Publications by authors named "Alexey V Onufriev"

Accuracy of binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a multidimensional optimization pipeline is used to find optimal atomic radii, specifically for binding calculations in the implicit solvent. To reduce overfitting, the optimization target includes separate, weighted contributions from both binding and hydration free energies.

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The ion atmosphere surrounding highly charged biomolecules, such as nucleic acids, is crucial for their dynamics, structure, and interactions. Here, we develop an approach for the explicit treatment of ions within an implicit solvent framework suitable for atomistic simulations of biomolecules. The proposed implicit solvent/explicit ions model, GBION, is based on a modified generalized Born (GB) model; it includes separate, modified GB terms for solute-ion and ion-ion interactions.

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The current practical "workhorses" of the atomistic implicit solvation─the Poisson-Boltzmann (PB) and generalized Born (GB) models─face fundamental accuracy limitations. Here, we propose a computationally efficient implicit solvation framework, the Implicit Water Multipole GB (IWM-GB) model, that systematically incorporates the effects of multipole moments of water molecules in the first hydration shell of a solute, beyond the dipole water polarization already present at the PB/GB level. The framework explicitly accounts for coupling between polar and nonpolar contributions to the total solvation energy, which is missing from many implicit solvation models.

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Background: Multiple studies have demonstrated a negative correlation between gene expression and positioning of genes at the nuclear envelope (NE) lined by nuclear lamina, but the exact relationship remains unclear, especially in light of the highly stochastic, transient nature of the gene association with the NE.

Results: In this paper, we ask whether there is a causal, systematic, genome-wide relationship between the expression levels of the groups of genes in topologically associating domains (TADs) of Drosophila nuclei and the probabilities of TADs to be found at the NE. To investigate the nature of this possible relationship, we combine a coarse-grained dynamic model of the entire Drosophila nucleus with genome-wide gene expression data; we analyze the TAD averaged transcription levels of genes against the probabilities of individual TADs to be in contact with the NE in the control and lamins-depleted nuclei.

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The accuracy of computational models of water is key to atomistic simulations of biomolecules. We propose a computationally efficient way to improve the accuracy of the prediction of hydration-free energies (HFEs) of small molecules: the remaining errors of the physics-based models relative to the experiment are predicted and mitigated by machine learning (ML) as a postprocessing step. Specifically, the trained graph convolutional neural network attempts to identify the "blind spots" in the physics-based model predictions, where the complex physics of aqueous solvation is poorly accounted for, and partially corrects for them.

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Experimentally, in the presence of the crowding agent polyethylene glycol (PEG), sodium ions compact double-stranded DNA more readily than potassium ions. Here, we have used molecular dynamics simulations and the "ion binding shells model" of DNA condensation to provide an explanation for the observed variations in condensation of short DNA duplexes in solutions containing different monovalent cations and PEG; several predictions are made. According to the model we use, externally bound ions contribute the most to the ion-induced aggregation of DNA duplexes.

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AmberTools is a free and open-source collection of programs used to set up, run, and analyze molecular simulations. The newer features contained within AmberTools23 are briefly described in this Application note.

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Background: Interactions among topologically associating domains (TADs), and between the nuclear envelope (NE) and lamina-associated domains (LADs) are expected to shape various aspects of three-dimensional (3D) chromatin structure and dynamics; however, relevant genome-wide experiments that may provide statistically significant conclusions remain difficult.

Results: We have developed a coarse-grained dynamical model of D. melanogaster nuclei at TAD resolution that explicitly accounts for four distinct epigenetic classes of TADs and LAD-NE interactions.

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Stability of a protein-ligand complex may be sensitive to pH of its environment. Here we explore, computationally, stability of a set of protein-nucleic acid complexes using fundamental thermodynamic linkage relationship. The nucleosome, as well as an essentially random selection of 20 protein complexes with DNA or RNA, are included in the analysis.

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Simulating water accurately has been a major challenge in atomistic simulations for decades. Inclusion of electronic polarizability effects holds considerable promise, yet existing approaches suffer from significant computational overheads compared to the widely used nonpolarizable water models. We have developed a globally optimal polarizable water model, OPC3-pol, that explicitly accounts for electronic polarizability with minimal impact on the computational efficiency.

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Closed-form, analytical approximations for electrostatic properties of molecules are of unique value as these can provide computational speed, versatility, and physical insight. Here, we have derived a simple, closed-form formula for the apparent surface charge (ASC) as well as for the electric field generated by a molecular charge distribution in aqueous solution. The approximation, with no fitted parameters, was tested against numerical solutions of the Poisson equation, where it has produced a significant speed-up.

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We propose an approach to help interpret polymer force-extension curves that exhibit plateau regimes. When coupled to a bead-spring dynamic model, the approach accurately reproduces a variety of experimental force-extension curves of long double-stranded DNA and RNA, including torsionally constrained and unconstrained DNA and negatively supercoiled DNA. A key feature of the model is a specific nonconvex energy function of the spring.

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Knowledge of insect population density is crucial for establishing management and conservation tactics and evaluating treatment efficacies. Here, we propose a simple and universal method for estimating the most probable absolute population density and its statistical bounds. The method is based on a novel relationship between experimentally measurable characteristics of insect trap systems and the probability to catch an insect located a given distance away from the trap.

