Computational Molecular Biophysics
Structural Bioinformatics

The Computational Structural Biology Lab (CSBL) has been established in 2016 at CSIR-Institute of Genomics and Integrative Biology, New Delhi, India.

We are exploring the huge diversity of biomolecular interactions and its association with human diseases. While biomolecules are simple polymers, remarkably their interactions reveal complex traits which in turn directly influences cellular architecture and behavior. We use state-of-the-art high-performance computing to characterize dynamic behaviour of biological macromolecules, and characterize their interactions.

Of particular interest to us are mechanisms by which proteins target specific membrane lipids and how their cross-talk involves coordinated action from protein and/or lipid structural conformations. While protein activity in relation to membrane lipids and its downstream regulation has been studied for years, very little is known about origin and evolution of functional states that act on membrane surfaces. We perform computational analyses involving structural bioinformatics and multi-scale molecular dynamics simulations to study unique and dynamic biology at atomistic scale. There are several other areas of interest that can be read from here.

 


Research

The goals of the Computational Structural Biology Lab are to use computational methods to study interesting problems at the interface of biology, physics and chemistry. More generally, the resulting hypothesis or methods are experimentally testable in collaboration with biomedical researchers to gain biological insights. The broader research themes are mentioned below:

What makes proteins work on mosaic membrane surfaces?

A fundamental principle in cell biology is the spatial coordination between different cells and within cells that is maintained by compartmentalizing cellular material into membranes. The protein organization within membrane is highly intricate and is tightly linked to location (cell-type specificity) and shape (protein conformational state) that govern a range of signaling activities. Membrane proteins comprise over 39% of human genome. Despite their essential role, they are relatively less studied.

More importantly, a large number of the cytoplasmic proteins involved in cell signaling and membrane trafficking reversibly associate with variety of cellular membranes in response to specific stimuli. Membrane recruitment of many such proteins is dependent on chemical modifications, or distinct membrane motifs that impart distinct attributes to protein functionality. The challenge therefore, is to predict mechanism by which cells localize proteins to sites on membrane where they can perform optimally and, in turn, interact with particular substrates.

Given the broad spectrum of proteins that interact with membranes, we are set out to understand protein-membrane dynamics in a model pathway - autophagy, a process to degrade cellular waste. In our earlier work, we had deciphered the molecular mechanism of LC3 membrane insertion, a key protein in autophagy. We are further geared up to understand how protein dynamics lead to formation of vesicles called autophagosomes.

One of our additional research interests in this theme is to develop methods to aid integration of experimental data with computational representations of biological membranes. We are currently working on development of methods to analyse large-scale structural data of heterogeneous membrane models to infer their mechanistic parameters.

Structural Bioinformatics

Structure of proteins is closely coupled with its function, as evidenced by many conformational changes observed in key cellular process. One of the major challenges in structural biology is to determine the structures and its dynamics of macromolecular complexes and to understand their function. A part of our efforts is to engage with experimental biologists to predict functional consequences of a protein with its bound ligands. We are working towards mapping mutations on known complexes associated with various diseases to understand dysfunctional protein character.

Structural Systems Biology

Resolving the molecular details of how biomolecules commit to cellular processes is an essential task in life science research. By investigating the relationship between complex data outputs emerging from structural biology, genomics, interaction data sets, imaging techniques, we intend to understand the link between gene to function.

The high-throughput sequencing data of whole genomes from clinical sources is emerging as a biggest paradigm in current century. We are currently working with several experimental groups to converge genomic and structural information onto biological pathways. Different measurements at different lengths and timescales may ultimately make it possible to understand the molecular mechanisms underlying various diseases.

 

 

