arXiv subjects

Nisanth N. Nair

Publications and source records attributed to Nisanth N. Nair.

18 recordsLinked to original sources

arXiv2026

Integrated Alchemical and Conformational Enhanced Sampling for Solvation Free Energy Calculations

Accurate solvation free energies from molecular dynamics simulations require efficient sampling of coupled slow variables, including solvent coordinates, solute conformational modes, and the alchemical coordinate $λ$. Here, we develop a $λ$-dynamics framework that combines mass scaling, on-the-fly probability enhanced sampling (OPES), and driven adiabatic free energy dynamics (d-AFED) to address these sampling challenges within a unified protocol. For rigid organic solutes, Hamiltonian replica exchange with mass scaling is first used to quantify the effect of octanol solvent relaxation. Reducing all octanol atomic masses by a factor of ten accelerates convergence by more than fivefold while preserving equilibrium solvation free energies. These calculations then provide reference benchmarks for $λ$-OPES, a dual-bias $λ$-dynamics strategy that combines the "standard" and "explore" variants of OPES to promote transitions along the alchemical coordinate. This approach reaches convergence on timescales comparable to replica exchange, but without predefined $λ$ windows or multiple parallel simulations. For flexible $N$-acetyl amino-acid amide solutes, $λ$-OPES is coupled with d-AFED on selected backbone and side-chain dihedrals to enable simultaneous alchemical and conformational enhanced sampling. This combined strategy improves agreement with experimental octanol-water partition coefficients and reduces the mean absolute error from 0.75 log units with $λ$-OPES alone to 0.30 log units with $λ$-OPES-d-AFED. Overall, this work establishes an integrated enhanced sampling protocol for solvation free energy calculations across rigid organic solutes and flexible peptide-like solutes, and provides a foundation for the application of alchemical free energy methods to larger and more conformationally complex systems.

physics.chem-ph↗

arXiv2025

Kinetics of Barrier Crossing Events from Temperature Accelerated Sliced Sampling Simulations

Temperature-accelerated sliced sampling (TASS) is a well-established enhanced sampling method that facilitates exhaustive exploration of high-dimensional collective variable (CV) space through directed sampling employing a combination of umbrella restraining biases, metadynamics biases, and temperature acceleration of CVs. In this work, we broaden the applicability of TASS by introducing a protocol for computing rate constants of barrier crossing events. The challenge addressed here is to recover kinetics from free energy data computed from different slices of the TASS simulation. The proposed protocol utilizes artificial neural networks based representation of high-dimensional free energy landscapes, and Infrequent Metadynamics. We demonstrate the accuracy of the approach by obtaining rate constants for the conformational change of alanine dipeptide in vacuo, the unbinding of benzamidine from trypsin, and the unbinding of aspirin from $β$-cyclodextrin.

physics.chem-ph↗

arXiv2025

Nature of Hydrated Electron in Varied Solvation Environments

Understanding the nature of solvated electrons is important in studying a range of chemical and biological phenomena. This study investigates the structural and dynamical behavior of an excess electron in water, examining different solvation environments, including liquid water, ice, monolayer, and chain. To accurately model these systems, we carry out molecular dynamics (MD) simulations using hybrid density functionals, employing the computationally efficient resonance-free multiple time-stepping based adaptively compressed exchange operator method. Through these simulations, we create a comprehensive and detailed picture of how excess electrons are solvated across different aqueous environments. We report the factors influence the localization and dynamic stability of the hydrated electron. The determinants include the presence and reorganization flexibility of the dangling OH groups and the spatial arrangement of the surrounding water molecules.

physics.comp-ph↗

arXiv2023

Speeding-up Hybrid Functional based Ab Initio Molecular Dynamics using Multiple Time-stepping and Resonance Free Thermostat