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We have compared distributions of sodium and potassium ions around double-stranded DNA, simulated using fixed charge SPC/E, TIP3P, and OPC water models and the Joung/Cheatham (J/C) ion parameter set, as well as the Li/Merz HFE 6-12 (L/M HFE) ion parameters for OPC water. In all the simulations, the ion distributions are in qualitative agreement with Manning's condensation theory and the Debye-Hückel theory, where expected. In agreement with experiment, binding affinity of monovalent ions to DNA does not depend on ion type in every solvent model.

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The intrinsically disordered, positively charged H4 histone tail is important for chromatin structure and function. We have explored conformational ensembles of human H4 tail in solution, with varying levels of charge neutralization via acetylation or amino-acid substitutions such as K→Q. We have employed an explicit water model shown recently to be well suited for simulations of intrinsically disordered proteins.

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A recently introduced family of globally optimal water models, OPC, has shown promise in a variety of biomolecular simulations, but properties of these water models outside of the liquid phase remain mostly unexplored. Here, we contribute to filling the gap by reporting melting temperatures of ice of OPC and OPC3 water models. Through the direct coexistence method, which we make available in the AMBER package, the melting points of OPC and OPC3 are estimated as 242 and 210 K, similar to TIP4P-Ew and SPC/E models, respectively, and appreciably below the experimental value of 273.

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Estimates of absolute pest population density are critical to pest management programs but have been difficult to obtain from capture numbers in pheromone-baited monitoring traps. In this paper, we establish a novel predictive relationship for a probability () of catching a male located at a distance from the trap with a plume reach .

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The ability to estimate protein-protein binding free energy in a computationally efficient via a physics-based approach is beneficial to research focused on the mechanism of viruses binding to their target proteins. Implicit solvation methodology may be particularly useful in the early stages of such research, as it can offer valuable insights into the binding process, quickly. Here we evaluate the potential of the related molecular mechanics generalized Born surface area (MMGB/SA) approach to estimate the binding free energy Δ between the SARS-CoV-2 spike receptor-binding domain and the human ACE2 receptor.

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The strong bending of polymers is poorly understood. We propose a general quantitative framework of polymer bending that includes both the weak and strong bending regimes on the same footing, based on a single general physical principle. As the bending deformation increases beyond a certain (polymer-specific) point, the change in the convexity properties of the effective bending energy of the polymer makes the harmonic deformation energetically unfavorable: in this strong bending regime the energy of the polymer varies linearly with the average bending angle as the system follows the convex hull of the deformation energy function.

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Accuracy of protein-ligand binding free energy calculations utilizing implicit solvent models is critically affected by parameters of the underlying dielectric boundary, specifically, the atomic and water probe radii. Here, a global multidimensional optimization pipeline is developed to find optimal atomic radii specifically for protein-ligand binding calculations in implicit solvent. The computational pipeline has these three key components: (1) a massively parallel implementation of a deterministic global optimization algorithm (VTDIRECT95), (2) an accurate yet reasonably fast generalized Born implicit solvent model (GBNSR6), and (3) a novel robustness metric that helps distinguish between nearly degenerate local minima via a postprocessing step of the optimization.

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Spatial organization of chromosome territories and interactions between interphase chromosomes themselves, as well as with the nuclear periphery, play important roles in epigenetic regulation of the genome function. However, the interplay between inter-chromosomal contacts and chromosome-nuclear envelope attachments in an organism's development is not well-understood. To address this question, we conducted microscopic analyses of the three-dimensional chromosome organization in malaria mosquitoes.

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Rigid n-point water models are widely used in atomistic simulations, but have known accuracy drawbacks. Increasing the number of point charges, as well as adding electronic polarizability, are two common strategies for accuracy improvements. Both strategies come at considerable computational cost, which weighs heavily against modest possible accuracy improvements in practical simulations.

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Unconstrained atomistic simulations of intrinsically disordered proteins and peptides (IDP) remain a challenge: widely used, "general purpose" water models tend to favor overly compact structures relative to experiment. Here we have performed a total of 93 μs of unrestrained MD simulations to explore, in the context of IDPs, a recently developed "general-purpose" 4-point rigid water model OPC, which describes liquid state of water close to experiment. We demonstrate that OPC, together with a popular AMBER force field ff99SB, offers a noticeable improvement over TIP3P in producing more realistic structural ensembles of three common IDPs benchmarks: 55-residue apo N-terminal zinc-binding domain of HIV-1 integrase ("protein IN"), amyloid β-peptide (Aβ) (residues 1-42), and 26-reside H4 histone tail.

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It would often be useful in computer simulations to use an implicit description of solvation effects, instead of explicitly representing the individual solvent molecules. Continuum dielectric models often work well in describing the thermodynamic aspects of aqueous solvation and can be very efficient compared to the explicit treatment of the solvent. Here, we review a particular class of so-called fast implicit solvent models, generalized Born (GB) models, which are widely used for molecular dynamics (MD) simulations of proteins and nucleic acids.

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