Bridging traditional and modern medicine with a data and informatics driven drug discovery framework

How could we possibly bridge elements from traditional medicinal knowledge and modern medicine with the help of computational tools to accelerate the drug discovery process?

Here I discuss an integrative strategy that is based on on our work conducted at CSIR-Institute of Himalayan Bioresource Technology (Palampur) and Indian Institute of Technology Jodhpur.

Diseases are manifestations of irregularities in cellular and molecular mechanisms. A large number of diseases have been scrutinized at the level of pathways and molecular causative agents, in addition to understanding contributing environmental factors. However, contrary to expectations, reductionist investigations of complex diseases have led to increase in noise making it difficult to ascertain specific causative molecular mechanisms that could be used to control the disease. Hence prompted by increasing need of integrating disparate molecular elements, systems biological strategies have been developed to create a holistic picture of molecular mechanisms underlying complex diseases. We have implemented network models, graph theoretical representations of interconnected systems, for the analysis of disease interactomes (Vashisht and Bagler, 2012; Randhawa and Bagler, 2012; Randhawa et al., 2013). These integrative models allow one to wade through the noise and to pin down specific targets and regulatory mechanisms, thus providing a rational strategy towards disease control. This approach has paved way for ‘network medicine’ towards deciphering causal relationship of diseases, molecular agents and regulatory mechanisms.

Historically, through trial and error, plant extracts have been identified as effective means of mitigating diseases without necessarily understanding their mode of action. Plants contain vast array of natural compounds with important pharmacological properties and their extracts have been used for treating various diseases from ancient times. Traditional medicinal systems are rich source of such information which is often complemented by modern medicinal studies. How could we possibly bridge traditional knowledge and modern medicine to facilitate accelerated drug discovery? Informed with our research explorations (Pathania et al., 2013;Pathania, Ramakrishnan, Randhawa, et al.,2015; Pathania, Ramakrishnan, and Bagler, 2015; Jain et al., 2015a; Perumal et al.,2015; Randhawa and Bagler, 2012; Randhawa etal., 2013; Vashisht and Bagler, 2012; Jain et al., 2015b; Jain and Bagler, 2015), we propose a data and informatics driven framework that juxtaposes systems biological models of complex diseases, reported efficacy of medicinal plant extracts, and compilations of structured libraries of small molecules, aimed at an effective and rational drug discovery process.

The proposed data and informatics driven integrative framework bridges traditional and modern medicine by bringing together various jigsaw pieces of knowledge as well as data enabled hypothesis driven search for therapeutic molecules. Following illustration depicts the framework and our contribution towards its various facets.

Ganesh Bagler

(An extended version of this article is to be published in the Advanced Techniques in Biology and Medicine journal)

References:

(1)   Vashisht,S. and Bagler,G. (2012) An Approach for the Identification of Targets Specific to BoneMetastasis Using Cancer Genes Interactome and Gene Ontology Analysis. PLoS ONE, 11, e49401.

(2)   Randhawa,V. and Bagler,G. (2012) Identification of SRC as a Potent Drug Target for Asthma, Using anIntegrative Approach of Protein Interactome Analysis and In Silico DrugDiscovery. OMICS A Journal of Integrative Biology, 16(10), 512–526.

(3)   Randhawa,V., Sharma,P, Bhushan,S and Bagler,G (2013) Identification of key nodes of Type 2 Diabetes Mellitus protein interactome andstudy of their interactions with phloridzin. OMICS A Journal of Integrative Biology, 17(6), 302–317.

(4)   Pathania,S, Randhawa,V and Bagler,G (2013) Prospecting for Novel Plant-Derived Molecules of Rauvolfia serpentina asInhibitors of Aldose Reductase, a Potent Drug Target for Diabetes and ItsComplications. PLoS ONE, 8, e61327.

(5)   Pathania,S., Ramakrishnan,S.M., Randhawa,V. and Bagler,G (2015) SerpentinaDB: a database of plant-derived moleculesof Rauvolfia serpentina. BMC Complementary and Alternative Medicine, 15, 262.

(6)   Pathania,S., Ramakrishnan,S.M., and Bagler,G. (2015) Phytochemica: a platform to explore phytochemicals ofmedicinal plants. Database (Oxford University Press), 2015, 1–8.

(7)   Jain,A, Rakhi,NK and Bagler,G (2015a) Spices form the basis of food pairing in Indian cuisine. arXiv:1502.03815.

(8)   Jain,A, Rakhi,NK and Bagler,G (2015b) Analysis of food pairing in regional cuisines of India. arXiv:1505.00890 (accepted, PLoS ONE).

(9)   Jain,A. and Bagler,G. (2015) Culinary evolution models for Indian cuisines. arXiv:1505.00155.

(10)  Perumal,S, Dubey,K, Badhwar,R, Kodimattan,JG, Sharma RK, Bagler,G, Madhan,B and Kar,K (2015) Capsaicin inhibits collagen fibril formation and increases the stability ofcollagen fibers. European Biophysical Journal, 44, 69–76.