Ab initio molecular dynamics (AIMD) based on density functional theory (DFT) has become a workhorse for studying the structure, dynamics, and reactions in condensed matter systems. Currently, AIMD simulations are primarily carried out at the level of generalized gradient approximation (GGA), which is at the 2nd rung of DFT-functionals in terms of accuracy. Hybrid DFT functionals which form the 4th rung in the accuracy ladder, are not commonly used in AIMD simulations as the computational cost involved is $100$ times or higher. To facilitate AIMD simulations with hybrid functionals, we propose here an approach that could speed up the calculations by ~30 times or more for systems with a few hundred of atoms. We demonstrate that, by achieving this significant speed up and making the compute time of hybrid functional based AIMD simulations at par with that of GGA functionals, we are able to study several complex condensed matter systems and model chemical reactions in solution with hybrid functionals that were earlier unthinkable to be performed.

physics.chem-ph↗

arXiv2022

Computational Study of pKa shift of Aspartate residue in Thioredoxin: Role of Configurational Sampling and Solvent Model

Alchemical free energy calculations are widely used in predicting pKa, and binding free energy calculations in biomolecular systems. These calculations are carried out using either Free Energy Perturbation (FEP) or Thermodynamic Integration (TI). Numerous efforts have been made to improve the accuracy and efficiency of such calculations, especially by boosting conformational sampling. In this paper, we use a technique that enhances the conformational sampling by temperature acceleration of collective variables for alchemical transformations and applies it to the prediction of pKa of the buried Asp 26 residue in thioredoxin protein. We discuss the importance of enhanced sampling in the pKa calculations. The effect of the solvent models in the computed pKa values is also presented.

cond-mat.soft↗

arXiv2022

Hybrid Functional and Plane Waves based Ab Initio Molecular Dynamics Study of the Aqueous Fe$^{2+}$/Fe$^{3+}$ Redox Reaction

Kohn-Sham density functional theory and plane wave basis set based ab initio molecular dynamics (AIMD) simulation is a powerful tool for studying complex reactions in solutions, such as electron transfer (ET) reactions involving Fe$^{2+}$/Fe$^{3+}$ ions in water. In most cases, such simulations are performed using density functionals at the level of Generalized Gradient Approximation (GGA). The challenge in modelling ET reactions is the poor quality of GGA functionals in predicting properties of such open-shell systems due to the inevitable self-interaction error (SIE). While hybrid functionals can minimize SIE, AIMD at that level of theory is typically 150 times slower than GGA for systems containing ~100 atoms. Among several approaches reported to speed-up AIMD simulations with hybrid functionals, the noise-stabilized MD (NSMD) procedure, together with the use of localized orbitals to compute the required exchange integrals, is an attractive option. In this work, we demonstrate the application of the NSMD approach for studying the Fe$^{2+}$/Fe$^{3+}$ redox reaction in water. It is shown here that long AIMD trajectories at the level of hybrid density functionals can be obtained using this approach. Redox properties of the aqueous Fe$^{2+}$/Fe$^{3+}$ system computed from these simulations are compared with the available experimental data for validation.

physics.chem-ph↗

arXiv2021

Improving the Scaling and Performance of Multiple Time Stepping based Molecular Dynamics with Hybrid Density Functionals

Density functionals at the level of the Generalized Gradient Approximation (GGA) and a plane-wave basis set are widely used today to perform ab initio molecular dynamics (AIMD) simulations. Going up in the ladder of accuracy of density functionals from GGA (2nd rung) to hybrid density functionals (4th rung) is much desired pertaining to the accuracy of the latter in describing structure, dynamics, and energetics of molecular and condensed matter systems. On the other hand, hybrid density functional based AIMD simulations are about two orders of magnitude slower than GGA based AIMD for systems containing ~100 atoms using ~100 compute cores. Two methods, namely MTACE and s-MTACE, based on a multiple time step integrator and adaptively compressed exchange operator formalism are able to provide a speed-up of about 7-9 in performing hybrid density functional based AIMD. In this work, we report an implementation of these methods using a task-group based parallelization within the CPMD program package, with the intention to take advantage of the large number of compute cores available on modern high-performance computing platforms. We present here the boost in performance achieved through this algorithm. This work also identifies the computational bottleneck in the s-MTACE method, and proposes a way to overcome that.

physics.comp-ph↗

arXiv2021

Boosting the Conformational Sampling by Combining Replica Exchange with Solute Tempering and Well-Sliced Metadynamics

