Three-dimensional Reference Interaction Site Model Research Articles

Prediction of Ca2+ Binding Site in Proteins With a Fast and Accurate Method Based on Statistical Mechanics and Analysis of Crystal Structures.

Predicting the precise locations of metal binding sites within metalloproteins is a crucial challenge in biophysics. A fast, accurate, and interpretable computational prediction method can complement the experimental studies. In the current work, we have developed a method to predict the location of Ca2+ ions in calcium-binding proteins using a physics-based method with an all-atom description of the proteins, which is substantially faster than the molecular dynamics simulation-based methods with accuracy as good as data-driven approaches. Our methodology uses the three-dimensional reference interaction site model (3D-RISM), a statistical mechanical theory, to calculate Ca2+ ion density around protein structures, and the locations of the Ca2+ ions are obtained from the density. We have taken previously used datasets to assess the efficacy of our method as compared to previous works. Our accuracy is 88%, comparable with the FEATURE program, one of the well-known data-driven methods. Moreover, our method is physical, and the reasons for failures can be ascertained in most cases. We have thoroughly examined the failed cases using different structural and crystallographic measures, such as B-factor, R-factor, electron density map, and geometry at the binding site. It has been found that x-ray structures have issues in many of the failed cases, such as geometric irregularities and dubious assignment of ion positions. Our algorithm, along with the checks for structural accuracy, is a major step in predicting calcium ion positions in metalloproteins.

The Three-Dimensional Reference Interaction Site Model Approach as a Promising Tool for Studying Hydrated Viruses and Their Complexes with Ligands.

Viruses are the most numerous biological form living in any ecosystem. Viral diseases affect not only people but also representatives of fauna and flora. The latest pandemic has shown how important it is for the scientific community to respond quickly to the challenge, including critically assessing the viral threat and developing appropriate measures to counter this threat. Scientists around the world are making enormous efforts to solve these problems. In silico methods, which allow quite rapid obtention of, in many cases, accurate information in this field, are effective tools for the description of various aspects of virus activity, including virus-host cell interactions, and, thus, can provide a molecular insight into the mechanism of virus functioning. The three-dimensional reference interaction site model (3D-RISM) seems to be one of the most effective and inexpensive methods to compute hydrated viruses, since the method allows us to provide efficient calculations of hydrated viruses, remaining all molecular details of the liquid environment and virus structure. The pandemic challenge has resulted in a fast increase in the number of 3D-RISM calculations devoted to hydrated viruses. To provide readers with a summary of this literature, we present a systematic overview of the 3D-RISM calculations, covering the period since 2010. We discuss various biophysical aspects of the 3D-RISM results and demonstrate capabilities, limitations, achievements, and prospects of the method using examples of viruses such as influenza, hepatitis, and SARS-CoV-2 viruses.

Effect of caffeine on the aggregation of amyloid-β-A 3D RISM study.

Alzheimer's disease is a detrimental neurological disorder caused by the formation of amyloid fibrils due to the aggregation of amyloid-β peptide. The primary therapeutic approaches for treating Alzheimer's disease are targeted to prevent this amyloid fibril formation using potential inhibitor molecules. The discovery of such inhibitor molecules poses a formidable challenge to the design of anti-amyloid drugs. This study investigates the effect of caffeine on dimer formation of the full-length amyloid-β using a combined approach of all-atom, explicit water molecular dynamics simulations and the three-dimensional reference interaction site model theory. The change in the hydration free energy of amyloid-β dimer, with and without the inhibitor molecules, is calculated with respect to the monomeric amyloid-β, where the hydration free energy is decomposed into energetic and entropic components, respectively. Dimerization is accompanied by a positive change in the partial molar volume. Dimer formation is spontaneous, which implies a decrease in the hydration free energy. However, a reverse trend is observed for the dimer with inhibitor molecules. It is observed that the negatively charged residues primarily contribute for the formation of the amyloid-β dimer. A residue-wise decomposition reveals that hydration/dehydration of the side-chain atoms of the charged amino acid residues primarily contribute to dimerization.

Solvent Distribution Effects on Quantum Chemical Calculations with Quantum Computers.

We present a combination of three-dimensional reference interaction site model self-consistent field (3D-RISM-SCF) theory and the variational quantum eigensolver (VQE) to consider the solvent distribution effects within the framework of quantum-classical hybrid computing. The present method, 3D-RISM-VQE, does not include any statistical errors from the solvent configuration sampling owing to the analytical treatment of the statistical solvent distribution. We apply 3D-RISM-VQE to compute the spatial distribution functions of solvent water around a water molecule, the potential and Helmholtz energy curves of NaCl, and to analyze the Helmholtz energy component and related properties of H2O and NH4+. Moreover, we utilize 3D-RISM-VQE to analyze the extent to which solvent effects alter the efficiency of quantum calculations compared with calculations in the gas phase using the L1-norms of molecular electronic Hamiltonians. Our results demonstrate that the efficiency of quantum chemical calculations on a quantum computer in solution is virtually the same as that in the gas phase.

