BITS Faculty Publications
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Item Force-induced unzipping of DNA in the presence of solvent molecules(Elsevier, 2024-04) Singh, NavinThe melting of double-stranded DNA (dsDNA) in the presence of solvent molecules is a fundamental process with significant implications for understanding the thermal and mechanical behavior of DNA and its interactions with the surrounding environment. The solvents play an essential role in the structural transformation of DNA subjected to a pulling force. In this study, we simulate the thermal and force induced denaturation of dsDNA and elucidate the solvent dependent melting behavior, identifying key factors that influence the stability of DNA melting in presence of solvent molecules. Using a statistical model, we first find the melting profile of short heterogeneous DNA molecules in the presence of solvent molecules in Force ensemble. We also investigate the effect of solvent's strengths on the melting profile of DNA. In the force ensemble, we consider two homogeneous DNA chains and apply the force on different locations along the chain in the presence of solvent molecules. Different pathways manifest the melting of the molecule in both ensembles, and we found several interesting features of melting DNA in a constant force ensemble, such as lower critical force when the chain is pulled from the base pair close to a solvent molecule. The results provide new insights into the force-induced unzipping of DNA and could be used to develop new methods for controlling the unzipping process. By providing a better understanding of melting and unzipping of dsDNA in the presence of solvent molecules, this study provides valuable guidelines for predicting DNA thermodynamic quantities and for designing DNA nanostructures.Item Molecular dynamics studies of temperature-induced DNA–cation interaction: role of valency and size(RSC, 2025) Singh, NavinIn many important biological functions like gene storage, transcription, and gene regulation, nucleic acids play a vital role. Cations like Na+, K+, Ca2+ and Mg2+ play a crucial role in nullifying the coulombic repulsions between the negatively charged phosphate backbone. Some studies show that monovalent cations are generally less strongly solvated than divalent cations. While the monovalent cations are found to be more localised at preferred sites with low occupancies, the divalent cations strongly and selectively bind to the DNA molecules. Understanding the role of these cations in the modulation of the DNA structure is crucial to understanding the biological function of the molecule. For biotechnological applications, the problem of salt/cation concentration and DNA carries an important weight. We consider these four cations in the present work and investigate their interactions with the negatively charged DNA molecule at different temperatures. Our studies reveal interesting and contrasting behaviour of these cations when they interact with DNA molecules. While the Na+ ions tend to stay near the minor grooves and do not change their location with temperature, K+ ions tend to bind DNA at the minor grooves at room temperature and change their location to the major grooves at higher temperatures. The Mg2+ ions change their location with temperature, while Ca2+ ions remain near the phosphate backbone at all temperatures.Item Melting profile of DNA in crowded solution: model-based study(MDPI, 2025) Singh, NavinRecent advances in molecular dynamics (MD) simulations and the introduction of artificial intelligence (AI) have resulted in a significant increase in accuracy for structure prediction. However, the cell is a highly crowded environment consisting of various macromolecules, such as proteins and nucleic acids. The macromolecular crowding and solution conditions, such as temperature, ion concentration, and the presence of crowders, significantly influence the molecular interactions between and structural changes in proteins and nucleic acids. In this study, we investigate the presence of crowders and their effect on the melting of DNA molecules by analyzing melting profiles of short and long heterogeneous DNA duplexes. In particular, we examine how multiple inert crowders, randomly distributed along long DNA chains, influence DNA melting. We find that the presence of crowders stabilizes double-stranded DNA (dsDNA), with this effect being more pronounced in short DNA duplexes. These findings complement in vitro observations and improve our understanding of dsDNA in cell-like environments.Item Physics-informed failure prediction in disordered systems sharing a common resource(Elsevier, 2026-03) Singh, NavinWe study the progressive degradation of disordered systems that experience multiple intermediate failures and equilibrations before collapsing while sharing a common resource. The system is modelled using a generalized Fibre Bundle framework, wherein individual elements fail upon exceeding their local thresholds, and their load is redistributed among surviving elements according to a prescribed load-sharing scheme. We employ two classes of disorder distributions: the two-parameter Weibull and a more flexible custom distribution. To predict the ultimate tensile strength (UTS) and critical burst size which characterize system failure in this model—we employ Artificial Neural Networks (ANNs) informed by theoretical expressions rooted in statistical physics. Our investigation shows that the predictive performance of ANNs is significantly improved (from 83% to 99%) by our Physics informed theoretical predictors. This approach reduces the need for large-scale simulations and is a more efficient way to estimate the reliability of such complex disordered systems.Item Pulling short DNA with mismatch base pairs(Springer, 2023-05) Singh, NavinDue to misincorporation during gene replication, the