AACR Centennial Conference: Translational Cancer Medicine-- Nov 4-8, 2007; Singapore

PL02-05 

All cancers are due to abnormalities in DNA. The availability of the human genome sequence has led to the proposal that resequencing of cancer genomes will reveal the full complement of somatic mutations and hence all the cancer genes. To explore the nature of the information that will be derived from cancer genome sequencing we have sequenced the coding exons of the family of 518 protein kinases, ~1.3Mb DNA per cancer sample, in 210 cancers of diverse histological types. Despite the screen being directed toward the coding regions of a gene family that has previously been strongly implicated in oncogenesis, the results indicate that the majority of somatic mutations detected are “passengers”. There is considerable variation in the number and pattern of these mutations between individual cancers, indicating substantial diversity of processes of molecular evolution between cancers. The imprints of exogenous mutagenic exposures, mutagenic treatment regimes and DNA repair defects can all be seen in the distinctive mutational signatures of individual cancers. This systematic mutation screen and others have previously yielded a number of cancer genes that are frequently mutated in one or more cancer types and which are now anticancer drug targets (for example BRAF , PIK3CA , and EGFR ). However, detailed analyses of the data from our screen additionally suggest that there exist a large number of additional “driver” mutations which are distributed across a substantial number of genes. It therefore appears that cells may be able to utilise mutations in a large repertoire of potential cancer genes to acquire the neoplastic phenotype. However, many of these genes are employed only infrequently. These findings may have implications for future anticancer drug development.

Patterns of Somatic Mutation in Human Cancer Genomes

Hypothetical Proteins are the proteins that are predicted to be expressed from an open reading frame (ORF), constituting a substantial fraction of proteomes in both prokaryotes and eukaryotes. Genome projects have led to the identification of many therapeutic targets, the putative function of the protein and their interactions. In this review we have enlisted various methods. Annotation linked to structural and functional prediction of hypothetical proteins assist in the discovery of new structures and functions serving as markers and pharmacological targets for drug designing, discovery and screening. Mass spectrometry is an analytical technique for validating protein characterisation. Matrix-assisted laser desorption ionization–mass spectrometry (MALDI-MS) is an efficient analytical method. Microarrays and Protein expression profiles help understanding the biological systems through a systems-wide study of proteins and their interactions with other proteins and non-proteinaceous molecules to control complex processes in cells and tissues and even whole organism. Next generation sequencing technology accelerates multiple areas of genomics research.

Annotation and curation of uncharacterized proteins- challenges

https://www.mdpi.com/2076-393X/8/3/423/pdf

Vaccine design from the ensemble of surface glycoprotein epitopes of SARS-CoV-2: An immunoinformatics approach

Structural and functional analysis of hypothetical and conserved proteins of Clostridium tetani

Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the challenge in understanding their diverse functions. Techniques to decipher sequence-structure-function relationship, especially in terms of functional modelling of the HPs have been developed by researchers, but using the features as classifiers for HPs has not been attempted. With the rise in number of annotation strategies, next-generation sequencing methods have provided further understanding the functions of HPs. In our previous work, we developed a six-point classification scoring schema with annotation pertaining to protein family scores, orthology, protein interaction/association studies, bidirectional best BLAST hits, sorting signals, known databases and visualizers which were used to validate protein interactions. In this study, we introduced three more classifiers to our annotation system, viz. pseudogenes linked to HPs, homology modelling and non-coding RNAs associated to HPs. We discuss the challenges and performance of these classifiers using machine learning heuristics with an improved accuracy from Perceptron (81.08 to 97.67), Naive Bayes (54.05 to 96.67), Decision tree J48 (67.57 to 97.00), and SMO_npolyk (59.46 to 96.67). With the introduction of three new classification features, the performance of the nine-point classification scoring schema has an improved accuracy to functionally annotate the HPs.

/pdf/a-model-to-predict-the-function-of-hypothetical-proteins-3p8nkmu9im.pdf

A model to predict the function of hypothetical proteins through a nine-point classification scoring schema.

