Vineetha Mandlik

Molecular evolution of the enzymes involved in the sphingolipid metabolism of Leishmania: selection pressure in relation to functional divergence and conservation.

BackgroundSelection pressure governs the relative mutability and the conservedness of a protein across the protein family. Biomolecules (DNA, RNA and proteins) continuously evolve under the effect of evolutionary pressure that arises as a consequence of the host parasite interaction. IPCS (Inositol phosphorylceramide synthase), SPL (Sphingosine-1-P lyase) and SPT (Serine palmitoyl transferase) represent three important enzymes involved in the sphingolipid metabolism of Leishmania. These enzymes are responsible for maintaining the viability and infectivity of the parasite and have been classified as druggable targets in the parasite metabolome.ResultsThe present work relates to the role of selection pressure deciding functional conservedness and divergence of the drug targets. IPCS and SPL protein families appear to diverge from the SPT family. The three protein families were largely under the influence of purifying selection and were moderately conserved baring two residues in the IPCS protein which were under the influence of positive selection. To further explore the selection pressure at the codon level, codon usage bias indices were calculated to analyze genes for their synonymous codon usage pattern. IPCS gene exhibited slightly lower codon bias as compared to SPL and SPT protein families.ConclusionEvolutionary tracing of the proposed drug targets has been done with a viewpoint that the amino-acids lining the drug binding pocket should have a lower evolvability. Sites under positive selection (HIS20 and CYS30 of IPCS) should be avoided during devising strategies for inhibitor design.

Biological Activity of Coumarin Derivatives as Anti-Leishmanial Agents

Cutaneous leishmaniasis affects nearly 0.7 to 1.3 million people annually. Treatment of this disease is difficult due to lack of appropriate medication and the growing problem of drug resistance. Natural compounds such as coumarins serve as complementary therapeutic agents in addition to the current treatment modalities. In this study, we have performed an in-silico screening of the coumarin derivatives and their anti-leishmanial properties has been explored both in-vitro and in-vivo. One of the compounds (compound 2) exhibited leishmanicidal activity and to further study its properties, nanoliposomal formulation of the compound was developed. Treatment of cutaneous lesions in BALB/c mice with compound 2 showed significantly reduced lesion size as compared to the untreated mice (p<0.05) suggesting that compound 2 may possess anti-leishmanial properties.

Molecular docking and molecular dynamics simulation study of inositol phosphorylceramide synthase – inhibitor complex in leishmaniasis: Insight into the structure based drug design

Inositol phosphorylceramide synthase (IPCS) has emerged as an important, interesting and attractive target in the sphingolipid metabolism of Leishmania. IPCS catalyzes the conversion of ceramide to IPC which forms the most predominant sphingolipid in Leishmania. IPCS has no mammalian equivalent and also plays an important role in maintaining the infectivity and viability of the parasite. The present study explores the possibility of targeting IPCS; development of suitable inhibitors for the same would serve as a treatment strategy for the infectious disease leishmaniasis. Five coumarin derivatives were developed as inhibitors of IPCS protein. Molecular dynamics simulations of the complexes of IPCS with these inhibitors were performed which provided insights into the binding modes of the inhibitors. In vitro screening of the top three compounds has resulted in the identification of one of the compounds (compound 3) which shows little cytotoxic effects. This compound therefore represents a good starting point for further in vivo experimentation and could possibly serve as an important drug candidate for the treatment of leishmaniasis.

Synthetic circuit of inositol phosphorylceramide synthase in Leishmania: a chemical biology approach

Building circuits and studying their behavior in cells is a major goal of systems and synthetic biology. Synthetic biology enables the precise control of cellular states for systems studies, the discovery of novel parts, control strategies, and interactions for the design of robust synthetic systems. To the best of our knowledge, there are no literature reports for the synthetic circuit construction for protozoan parasites. This paper describes the construction of genetic circuit for the targeted enzyme inositol phosphorylceramide synthase belonging to the protozoan parasite Leishmania. To explore the dynamic nature of the circuit designed, simulation was done followed by circuit validation by qualitative and quantitative approaches. The genetic circuit designed for inositol phosphorylceramide synthase (Biomodels Database—MODEL1208030000) shows responsiveness, oscillatory and bistable behavior, together with intrinsic robustness.

LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database) is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level.

System pharmacogenomics application in infectious diseases

Abstract The new era in systems pharmacology has revolutionized the human biology. Its applicability, precise treatment, adequate response and safety measures fit into all the paradigm of medical/clinical practice. The importance of mathematical models in understanding the disease pathology and epideomology is now being realized. The advent of high-throughput technologies and the emergence of systems biology have resulted in the creation of systems pharmacogenomics and the focus is now on personalized medicine. However, there are some regulatory issues that need to be addresssed; are we ready for this universal adoption? This article details some of the infectious disease pharmacogenomics to the developments in this area.

Microbial Chassis Assisting Retrosynthesis

Synthetic biology has come a long way from constructing simple regulatory element to de novo pathway construction in heterologous host chassis. This is achieved by the transfer of the desired pathway from a rare organism to an organism that can be readily genetically engineered. These developments have great potential for application in biosynthesis of drugs, biofuels and bulk chemicals from simple and inexpensive starting material. As the complexity within a re-engineered system increases, there is an increasing need for efficient computational tools that can support them. Myriad of algorithms are available and are being developed that aid the re-engineering of pathways that help select and prioritize pathways, optimize enzyme performance, select parts for constructing the pathway, metabolic modelling and flux analysis and final integration into the chassis. This chapter gives a gist into the development of de novo pathway, the bioinformatics tools available, future challenges and research efforts needed for the implementation of synthetic biology for the production of key metabolites.

Application of Artificial Neural Networks in Modern Drug Discovery

Abstract Artificial neural networks are abstract models that mimic the complex structure and functioning of the brain. They are widely being used in the fields of systems biology and drug discovery for resolving complexity associated with mathematical models, virtual screening of compounds, deciphering quantitative structure–activity relationships, estimation of pharmacokinetic and pharmacodynamics properties, and during formulation development. With a number of variables deciding the outcome, neural networks are excellent in deciphering nonlinear relationships among the variables and predicting the outcome way before in the drug discovery process. The traditional drug discovery process often proves to be lengthy, expensive, and difficult. The present chapter discusses the possibility of using artificial neural networks to improve the efficiency and speed of therapeutic discovery.

Regulatory dynamics of network architecture and function in tristable genetic circuit of Leishmania: a mathematical biology approach.

The emerging field of synthetic biology has led to the design of tailor-made synthetic circuits for several therapeutic applications. Biological networks can be reprogramed by designing synthetic circuits that modulate the expression of target proteins. IPCS (inositol phosphorylceramide synthase) has been an attractive target in the sphingolipid metabolism of the parasite Leishmania. In this study, we have constructed a tristable circuit for the IPCS protein. The circuit has been validated and its long-term behavior has been assessed. The robustness and evolvability of the circuit has been estimated using evolutionary algorithms. The tristable synthetic circuit has been specifically designed to improve the rate of production of phosphatidylcholine: ceramide cholinephosphotransferase 4 (SLS4 protein). Site-specific delivery of the circuit into the parasite-infected macrophages could serve as a possible therapeutic intervention of the infectious disease ‘Leishmaniasis’.