Computational Investigation of the Metal and Ligand Substitution Effects on the Structure and Electronic States of the Phosphoranimide Tetramer Complexes of Cu(I), Ni(I), Co(I), and Fe(I).

The structurally unique saddle-shaped paramagnetic tetrametallic clusters of Co(I) and Ni(I) with phosphoranimide ligands have been synthesized and proposed as catalyst precursors. The analogous Cu(I) nanocluster is planar and diamagnetic. These notable variations in geometry and ground electronic states indicate that the effect of metal and ligand substituents on the structure and electronic properties of these complexes requires investigation. We present a computational study of a series of these novel homoleptic complexes containing Co(I), Ni(I), and Cu(I) as well as Fe(I) coordinated to phosphoranimides with electron-donating and withdrawing substituents, conducted at the relativistic density functional theory level using ZORA-PBE/TZP. The optimized structures of the saddle-shaped Co(I) and Ni(I) and planar Cu(I) tetramers with linear N-M-N coordination are validated with respect to X-ray diffraction determinations. The ground-state analysis indicates that Cu(I) complexes are diamagnetic, whereas Ni(I) and Co(I) complexes are in high-spin states, in agreement with magnetic susceptibility measurements. The computational results show that Fe(I) complexes are saddle shaped and high spin. The Co(I) complex is stabilized by a metal macrocycle distortion from square to diamond, as elucidated from its Walsh diagram. The effects of metals and ligand substituents on the ground electronic state, metal center coordination environment, and energy of the complexes are investigated. The bulky tertiary butyl substituent causes the largest saddle-shape distortion of the tetramer marcocycle, which partially offsets its electron-donating effect. Macrocycle distortions with N-M-N site angles ranging from obtuse to alternating obtuse reflex are correlated with the increasing number of unpaired electrons. The phenyl-substituted complexes are expected to have the highest reactivity toward electrophiles. Understanding the interplay between structural and electronic parameters is intended to guide the development of synthetic cooperative systems for multielectron redox reactions, models of biological systems, and molecular magnets.

Understanding the Liquid States of Cyclic Hydrocarbons Containing N, O, and S Atoms via the 3D-RISM-KH Molecular Solvation Theory.

The 3D-reference interaction site model (3D-RISM) molecular solvation theory in combination with the Kovalenko-Hirata (KH) closure is extended to seven heterocyclic liquids to understand their liquid states and to test the performance of the theory in solvation free energy (SFE) calculations of solutes in select solvents. The computed solvent site distribution profiles were compared with the all-atom molecular dynamics (MD) simulations, showing comparable performances. The computational results were compared against the structural parameters for liquids, whenever available, as well as against the experimental SFEs. The liquids are found to have local ordered structures held together via weak interactions in both the RISM and MD simulations. The 3D-RISM-KH computed SFEs are in good agreement with the benchmark values for the tetrahydrothiophene-S,S-dioxide, and showed comparatively larger deviations in the case of the SFEs in the tetrahydrofuran continuum.

Predicting PAMPA permeability using the 3D-RISM-KH theory: are we there yet?

The parallel artificial membrane permeability assay (PAMPA), a non-cellular lab-based assay, is extensively used to measure the permeability of pharmaceutical compounds. PAMPA experiments provide a working mimic of a molecule passing through cells and PAMPA values are widely used to estimate drug absorption parameters. There is an increased interest in developing computational methods to predict PAMPA permeability values. We developed an in silico model to predict the permeability of compounds based on the PAMPA assay. We used the three-dimensional reference interaction site model (3D-RISM) theory with the Kovalenko-Hirata (KH) closure to calculate the excess chemical potentials of a large set of compounds and predicted their apparent permeability with good accuracy (mean absolute error or MAE = 0.69 units) when compared to a published experimental data set. Furthermore, our in silico PAMPA protocol performed very well in the binary prediction of 288 compounds as being permeable or impermeable (precision = 94%, accuracy = 93%). This suggests that our in silico protocol can mimic the PAMPA assay and could aid in the rapid discovery or screening of potentially therapeutic drug leads that can be delivered to a desired tissue.

Biomolecular Simulations with the Three-Dimensional Reference Interaction Site Model with the Kovalenko-Hirata Closure Molecular Solvation Theory.

