Pradip K. Bhatnagar, Ph.D.
Former President & Head, Daiichi Sankyo Life Science Research Centre, India
Strategies for Diseases/Target Selection for Drug Discovery and a Multi-Targeted Approach to Metabolic Disorder
Drug discovery and development is a high risk and expensive undertaking. Although, technologies, such as, bioinformatics, genomics, high throughput screening and computer-aided design have helped identify targets, biomarkers, lead candidates and reduced the time required for advancing an idea from bench to clinic, but it still takes 10-12 years and costs approximately one billion dollars to bring a drug to market globally. Therefore, it is imperative that the strategies to reduce the risk and increase efficiency are carefully selected. In this presentation I would discuss strategies for selecting potential diseases, targets and provide an example of multi-targeted approach to metabolic disorder.
Sanjeeva Srivastava, Ph.D.
Assistant Professor, Proteomics Lab, IIT-Bombay, India
Identification of Potential Early Diagnostic Biomarkers for Gliomas and Various Infectious Diseases using Proteomic Technologies
The spectacular advancements achieved in the field of proteomics research during the last decade have propelled the growth of proteomics for clinical research. Recently, comprehensive proteomic analyses of different biological samples such as serum or plasma, tissue, CSF, urine, saliva etc. have attracted considerable attention for the identification of protein biomarkers as early detection surrogates for diseases (Ray et al., 2011). Biomarkers are biomolecules that can be used for early disease detection, differentiation between closely related diseases with similar clinical manifestations as well as aid in scrutinizing disease progression. Our research group is performing in-depth analysis of alteration in human proteome in different types of brain tumors and various pathogenic infections to obtain mechanistic insight about the disease pathogenesis and host immune responses, and identification of surrogate protein markers for these fatal human diseases.
Applying 2D-DIGE in combination with MALDI-TOF/TOF MS we have analyzed the serum and tissue proteome profiles of glioblastoma multiforme; the most common and lethal adult malignant brain tumor (Gollapalli et al., 2012) (Figure 1). Results obtained were validated by employing different immunoassay-based approaches. In serum proteomic analysis we have identified some interesting proteins like haptoglobin, ceruloplasmin, vitamin-D binding protein etc. Moreover, proteomic analysis of different grades (grade-I to IV) of gliomas and normal brain tissue was performed and differential expressions of quite a few proteins such as SIRT2, GFAP, SOD, CDC42 have been identified, which have significant correlation with the tumor growth. While proteomic analysis of cerebrospinal fluid from low grade (grade I & II) vs. high grade (grade III & IV) gliomas revealed modulation of CSF levels of apolipoprotein E, dickkopf related protein 3, vitamin D binding protein and albumin in high grade gliomas. The prospective candidates identified in our studies provide a mechanistic insight of glioma pathogenesis and identification of potential biomarkers. We are also studying the role of JAK/STAT interactome and therapeutic potential of STAT3 inhibitors in gliomas using proteomics approach. Several candidates of the JAK/STAT interactome were identified with altered expression and a significant correlation was observed between STAT3 and PDK1 transcript expression level.
We have also investigated the changes in human serum proteome in different infectious diseases including falciparum and vivax malaria (Ray et al., 2012a; Ray et al., 2012b), dengue (Ray et al., 2012c) and leptospirosis (Srivastava et al., 2012). Although, quite a few serum proteins were found to be commonly altered in different infectious diseases and might be a consequence of inflammation mediated acute phase response signaling, uniquely modulated candidates were identified in each pathogenic infection indicating the some inimitable responses. Further, a panel of identified proteins consists of six candidates; serum amyloid A, hemopexin, apolipoprotein E, haptoglobin, retinol-binding protein and apolipoprotein A-I was used to build statistical sample class prediction models employing PLSDA and other classification methods to predict the clinical phenotypic classes and 91.37% overall prediction accuracy was achieved (Figure 2). ROC curve analysis was carried out to evaluate the individual performance of classifier proteins. The excellent discrimination among the different disease groups on the basis of differentially expressed proteins demonstrates the potential diagnostic implications of this analytical approach.
Keywords: Diagnostic biomarkers, Gliomas, Infectious Diseases, Proteomics, Serum proteome
Acknowledgments: This disease biomarker discovery research was supported by Department of Biotechnology, India grant (No. BT/PR14359/MED/30/916/2010), Board of Research in Nuclear Sciences (BRNS) DAE young scientist award (2009/20/37/4/BRNS) and a startup grant 09IRCC007 from the IIT Bombay. The active support from Advanced Center for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Hospital (TMH), and Seth GS Medical College and KEM Hospital Mumbai, India in clinical sample collection process is gratefully acknowledged.
References :
- Ray S, Reddy PJ, Jain R, Gollapalli K. Moiyadi A, Srivastava S. Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead. Proteomics 11: 2139-61, 2011.
- Gollapalli K, Ray S, Srivastava R, Renu D, Singh P, Dhali S, Dikshit JB, Srikanth R, Moiyadi A, Srivastava S. Investigation of serum proteome alterations in human glioblastoma multiforme. Proteomics 12(14): 2378-90, 2012.
