arXiv subjects

Sandipan Mohanty

Publications and source records attributed to Sandipan Mohanty.

13 recordsLinked to original sources

arXiv2026

Designing lattice proteins with variational quantum algorithms

Quantum heuristics have shown promise in solving various optimization problems, including lattice protein folding. Equally relevant is the inverse problem, protein design, where one seeks sequences that fold to a given target structure. The latter problem is often split into two steps: (i) searching for sequences that minimize the energy in the target structure, and (ii) testing whether the generated sequences fold to the desired structure. Here, we investigate the utility of variational quantum algorithms for the first of these two steps on today's noisy intermediate-scale quantum devices. We focus on the sequence optimization task, which is less resource-demanding than folding computations. We test the quantum approximate optimization algorithm and variants of it, with problem-informed quantum circuits, as well as the hardware-efficient ansatz, with problem-agnostic quantum circuits. While the former approach, with a careful choice of mixer, yields good results in noiseless simulations (success probability $\geq$0.95 in all instances), its performance drops drastically under noise. With the problem-agnostic circuits, which are more compatible with hardware constraints, improved performance is observed in noisy simulations, compared to their problem-informed counterparts. When running the problem-agnostic circuits on a real quantum device, with parameters taken from simulations, we obtain a significant success probability ($\geq$0.2) in most instances.

quant-ph↗

arXiv2025

Folding lattice proteins confined on minimal grids using a quantum-inspired encoding

Steric clashes pose a challenge when exploring dense protein systems using conventional explicit-chain methods. A minimal example is a single lattice protein confined on a minimal grid, with no free sites. Finding its minimum energy is a hard optimization problem, withsimilarities to scheduling problems. It can be recast as a quadratic unconstrained binary optimization (QUBO) problem amenable to classical and quantum approaches. We show that this problem in its QUBO form can be swiftly and consistently solved for chain length 48, using either classical simulated annealing or hybrid quantum-classical annealing on a D-Wave system. In fact, the latter computations required about 10 seconds. We also test linear and quadratic programming methods, which work well for a lattice gas but struggle with chain constraints. All methods are benchmarked against exact results obtained from exhaustive structure enumeration, at a high computational cost.

quant-ph↗

arXiv2024

Using quantum annealing to design lattice proteins

Quantum annealing has shown promise for finding solutions to difficult optimization problems, including protein folding. Recently, we used the D-Wave Advantage quantum annealer to explore the folding problem in a coarse-grained lattice model, the HP model, in which amino acids are classified into two broad groups: hydrophobic (H) and polar (P). Using a set of 22 HP sequences with up to 64 amino acids, we demonstrated the fast and consistent identification of the correct HP model ground states using the D-Wave hybrid quantum-classical solver. An equally relevant biophysical challenge, called the protein design problem, is the inverse of the above, where the task is to predict protein sequences that fold to a given structure. Here, we approach the design problem by a two-step procedure, implemented and executed on a D-Wave machine. In the first step, we perform a pure sequence-space search by varying the type of amino acid at each sequence position, and seek sequences which minimize the HP-model energy of the target structure. After mapping this task onto an Ising spin glass representation, we employ a hybrid quantum-classical solver to deliver energy-optimal sequences for structures with 30-64 amino acids, with a 100% success rate. In the second step, we filter the optimized sequences from the first step according to their ability to fold to the intended structure. In addition, we try solving the sequence optimization problem using only the QPU, which confines us to sizes $\le$20, due to exponentially decreasing success rates. To shed light on the pure QPU results, we investigate the effects of control errors caused by an imperfect implementation of the intended Hamiltonian on the QPU, by numerically analyzing the Schrödinger equation. We find that the simulated success rates in the presence of control noise semi-quantitatively reproduce the modest pure QPU results for larger chains.

