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Saikat Chakrabarti, PhD

Post Doctoral Fellow

National Center for Biotechnology Information

National Library of Medicine

National Institutes of Health

USA

Phone: 301-496-6474

 

Research interests:

I have gained substantial experience in protein structural analysis and application of bioinformatics and computational tools in understanding the structure, function and evolutionary relationships amongst proteins. The theme of my Ph.D. thesis was to detect and analyze the underlined structural similarity amongst proteins that are highly diverse in terms of sequence homology. I analyzed and examined structural similarity among distantly related proteins by identifying set of structural motifs that usually do not get detected by sequence similarity approaches. These set of motifs are very important in forming the common core of structurally similar proteins and provide important information towards convergent evolutionary pressure at protein structure level. Further, these motifs are utilized in other important aspects such as improvement of homology modeling, multiple sequence alignment and database search for similar sequences.

 

I have been a post doctoral fellow in the Computational Biology Branch (CBB) of the National Center for Biotechnology Information (NCBI) under Prof. Stephen H. Bryant’s supervision since July 2004.  At the NCBI, I have been involved in development of algorithms that can successfully detect inherent mistakes within a multiple sequence alignment and subsequently rectify that by implementing an iterative alignment refinement procedure. This refinement algorithm improves the accuracy of conserved protein domain alignments and the sensitivity of search profiles constructed from these alignments. Identification and subsequent prediction of functionally important sites for proteins is very important and challenging field in biological research. I performed a detailed analysis of evolutionary conservation patterns at molecular and biological function level for a large set of known functionally important sites extracted from a wide range of protein families. I compared the degree of conservation across different functional categories to understand varying evolutionary constraints at functionally important sites.  The compositional and evolutionary information at functional important sites has been compiled into a library of functional templates, which is used to predict functionally important sites in other families. I am also interested in understanding the varying degree of evolutionary selection pressure on certain important sites that determine the specificity for different sub groups within a large and diverse family of proteins. I am undertaking a study that aims to examine such evolutionary events in great detail and eventually developing a method that can successfully predict sub family specific functional important sites.

 

 

Qualifications:

 

1.      Bachelor of Science in Physiology (1997). Raja Peary Mohan College. Uttarpara. WB, India.

2.      Master of Science in Biophysics, Molecular Biology and genetics (1999). University of Calcutta. WB, India.

3.      Received Ph.D. for the thesis entitled ‘Analysis and Prediction of Distant Similarities among Proteins’ under the guidance of Dr. R. Sowdhamini at National Centre for Biological Science, Bangalore, India.

4.      Visiting fellow (postdoctoral fellow) at the National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore. April 2004 -- June 2004.

5.      Visiting fellow (postdoctoral fellow) at NCBI/NLM/NIH, USA. July 2004 – continuing.

 

 

 

Field of expertise:

 

Computational and bioinformatics approaches to understand the relationship between protein sequence, structure, function and their evolution.

Expertise comprises but not limited to

 

  1. Large scale sequence and genome analysis.
  2. Multiple sequence alignment, improvement of alignment.
  3. Analysis of protein structural similarity.
  4. Protein structure prediction, homology modeling.
  5. Protein-protein interaction, small molecule docking.
  6. Pattern recognition, sequence and structural motif based research.
  7. Functional analysis and prediction of protein function.
  8. Coevolutionary analysis.

 

Databases, Servers and Software developed:

  • SMoS: A database for structural motif for multi member superfamilies.

      http://caps.ncbs.res.in/SMoS/index.htm

  • SSToSS: A database for structural motif for single member superfamilies.

      http://caps.ncbs.res.in/SSTOSS/index.htm

      http://caps.ncbs.res.in/SMotif/index.html

      ftp://ftp.ncbi.nih.gov/pub/REFINER

  • FIC_patternDb: A library of functional templates with compositional and evolutionary conservation pattern.

      ftp://ftp.ncbi.nih.gov/pub/lanczyck/limacs

  • LIMACS: A program for prediction of functionally important sites.

      ftp://ftp.ncbi.nih.gov/pub/lanczyck/limacs

  • SPEER: A program for identification of subfamily specific sites.

 

 

Publications:

 

 Book Chapters:

 

1.      Chakrabarti, S., Bhavana, S., Mallika, V., and Sowdhamini, R. (2002) Protein Structural Similarities and Prediction of Protein Function. Recent Trends in Chemistry. Ed. Srivastava, M.M. India.

2.      Chakrabarti, S and Sowdhamini, R. (2003) Potentials of fold recognition methods in structure prediction of homoserine lactone synthases. Recent Trends in Bioinformatics. Ed. P. Shanmughavel, MKU, Madurai.

3.   S. Sandhya, C. Jayadev, K.R. Abhinandan, S. Chakrabarti, R.  Sowdhamini and N. Srinivasan (2005) Relating Protein Families in Sequence space through Multiple Intermediates. Mathematical Biology: Recent Trends. Eds. Peeyush Chandra and B. V. Rathish Kumar, India.

3.       

 Web Publication:

4.       