- Ray S, Renu D, Srivastava R, Gollapalli K, Taur S, Jhaveri T, Dhali S, Chennareddy S, Potla A, Dikshit JB, Srikanth R, Gogtay N, Thatte U, Patankar S, Srivastava S. Proteomic investigation of falciparum and vivax malaria for identification of surrogate protein markers. PLoS One 7(8): e41751, 2012a.
- Ray S, Kamath KS, Srivastava R, Raghu D, Gollapalli K, Jain R, Gupta SV, Ray S, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Patankar S, Srivastava S. Serum proteome analysis of vivax malaria: An insight into the disease pathogenesis and host immune response. J Proteomics 75(10): 3063-80, 2012b.
- Srivastava R, Ray S, Vaibhav V, Gollapalli K, Jhaveri T, Taur S, Dhali S, Gogtay N, Thatte U, Srikanth R, Srivastava S. Serum profiling of leptospirosis patients to investigate proteomic alterations. J Proteomics 76: 56-68, 2012.
- Ray S, Srivastava R, Tripathi K, Vaibhav V, Srivastava S. Serum proteome changes in dengue virus-infected patients from a dengue-endemic area of India: towards new molecular targets? OMICS 16(10): 527-36, 2012c.
* Correspondence: Dr. Sanjeeva Srivastava, Department of Biosciences and Bioengineering, IIT Bombay, Mumbai 400 076, India: E-mail: sanjeeva@iitb.ac.in; Phone: +91-22-2576-7779, Fax: +91-22-2572-3480
Rajgopal Srinivasan, Ph.D.
Principal Scientist & Head Bio IT R&D, TCS Innovation Labs, India
Interpretation of Genomic Variation – Identifying Rare Variations Leading to Disease
Genome sequencing technologies are generating an abundance of data on human genetic variations. A big challenge lies in interpreting the functional relevance of such variations, especially in clinical settings. A first step in understanding the clinical relevance of genetic variations is to annotate the variants for region of occurrence, degree of conservation both within and across species, pattern of variation across related individuals, novelty of the variation and know effects of related variations. Several tools already exist for this purpose. However, these tools have their strengths and weaknesses. A second issue is the development of algorithms, which, given a rich annotation of variants are able to prioritize the variants as being relevant to the phenotype under investigation.
In my talk I will detail work that has been done in our labs to address both of the above problems. I will also illustrate the application of these tools that helped identify a rare mutation in the ATM gene leading to a diagnosis of AT in two infants.
Michelle Hermiston, MD, Ph.D.
Assistant Professor, Department of Pediatrics University of California San Francisco, USA
Interrogating Signaling Networks at the Single Cell Level In Primary Human Patient Samples
Multiparameter phosphoflow cytometry is a highly sensitive proteomic approach that enables monitoring of biochemical perturbations at the single cell level. By combining antisera to cell surface markers and key intracellular proteins, perturbations in signaling networks, cell survival and apoptosis mediators, cell cycle regulators, and/or modulators of other cellular processes can be analyzed in a highly reproducible and sensitive manner in the basal state and in response to stimulation or drug treatment. Advantages of this approach include the ability to identify the biochemical consequences of genetic and/or epigenetic changes in small numbers of cells, to map potential interplay between various signaling networks simultaneously in a single cell, and to interrogate potential mechanisms of drug resistance or response in a primary patient sample. Application of this technology to patients with acute lymphoblastic leukemia or the autoimmune disease systemic lupus erythematosus (SLE) will be discussed.
Kal Ramnarayan, Ph.D.
Co-founder President & Chief Scientific Officer, Sapient Discovery, San Diego, CA, USA
A cost-effective approach to Protein Structure-guided Drug Discovery: Aided by Bioinformatics, Chemoinformatics and computational chemistry
With the mapping of the human genome completed almost a decade ago, efforts are still underway to understand the gene products (i.e., proteins) in the human biological and disease pathways. Deciphering such information is very important for the discovery and development of small molecule drugs as well as protein therapeutics for various human diseases for which no cure exists. As an example, with more than 500 members, the kinase family of protein targets continues to be an important and attractive class for drug discovery. While how many of the members in this family are actually druggable is still to be established, there are several ongoing efforts on this class of proteins across a broad spectrum of disease categories. Even though in general the protein structural topology might looks similar, there are issues with respect selectivity of identified small molecule inhibitors when, the lead molecule discovery is carried out at the ATP binding site. As an added complexity, allosteric modulators are needed for some of the members, but the actual site for such modulation on the protein target can not resolved with uncertainty. In this presentation we will describe a bioinformatics and computational based platform for small molecule discovery for protein targets that are involved in protein-protein interactions as well as targets like kinases and phosphatases. We will describe a computational approach in which we have used an informatics based platform with several hundred kinases to sort through in silico and identify inhibitors that are likely to be highly selective in the lead generation phase. We will discuss the implication of this approach on the drug discovery of the kinase and phosphatase classes in general and independent of the disease category.