Methods that combine collective variable (CV) based enhanced sampling and global tempering approaches are used in speeding-up the conformational sampling and free energy calculation of large and soft systems with a plethora of energy minima. In this paper, a new method of this kind is proposed in which the well-sliced metadynamics approach (WSMTD) is united with Replica Exchange with Solute Tempering (REST2) method. WSMTD employs a divide-and-conquer strategy wherein high-dimensional slices of a free energy surface are independently sampled and combined. The method enables one to accomplish a controlled exploration of the CV-space with a restraining bias as in umbrella sampling (US), and enhance-sampling of one or more orthogonal CVs using a metadynamics (MTD) like bias. The new hybrid method proposed here enables boosting the sampling of more slow degrees of freedom in WSMTD simulations, without the need to specify associated CVs, through a replica exchange scheme within the framework of REST2. The high-dimensional slices of the probability distributions of CVs computed from the united WSMTD and REST2 simulations are subsequently combined using the weighted histogram analysis method (WHAM) to obtain the free energy surface. We show that the new method proposed here is accurate, improves the conformational sampling, and achieves quick convergence in free energy estimates. We demonstrate this by computing the conformational free energy landscapes of solvated alanine tripeptide and Trp-cage mini protein in explicit water.

physics.comp-ph↗

arXiv2021

Mean Force Based Temperature Accelerated Sliced Sampling: Efficient Reconstruction of High Dimensional Free Energy Landscapes

Temperature Accelerated Sliced Sampling (TASS) is an efficient method to compute high dimensional free energy landscapes. The original TASS method employs the Weighted Histogram Analysis Method (WHAM) which is an iterative post-processing to reweight and stitch high dimensional probability distributions in sliced windows that are obtained in the presence of restraining biases. The WHAM necessitates that TASS windows lie close to each other for proper overlap of distributions and span the collective variable space of interest. On the other hand, increase in number of TASS windows implies more number of simulations, and thus it affects the efficiency of the method. To overcome this problem, we propose herein a new mean-force (MF) based reweighting scheme called TASS-MF, which enables accurate computation with a fewer number of windows devoid of the WHAM post-processing. Application of the technique is demonstrated for alanine di- and tripeptides in vacuo to compute their two- and four-dimensional free energy landscapes, the latter of which is formidable in conventional umbrella sampling and metadynamics. The landscapes are computed within a kcal/mol accuracy, ensuring a safe usage for broad applications in computational chemistry.

physics.comp-ph↗

arXiv2021

Achieving an Order of Magnitude Speed-up in Hybrid Functional and Plane Wave based Ab Initio Molecular Dynamics: Applications to Proton Transfer Reactions in Enzymes and in Solution

Ab initio molecular dynamics (AIMD) with hybrid density functionals and plane wave basis is computationally expensive due to the high computational cost of exact exchange energy evaluation. Recently, we proposed a strategy to combine adaptively compressed exchange (ACE) operator formulation and multiple time step (MTS) integration scheme to reduce the computational cost significantly [J. Chem. Phys. 151, 151102 (2019)]. However, it was found that the construction of the ACE operator, which has to be done at least once in every MD time step, is computationally expensive. In the present work, systematic improvements are introduced to further speed-up by employing localized orbitals for the construction of the ACE operator. By this, we could achieve a computational speed-up of an order of magnitude for a periodic system containing 32-water molecules. Benchmark calculations were carried out to show the accuracy and efficiency of the method in predicting the structural and dynamical properties of bulk water. To demonstrate the applicability, computationally intensive free energy computations at the level of hybrid density functional theory were performed to investigate (a) methyl formate hydrolysis reaction in neutral aqueous medium and (b) proton transfer reaction within the active site residues of class-C $β$-lactamase enzyme.

physics.chem-ph↗

arXiv2020

Improving the Exploration of High Dimensional Free Energy Landscape by a Combination of Temperature Accelerated Sliced Sampling and Parallel Biasing

