T cell receptors employ diverse strategies to target a p53 cancer neoantigen

Adoptive cell therapy with tumor-specific T cells can mediate durable cancer regression. The prime target of tumor-specific T cells are neoantigens arising from mutations in self-proteins during malignant transformation. To understand T cell recognition of cancer neoantigens at the atomic level, we studied oligoclonal T cell receptors (TCRs) that recognize a neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by the major histocompatibility complex class I molecule HLA-A2. We previously reported the structures of three p53R175H-specific TCRs (38-10, 12-6, and 1a2) bound to p53R175H and HLA-A2. The structures showed that these TCRs discriminate between WT and mutant p53 by forming extensive interactions with the R175H mutation. Here, we report the structure of a fourth p53R175H-specific TCR (6-11) in complex with p53R175H and HLA-A2. In contrast to 38-10, 12-6, and 1a2, TCR 6-11 makes no direct contacts with the R175H mutation, yet is still able to distinguish mutant from WT p53. Structure-based in silico mutagenesis revealed that the 60-fold loss in 6-11 binding affinity for WT p53 compared to p53R175H is mainly due to the higher energetic cost of desolvating R175 in the WT p53 peptide during complex formation than H175 in the mutant. This indirect strategy for preferential neoantigen recognition by 6-11 is fundamentally different from the direct strategies employed by other TCRs and highlights the multiplicity of solutions to recognizing p53R175H with sufficient selectivity to mediate T cell killing of tumor but not normal cells.     

Database of cell signaling enzymes

This paper describes a database for cell signaling enzymes. Our web database offers methods to study, interpret and compare cell-signaling enzymes. Searching and retrieving data from this database has been made easy and user friendly and it is well integrated with other related databases. We believe the end user will be benefited from this database. AVAILABILITY: http://www.sastra.edu/dcse/index.html.     

Modeling of the potential coiled-coil structure of snapin protein and its interaction with SNARE complex

Autism is a developmental disability causing learning and memory disorder. The heart of the search for a cure for this syndrome is the need to understand dendrite branch patterning, a process crucial for proper synaptic transmission. Due to the association of snapin with the SNARE complex and its role in synaptic transmission it is reported as a potential drug target for autism therapies. We wish to impart the noesis of the 3D structure of the snapin protein, and in this chase we predict the native structure from its sequence of amino acid residues using the classical Comparative protein structure modeling methods. The predicted protein model can be of great assistance in understanding the structural insights, which is necessary to understand the protein function. Understanding the interactions between snapin and SNARE complex is crucial in studying its role in the neurotransmitter release process. We also presented a computational model that shows the interaction between the snapin and SNAP-25 protein, a part of the larger SNARE complex.     

Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants

The SARS-CoV-2 pandemic highlights the need for a detailed molecular understanding of protective antibody responses. This is underscored by the emergence and spread of SARS-CoV-2 variants, including Alpha (B.1.1.7) and Delta (B.1.617.2), some of which appear to be less effectively targeted by current monoclonal antibodies and vaccines. Here we report a high resolution and comprehensive map of antibody recognition of the SARS-CoV-2 spike receptor binding domain (RBD), which is the target of most neutralizing antibodies, using computational structural analysis. With a dataset of nonredundant experimentally determined antibody-RBD structures, we classified antibodies by RBD residue binding determinants using unsupervised clustering. We also identified the energetic and conservation features of epitope residues and assessed the capacity of viral variant mutations to disrupt antibody recognition, revealing sets of antibodies predicted to effectively target recently described viral variants. This detailed structure-based reference of antibody RBD recognition signatures can inform therapeutic and vaccine design strategies.     

Probiotic Potential of Bacillus Strains Isolated from an Acidic Fermented Food Idli

Present study is intended to assess the probiotic properties of Bacillus spp. isolated from idli batter, a traditional fermented food of Southern India and Sri Lanka. A total of 32 isolates were screened for potential pathogenic behaviour through haemolysis assay, DNase activity and antibiotics sensitivity. Two of the isolates were found to be potentially safe and identified as Bacillus spp. These strains were characterized for in vitro probiotic attributes and antioxidant activity. Both the strains showed strong acid and bile tolerance, transit tolerance, lysozyme tolerance, cell surface hydrophobicity, auto-aggregation, co-aggregation, biofilm formation potential and adhesion to human colon adenocarcinoma (HT 29) cell line demonstrating potential probiotic ability. These strains also exhibited considerable cholesterol binding, thermostability, β-galactosidase production, proteolytic, amylolytic and lipolytic activity. Cell-free supernatant inhibited the biofilm formation by Pseudomonas aeruginosa (KT266804) to 90%. Intact cells showed significant DPPH (41%), hydroxyl (31%), radical scavenging activity and lipid peroxidation inhibition (20.38%), while cell-free extracts exhibited significant superoxide anion radical scavenging activity (16.25%). Results revealed that isolates could be potential probiotic candidate after further assessment of in vivo probiotic properties and safety evaluation and could be utilised as starter cultures in functional foods.