1.      Chakrabarti, S., Venkataramanan, K., and Sowdhamini, R. (2003) Enhancement of PASS2 database by the Inclusion of Structural Motifs of Aligned Protein Domain Superfamilies. Nucleic Acids Res., http://www3.oup.co.uk/nar/database/summary/275.

 

2.       Chakrabarti, S., Manohari, G., and Sowdhamini, R. (2003) SSToSS: A database of Sequence-Structural Templates of Single member Superfamilies. Nucleic Acids Res., http://www3.oup.co.uk/nar/database/summary/530.

 

 

Research Articles:

 

1)      Chakrabarti, S and Sowdhamini, R (2003) Functional sites and evolutionary connections of Acyl Homoserine Lactone synthases.

Protein Eng. 16, 271- 278.

 

2)      Chakrabarti, S., Venkataramanan, K., and Sowdhamini, R. (2003) SMoS: A database of Structural Motifs of Superfamily. Protein Eng.

2003 Nov; 16, 791-3.

 

3)      Chakrabarti, S, and Sowdhamini, R. (2003) Regions of minimal structural variation among members of protein domain superfamilies:

Application to remote homology detection and modeling using distant relationships.  FEBS Letters. 569, 31-6.

 

4)      Chakrabarti, S., Jaisurya, J., and Sowdhamini, R. Improvement of Comparative Modeling: application of spatial orientation of motifs as

additional restraints (2004). Journal of Molecular Modeling. 10, 69-75.

 

5)      Chakrabarti, S., Bhardwaj, N., Prem, AA, and Sowdhamini R. (2004) Improvement of Alignment Accuracy Utilizing Sequentially Conserved

Motifs. BMC Bioinformatics Oct 28; 5 (1):167.

 

6)      Chakrabarti, S., Prem, AA., Bhardwaj, N, and Sowdhamini R (2004).SCANMOT: search for protein homologues in sequence databases using simultaneous

restraints of multiple motifs. Nucleic Acid Research, 33:W274-6.

 

7)      S. Sandhya, S. Chakrabarti, K.R. Abhinandan, R. Sowdhaminiand N. Srinivasan. (2005). Detection of remote similarities between proteins by cascading PSI-

BLAST. Journal of Biomolecular Structure and Dynamics. 23(3):283-98.

 

8)      Bhadra R, Sandhya S, Abhinandan KR, Chakrabarti S, Sowdhamini R, Srinivasan N. (2006). Cascade PSI-BLAST web server: a remote homology search tool for

relating protein domains. Nucleic Acids Res. 34:W143-6.  

 

9)      Chakrabarti, S., Lanczycki, CJ., Panchenko, AR., Przytycka, TM., Thiessen, PA and Bryant SH. (2006). Refining multiple sequence alignments with conserved

core regions. Nucleic Acid Res. 34, 2598-606.

 

10)  Chakrabarti, S., Manohari, G., Pugalenthi, G. and R. Sowdhamini. (2006). SSToSS - Sequence-Structural Templates of Single-member Superfamilies.

In Sillico Biology.6, 0029.

 

11)  Saikat Chakrabarti, Christopher J. Lanczycki, Anna R. Panchenko, Teresa M. Przytycka, Paul A. Thiessen and Stephen H. Bryant. (2006).

State of the art: refinement of multiple sequence alignments. BMC Bioinformatics.7, 499.

 

12)  Saikat Chakrabarti* and Christopher J. Lanczycki. (2006). Analysis and Prediction of Functionally Important Sites in Proteins. Protein Science. 16, 4-13.

 

13)  Ganesan Pugalenthi, P.N. Suganthan, R. Sowdhamini and Saikat Chakrabarti*. (2007). SMotif: A server for structural motifs in proteins. Bioinformatics. Jan 19.

 

14)  Ganesan Pugalenthi, P.N. Suganthan, R. Sowdhamini and Saikat Chakrabarti*. (2008). MegaMotifBase: a database of structural motifs in protein families and superfamilies. Nucleic Acid Res.36(Database issue):D218-21.

 

15)  Saikat Chakrabarti*, Stephen H. Bryant and Anna R. Panchenko (2007). Functional specificity lies within the properties and evolutionary changes of amino acids. J Mol Biol. 373(3):801-10

 

16)  Christopher J. Lanczycki and Saikat Chakrabarti*. (2008). A template matching method for the prediction of functionally important sites. Bioinformation. 22; 2(7):279-83.

 

17)   Saikat Chakrabarti* and Anna R. Panchenko*. (2008). Coevolution in defining the functional specificity. PROTEINS (in press).

 

18)  Ganesan Pugalenthi, Tang K, P.N. Suganthan, Christopher J. Lanczycki and Saikat Chakrabarti*. (2008). Prediction functionally important sites of proteins using neural networks. (in preparation).

 

19)  Ganesan Pugalenthi, Tang K, P.N. Suganthan and Saikat Chakrabarti*. (2008). Analysis and prediction of structurally conserved regions in proteins using neural networks. (in preparation).

 

*Author for correspondence.