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Tools for RNA structural Informatics: BPFIND, INCAR and VASTERN

Tools for RNA structural Informatics: BPFIND, INCAR and VASTERN Sohini Bhattacharya, B. Ram Sagar, Dhananjay Bhattacharyya, Gopalakrishnan Bulusu and Abhijit Mitra. Centre for Computational Natural Science and Bioinformatics. Factors responsible for huge structural Diversity in RNA.

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Tools for RNA structural Informatics: BPFIND, INCAR and VASTERN

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  1. Tools for RNA structural Informatics: BPFIND, INCAR and VASTERN Sohini Bhattacharya, B. Ram Sagar, Dhananjay Bhattacharyya, Gopalakrishnan Bulusu and Abhijit Mitra Centre for Computational Natural Science and Bioinformatics

  2. Factors responsible for huge structural Diversity in RNA Interactions

  3. Complex RNA structure:Need for Interaction mining Some rules are needed to find out recurring combinations of such non canonical base pairs and all other inter-nucleotide contacts which are organized into simple and higher order structural motif, which may be responsible for diverse RNA functionalities . Automated tools are required for interaction mining For interaction mining, a tool should be able to detect the following , Available tools : NDB,FR3D

  4. Problems and Issues • Major challenges • Absence of H atom coordinates in crystal structure • Wide range of variation in resolution of crystal structures • We have developed BPFIND (BasePair Finder) – Developed in SINP Kolkata. INCAR (Inter Nucleotide Contact annotator in RNA) – Developed in CCNSB, IIIT-Hyderabad. To visualize RNA structure interactively, we have developed VASTERN (Visual Analysis of Structure Energy Relationship in Nucleic acids) -Developed in CCNSB,IIIT-Hyderabad

  5. Target of BPFind and INCAR INCAR Bottoms Up Base-pairs, triples and higher order interaction having at least one H-bond Include backbone phosphate mediated interactions Include water and metal ion mediated interactions Include Sugar O2’ – mediated H – bonds Include Bifurcated H – bonds Base-pairs and triples having at least two H-bonds BP Find Top down

  6. BPFIND: A hypothesis driven algorithm • To define proper pairing of two bases involving at least two hydrogen bonds the following two criteria have been considered. • Distances (D-A) ≤ 3.8 Å [default] • Pseudo angles D-A-PA and PD-D-A ≥ 120º [default]. • Goodness and planarity of the detected base-pair has been checked by evaluating composite quantitative parameter called E-value. Smaller E value implies good quality of base-pair. Distances of N3(U1)-O4(U2) and O2(U1)–N3(U2) Pseudo angles defined by N3(U1)-O4(U2)-C5*(U2) O2(U1)-N3(U2)-C6*(U2) N1*(U1)-O2(U1)- N3(U2) C6*(U1)- N3(U1)- O4(U2) U1 U2 Underlined ATOMS* with a ‘*’ and an underline represent predefined precursor Atoms.

  7. Advantages and disadvantages of BPFind • BPFind can identify- • canonical and non-canonical base-pairs ( having atleast two h-bonds) • higher order structures like base triples base-pair bifurcations. • Protonated base-pairs. • The secondary structural arrangements and complicated folding patterns of RNA in simple manner. • BPFind Can not detect- • Backbone phosphate mediated interactions. • Metal ion and water molecule based interactions. • single h-bonded and deformed base pairs and triples Structure of a part of 50S Ribosomal subunit (PDB ID: 1FFK) BPFind Output

  8. INCAR : Workflow INCAR : A bottom-up approach Possible donor and acceptor atoms in all four residues

  9. Information INCAR provides Analysis of weak and ‘non-base specific’ interactions in RNA. • Weak h-bond (CHO & CHN ) is 40% of the total h-bonding interaction present in our analysis dataset. • Non base specific h-bonds is approximately 65% of all interactions Analysis of Base-phosphate (BPh) interactions. • Dominance of Guanine residue in base-phosphate interactions due to due of its role in different motifs (tetraloops, sarcin-ricin). Analysis of Bifurcated hydrogen bonding geometries in RNA. • All bifurcated geometries are classified in five different classes like D-H-AA, D-HH-AA, DD-HH-A, D-H-A-D, D-HH-A • DD-HH-A geometry is predominantly observed due to the simultaneous involvement of C-H groups of sugar with O2’/O4’/O5’/O1P/O2P atoms of adjacent nucleotides. Analysis of water and ion-mediated base-pairs • Accounts for 14% of all interactions in RNA. Most of these are involved with sugar-phosphate backbone of RNA (Ion/Water – O1P/O2P/O3’/O5’). Analysis of higher order interactions in RNA. • Higher order interactions such as triplets, quartets etc. have been detected and classified based on spatial topology. Pentads and hexads also have been detected. • 67% triplets are mediated by a W:WC base-pair and 33% are mediated by a non W:WC base-pair. INCAR output has been benchmarked with existing softwares like BPFind and FR3D

  10. Additional Information that INCAR Provides Tertiary interaction identified in Ribozyme BPFind FR3D INCAR

  11. Applications of INCAR Comparative analysis of functionally related RNA structures Identification of different structural elements and motifs in RNA structures Analysis of RNA structural dynamics Network of Hydrogen bonds made by Lysine with neighboring nucleotides in Lysine Riboswitch over a period of simulation

  12. VASTERN : An interactive way to visualize RNA structure The information we can retrieve using BPFind and INCAR, can be further analyzed visually and interactively with VASTERN(Visual Analysis of Structure Energy Relationship in Nucleic acids ). This tool allow users to navigate backbone torsion/pseudo-torsion and base-pairing interactions along with the corresponding structure in a JMol window. How VASTERN works.. Play

  13. Summary and Conclusions • Proper understanding of mystery of functional RNA requires automated interaction mining. • Interaction mining also useful to study RNA structure using graph theoretical approaches • BPFind and INCAR can navigate this large space though a complementary approach. • BPFind is designed to detect and annotate base-pair and triples which are good enough in terms of geometry. • INCAR is designed to detect all interactions beyond the good base pairs and usual base-base, and sugar O2’ mediated interactions.

  14. Acknowledgements • DBT, India, for financial support [grant numbers R-11429/BID/07/272/2008 and BT/PR5451/BID/07/111/2004] • Mrityunjay , Ujjaval, and Aman (Technical Support for VASTERN) • Eshita, and Pushpa ( Support for INCAR) • Monika, Bipin, Preethi, Vivek , and Antarip • SukanyaHalder (For BPFind) • All faculties in CCNSB for their support and guidance • All my other friends and colleagues THANK YOU..

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