Senthilkumar Kailasam

MolBridge: a program for identifying nonbonded interactions in small molecules and biomolecular structures

Identification and analysis of nonbonded interactions within a molecule and with the surrounding molecules are an essential part of structural studies, given the importance of these interactions in defining the structure and function of any supramolecular entity. MolBridge is an easy to use algorithm based purely on geometric criteria that can identify all possible nonbonded interactions, such as hydrogen bond, halogen bond, cation-pi, pi-pi and van der Waals, in small molecules as well as biomolecules. The user can either upload three-dimensional coordinate files or enter the molecular ID corresponding to the relevant database. The program is available in a standalone form and as an interactive web server with Jmol and JME incorporated into it. The program is freely downloadable and the web server version is also available at http://nucleix.mbu.iisc.ernet.in/molbridge/index.php.

Sequence dependent variations in RNA duplex are related to non-canonical hydrogen bond interactions in dinucleotide steps

BackgroundSequence determines the three-dimensional structure of RNAs, and thereby plays an important role in carrying out various biological functions. RNA duplexes containing Watson-Crick (WC) basepairs, interspersed with non-Watson-Crick basepairs, are the dominant structural unit and form the scaffold for the 3-dimensional structure of RNA. It is therefore crucial to understand the geometric variation in the dinucleotide steps that form the helices. We have carried out a detailed analysis of the dinucleotide steps formed by AU and GC Watson-Crick basepairs in RNA structures (both free and protein bound) and compared the results to that seen in DNA. Further, the effect of protein binding on these steps was examined by comparing steps in free RNA structures with protein bound RNA structures.ResultsCharacteristic sequence dependent geometries are observed for the RR, RY and YR type of dinucleotide steps in RNA. Their geometric parameters show correlated variations that are different from those observed in B-DNA helices. Subtle, but statistically significant differences are seen in roll, slide and average propeller-twist values, between the dinucleotide steps of free RNA and protein bound RNA structures. Many non-canonical cross-strand and intra-strand hydrogen bonds were identified that can stabilise the RNA dinucleotide steps, among which YR steps show presence of many new unreported interactions.ConclusionsOur work provides for the first time a detailed analysis of the conformational preferences exhibited by Watson-Crick basepair containing steps in RNA double helices. Overall, the WC dinucleotide steps show considerable conformational variability. Furthermore, we have identified hydrogen bond interactions in several of the dinucleotide steps that could play a role in determining the preferred geometry, in addition to the intra-basepair hydrogen bonds and stacking interactions. Protein binding affects the conformation of the steps that are in direct contact, as well as allosterically affect the steps that are not in direct physical contact.

Stacking interactions in RNA and DNA: Roll-slide energy hyperspace for ten unique dinucleotide steps

Understanding dinucleotide sequence directed structures of nuleic acids and their variability from experimental observation remained ineffective due to unavailability of statistically meaningful data. We have attempted to understand this from energy scan along twist, roll, and slide degrees of freedom which are mostly dependent on dinucleotide sequence using ab initio density functional theory. We have carried out stacking energy analysis in these dinucleotide parameter phase space for all ten unique dinucleotide steps in DNA and RNA using DFT‐D by ωB97X‐D/6‐31G(2d,2p), which appears to satisfactorily explain conformational preferences for AU/AU step in our recent study. We show that values of roll, slide, and twist of most of the dinucleotide sequences in crystal structures fall in the low energy region. The minimum energy regions with large twist values are associated with the roll and slide values of B‐DNA, whereas, smaller twist values correspond to higher stability to RNA and A‐DNA like conformations. Incorporation of solvent effect by CPCM method could explain the preference shown by some sequences to occur in B‐DNA or A‐DNA conformations. Conformational preference of BII sub‐state in B‐DNA is preferentially displayed mainly by pyrimidine–purine steps and partly by purine–purine steps. The purine–pyrimidine steps show largest effect of 5‐methyl group of thymine in stacking energy and the introduction of solvent reduces this effect significantly. These predicted structures and variabilities can explain the effect of sequence on DNA and RNA functionality.

A Combined Molecular Docking/Dynamics Approach to Study Selectivity and Binding Affinity of L-Stereoisomer RNA Aptamer Towards CCL2 and Related Chemokines

CC chemokine ligand 2 (CCL2)- also known as Monocyte Chemoattractant Protein 1- is a primary chemoattractant in monocytes. It has a high-affinity interaction with chemokine receptor 2 (CCR2) and causes calcium mobilization and chemotaxis. In inflammatory processes and cancer, CCL2 is highly expressed. Preventing CCL2 function by interfering with CCL2-CCR2 binding can alleviate complications seen in many inflammatory diseases. Many oligonucleotide-based aptamers that target proteins are currently being developed to block the interaction of the target protein with other molecules. An L-stereoisomer oligonucleotide aptamer (emapticap pegol), targeting CCL2 was identified by Noxxon Pharma AG using an in vitro process known as “systematic evolution of ligands by exponential enrichment” (SELEX). This L-RNA aptamer was used to treat patients with diabetic nephropathy and completed Phase IIa of clinical trials. The mode of action of the drug was deciphered using a combination of binding and structural data; however, this data could not fully explain the observed selectivity profile of the L-aptamer. In this work, using molecular dynamics simulation approach, we were able to understand the dynamic behaviour of L-aptamer in free form and in complex with various chemokines, including CCL2. Furthermore, using calculated binding free energy, we were able to explain the experimentally observed binding affinity profile. Our present work provides a complete structural understanding of L-aptamer with various chemokines and also provides inputs to optimise the design of the L-aptamers which will further improve binding specificity towards CCL2.