Sagar Pandit

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Papers by Sagar Pandit

Molecular Dynamics Simulation of a Dipalmitoylphosphatidylcholine Bilayer with NaCl

Carolina Digital Repository (University of North Carolina at Chapel Hill), 2003

Molecular dynamics simulations are performed on two hydrated dipalmitoylphosphatidylcholine bilay... more Molecular dynamics simulations are performed on two hydrated dipalmitoylphosphatidylcholine bilayer systems: one with pure water and one with added NaCl. Due to the rugged nature of the membrane/electrolyte interface, ion binding to the membrane surface is characterized by the loss of ion hydration. Using this structural characterization, binding of Na 1 and Cl ÿ ions to the membrane is observed, although the binding of Cl ÿ is seen to be slightly weaker than that of Na 1 . Dehydration is seen to occur to a different extent for each type of ion. In addition, the excess binding of Na 1 gives rise to a net positive surface charge density just outside the bilayer. The positive density produces a positive electrostatic potential in this region, whereas the system without salt shows an electrostatic potential of zero.

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Complexation of Phosphatidylcholine Lipids with Cholesterol

Carolina Digital Repository (University of North Carolina at Chapel Hill), 2004

It is postulated that the specific interactions between cholesterol and lipids in biological memb... more It is postulated that the specific interactions between cholesterol and lipids in biological membranes are crucial in the formation of complexes leading subsequently to membrane domains (so-called rafts). These interactions are studied in molecular dynamics simulations performed on a dipalmitoylphosphatidylcholine (DPPC)-cholesterol bilayer mixture and a dilauroylphosphatidylcholine (DLPC)-cholesterol bilayer mixture, both having a cholesterol concentration of 40 mol %. Complexation of the simulated phospholipids with cholesterol is observed and visualized, exhibiting 2:1 and 1:1 stoichiometries. The most popular complex is found to be 1:1 in the case of DLPC, whereas the DPPC system carries a larger population of 2:1 complexes. This difference in the observed populations of complexes is shown to be a result of differences in packing geometry and phospholipid conformation due to the differing tail length of the two phosphatidylcholine lipids. Furthermore, aggregation of these complexes appears to form hydrogen-bonded networks in the system containing a mixture of cholesterol and DPPC. The CHÁÁÁO hydrogen bond plays a crucial role in the formation of these complexes as well as the hydrogen bonded aggregates. The aggregation and extension of such a network implies a possible means by which phospholipid:cholesterol domains form.

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Approximate Algorithms for Computing Spatial Distance Histograms with Accuracy Guarantees

IEEE Transactions on Knowledge and Data Engineering, Sep 1, 2013

Particle simulation has become an important research tool in many scientific and engineering fiel... more Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to database storage and query processing. One of the queries against particle simulation data, the spatial distance histogram (SDH) query, is the building block of many high-level analytics, and requires quadratic time to compute using a straightforward algorithm. Previous work has developed efficient algorithms that compute exact SDHs. While beating the naive solution, such algorithms are still not practical in processing SDH queries against large-scale simulation data. In this paper, we take a different path to tackle this problem by focusing on approximate algorithms with provable error bounds. We first present a solution derived from the aforementioned exact SDH algorithm, and this solution has running time that is unrelated to the system size N. We also develop a mathematical model to analyze the mechanism that leads to errors in the basic approximate algorithm. Our model provides insights on how the algorithm can be improved to achieve higher accuracy and efficiency. Such insights give rise to a new approximate algorithm with improved time/accuracy tradeoff. Experimental results confirm our analysis.

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Mixed Bilayer Containing Dipalmitoylphosphatidylcholine and Dipalmitoylphosphatidylserine: Lipid Complexation, Ion Binding, and Electrostatics

Biophysical Journal, Nov 1, 2003

Two mixed bilayers containing dipalmitoylphosphatidylcholine and dipalmitoylphosphatidylserine at... more Two mixed bilayers containing dipalmitoylphosphatidylcholine and dipalmitoylphosphatidylserine at a ratio of 5:1 are simulated in NaCl electrolyte solutions of different concentration using the molecular dynamics technique. Direct NHÁÁÁO and CHÁÁÁO hydrogen bonding between lipids was observed to serve as the basis of interlipid complexation. It is deduced from our results and previous studies that dipalmitoylphosphatidylcholine alone is less likely to form interlipid complexes than in the presence of bound ions or other bilayer ''impurities'' such as dipalmitoylphosphatidylserine. The binding of counterions is observed and quantitated. Based upon the calculated ion binding constants, the Gouy-Chapman surface potential (c 0 GC ) is calculated. In addition we calculated the electrostatic potential profile (F) by twice integrating the system charge distribution. A large discrepancy between c 0 GC and the value of F at the membrane surface is observed. However, at ''larger'' distance from the bilayer surface, a qualitative similarity in the z-profiles of F and c GC is seen. The discrepancy between the two potential profiles near the bilayer surface is attributed to the discrete and nonbulk-like nature of water in the interfacial region and to the complex geometry of this region.