The statistical mechanics-based 3-dimensional reference interaction site model with the Kovalenko-Hirata closure (3D-RISM-KH) molecular solvation theory has proven to be an essential part of a multiscale modeling framework, covering a vast region of molecular simulation techniques. The successful application ranges from the small molecule solvation energy to the bulk phase behavior of polymers, macromolecules, etc. The 3D-RISM-KH successfully predicts and explains the molecular mechanisms of self-assembly and aggregation of proteins and peptides related to neurodegeneration, protein-ligand binding, and structure-function related solvation properties. Upon coupling the 3D-RISM-KH theory with a novel multiple time-step molecular dynamic (MD) of the solute biomolecule stabilized by the optimized isokinetic Nosé-Hoover chain thermostat driven by effective solvation forces obtained from 3D-RISM-KH and extrapolated forward by generalized solvation force extrapolation (GSFE), gigantic outer time-steps up to picoseconds to accurately calculate equilibrium properties were obtained in this new quasidynamics protocol. The multiscale OIN/GSFE/3D-RISM-KH algorithm was implemented in the Amber package and well documented for fully flexible model of alanine dipeptide, miniprotein 1L2Y, and protein G in aqueous solution, with a solvent sampling rate ~150 times faster than a standard MD simulation in explicit water. Further acceleration in computation can be achieved by modifying the extent of solvation layers considered in the calculation, as well as by modifying existing closure relations. This enhanced simulation technique has proven applications in protein-ligand binding energy calculations, ligand/solvent binding site prediction, molecular solvation energy calculations, etc. Applications of the RISM-KH theory in molecular simulation are discussed in this work.

Tryptophan 32 mediates SOD1 toxicity in a in vivo motor neuron model of ALS and is a promising target for small molecule therapeutics.

SOD1 misfolding, toxic gain of function, and spread are proposed as a pathological basis of amyotrophic lateral sclerosis (ALS), but the nature of SOD1 toxicity has been difficult to elucidate. Uniquely in SOD1 proteins from humans and other primates, and rarely in other species, a tryptophan residue at position 32 (W32) is predicted to be solvent exposed and to participate in SOD1 misfolding. We hypothesized that W32 is influential in SOD1 acquiring toxicity, as it is known to be important in template-directed misfolding. We tested if W32 contributes to SOD1 cytotoxicity and if it is an appropriate drug target to ameliorate ALS-like neuromuscular deficits in a zebrafish model of motor neuron axon morphology and function (swimming). Embryos injected with human SOD1 variant with W32 substituted for a serine (SOD1W32S) had reduced motor neuron axonopathy and motor deficits compared to those injected with wildtype or disease-associated SOD1. A library of FDA-approved small molecules was ranked with virtual screening based on predicted binding to W32, and subsequently filtered for analogues using a pharmacophore model based on molecular features of the uracil moiety of a small molecule previously predicted to interact with W32 (5'-fluorouridine or 5'-FUrd). Along with testing 5'-FUrd and uridine, a lead candidate from this list was selected based on its lower toxicity and improved blood brain barrier penetrance; telbivudine significantly rescued SOD1 toxicity in a dose-dependent manner. The mechanisms whereby the small molecules ameliorated motor neuron phenotypes were specifically mediated through human SOD1 and its residue W32, because these therapeutics had no measurable impact on the effects of UBQLN4D90A, EtOH, or tryptophan-deficient human SOD1W32S. By substituting W32 for a more evolutionarily conserved residue (serine), we confirmed the significant influence of W32 on human SOD1 toxicity to motor neuron morphology and function; further, we performed pharmaceutical targeting of the W32 residue for rescuing SOD1 toxicity. This unique residue offers future novel insights into SOD1 stability and toxic gain of function, and therefore poses an potential target for drug therapy.

Application of the 3D-RISM-KH molecular solvation theory for DMSO as solvent.

The molecular solvation theory in the form of the Three-Dimensional Reference Interaction Site Model (3D-RISM) with Kovalenko-Hirata (KH) closure relation is benchmarked for use with dimethyl sulfoxide (DMSO) as solvent for (bio)-chemical simulation within the framework of integral equation formalism. Several force field parameters have been tested to correctly reproduce solvation free energy in DMSO, ion solvation in DMSO, and DMSO coordination prediction. Our findings establish a united atom (UA) type parameterization as the best model of DMSO for use in 3D-RISM-KH theory based calculations.

Prediction of P-glycoprotein inhibitors with machine learning classification models and 3D-RISM-KH theory based solvation energy descriptors.