Genome sequencing projects has led to an explosion of large amount of gene products in which many are of hypothetical proteins with unknown function. Analyzing and annotating the functions of hypothetical proteins is important in Staphylococcus aureus which is a pathogenic bacterium that cause multiple types of diseases by infecting various sites in humans and animals. In this study, ten hypothetical proteins of Staphylococcus aureus were retrieved from NCBI and analyzed for their structural and functional characteristics by using various bioinformatics tools and databases. The analysis revealed that some of them possessed functionally important domains and families and protein-protein interacting partners which were ABC transporter ATP-binding protein, Multiple Antibiotic Resistance (MAR) family, export proteins, Helix-Turn-helix domains, arsenate reductase, elongation factor, ribosomal proteins, Cysteine protease precursor, Type-I restriction endonuclease enzyme and plasmid recombination enzyme which might have the same functions in hypothetical proteins. The structural prediction of those proteins and binding sites prediction have been done which would be useful in docking studies for aiding in the drug discovery.

/pdf/computational-structural-and-functional-analysis-of-4wzc4l2sue.pdf

Computational structural and functional analysis of hypothetical proteins of Staphylococcus aureus.

In silico Molecular Interaction Studies of Gamma-hemolysin of Staphylococcus aureus with Flavonoid Compounds

Background Superantigens of Staphylococcus aureus namely enterotoxin A, exfoliative toxin A, and Toxic shock syndrome toxin-1 cause detrimental effects on the cells of the immune system. Methods In this work, the toxins were downloaded from the Protein DataBank database and energies were minimized using KoBaMIN server. Forty flavonoids compounds were identified by pubchem compound database through extensive literature study and their 3D structures were obtained by submitting SMILES to CORINA tool. Based on Lipinski's rule of five, the molecules were filtered that resulted in 27 compounds. Molecular docking was performed for identifying the binding and interaction sites of flavonoids with the toxins using Autodock 4. Results and conclusion The docked complexes were then subjected to molecular dynamics simulation using Gromacs. The analysis revealed the stability of the complexes as indicated by three hydrogen bonds formed during the simulation time period of 20 ns.

Molecular Binding and Simulation Studies of Staphylococcus aureus Superantigens with Flavonoid Compounds

Recent investigations have rapidly added crucial new insights into the complex functions of the normal BCR gene and of the BCR-ABL chimaera. They are yielding potential therapeutic breakthroughs in the treatment of Philadelphia (Ph) chromosome-positive leukemias. The objective of the present in silico research investigation is to find out whether the functional part (beta-turns) is present in the mutated amino acids of BCR (Breakpoint cluster region) protein. Two significant steps are involved in this study. First, we performed protein sequence modeling of BCR using automated protein modeling servers and the 3D structure was visualized using molecular visualization software and tools. In the second step, the function domains and motifs regions of BCR gene-coded protein is predicted using “PDBsum generate” tool in order to show where exactly the beta-turns lie on the clinically-proven mutated amino acids of BCR protein. The results of our investigation can be used as potential drug binding sites in the field of drug docking studies. It can act as a potential therapeutic agent for Chronic Myeloid Leukemia (CML) type of Leukemia.

Identification of the motifs of beta-turns and mutated amino acids studies on BCR (Breakpoint cluster region) protein using Insilico techniques

Structures of proteins are maintained by various non-covalent interactions, including Cation-pi interaction. In this study, we have investigated those interactions responsible for maintaining structures in toxins produced by Staphylococcus aureus. Toxins are potent activators of the immune system that produce a variety of diseases in humans by direct binding of major histocompatibility complex (MHC) class II molecules on Antigen presenting cells and active T cells bearing a particular T-cell receptor beta chain variable (Vβ) domain. Considering its importance in clinical aspects, we analyzed the interactions in 24 different toxins of the bacterium by in silico with respect to structure, stability involving secondary structures, conservation scores, solvent accessibility and stabilization centers. Out of 24 toxins investigated, we found cation-pi interactions in 22 proteins and there is a preference of Lys over Arg in cationic residues and Tyr among pi residues. The least energy value of -109.65 kcal/mol of Toxic Shock Syndrome Toxin (PDB code 2QIL) revealed its greater stability. The residues involved in forming cation- pi interactions are found buried inside the protein and highly conserved. The analysis inferred that the interaction is found common and important for maintaining the protein structure, stability to deliver the toxicity and disease mechanism in host.

Ramadevi Mohan

Papers

Computational structural and functional analysis of hypothetical proteins of Staphylococcus aureus.

In silico Molecular Interaction Studies of Gamma-hemolysin of Staphylococcus aureus with Flavonoid Compounds

Molecular Binding and Simulation Studies of Staphylococcus aureus Superantigens with Flavonoid Compounds

Identification of the motifs of beta-turns and mutated amino acids studies on BCR (Breakpoint cluster region) protein using Insilico techniques

Cation-pi analysis in staphylococcus aureus toxins – an in silico approach