Zeeshan Iqbal

CREB in long‐term potentiation in hippocampus: Role of post‐translational modifications‐studies In silico

The multifunctionality of proteins is dictated by post‐translational modifications (PTMs) which involve the attachment of small functional groups such as phosphate and acetate, as well as carbohydrate moieties. These functional groups make the protein perform various functions in different environments. PTMs play a crucial role in memory and learning. Phosphorylation of synaptic proteins and transcription factors regulate the generation and storage of memory. Among these is the cAMP‐regulated element binding protein CREB that regulates CRE containing genes like c‐fos. Both phosphorylation and acetylation control the function of CREB as a transcription factor. CREB is also susceptible to O‐GlcNAc modification, which inhibits its activity. O‐GlcNAc modification occurs on the same or neighboring Ser/Thr residues akin to phosphorylation. An interplay between these modifications was shown to operate in nuclear and cytoplasmic proteins. In this study computational methods were utilized to predict different modification sites in CREB. These in silico results suggest that phosphorylation, O‐GlcNAc modification and acetylation modulate the transcriptional activity of CREB and thus dictate its contribution to synaptic plasticity. J. Cell. Biochem. 112: 138–146, 2011.

Influence of the sequence environment and properties of neighboring amino acids on amino-acetylation: relevance for structure-function analysis.

Proteins function is regulated by co‐translational modifications and post‐translational modifications (PTMs) such as phosphorylation, glycosylation, and acetylation, which induce proteins to perform multiple tasks in a specified environment. Acetylation takes place post‐translationally on the ε‐amino group of Lys in histone proteins, allowing regulation of gene expression. Furthermore, amino group acetylation also occurs co‐translationally on Ser, Thr, Gly, Met, and Ala, possibly contributing to the stability of proteins. In this work, the influence of amino acids next to acetylated sites has been investigated by using MAPRes (Mining Association Patterns among preferred amino acid residues in the vicinity of amino acids targeted for PTMs). MAPRes was utilized to examine the sequence patterns vicinal to modified and non‐modified residues, taking into account their charge and polarity. The PTMs data were further sub‐divided according to their sub‐cellular location (nuclear, mitochondrial, and cytoplasmic), and their association patterns were mined. The association patterns mined by MAPRes for acetylated and non‐acetylated residues are consistent with the existing literature but also revealed novel patterns. These rules have been utilized to describe the acetylation and its effects on the protein structure‐function relationship. J. Cell. Biochem. 114: 874–887, 2013.

Exploring the Sequence Context of Phosphorylatable Amino Acids: The Contribution of the Upgraded MAPRes Tool

Several models that predict where post‐translational modifications are likely to occur and formulate the corresponding association rules are available to analyze the functional potential of a protein sequence, but an algorithm incorporating the functional groups of the involved amino acids in the sequence analyses process is not yet available. In its previous version, MAPRes was utilized to investigate the influence of the surrounding amino acids of post‐ translationally and co‐translationally modifiable sites. The MAPRes has been upgraded to take into account the different biophysical and biochemical properties of the amino acids that have the potential to influence different post‐ translational modifications (PTMs). In the present study, the upgraded version of MAPRes was implemented on phosphorylated Ser/Thr/Tyr data by considering the polarity and charge of the surrounding amino acids. The patterns mined by MAPRes incorporating structural information on polarity and charge of amino acids suggest distinct structure‐function relationships for phosphorylated serines in a multifunctional protein such as the insulin‐receptor substrate‐1 (IRS‐1) protein. The new version of MAPRes is freely available at http://www.imsb.edu.pk/Database.htm. J. Cell. Biochem. 116: 370–379, 2015.

O-GlcNAc modification of the anti-malarial vaccine candidate PfAMA1: in silico-defined structural changes and potential to generate a better vaccine.