Development of novel in silico methods for questing novel PgP inhibitors is crucial for the reversal of multi-drug resistance in cancer therapy. Here, we report machine learning based binary classification schemes to identify the PgP inhibitors from non-inhibitors using molecular solvation theory with excellent accuracy and precision. The excess chemical potential and partial molar volume in various solvents are calculated for PgP± (PgP inhibitors and non-inhibitors) compounds with the statistical-mechanical based three-dimensional reference interaction site model with the Kovalenko-Hirata closure approximation (3D-RISM-KH molecular theory of solvation). The statistical importance analysis of descriptors identified the 3D-RISM-KH based descriptors as top molecular descriptors for classification. Among the constructed classification models, the support vector machine predicted the test set of Pgp± compounds with highest accuracy and precision of ~ 97% for test set. The validation of models confirms the robustness of state-of-the-art molecular solvation theory based descriptors in identification of the Pgp± compounds.

Predicting skin permeability using the 3D-RISM-KH theory based solvation energy descriptors for a diverse class of compounds.

The state-of-the-art molecular solvation theory is used to predict skin permeability of a large set of compounds with available experimental skin permeability coefficient (logKP). Encouraging results are obtained pointing to applicability of a novel quantitative structure activity model that uses statistical physics based 3D-RISM-KH theory for solvation free energy calculations as a primary descriptor for the prediction of logKP with relative mean square error of 0.77 units.

The role of hydration effects in 5-fluorouridine binding to SOD1: insight from a new 3D-RISM-KH based protocol for including structural water in docking simulations.

Misfolded Cu/Zn superoxide dismutase enzyme (SOD1) shows prion-like propagation in neuronal cells leading to neurotoxic aggregates that are implicated in amyotrophic lateral sclerosis (ALS). Tryptophan-32 (W32) in SOD1 is part of a potential site for templated conversion of wild type SOD1. This W32 binding site is located on a convex, solvent exposed surface of the SOD1 suggesting that hydration effects can play an important role in ligand recognition and binding. A recent X-ray crystal structure has revealed that 5-Fluorouridine (5-FUrd) binds at the W32 binding site and can act as a pharmacophore scaffold for the development of anti-ALS drugs. In this study, a new protocol is developed to account for structural (non-displaceable) water molecules in docking simulations and successfully applied to predict the correct docked conformation binding modes of 5-FUrd at the W32 binding site. The docked configuration is within 0.58 Å (RMSD) of the observed configuration. The docking protocol involved calculating a hydration structure around SOD1 using molecular theory of solvation (3D-RISM-KH, 3D-Reference Interaction Site Model-Kovalenko-Hirata) whereby, non-displaceable water molecules are identified for docking simulations. This protocol was also used to analyze the hydrated structure of the W32 binding site and to explain the role of solvation in ligand recognition and binding to SOD1. Structural water molecules mediate hydrogen bonds between 5-FUrd and the receptor, and create an environment favoring optimal placement of 5-FUrd in the W32 binding site.

Performance of 3D-RISM-KH in Predicting Hydration Free Energy: Effect of Solute Parameters.

The three-dimensional reference interaction site model molecular solvation theory with the Kovalenko-Hirata closure relation has been shown to produce excellent solvation characteristics for a large class of (bio)chemical systems in solution. Correct calculation of hydration free energy is central to successful application of any solvation model. In order to find out the best possible force-field parameters to be used for hydration free energy calculation with the aforementioned theory, we have developed an extended database containing a large number of experimental solvation free energies available in the current literature and used a plethora of theoretical models for assessment. The general Amber force field was found to perform satisfactorily, whereas special care should be taken in solute charge assignment with the universal force field.

Enhanced solvation force extrapolation for speeding up molecular dynamics simulations of complex biochemical liquids.

We propose an enhanced approach to the extrapolation of mean potential forces acting on atoms of solute macromolecules due to their interactions with solvent atoms in complex biochemical liquids. It improves and extends our previous extrapolation schemes by additionally including new techniques such as an exponential scaling transformation of coordinate space with weights complemented by an automatically adjusted balancing between the least square minimization of force deviations and the norm of expansion coefficients in the approximation. The expensive mean potential forces are treated in terms of the three-dimensional reference interaction site model with Kovalenko-Hirata closure molecular theory of solvation. During the dynamics, they are calculated only after every long (outer) time interval, i.e., quite rarely to reduce the computational costs. At much shorter (inner) time steps, these forces are extrapolated on the basis of their outer values. The equations of motion are then solved using a multiple time step integration within an optimized isokinetic Nosé-Hoover chain thermostat. The new approach is applied to molecular dynamics simulations of various systems consisting of solvated organic and biomolecules of different complexity. For example, we consider hydrated alanine dipeptide, asphaltene in toluene solvent, miniprotein 1L2Y, and protein G in aqueous solution. It is shown that in all these cases, the enhanced extrapolation provides much better accuracy of the solvation force approximation than the existing approaches. As a result, it can be used with much larger outer time steps, leading to a significant speedup of the simulations.