Biased sampling methods such as the Temperature Accelerated Sliced Sampling (TASS), which can explore high dimensional collective variable (CV) space, is of great interest in free energy calculations. Such methods can efficiently sample configurational space even when a large number of CVs for biasing are used while many conventional methods are limited to two or three CVs. In this paper, we propose a modification to the TASS method, called Parallel Bias TASS or PBTASS, wherein a multidimensional parallel metadynamics bias is incorporated on a selected set of CVs. The corresponding time-dependent reweighting equations are derived, and the method is benchmarked. In particular, we compare the accuracy and efficiency of PBTASS with various methods viz. standard TASS, Temperature Accelerated Molecular Dynamics/driven-Adiabatic Free Energy Dynamics, and Parallel Bias Metadynamics. We demonstrate the capability of the PBTASS method by reconstructing the eight-dimensional free energy surface of alanine pentapeptide in vacuo from a 25 ns long trajectory. Free energy barriers and free energies of high energy saddle points on the high dimensional free energy landscape of this system are reported.

physics.comp-ph↗

arXiv2020

Efficient Computation of Free Energy Surfaces of Chemical Reactions using Ab Initio Molecular Dynamics with Hybrid Functionals and Plane Waves

Ab initio molecular dynamics (AIMD) simulations employing density functional theory (DFT) and plane waves are routinely carried out using density functionals at the level of Generalized Gradient Approximation (GGA). AIMD simulations employing hybrid density functionals are of great interest as it offers more accurate description of structural and dynamic properties than the GGA functionals. However, computational cost for carrying out calculations using hybrid functionals and plane wave basis set is at least two order of magnitude higher than GGA functionals. Recently, we proposed a strategy that combined the adaptively compressed exchange operator formulation and the multiple time step integration scheme to reduce the computational cost about an order of magnitude [J. Chem. Phys. 151, 151102 (2019)]. In this work, we demonstrate the application of this method to study chemical reactions, in particular, formamide hydrolysis in alkaline aqueous medium. By actuating our implementation with the well-sliced metadynamics scheme, we are able to compute the two-dimensional free energy surface of this reaction at the level of hybrid-DFT. Accuracy of PBE0 (hybrid) and PBE (GGA) functionals in predicting the free energetics of the chemical reaction is investigated here.

physics.chem-ph↗

arXiv2019

Speeding-up Ab Initio Molecular Dynamics with Hybrid Functionals using Adaptively Compressed Exchange Operator based Multiple Timestepping

Ab initio molecular dynamics (AIMD) simulations using hybrid density functionals and plane waves are of great interest owing to the accuracy of this approach in treating condensed matter systems. On the other hand, such AIMD calculations are not routinely carried out since the computational cost involved in applying the Hartree Fock exchange operator is very high. In this work, we make use of a strategy that combines adaptively compressed exchange operator formulation and multiple time step integration to significantly reduce the computational cost of these simulations. We demonstrate the efficiency of this approach for a realistic condensed matter system.

physics.chem-ph↗

arXiv2017

Hydrolysis of Cephalexin and Meropenem by New Delhi Metallo $β$-Lactamase: Substrate Protonation Mechanism is Drug Dependent

Emergence of antibiotic resistance due to New Delhi Metallo $β$-lactamase (NDM-1) bacterial enzymes is of great concern due to their ability to hydrolyze wide range of antibiotics. Efforts are ongoing to obtain the atomistic details of the hydrolysis mechanism in order to develop novel drugs and inhibitors against NDM-1. Especially, it remains elusive how drug molecules of different family of antibiotics are hydrolyzed by NDM-1 in an efficient manner. Here we report the detailed molecular mechanism of NDM-1 catalyzed hydrolysis of cephalexin, a cephalosporin family drug, and meropenem, a carbapenem family drug. This study employs molecular dynamics (MD) simulations using hybrid quantum mechanical/molecular mechanical (QM/MM) methods at the density functional theory level, based on which reaction pathways and the associated free energies are obtained. We find that the mechanism and the free energy barrier for the ring-opening step are the same for both the drug molecules, while the subsequent protonation step differs. In particular, we observe that the mechanism of the protonation step depends on the R2 group of the drug molecule. Our simulations show that allylic carbon protonation occurs in the case of cephalexin drug molecule where Lys211 is the proton donor and the proton transfer occurs via a water chain formed (only) at the ring-opened intermediate structure. Based on the free energy profiles, the overall kinetics of the drug hydrolysis is discussed. Finally, we show that the proposed mechanisms and free energy profiles could explain various experimental observations.