     

Database of neurodegenerative disorders

A neurological disorder is a disorder caused by the deterioration of certain nerve cells called neurons. Changes in these cells cause them to function abnormally, eventually bringing about their death. In this paper we present a comprehensive database for neurodegenerative diseases, a first-of-its kind covering all known or suspected genes, proteins, pathways related to neurodegenerative diseases. This dynamically compiled database allows researchers to link neurological disorders to the candidate genes & proteins. It serves as a tool to navigate potential gene-protein-pathway relationships in the context of neurodegenerative diseases. The neurodegenerative disorder database covers more then 100 disease concepts including synonyms and research topics. The current version of the database provides links to 728 abstracts and over 203 unique genes/proteins with 137 drugs. Also it is integrated well with other related databases. The aim of this database is to provide the researcher with a quick overview of potential links between genes and proteins with related neurodegenerative diseases. Thus DND providing a user-friendly interface is designed as a source to enhance research on neurodegenerative disorders.

Availability     

TeCK database: a comprehensive collection of telomeric and centromeric sequences with their associated proteins

Telomeres and centromere are two essential features of all eukaryotic chromosomes. They provide function that is necessary for the stability of chromosomes. We developed a comprehensive database named TeCK, which covers a gamut of sequence and other related information about telomeric patterns, telomere repeat sequences, centromere sequences and centromeric patterns present in chromosomes. It also contains information about telomerase ribo-nucleoprotein complexes, centromere binding protein and centromere DNA-binding protein complexes. The database also includes a collection of all kinetochore-associated proteins including inner, outer and central kinetochore proteins. The database can be searched using a user-friendly web interface. AVAILABILITY: http://www.bioinfosastra.com/services/teck/index.html.     

Sequence and Structure Signatures of Cancer Mutation Hotspots in Protein Kinases

Protein kinases are the most common protein domains implicated in cancer, where somatically acquired mutations are known to be functionally linked to a variety of cancers. Resequencing studies of protein kinase coding regions have emphasized the importance of sequence and structure determinants of cancer-causing kinase mutations in understanding of the mutation-dependent activation process. We have developed an integrated bioinformatics resource, which consolidated and mapped all currently available information on genetic modifications in protein kinase genes with sequence, structure and functional data. The integration of diverse data types provided a convenient framework for kinome-wide study of sequence-based and structure-based signatures of cancer mutations. The database-driven analysis has revealed a differential enrichment of SNPs categories in functional regions of the kinase domain, demonstrating that a significant number of cancer mutations could fall at structurally equivalent positions (mutational hotspots) within the catalytic core. We have also found that structurally conserved mutational hotspots can be shared by multiple kinase genes and are often enriched by cancer driver mutations with high oncogenic activity. Structural modeling and energetic analysis of the mutational hotspots have suggested a common molecular mechanism of kinase activation by cancer mutations, and have allowed to reconcile the experimental data. According to a proposed mechanism, structural effect of kinase mutations with a high oncogenic potential may manifest in a significant destabilization of the autoinhibited kinase form, which is likely to drive tumorigenesis at some level. Structure-based functional annotation and prediction of cancer mutation effects in protein kinases can facilitate an understanding of the mutation-dependent activation process and inform experimental studies exploring molecular pathology of tumorigenesis.     

Computational screening of inhibitors for HIV-1 integrase using a receptor based pharmacophore model

The HIV (human immuno-deficiency virus) integrase has a crucial role in viral replication. Moreover, it has no cellular homologue in humans. Hence, it is considered as an attractive drug target. Many inhibitors against the integrase protein has been designed and discussed. The Y-3 inhibitor (4-acetyl amino-5-hydroxy naphthalene - 2, 7- disulfonic acid) is already known to inhibit HIV-1 integrase. However, it is not suitable as a drug like candidate due to its high cyto-toxicity. In this report, a pharmacophore model for HIV integrase is described using the already known Y-3 inhibitor binding site. Fourteen compounds chemically related to the Y-3 inhibitor were generated using the described pharmacophore model and reported. Subsequent computational analysis showed that these compounds have interactions with the Y3 binding site and their possible utility as an integrase inhibitor is discussed.