accuracy of the gene expression is often compromised. This results in a mismatch or defective pair in the DNA molecule (James et al. 2016). Here, we present our study of the stability of DNA with defects in the thermal and force ensembles. We consider DNA with a different number of defects from 2to16 and study how the denaturation process differs in both ensembles. Using a statistical model, we calculate the melting point of the DNA chain in both the ensemble. Our findings display different manifestations of DNA denaturation in thermal and force ensembles. While the DNA with defects denatures at a lower temperature than the intact DNA, the point from which the DNA is pulled is important in force ensemble.Item Melting of dsDNA attached with AuNPs(Springer, 2023-07) Singh, NavinDNA-linked gold nanoparticles (DNA-AuNPs) are combined nanomaterials that contain the optical and electronic properties of AuNPs with the unique functions of DNA. These hybrid systems are used in various nanobiotechnology, medical, and pharmaceutical sciences (Löwe et al. in FEBS J 287(23):5039, 2020; Speer et al. in Annu Rev Biophys 51:267, 2022). In recent years, there has been an increasing interest in studying the behavior of DNA-AuNPs in the presence of molecular solvents. In the present work, we study the thermal melting of DNA-linked gold nanoparticles (DNA-AuNP). In the first part of the study, we find the melting profile of short heterogeneous DNA-linked AuNP in the presence of solvent in the solution. We also study the effect of the location of the gold nanoparticle attached to the DNA molecule. In this case, we move the location of the AuNP from one end to the other. We found that while the melting temperature is susceptible to the location of the AuNP when it is near the ends, there is a region in the middle section of the chain where the melting temperature remains constant.Item A neural network regression model for estimating the lifespan of a Fibre Bundle(IOP, 2023-09) Singh, NavinFibre Bundle Models (FBMs) use generalized distributions like the Weibull distribution to study the failure mechanics of disordered material under different load-sharing schemes. Here we attempt to use a simple neural network regression model to estimate the lifespan of Fibre Bundles for axial loading under the Global Load Sharing (GLS) scheme. We find that using neural networks can give a reliable estimate (within ∼2%) of the lifespan for different initial conditions. We also develop a semi-analytical expression for the lifespan of a bundle of fibres. The aim is to establish an empirical relationship using a neural network regression (NNR) method that helps us estimate the ultimate tensile strength. The expressions and methods developed here can be a precursor to future investigation under those cited in the following section(s).Item The crowding effect on the melting of short DNA: Comparison with experiments(ARXIV, 2022-02) Singh, NavinWe study the effect of crowders on the melting profile of homogeneous and heterogeneous DNA molecules. We find out the melting profile of short DNA molecules and compare our findings with the experiments. We consider some random distribution of crowders along the chain, and by finding out the best match with the experiments, we attempt to identify the location of crowders in the experimental findings of Ghosh \cite{Ghosh_PNAS_2020}. We also study the melting of homogeneous DNA molecules of different lengths (25, 50, 75) in the presence of only one crowder in the chain. By varying the location of the crowder from one end to the other, we find that the melting temperature is susceptible to the location of the crowder at the ends. At the same time, there is minimal effect on the melting temperature due to the location of the crowder. {\it In vivo}, the strength of a crowders may vary along the chain. We study the melting of long heterogeneous chain in presence of five crowders of different strength. We find that there is a significant variation in the melting process of DNA in presence of crowders of variable strengthItem DNA Molecule Confined in a Cylindrical Shell: Effect of Partial Confinement(Springer, 2022-02) Singh, NavinTo study the behaviour of DNA molecules during the encapsulation process is a topic of intense research. In the present work, we investigate the stability of the double-stranded DNA molecule of different lengths in a confined shell using a statistical model. The DNA molecules of different lengths are confined in a cylindrical shell either partially or entirely. We consider cylinders of different sizes and study the effect of the size of the cylinder on the microscopic details of the opening of the base pairs.Item Comparative Study of Convolutional Neural Network Object Detection Algorithms for Image Processing(IEEE, 2023) Singh, NavinThis paper presents a comparative study on three Convolutional Neural Network (CNN) object detection algorithms to find the best detector based on the combination of speed and accuracy on a personal computer. The MATLAB® development environment is used to evaluate three different object detector algorithms, namely Faster Region-Based Convolutional Network (R-CNN), Single Shot Detector (SSD) and You Only Look Once (YOLO). These algorithms are trained, and their performance metrics are tested on a small sample dataset. The results show that the SSD object detector algorithm performs best when considering both performance and processing speeds. Faster R-CNN detected objects at an average speed of 4.838 seconds and achieved a mean average precision of 0.76 with an average loss of 0.429. SSD detected objects at an average speed of 0.377 seconds and achieved a mean average precision of 0.92 with an average loss of 1.754. YOLO v3 detected objects at an average speed of 1.004 seconds and achieved a mean average precision of 0.81 with an average loss of 2.739.