Publications

         @corresponding author

  1. A conserved degron containing an amphipathic helix regulates the cholesterol mediated turnover of human squalene monooxygenase, a rate-limiting enzyme in cholesterol synthesis.
    Chua NK, Howe V, Jatana N, Thukral L, Brown AJ.
    J Biol Chem. 2017 Sep 27. pii: jbc.M117.794230. doi: 10.1074/jbc.M117.794230.
    [Pubmed] [Article]
  2. Mapping architectural and transcriptional alterations in non-lesional and lesional epidermis in vitiligo.
    Singh A, Gotherwal V, Junni P, Vijayan V, Tiwari M, Ganju P, Kumar A, Sharma P, Fatima T, Gupta A, Holla A, Kar HK, Khanna S, Thukral L, Malik G, Natarajan K, Gadgil CJ, Lahesmaa R, Natarajan VT, Rani R, Gokhale RS.
    Sci Rep. 2017 Aug 29;7(1):9860. doi: 10.1038/s41598-017-10253-w.
    [Pubmed] [Article]
  3. Classical autophagy proteins LC3B and ATG4B facilitate melanosome movement on cytoskeletal tracks.
    Ramkumar A, Murthy D, Raja DA, Singh A, Krishnan A, Khanna S, Vats A, Thukral L, Sharma P, Sivasubbu S, Rani R, Natarajan VT, Gokhale RS.
    Autophagy. 2017 Aug 3;13(8):1331-1347. doi: 10.1080/15548627.2017.1327509
    [Pubmed] [Article]
  4. Lipidated proteins: Spotlight on protein-membrane binding interfaces.
    Ray A, Jatana N, Thukral L@.
    Prog Biophys Mol Bio. 2017 doi: 10.1016/j.pbiomolbio. 2017.01.002.
    [Pubmed] [Article]
  5. Theoretical-computational characterization of the temperature-dependent folding thermodynamics of a beta-hairpin peptide.
    Daidone I, Zanetti-Polzi L, Thukral L, Alekozai E, Amadei A.
    Chem Phys Lett. 2016. 659():247--251.
    [Pubmed] [Article]
  6. Structural signatures of DRD4 mutants revealed using molecular dynamics simulations: Implications for drug targeting.
    Jatana N, Thukral L@, Latha N@.
    J Mol Model. 2016. 22(1):14.
    [Pubmed] [Article]
  7. Decoding structural properties of a partially unfolded protein substrate: en route to chaperone binding.
    Nagpal S, Tiwari S, Mapa K, Thukral L@.
    PLoS Comput. Biol. 2015. 11(9):e1004496.
    [Pubmed] [Article]
  8. Molecular mechanism underlying recruitment and insertion of lipid-anchored LC3 proteins into membranes.
    Thukral L@, Sengupta D, Ramkumar A, Murthy D, Agrawal N, Gokhale RS@.
    Biophys J. 2015. 109(10):2067-78.
    [Pubmed] [Article]
  9. Unsaturated Lipid Assimilation by Mycobacteria Requires Auxiliary cis-trans Enoyl CoA Isomerase.
    Srivastava S, Chaudhary S, Thukral L, Shi C, Gupta RD, Gupta R, Priyadarshan K, Vats A, Haque AS, Sankaranarayanan R, Natarajan VT, Sharma R, Aldrich CC, Gokhale RS.
    Chem Biol. 2015. 17;22(12):1577-87.
    [Pubmed] [Article]
  10. Beta-structure within the denatured state of the helical protein domain BBL.
    Thukral L, Schwarze S, Daidone I, Neuweiler H
    J. Mol. Bio. 2015. 427(19):3166-76.
    [Pubmed] [Article]
  11. Molecular Modeling indicates that homocysteine induces conformational changes in the structure of putative target proteins.
    Silla Y, Ray A, Thukral L, Sengupta S.
    J. Proteins and Proteomics. 2015. 6(3), 271-286.
    [Pubmed] [Article]
  12. Structure and dynamics of DRD4 bound to an agonist and an antagonist using in silico approaches
    Jatana N, Thukral L@, Latha N@
    Proteins. 2015. 83(5):867-80.
    [Pubmed] [Article]
  13. Monitoring the folding kinetics of a beta-hairpin by time-resolved IR spectroscopy in silico.
    Daidone I, Thukral L, Smith JC, Amadei A.
    J Phys Chem B. 2015. 119(14):4849-56.
    [Pubmed] [Article]
  14. Lipid protein interactions in membranes: implications for health and disease.
    Thukral L, Brown AJ.
    Clin. Lipidol. 2013. 8(1), 43-45.
    [Pubmed] [Article]
  15. Structured pathway across the transition state for peptide folding revealed by molecular dynamics simulations.
    Thukral L, Daidone I, Smith C. J.
    PLoS Comput. Biol. 2011. 7 (9): e1002137.
    [Pubmed] [Article]
  16. Common folding mechanism of a beta-hairpin peptide via non-native turn formation revealed by unbiased molecular dynamics simulations
    Thukral L, Smith C. J, Daidone I.
    J. Am. Chem. Soc. (2009). 131 (50), 18147-18152.
    [Pubmed] [Article]
  17. ProRegIn: A Regularity Index for the selection of native-like tertiary structures of proteins.
    Thukral L, Shenoy S R, Bhushan Kumkum, Jayaram B.
    Journal of Biosciences. 2007. 32(1), 71-81.
    [Pubmed] [Article]


 

 

Lab Members

Lipi Thukral Principal Investigator
Nidhi Jatana Batra DBT-RA Research Fellow
2014-Present
Arjun Ray PhD student (in collaboration with Dr. Sengupta)
2013-Present
Surabhi Rathore PhD student
2017 onwards
Md. Asad Ansari Project Student (in collaboration with Dr. Bajaj)
2017-Present
Arvind Iyer Mtech Trainee
IIIT Delhi

 

 

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Location

Computational Structural Biology Lab
CSIR-Institute of Genomics and Integrative Biology
South Campus, Mathura Road
New Delhi 110020 (India)
Phone: +91-11-29879223
Email: lipi.thukral at igib.in

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