed that the Sri Lankan R. unicolor is genetically different from the Indian R. unicolor and other R. unicolor subspecies. The divergence occurred approximately 1.1 MYA (million years ago) in the Pleistocene era. The results are essential for designing new conservation platforms for these Sambar deer species.