physics.chem-ph↗

arXiv2016

Exploring High Dimensional Free Energy Landscapes: Temperature Accelerated Sliced Sampling

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques.

physics.chem-ph↗

arXiv2016

CPMD/GULP QM/MM Interface for Modeling Periodic Solids: Implementation and its Application in the Study of Y-Zeolite Supported Rh$_n$ Clusters

We report here the development of hybrid quantum mechanics/molecular mechanics (QM/MM) interface between the plane-wave density functional theory based CPMD code and the empirical force-field based GULP code for modeling periodic solids and surfaces. The hybrid QM/MM interface is based on the electrostatic coupling between QM and MM regions. The interface is designed for carrying out full relaxation of all the QM and MM atoms during geometry optimizations and molecular dynamics simulations, including the boundary atoms. Both Born-Oppenheimer and Car-Parrinello molecular dynamics schemes are enabled for the QM part during the QM/MM calculations. This interface has the advantage of parallelization of both the programs such that the QM and MM force evaluations can be carried out in parallel in order to model large systems. The interface program is first validated for total energy conservation and parallel scaling performance is benchmarked. Oxygen vacancy in α-cristobalite is then studied in detail and the results are compared with a fully QM calculation and experimental data. Subsequently, we use our implementation to investigate the structure of rhodium cluster (Rh$_n$ ; $n$=2 to 6) formed from Rh(C$_2$H$_4$)$_2$ complex adsorbed within a cavity of Y-zeolite in a reducible atmosphere of H$_2$ gas.

physics.comp-ph↗

arXiv2016

Sampling Free Energy Surfaces as Slices by Combining Umbrella Sampling and Metadynamics

Metadynamics (MTD) is a very powerful technique to sample high-dimensional free energy landscapes, and due to its self-guiding property, the method has been successful in studying complex reactions and conformational changes. MTD sampling is based on filling the free energy basins by biasing potentials and thus for cases with flat, broad and unbound free energy wells, the computational time to sample them becomes very large. To alleviate this problem, we combine the standard Umbrella Sampling (US) technique with MTD to sample orthogonal collective variables (CVs) in a simultaneous way. Within this scheme, we construct the equilibrium distribution of CVs from biased distributions obtained from independent MTD simulations with umbrella potentials. Reweighting is carried out by a procedure that combines US reweighting and Tiwary-Parrinello MTD reweighting within the Weighted Histogram Analysis Method (WHAM). The approach is ideal for a controlled sampling of a CV in a MTD simulation, making it computationally efficient in sampling flat, broad and unbound free energy surfaces. This technique also allows for a distributed sampling of a high-dimensional free energy surface, further increasing the computational efficiency in sampling. We demonstrate the application of this technique in sampling high-dimensional surface for various chemical reactions using ab initio and QM/MM hybrid molecular dynamics simulations. Further, in order to carry out MTD bias reweighting for computing forward reaction barriers in ab initio or QM/MM simulations, we propose a computationally affordable approach that does not require recrossing trajectories.

physics.comp-ph↗

arXiv2010

Charge Localization Dynamics induced by Oxygen Vacancies on the Titania TiO$_2$(110) Surface

The dynamics of an F--center created by an oxygen vacancy on the $\mathrm{TiO_{2}(110)}$ rutile surface has been investigated using {\it ab initio} molecular dynamics. These simulations uncover a truly complex, time-dependent behavior of fluctuating electron localization topologies in the vicinity of the oxygen vacancy. Although the two excess electrons are found to populate preferentially the second subsurface layer, they occasionally visit surface sites and also the third subsurface layer. This dynamical behavior of the excess charge explains hitherto conflicting interpretations of both theoretical findings and experimental data.

cond-mat.mtrl-sci↗