Multiscale methods framework: self-consistent coupling of molecular theory of solvation with quantum chemistry, molecular simulations, and dissipative particle dynamics.

In this work, we will address different aspects of self-consistent field coupling of computational chemistry methods at different time and length scales in modern materials and biomolecular science. Multiscale methods framework yields dramatically improved accuracy, efficiency, and applicability by coupling models and methods on different scales. This field benefits many areas of research and applications by providing fundamental understanding and predictions. It could also play a particular role in commercialization by guiding new developments and by allowing quick evaluation of prospective research projects. We employ molecular theory of solvation which allows us to accurately introduce the effect of the environment on complex nano-, macro-, and biomolecular systems. The uniqueness of this method is that it can be naturally coupled with the whole range of computational chemistry approaches, including QM, MM, and coarse graining.

Cellulose Aggregation under Hydrothermal Pretreatment Conditions.

Cellulose, the most abundant biopolymer on Earth, represents a resource for sustainable production of biofuels. Thermochemical treatments make lignocellulosic biomaterials more amenable to depolymerization by exposing cellulose microfibrils to enzymatic or chemical attacks. In such treatments, the solvent plays fundamental roles in biomass modification, but the molecular events underlying these changes are still poorly understood. Here, the 3D-RISM-KH molecular theory of solvation has been employed to analyze the role of water in cellulose aggregation under different thermodynamic conditions. The results show that, under ambient conditions, highly structured hydration shells around cellulose create repulsive forces that protect cellulose microfibrils from aggregating. Under hydrothermal pretreatment conditions, however, the hydration shells lose structure, and cellulose aggregation is favored. These effects are largely due to a decrease in cellulose-water interactions relative to those at ambient conditions, so that cellulose-cellulose attractive interactions become prevalent. Our results provide an explanation to the observed increase in the lateral size of cellulose crystallites when biomass is subject to pretreatments and deepen the current understanding of the mechanisms of biomass modification.

SAMPL5: 3D-RISM partition coefficient calculations with partial molar volume corrections and solute conformational sampling.

Implicit solvent methods for classical molecular modeling are frequently used to provide fast, physics-based hydration free energies of macromolecules. Less commonly considered is the transferability of these methods to other solvents. The Statistical Assessment of Modeling of Proteins and Ligands 5 (SAMPL5) distribution coefficient dataset and the accompanying explicit solvent partition coefficient reference calculations provide a direct test of solvent model transferability. Here we use the 3D reference interaction site model (3D-RISM) statistical-mechanical solvation theory, with a well tested water model and a new united atom cyclohexane model, to calculate partition coefficients for the SAMPL5 dataset. The cyclohexane model performed well in training and testing ([Formula: see text] for amino acid neutral side chain analogues) but only if a parameterized solvation free energy correction was used. In contrast, the same protocol, using single solute conformations, performed poorly on the SAMPL5 dataset, obtaining [Formula: see text] compared to the reference partition coefficients, likely due to the much larger solute sizes. Including solute conformational sampling through molecular dynamics coupled with 3D-RISM (MD/3D-RISM) improved agreement with the reference calculation to [Formula: see text]. Since our initial calculations only considered partition coefficients and not distribution coefficients, solute sampling provided little benefit comparing against experiment, where ionized and tautomer states are more important. Applying a simple [Formula: see text] correction improved agreement with experiment from [Formula: see text] to [Formula: see text], despite a small number of outliers. Better agreement is possible by accounting for tautomers and improving the ionization correction.

Electric Interfacial Layer of Modified Cellulose Nanocrystals in Aqueous Electrolyte Solution: Predictions by the Molecular Theory of Solvation.