John Stanley, Satheesh Babu, Ramacahandran T and Bipin Nair
Pt-Pd decorated TiO2 nanotube array for the non-enzymatic determination of glucose in neutral medium
Rapidly expanding diabetic population and the complications associated with elevated glycemic levels necessitates the need for a highly sensitive, selective and stable blood glucose measurement strategy. The high sensitivity and selectivity of enzymatic sensors together with viable manufacturing technologies such as screen-printing have made a great social and economic impact. However, the intrinsic nature of the enzymes leads to lack of stability and consequently reduces shelf life and imposes the need for stringent storage conditions. As a result much effort has been directed towards the development of ‘enzyme-free’ glucose sensors (Park et al. 2006). In this paper, a non-enzymatic amperometric sensor for selective and sensitive direct electrooxidation of glucose in neutral medium was fabricated based on Platinum-Palladium (Pt–Pd) nanoparticle decorated titanium dioxide (TiO2) nanotube arrays. Highly ordered TiO2 nanotube arrays were obtained using a single step anodization process (Grimes C A and Mor G K 2009) over which Pt–Pd nanoparticles where electrochemically deposited. Scanning Electron Microscopy (SEM) analysis revealed the diameter of the TiO2 nanotubes to be approximately 40 nm. Elemental analysis after electrochemical deposition confirms the presence of Pt–Pd. Electrochemical characterization of the sensor was carried out using cyclic voltammetry technique (−1.0 to +1.0V) in phosphate buffer saline (PBS) pH 7.4. All further glucose oxidation studies were performed in PBS (pH 7.4). The sensor exhibited good linear response towards glucose for a concentration range of 1 μM to 20mM with a linear regression coefficient of R = 0.998. The electrodes are found to be selective in the presence of other commonly interfering molecules such as ascorbic acid, uric acid, dopamine and acetamidophenol. Thus a nonenzymatic sensor with good selectivity and sensitivity towards glucose in neutral medium has been developed.
The global healthcare scene of which the pharmaceutical industry and its products are integral components is today at the cross roads. The high and unaffordable costs of drug research with estimates of over 1 billion dollars for every new drug discovered and developed, the very low success rates, the high degree of obsolescence due to undesirable adverse drug reactions, the decline in the development pipeline of new drugs, patent expiries leading to generic competition and the public’s disillusionment with use of chemicals for human consumption as drugs have all significantly contributed to the problems of this lifeline industry. The strategy adopted by the large R&D based Corporations to get bigger and bigger through mergers and acquisitions to improve cost-effectiveness and productivity of R&D has so far not worked effectively. Consequently, one of the recent trends in healthcare, articulated by many experts is to look for alternate or even complementary approaches to reduce the impact of rising costs of drugs on healthcare. Various new strategies for drug discovery such as the use of Natural Products especially medicinal plants are being actively pursued by healthcare planners and providers. Side by side, traditional systems of medicine whether from the oriental countries or the western nations are also having a serious relook to understand their usefulness in healthcare. To achieve its legitimate position in the healthcare scenario, it is essential to scientifically validate their claimed utility through appropriate and systematic research efforts including pre-clinical and clinical studies. In addition to their own use as medicines, knowledge on the Indian Traditional Medicines can be used as a platform for new drug discovery. The huge potential for carrying out systematic R&D programs for new Drug Discovery based on natural products and possible strategies to realise them in the coming decades will be explained in this presentation.
Ramani A. Aiyer, Ph.D., MBA
Principal, Shasta BioVentures, San Jose, CA, USA
New Drug R&D in India: Challenges & Opportunities
New drug discovery and development has become a global endeavor, with Western big pharmaceutical companies farming out more and more chemistry and biology research to Asia, particularly India and China. During the last decade, several Indian pharmaceutical companies have embarked on ambitious R&D programs, with slow but steady progress in developing new chemical / molecular entities. The Indian government has also made a strong commitment to promote innovation and entrepreneurship in the biotechnology sector. The first part of the talk will focus on a case study showing the entire process of discovery and development of a new drug recently launched for Rheumatoid Arthritis. We will then address the challenges of conducting innovative R&D in India and actions necessary to overcome them. The second part of the talk will make the case for developing Ayurvedic drug formulations for the Western / Global markets, again using the example of Rheumatoid Arthritis (Aamavaata). Ayurveda takes a holistic approach to disease diagnosis and therapy based on interactions among body type (prakriti), tri-doshas (three body humors), sapta-dhatus (seven tissues) and malas (excretions). The drugs prescribed are usually herbo-mineral formulations comprising multiple medicinal plants and / or metals. The manufacturing processes date back to Ayurvedic texts several thousand years old, and are compiled in the Ayurvedic Pharmacopeia. Also, the treatment modalities and drug formulations are “personalized” to fit different patient types, based on the holistic diagnoses mentioned earlier. There is a tremendous need to establish a sound basis for Ayurvedic drug discovery R&D for the modern world. We must find a scientific and ethical way to leverage the vast body of anecdotal and possibly retrospective data on patients undergoing Ayurvedic treatment. Combined with in vitro and in vivo biological data on Ayurvedic herbo-mineral formulations, the adoption of stringent manufacturing practices, and designing sound clinical trials to establish the safety and efficacy, India has a golden opportunity to expand the reach of Ayurvedic drugs into Western / Global medical practice.