quant-ph↗

arXiv2022

Folding lattice proteins with quantum annealing

Quantum annealing is a promising approach for obtaining good approximate solutions to difficult optimization problems. Folding a protein sequence into its minimum-energy structure represents such a problem. For testing new algorithms and technologies for this task, the minimal lattice-based HP model is well suited, as it represents a considerable challenge despite its simplicity. The HP model has favorable interactions between adjacent, not directly bound hydrophobic residues. Here, we develop a novel spin representation for lattice protein folding tailored for quantum annealing. With a distributed encoding onto the lattice, it differs from earlier attempts to fold lattice proteins on quantum annealers, which were based upon chain growth techniques. With our encoding, the Hamiltonian by design has the quadratic structure required for calculations on an Ising-type annealer, without having to introduce any auxiliary spin variables. This property greatly facilitates the study of long chains. The approach is robust to changes in the parameters required to constrain the spin system to chain-like configurations, and performs very well in terms of solution quality. The results are evaluated against existing exact results for HP chains with up to $N=30$ beads with 100% hit rate, thereby also outperforming classical simulated annealing. In addition, the method allows us to recover the lowest known energies for $N=48$ and $N=64$ HP chains, with similar hit rates. These results are obtained by the commonly used hybrid quantum-classical approach. For pure quantum annealing, our method successfully folds an $N=14$ HP chain. The calculations were performed on a D-Wave Advantage quantum annealer.

quant-ph↗

arXiv2018

Markov modeling of peptide folding in the presence of protein crowders

We use Markov state models (MSMs) to analyze the dynamics of a $β$-hairpin-forming peptide in Monte Carlo (MC) simulations with interacting protein crowders, for two different types of crowder proteins [bovine pancreatic trypsin inhibitor (BPTI) and GB1]. In these systems, at the temperature used, the peptide can be folded or unfolded and bound or unbound to crowder molecules. Four or five major free-energy minima can be identified. To estimate the dominant MC relaxation times of the peptide, we build MSMs using a range of different time resolutions or lag times. We show that stable relaxation-time estimates can be obtained from the MSM eigenfunctions through fits to autocorrelation data. The eigenfunctions remain sufficiently accurate to permit stable relaxation-time estimation down to small lag times, at which point simple estimates based on the corresponding eigenvalues have large systematic uncertainties. The presence of the crowders have a stabilizing effect on the peptide, especially with BPTI crowders, which can be attributed to a reduced unfolding rate $k_\text{u}$, while the folding rate $k_\text{f}$ is left largely unchanged.

physics.bio-ph↗

arXiv2015

The Mont-Blanc Project: First Phase Successfully Finished

Running from October 2011 to June 2015, the aim of the European project Mont-Blanc has been to develop an approach to Exascale computing based on embedded power-efficient technology. The main goals of the project were to i) build an HPC prototype using currently available energy-efficient embedded technology, ii) design a Next Generation system to overcome the limitations of the built prototype and iii) port a set of representative Exascale applications to the system. This article summarises the contributions from the Leibniz Supercomputing Centre (LRZ) and the Juelich Supercomputing Centre (JSC), Germany, to the Mont-Blanc project.

cs.DC↗

arXiv2009

An effective all-atom potential for proteins

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary structure. Results obtained using the final form of the potential are presented for all these peptides. The same model, with unchanged parameters, is furthermore applied to a heterodimeric coiled-coil system, a mixed alpha/beta protein and a three-helix-bundle protein, with very good results. The computational efficiency of the potential makes it possible to investigate the free-energy landscape of these 49--67-residue systems with high statistical accuracy, using only modest computational resources by today's standards.

q-bio.BM↗

arXiv2004

Folding thermodynamics of peptides

A simplified interaction potential for protein folding studies at the atomic level is discussed and tested on a set of peptides with about 20 residues each. The test set contains both alpha-helical (Trp cage, Fs) and beta-sheet (GB1p, GB1m2, GB1m3, Betanova, LLM) peptides. The model, which is entirely sequence-based, is able to fold these different peptides for one and the same choice of model parameters. Furthermore, the melting behavior of the peptides is in good quantitative agreement with experimental data. Apparent folded populations obtained using different observables are compared, and are found to be very different for some of the peptides (e.g., Betanova). In other cases (in particular, GB1m2 and GB1m3), the different estimates agree reasonably well, indicating a more two-state-like melting behavior.