The X-ray crystal structure-based models of Iα cellulose nanocrystals (CNC), both pristine and containing surface sulfate groups with negative charge 0-0.34 e/nm(2) produced by sulfuric acid hydrolysis of softwood pulp, feature a highly polarized "crystal-like" charge distribution. We perform sampling using molecular dynamics (MD) of the structural relaxation of neutral pristine and negatively charged sulfated CNC of various lengths in explicit water solvent and then employ the statistical mechanical 3D-RISM-KH molecular theory of solvation to evaluate the solvation structure and thermodynamics of the relaxed CNC in ambient aqueous NaCl solution at a concentration of 0.0-0.25 mol/kg. The MD sampling induces a right-hand twist in CNC and rearranges its initially ordered structure with a macrodipole of high-density charges at the opposite faces into small local spots of alternating charge at each face. This surface charge rearrangement observed for both neutral and charged CNC significantly affects the distribution of ions around CNC in aqueous electrolyte solution. The solvation free energy (SFE) of charged sulfated CNC has a minimum at a particular electrolyte concentration depending on the surface charge density, whereas the SFE of neutral CNC increases linearly with NaCl concentration. The SFE contribution from Na(+) counterions exhibits behavior similar to the NaCl concentration dependence of the whole SFE. An analysis of the 3D maps of Na(+) density distributions shows that these model CNC particles exhibit the behavior of charged nanocolloids in aqueous electrolyte solution: an increase in electrolyte concentration shrinks the electric interfacial layer and weakens the effective repulsion between charged CNC particles. The 3D-RISM-KH method readily treats solvent and electrolyte of a given nature and concentration to predict effective interactions between CNC particles in electrolyte solution. We provide CNC structural models and a modeling procedure for studies of effective interactions and the formation of ordered phases of CNC suspensions in electrolyte solution.

Role of water in ligand binding to maltose-binding protein: insight from a new docking protocol based on the 3D-RISM-KH molecular theory of solvation.

Maltose-binding protein is a periplasmic binding protein responsible for transport of maltooligosaccarides through the periplasmic space of Gram-negative bacteria, as a part of the ABC transport system. The molecular mechanisms of the initial ligand binding and induced large scale motion of the protein's domains still remain elusive. In this study, we use a new docking protocol that combines a recently proposed explicit water placement algorithm based on the 3D-RISM-KH molecular theory of solvation and conventional docking software (AutoDock Vina) to explain the mechanisms of maltotriose binding to the apo-open state of a maltose-binding protein. We confirm the predictions of previous NMR spectroscopic experiments on binding modes of the ligand. We provide the molecular details on the binding mode that was not previously observed in the X-ray experiments. We show that this mode, which is defined by the fine balance between the protein-ligand direct interactions and solvation effects, can trigger the protein's domain motion resulting in the holo-closed structure of the maltose-binding protein with the maltotriose ligand in excellent agreement with the experimental data. We also discuss the role of water in blocking unfavorable binding sites and water-mediated interactions contributing to the stability of observable binding modes of maltotriose.

Computational study of the effect of dispersion interactions on the thermochemistry of aggregation of fused polycyclic aromatic hydrocarbons as model asphaltene compounds in solution.

Density functional theory (DFT), Møller-Plesset second-order perturbation theory (MP2), and semiempirical methods are employed for the geometry optimization and thermochemistry analysis of π-π stacked di-, tri-, tetra-, and pentamer aggregates of the fused polycyclic aromatic hydrocarbons (PAHs) naphthalene, anthracene, phenanthrene, tetracene, pyrene, and coronene as well as benzene. These aggregates (stabilized by dispersion interactions) are highly relevant to the intermolecular aggregation of asphaltenes, major components of heavy petroleum. The strength of π-π stacking interaction is evaluated with respect to the π-stacking distance and thermochemistry results, such as aggregation enthalpies, entropies, and Gibbs free energies (ΔG(298)). For both π-stacking interplanar distances and thermochemistry, the ωB97X-D functional with an augmented damped R(-6) dispersion correction term and MP2 are in the closest agreement with the highly accurate spin-component scaled MP2 (SCS-MP2) method that we selected as a reference. The ΔG(298) values indicate that the aggregation of coronene is spontaneous at 298 K and the formation of pyrene dimers occurs spontaneously at temperature lower than 250 K. Aggregates of smaller PAHs would be stable at even lower temperature. These findings are supported by X-ray crystallographic determination results showing that among the PAHs studied only coronene forms continuous stacked aggregates in single crystals, pyrene forms dimers, and smaller PAHs do not form π-π stacked aggregates. Thermochemistry analysis results show that PAHs containing more than four fused benzene rings would spontaneously form aggregates at 298 K. Also, round-shaped PAHs, such as phenanthrene and pyrene, form more stable aggregates than linear PAHs, such as anthracene and tetracene, due to decreased entropic penalty. These results are intended to help guide the synthesis of model asphaltene compounds for spectroscopic studies so as to help understand the aggregation behavior of heavy petroleum.