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Molecular basis for higher affinity of SARS‐CoV‐2 spike RBD for human ACE2 receptor

Proteins: Structure, Function, and Bioinformatics, 2021

Severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) has caused substantially more infect... more Severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) has caused substantially more infections, deaths, and economic disruptions than the 2002‐2003 SARS‐CoV. The key to understanding SARS‐CoV‐2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV‐2's spike protein stronger than SARS‐CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X‐ray structures. To go beyond insights gained from X‐ray structures and investigate the role of thermal fluctuations in structure, we employ all‐atom molecular dynamics simulations. Microseconds‐long simulations reveal that while CoV and CoV‐2 spike‐ACE2 interfaces have similar conformational binding modes, CoV‐2 spike interacts with ACE2 via a larger combinatorics of pola...

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Transferable interactions of Li+ and Mg2+ ions in polarizable models

The Journal of Chemical Physics, 2020

Therapeutic implications of Li+, in many cases, stem from its ability to inhibit certain Mg2+-dep... more Therapeutic implications of Li+, in many cases, stem from its ability to inhibit certain Mg2+-dependent enzymes, where it interacts with or substitutes for Mg2+. The underlying details of its action are, however, unknown. Molecular simulations can provide insights, but their reliability depends on how well they describe relative interactions of Li+ and Mg2+ with water and other biochemical groups. Here, we explore, benchmark, and recommend improvements to two simulation approaches: the one that employs an all-atom polarizable molecular mechanics (MM) model and the other that uses a hybrid quantum and MM implementation of the quasi-chemical theory (QCT). The strength of the former is that it describes thermal motions explicitly and that of the latter is that it derives local contributions from electron densities. Reference data are taken from the experiment, and also obtained systematically from CCSD(T) theory, followed by a benchmarked vdW-inclusive density functional theory. We fin...

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Molecular basis for SARS-CoV-2 spike affinity for human ACE2 receptor

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infect... more Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARS-CoV. The key to understanding SARS-CoV-2’s higher infectivity may lie in its host receptor recognition mechanism. This is because experiments show that the human ACE2 protein, which serves as the primary receptor for both CoVs, binds to CoV-2’s spike protein 5-20 fold stronger than SARS-CoV’s spike protein. The molecular basis for this difference in binding affinity, however, remains unexplained and, in fact, a comparison of X-ray structures leads to an opposite proposition. To gain insight, we use all-atom molecular dynamics simulations. Free energy calculations indicate that CoV-2’s higher affinity is due primarily to differences in specific spike residues that are local to the spike-ACE2 interface, although there are allosteric effects in binding. Comparative analysis of equilibrium simulations reveals that while both CoV ...

Push-based system for molecular simulation data analysis

2015 IEEE International Conference on Big Data (Big Data), 2015

Many scientific fields generate, and require manipulation of big data. Known scientific data anal... more Many scientific fields generate, and require manipulation of big data. Known scientific data analysis systems, as well as traditional DBMSs, follow a pull-based architectural design, where the executed queries mandate the data needed. This design, while suitable for traditional transaction-based workloads where number of queries retrieve small parts of data located at various places of the database, is ill-fitted for applications involving complex analysis on most of the data. Such design involves redundant and random I/O, considerably affecting the data throughput in the system. In this paper, we design and implement a push-based type system that allows high-throughput data analysis in the process of scientific discovery. Our design improves throughput in two ways: i) it uses a sequential scanbased I/O framework that loads the data into the main memory, and then ii) the system pushes the loaded data to a number of pre-programmed queries. By this way the system lowers the unnecessary I/O overhead imposed by the randomized, indexbased scan and that of a multiple data reads if each query were to be fed separately. Considering the amount of data and the number of executed queries, we believe our system provides substantial improvement over the current data analyzing systems. The efficiency of the proposed system is backed by the results of extensive experiments using real MS data. The running times of our system are compared to those of the GROMACS system. The comparison shows the advantage and the potential of using such push-based system for data system analysis.