The complex life cycle of plasmodial parasites makes the selection of a single subunit protein a less than optimal strategy to generate an efficient vaccinal protection against malaria. Moreover, the full protection afforded by malarial proteins carried by intact parasites implies that immune responses against different antigens expressed in different phases of the cycle are required, but also suggests that native malarial antigens are presented to the host immune system in a manner that recombinant proteins do not achieve. The malarial apical membrane antigen 1 (AMA1) represents a suitable vaccine candidate because AMA1 is expressed on sporozoites and merozoites and allows them to invade hepatocytes and erythrocytes, respectively. Anti-AMA1 antibodies and cytotoxic T-cells are therefore expected to interfere both with the primary invasion of hepatocytes by sporozoites and with the later propagation of merozoites in erythrocytes, and thus efficiently counteract parasite development in its human host. AMA1 bears potential glycosylation sites and the human erythrocytic O-linked N-acetylglucosamine transferase (OGT) could glycosylate AMA1 through combinatorial metabolism. This hypothesis was tested in silico by developing binding models of AMA1 with human OGT complexed with UDP-GlcNc, and followed by the binding of O-GlcNAc with the hydroxyl group of AMA1 serine and threonine residues. Our results suggests that AMA1 shows potential for glycosylation at Thr517 and Ser498 and that O-GlcNAc AMA1 may constitute a conformationally more appropriate antigen for developing a protective anti-malarial immune response.

Computational modeling and biomarker studies of pharmacological treatment of Alzheimer's disease (Review)

Alzheimers disease (AD) is a complex and multifactorial disease. In order to understand the genetic influence in the progression of AD, and to identify novel pharmaceutical agents and their associated targets, the present study discusses computational modeling and biomarker evaluation approaches. Based on mechanistic signaling pathway approaches, various computational models, including biochemical and morphological models, are discussed to explore the strategies that may be used to target AD treatment. Different biomarkers are interpreted on the basis of morphological and functional features of amyloid β plaques and unstable microtubule-associated tau protein, which is involved in neurodegeneration. Furthermore, imaging and cerebrospinal fluids are also considered to be key methods in the identification of novel markers for AD. In conclusion, the present study reviews various biochemical and morphological computational models and biomarkers to interpret novel targets and agonists for the treatment of AD. This review also highlights several therapeutic targets and their associated signaling pathways in AD, which may have potential to be used in the development of novel pharmacological agents for the treatment of patients with AD. Computational modeling approaches may aid the quest for the development of AD treatments with enhanced therapeutic efficacy and reduced toxicity.

Stereoelectronic effect in amino acids and its influence on modification potential of proteins: In silico approach

