Database Creator for Mass Analysis of Peptides and Proteins, DC-MAPP: A Standalone Tool for Simplifying Manual Analysis of Mass Spectral Data to Identify Peptide/Protein Sequences.

Proteomic studies typically involve the use of different types of software for annotating experimental tandem mass spectrometric data (MS/MS) and thereby simplifying the process of peptide and protein identification. For such annotations, these softwares calculate the m/z values of the peptide/protein precursor and fragment ions, for which a database of protein sequences must be provided as an input file. The calculated m/z values are stored as another database, which the user usually cannot view. Database Creator for Mass Analysis of Peptides and Proteins (DC-MAPP) is a novel standalone software that can create custom databases for "viewing" the calculated m/z values of precursor and fragment ions, prior to the database search. It contains three modules. Peptide/Protein sequences as per user's choice can be entered as input to the first module for creating a custom database. In the second module, m/z values must be queried-in, which are searched within the custom database to identify protein/peptide sequences. The third module is suited for peptide mass fingerprinting, which can be used to analyze both ESI and MALDI mass spectral data. The feature of "viewing" the custom database can be helpful not only for better understanding the search engine processes, but also for designing multiple reaction monitoring (MRM) methods. Post-translational modifications and protein isoforms can also be analyzed. Since, DC-MAPP relies on the protein/peptide "sequences" for creating custom databases, it may not be applicable for the searches involving spectral libraries. Python language was used for implementation, and the graphical user interface was built with Page/Tcl, making this tool more user-friendly. It is freely available at https://vit.ac.in/DC-MAPP/.

Unveiling the vulnerabilities of synthetic lethality in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most invasive molecular subtype of breast cancer (BC), accounting for about nearly 15% of all BC cases reported annually. The absence of the three major BC hormone receptors, Estrogen (ER), Progesterone (PR), and Human Epidermal Growth Factor 2 (HER2) receptor, accounts for the characteristic "Triple negative" phraseology. The absence of these marked receptors makes this cancer insensitive to classical endocrine therapeutic approaches. Hence, the available treatment options remain solemnly limited to only conventional realms of chemotherapy and radiation therapy. Moreover, these therapeutic regimes are often accompanied by numerous treatment side-effects that account for early distant metastasis, relapse, and shorter overall survival in TNBC patients. The rigorous ongoing research in the field of clinical oncology has identified certain gene-based selective tumor-targeting susceptibilities, which are known to account for the molecular fallacies and mutation-based genetic alterations that develop the progression of TNBC. One such promising approach is synthetic lethality, which identifies novel drug targets of cancer, from undruggable oncogenes or tumor-suppressor genes, which cannot be otherwise clasped by the conventional approaches of mutational analysis. Herein, a holistic scientific review is presented, to undermine the mechanisms of synthetic lethal (SL) interactions in TNBC, the epigenetic crosstalks encountered, the role of Poly (ADP-ribose) polymerase inhibitors (PARPi) in inducing SL interactions, and the limitations faced by the lethal interactors. Thus, the future predicament of synthetic lethal interactions in the advancement of modern translational TNBC research is assessed with specific emphasis on patient-specific personalized medicine.

In-silico molecular modelling, MM/GBSA binding free energy and molecular dynamics simulation study of novel pyrido fused imidazo[4,5-c]quinolines as potential anti-tumor agents.

With an alarming increase in the number of cancer patients and a variety of tumors, it is high time for intensive investigation on more efficient and potent anti-tumor agents. Though numerous agents have enriched the literature, still there exist challenges, with the availability of different targets and possible cross-reactivity. Herein we have chosen the phosphoinositide 3-kinase (PI3K) as the target of interest and investigated the potential of pyrido fused imidazo[4,5-c]quinoline derivatives to bind strongly to the active site, thereby inhibiting the progression of various types of tumors. The AutoDock, Glide and the Prime-MM/GBSA analysis are used to execute the molecular docking investigation and validation for the designed compounds. The anti-tumor property evaluations were carried out by using PASS algorithm. Based on the GLIDE score, the binding affinity of the designed molecules towards the target PI3K was evaluated. The energetics associated with static interactions revealed 1j as the most potential candidate and the dynamic investigations including RMSD, RMSF, Rg, SASA and hydrogen bonding also supported the same through relative stabilization induced through ligand interactions. Subsequently, the binding free energy of the Wortmannin and 1j complex calculated using MM-PBSA analysis. Further evaluations with PASS prediction algorithm also supported the above results. The studies reveal that there is evidence for considering appropriate pyrido fused imidazo[4,5-c]quinoline compounds as potential anti-tumor agents.

Analysis of core-periphery organization in protein contact networks reveals groups of structurally and functionally critical residues.

The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the native states of 66 proteins (belonging to different families) in terms of their core-periphery organization. The resulting hierarchical classification of the amino acid constituents of a protein arranges the residues into successive layers - having higher core order - with increasing connection density, ranging from a sparsely linked periphery to a densely intra-connected core (distinct from the earlier concept of protein core defined in terms of the three-dimensional geometry of the native state, which has least solvent accessibility). Our results show that residues in the inner cores are more conserved than those at the periphery. Underlining the functional importance of the network core, we see that the receptor sites for known ligand molecules of most proteins occur in the innermost core. Furthermore, the association of residues with structural pockets and cavities in binding or active sites increases with the core order. From mutation sensitivity analysis, we show that the probability of deleterious or intolerant mutations also increases with the core order. We also show that stabilization centre residues are in the innermost cores, suggesting that the network core is critically important in maintaining the structural stability of the protein. A publicly available Web resource for performing core-periphery analysis of any protein whose native state is known has been made available by us at http://www.imsc.res.in/ ~sitabhra/proteinKcore/index.html.