Optimization of Coarse-Grained Water-Ion Interaction Parameters for Biological Simulation

Biophysical Journal, 2014

Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased d... more Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased dynamics in which detailed balance is maintained on average. Non-equilibrium processes are described by suitable subsets of the equilibrium ensemble. Here, we employ the "weighted ensemble" (WE) simulation protocol to generate equilibrium trajectory ensembles and extract nonequilibrium subsets for computing kinetic quantities. States do not need to be chosen in advance. The procedure formally allows estimation of kinetic rates between arbitrary states chosen after the simulation, along with their equilibrium populations. We also describe a related history-dependent matrix procedure for estimating equilibrium and non-equilibrium observables when phase space has been divided into arbitrary non-Markovian regions, whether in WE or ordinary simulation. The methods are successfully applied and validated on two molecular systems: explicitly solvated methane association and implicitly solvated Ala-4 peptide.

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Reactive Molecular Dynamics: Numerical Methods and Algorithmic Techniques

SIAM Journal on Scientific Computing, 2012

Modeling atomic and molecular systems requires computation-intensive quantum mechanical methods s... more Modeling atomic and molecular systems requires computation-intensive quantum mechanical methods such as, but not limited to, density functional theory [R. A. Friesner, Proc. Natl. Acad. Sci. USA, 102 (2005), pp. 6648-6653]. These methods have been successful in predicting various properties of chemical systems at atomistic scales. Due to the inherent nonlocality of quantum mechanics, the scalability of these methods ranges from O(N 3 ) to O(N 7 ) depending on the method used and approximations involved. This significantly limits the size of simulated systems to a few thousand atoms, even on large scale parallel platforms. On the other hand, classical approximations of quantum systems, although computationally (relatively) easy to implement, yield simpler models that lack essential chemical properties such as reactivity and charge transfer. The recent work of van Duin et al. [J. Phys. Chem. A, 105 (2001), pp. 9396-9409] overcomes the limitations of nonreactive classical molecular dynamics (MD) approximations by carefully incorporating limited nonlocality (to mimic quantum behavior) through an empirical bond order potential. This reactive classical MD method, called ReaxFF, achieves essential quantum properties, while retaining the computational simplicity of classical MD, to a large extent. Implementation of reactive force fields presents significant algorithmic challenges. Since these methods model bond breaking and formation, efficient implementations must rely on complex dynamic data structures. Charge transfer in these methods is accomplished by minimizing electrostatic energy through charge equilibration. This requires the solution of large linear systems (10 8 degrees of freedom and beyond) with shielded electrostatic kernels at each time-step. Individual time-steps are themselves typically in the range of tenths of femtoseconds, requiring optimizations within and across time-steps to scale simulations to nanoseconds and beyond, where interesting phenomena may be observed. In this paper, we present implementation details of sPuReMD (serial Purdue reactive molecular dynamics program), a unique reactive classical MD code. We describe various data structures, and the charge equilibration solver at the core of the simulation engine. This Krylov subspace solver relies on a preconditioner based on incomplete LU factorization with thresholds (ILUT), specially targeted to our application. We comprehensively validate the performance and accuracy of sPuReMD on a variety of hydrocarbon systems. In particular, we show excellent per-time-step time, linear time scaling in system size, and a low memory footprint. sPuReMD is a freely distributed software with GPL and is currently being used to model diverse systems ranging from oxidative stress in biomembranes to strain relaxation in Si-Ge nanorods.

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Computing Spatial Distance Histograms Efficiently in Scientific Databases

Particle simulation has become an important research tool in many scientific and engineering fiel... more Particle simulation has become an important research tool in many scientific and engineering fields. Data generated by such simulations impose great challenges to database storage and query processing. One of the queries against particle simulation data, the spatial distance histogram (SDH) query, is the building block of many high-level analytics, and requires quadratic time to compute using a straightforward algorithm. In this paper, we propose a novel algorithm to compute SDH based on a data structure called density map, which can be easily implemented by augmenting a Quad-tree index. We also show the results of rigorous mathematical analysis of the time complexity of the proposed algorithm: our algorithm runs on Θ(N 3 2 ) for two-dimensional data and Θ(N 5 3 ) for three-dimensional data, respectively. We also propose an approximate SDH processing algorithm whose running time is unrelated to the input size N . Experimental results confirm our analysis and show that the approximate SDH algorithm achieves very high accuracy.

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