q-bio.BM↗

arXiv2004

Oligomerization of amyloid Abeta peptides using hydrogen bonds and hydrophobicity forces

The 16-22 amino acid fragment of the beta-amyloid peptide associated with the Alzheimer's disease, Abeta, is capable of forming amyloid fibrils. Here we study the aggregation mechanism of Abeta(16-22) peptides by unbiased thermodynamic simulations at the atomic level for systems of one, three and six Abeta(16-22) peptides. We find that the isolated Abeta(16-22) peptide is mainly a random coil in the sense that both the alpha-helix and beta-strand contents are low, whereas the three- and six-chain systems form aggregated structures with a high beta-sheet content. Furthermore, in agreement with experiments on Abeta(16-22) fibrils, we find that large parallel beta-sheets are unlikely to form. For the six-chain system, the aggregated structures can have many different shapes, but certain particularly stable shapes can be identified.

q-bio.BM↗

arXiv2002

Recent Developments in the Lund Model

A brief introduction to the String Fragmentation Model and its consequences is presented. We discuss the fragmentation of a general multi-gluon string and show that it can be formulated as the production of a set of ''plaquettes'' between the hadronic curve and the directrix. We also discuss certain interesting scaling properties of the partonic states obtained from standard parton shower algorithms like those in Pythia and Ariadne, which are communicated to the final state hadrons obtained through our hadronisation procedure.

hep-ph↗

arXiv2002

Bose Einstein Correlations in the Lund Model for Multijet Systems

The interference based analysis of Bose Einstein Correlations in the Lund Model has hitherto been limited to simple strings without gluonic excitations. A new fragmentation method based on the Area Law in the Lund Model allows such an analysis to be extended to multigluon strings.

hep-ph↗

arXiv2002

The Lambda-Measure and the Generalised Dipoles in the Lund Model

We demonstrate that the multiple gluon emission phase space in the dipole cascade model has a strong linear correlation with the number of gluons emitted. The number of gluons per unit available phase space at a certain resolution scale is found to be remarkably independent of the cms energy and global event properties like thrust, and even changes in the ordering variable or resolution scale. We show that the distribution of sizes of gluon-gluon dipoles in a parton cascade has stability properties which are sufficient to account for those of the phase space variable. We observe that certain more abstract entities, defined in the context of hadronisation and related to the gluon emission phase space, share those properties of colour dipoles and name them Generalised Dipoles. We also present an analytical model to qualitatively describe our findings.

hep-ph↗

arXiv2001

The Lund Fragmentation Process for a Multi-gluon String According to the Area Law

The Lund Area Law describes the probability for the production of a set of colourless hadrons from an initial set of partons, in the Lund string fragmentation model. In this paper we will present a general method to implement the Area Law for a multi-gluon string state. The partonic states are in general given by a perturbative QCD cascade and are consequently defined only down to a cutoff in the energy momentum fluctuations. We will show that our method defines the states down to the hadronic mass scale inside an analytically calculable scenario. We will then show that there is a differential version of our process which is closely related to the generalised rapidity range λ, which has been used as a measure on the partonic states. We identify λas the area spanned between the directrix curve (the curve given by the parton energy momentum vectors laid out in colour order, which determines the string surface) and the average curve (to be called the P-curve) of the stochastic X-curves (curves obtained when the hadronic energy-momentum vectors are laid out in rank order). Finally we show that from the X-curve corresponding to a particular stochastic fragmentation situation it is possible to reproduce the directrix curve (up to one starting vector and a set of sign choices, one for each hadron).

hep-ph↗