Plant biomass recalcitrance: effect of hemicellulose composition on nanoscale forces that control cell wall strength.

Efficient conversion of lignocellulosic biomass to second-generation biofuels and valuable chemicals requires decomposition of resilient plant cell wall structure. Cell wall recalcitrance varies among plant species and even phenotypes, depending on the chemical composition of the noncellulosic matrix. Changing the amount and composition of branches attached to the hemicellulose backbone can significantly alter the cell wall strength and microstructure. We address the effect of hemicellulose composition on primary cell wall assembly forces by using the 3D-RISM-KH molecular theory of solvation, which provides statistical-mechanical sampling and molecular picture of hemicellulose arrangement around cellulose. We show that hemicellulose branches of arabinose, glucuronic acid, and especially glucuronate strengthen the primary cell wall by strongly coordinating to hydrogen bond donor sites on the cellulose surface. We reveal molecular forces maintaining the cell wall structure and provide directions for genetic modulation of plants and pretreatment design to render biomass more amenable to processing.

Multi-scale modeling and synthesis of polyester ionomers.

Simulations of microphase separation are carried out using the dissipative particle dynamics (DPD). By varying the concentration and temperature of resin solutions we explore mesomorphologies supported by the all-atom models. We found that for a low degree of functionalization the homogeneously distributed ionomers self-assemble into spherical micelles at solid loads below 31 wt%, subject to the activation energy barrier for the gradual growth of pre-micellar aggregates. Computed optimum aggregation numbers exhibit sensitivity to both the temperature-dependent interfacial tension and the ionic content and compare well with the experimental observations.

Multiple time step molecular dynamics in the optimized isokinetic ensemble steered with the molecular theory of solvation: accelerating with advanced extrapolation of effective solvation forces.

We develop efficient handling of solvation forces in the multiscale method of multiple time step molecular dynamics (MTS-MD) of a biomolecule steered by the solvation free energy (effective solvation forces) obtained from the 3D-RISM-KH molecular theory of solvation (three-dimensional reference interaction site model complemented with the Kovalenko-Hirata closure approximation). To reduce the computational expenses, we calculate the effective solvation forces acting on the biomolecule by using advanced solvation force extrapolation (ASFE) at inner time steps while converging the 3D-RISM-KH integral equations only at large outer time steps. The idea of ASFE consists in developing a discrete non-Eckart rotational transformation of atomic coordinates that minimizes the distances between the atomic positions of the biomolecule at different time moments. The effective solvation forces for the biomolecule in a current conformation at an inner time step are then extrapolated in the transformed subspace of those at outer time steps by using a modified least square fit approach applied to a relatively small number of the best force-coordinate pairs. The latter are selected from an extended set collecting the effective solvation forces obtained from 3D-RISM-KH at outer time steps over a broad time interval. The MTS-MD integration with effective solvation forces obtained by converging 3D-RISM-KH at outer time steps and applying ASFE at inner time steps is stabilized by employing the optimized isokinetic Nosé-Hoover chain (OIN) ensemble. Compared to the previous extrapolation schemes used in combination with the Langevin thermostat, the ASFE approach substantially improves the accuracy of evaluation of effective solvation forces and in combination with the OIN thermostat enables a dramatic increase of outer time steps. We demonstrate on a fully flexible model of alanine dipeptide in aqueous solution that the MTS-MD/OIN/ASFE/3D-RISM-KH multiscale method of molecular dynamics steered by effective solvation forces allows huge outer time steps up to tens of picoseconds without affecting the equilibrium and conformational properties, and thus provides a 100- to 500-fold effective speedup in comparison to conventional MD with explicit solvent. With the statistical-mechanical 3D-RISM-KH account for effective solvation forces, the method provides efficient sampling of biomolecular processes with slow and/or rare solvation events such as conformational transitions of hydrated alanine dipeptide with the mean life times ranging from 30 ps up to 10 ns for "flip-flop" conformations, and is particularly beneficial for biomolecular systems with exchange and localization of solvent and ions, ligand binding, and molecular recognition.