T increasing availability of recombinant components of the human proteome and multiplex array platforms provide unique opportunities for both targeted and discovery-driven analyses of auto-antibody repertoires. We previously identified enriched affinity for 51 out of 11,520 human protein fragments by plasma IgG of individuals with Multiple Sclerosis (MS). Almost all of these antigens were novel auto-antibody targets not previously described in the context of MS. Here, we present an in-depth analysis and further characterization of these previously identified targets together with targets suggested in literature (e.g., KIR4.1) using an independent cohort of 2,169 plasma samples from MS cases and population-based controls on bead-based antigen arrays.We confirmed and strengthened the presence of auto-antibodies against one of our previously proposed targets, a calcium-activated chloride channel protein called Anoctamin 2 (ANO2) in ~15% of MS cases. Here, auto-antibodies against AN02 revealed the most prominent difference within the IgG repertoire between MS cases and controls. These results were reproduced for a subset of samples in independent assays performed at a different laboratory. Using peptide arrays, ANO2 autoantibody epitopes were mapped with higher amino acid resolution. Additionally, we found that the conspicuous HLA complex MS-associated risk genes interacted strongly with the presence of ANO2 auto-antibodies, reinforcing a potential role of the ANO2 auto-reactivity in MS ethiopathogenesis. Further immunofluorescence analysis on human MS brain tissue revealed a clear increase in ANO2 staining as small cellular aggregates near and inside MS lesions. These findings demonstrate the potential for the existence of an ANO2 autoimmune sub-phenotype in MS. They lay the ground for further studies focusing on this particular target with regard to its pathogenic role in MS either directly or as an epiphenomenon.A interesting use of proteomics is using specific protein biomarkers to early stage biomedical diagnose and drug discovery improve. Biomarkers are discrete proteins or other molecular entities that act as surrogate markers for the presence of disease. Despite the relevant improvements of the past decades, the development of highly sensitive analytical methodologies for low abundance biomarkers identification, in complex mixtures of proteins remains being challenging in modern proteomics. Immunology laboratories widely rely on the enzyme linked immunosorbent assay (ELISA) for protein detection and identification. However, despite the high sensitivity of the method, target of several biomarkers in parallel in single samples cannot easily be performed with emissive reporters-based ELISA protocols due to the broad spectral characteristics. Innovative approaches to obtain sensitivity enhancements with detection limits even down to the single molecule have been proposed in the nanotechnology framework. In the nanoplasmonics field, Surface Enhanced Raman Scattering (SERS) spectroscopy has been performed as an ultrasensitive, fast and universal analytical technique. In this context, we have recently developed a method to allow the selective identification of specific biomarkers in complex matrices such as human plasma and serum opening the possibility of highly sensitive multiplexing diagnosis or medical investigations.F early observations indicating that amino acids were a convenient subset of the metabolome to investigate changes in metabolism associated with various physiological states, we have developed a technology package (“AminoIndex technology”) to generate biomarkers for various disease and physiological states using plasma amino acid concentration data and have commercialized a service based on this technology. In order to achieve commercialization, various problems ranging from sample handling, throughput, standardization and follow-up services had to be overcome and some of these issues which may be relevant to other biomarker commercialization will be addressed in the presentation. So far, “AminoIndex technology” has been used to generate risk biomarkers for gastric, lung, colorectal, prostate and breast cancer and since its launch as a biomarker service in April 2011 in Japan, it has been adopted by over 900 hospitals and clinics as an optional blood test and has led to the receipt of various awards in Japan. Research is ongoing to add other cancer risk biomarkers as well as biomarkers for other diseases risks. The advantage of “AminoIndex technology” is that one measurement of plasma amino acids potentially allows the determination of multiple biomarkers as each biomarker is composed of multiple amino acids. We believe that in the near future, other validated metabolites and omics data could be added to the current analytical platform increasing discriminative power. Although there are a number of issues still need refinement, we believe that the “AminoIndex technology” platform can play a role in tailor-made nutrition and medicine.P are major functional molecules in complex biological systems. One protein may involve in different and unrelated functions, and able to mediate coordinated adaptive responses across cellular compartments. Changes in local environments can induce functional switches by altering protein conformation. The majority of the bioactive and functional proteins (in vivo) are modified proteins (glycoproteins, lipoproteins and phosphoproteins). The 3D structure and function of proteins are often studied in vitro with no consideration of actual in vivo conformation or environment of proteins. The functions of modified proteins are difficult to predict as the structural consequences of a given modification will depend, particularly in vivo, upon interactions with other proteins. The analyses of surrounded amino acids of modified residues are vitally important to identify specific modified residues and consequently the development of its correlation with protein function. MAPRes (Mining association patterns among preferred amino acid residues in the vicinity of amino acids targeted for post-translational modifications) algorithm has capacity to mine significantly preferred amino acids in surroundings of modified residues and establish correlation between them. The charge and polarity of the neighboring amino acids of modified residues have also been considered in upgraded version of MAPRes. Currently, the stereoelectronic effect of the surrounded amino acids has been considered as the most significant property to identify the specific modifications and functional regulations of the proteins.A proposed discrete real-scale hierarchical repeated pattern type called T-pattern has been found in many kinds of verbal and non-verbal human, animal and neuronal behavior and interactions and seems characteristic of DNA patterns such as exons and genes. Functional analogies also seem to exist. Such structural self-similarity over a number of levels of biological organization suggests the possibility of a unified mathematical, bioinformatics and system biological approach. The T-pattern, a synchronic and sequential hierarchical pattern of patterns etc with statistically significant constraints on the distances between its components over its occurrences that is having approximate translation symmetry is described together with its extensions called T-system and a special purpose detection software, THEME. T-patterns may be seen as a particular kind of statistical pseudo-fractal objects on one dimension but extendable to n dimensions. Illustrative results with statistical (Monte Carlo) and external validation from human and neuronal interactions are presented and compared with the structure of exons, genes and chromosomes.