Assessment of the applicability of the LFC/3D-RISM-SCF scheme for pKa prediction in methanol solutions

Abstract The applicability of the linear fitting correction with the three-dimensional reference interaction-site model self-consistent field (LFC/3D-RISM-SCF) scheme, a pKa prediction scheme, for methanol solutions was investigated. The correlation between experimental and predicted pKa values of dissociative molecules with phenol, amine, and carboxyl derivatives was examined. The pKa values of the LFC/3D-RISM-SCF results showed a good linear correlation with the experimental pKa. This result demonstrates that the LFC/3D-RISM-SCF method can be applied to a variety of solvents other than water.

Computational Analysis of Excited-State Properties of MoS2 Nanosheet Modified with a Pyrene Derivative

MoS2, a representative transition metal dichalcogenides (TMD), is known to undergo the hydrogen evolution reaction in the exfoliated state, and its use as an auxiliary catalyst in place of platinum has been widely reported. Recently, the exfoliation of bulk MoS2 and efficient covalent modification of MoS2 nanosheets with N-bromobenzylmaleimide was successfully achieved using a planetary ball mill. For the photofunctionalization of MoS2, further coupling reaction with a pyrene derivative produced pyrene-benzyl-maleimide-MoS2 (Py-Bn-Mal-MoS2) nanosheet. The absorption spectrum of Py-Bn-Mal-MoS2 shows peaks similar to that of 1-phenylpyrene. On the other hand, the emission spectrum of Py-Bn-Mal-MoS2 is much different from that of 1-phenylpyrene. Furthermore, the emission peak of Py-Bn-Mal-MoS2 is more redshifted with increasing solvent polarity. However, the detailed mechanism is unclear. In this study, we investigated the excited-state properties of Py-Bn-Mal-MoS2 with theoretical methods. First, we constructed model systems of Py-Bn-Mal-MoS2 nanosheet and performed time-dependent density functional theory (TDDFT) calculations. The calculated molecular orbitals and dipole moment changes demonstrated that the emission is a charge transfer transition from the pyrene moiety to MoS2 nanosheet. Next, we performed three-dimensional reference interaction site model (3D-RISM) calculations, which is based on the integral equation theory of molecular liquids, to assess the solvent dependence of emission energies. The calculated results reproduced the experimental solvent dependence well. The distributions of polar solvent molecules showed strong interaction between the excited state of Py-Bn-Mal-MoS2 and solvent molecules. This study supports the potential of covalent modification of MoS2 for photocatalytic applications.

Selective molecular recognition of amino acids and their derivatives by cucurbiturils in aqueous solution: An MD/3D-RISM study

The three-dimensional reference interaction site model theory was utilized to investigate cucurbituril–guest binding and its corresponding solvation structure. In this study, glycine, tryptophan, phenylalanine and their derivatives were employed as representatives of guest molecules. In the case of aromatic amino acids, phenylalanine shows the most significant binding affinity in cucurbit-7-uril, whereas tryptophan provides the highest binding affinity in cucurbit-8-uril. Although these guest molecules are very similar in molecular volumes, their chemical and physical properties are different. These findings agree well with reports from previous studies. We also found that the substitution of the tert-butyl (–C(CH3)3) group at the para-position in phenylalanine provides the highest binding affinity gain among all derivatives. Moreover, the unbound state of glycine is pointed out.

A method for protein structure sampling under three-dimensional reference interaction site model solvation based on hybrid Monte Carlo framework

An efficient sampling method for protein structure using molecular dynamics (MD) simulation and a three-dimensional reference interaction-site model (3D-RISM) theory has been developed based on the hybrid Monte Carlo framework. In this method, new structures are generated by MD simulation with the generalized Born implicit solvent model and the Metropolis-like criterion to accept or reject the structure candidate is applied based on the free energy corresponding to the 3D-RISM Hamiltonian at each specified time propagation interval. The resulting ensemble of structures satisfies the 3D-RISM Hamiltonian-based equilibrium distribution. The method was applied to alanine dipeptide and methionine-enkephalin polypeptides in aqueous solution as test cases. The results demonstrated the efficiency of the method.

Molecular insight on hydration of protein tyrosine phosphatase 1B and its complexes with ligands

Knowledge of hydration and the role of solvent in protein–ligand (P-L) binding is essential for rational drug design. In this direction, a complete description of P-L binding requires a clear understanding of the change in protein and ligand hydration states when they form a complex. In the present work, we investigated the 3D-hydration of protein tyrosine phosphatase 1B (PTP1B) in the unbound and bound states and changes in this process occurring upon the complex formation with 2HB1 and 2QBP inhibitors as an example. To this end, we have used a simplified version of the site density functional theory - the three-dimensional reference interaction site model. The obtained data indicate that both the ligands and PTP1B in unbound state are well-hydrated. Upon complex formation, the ligands experience significant dehydration, while the level of PTP1B hydration changes little. Moreover, the hydrated state of P-L complex remains practically the same as for liganded PTP1B itself. In this case, some of the waters are partly “collectivized” by the protein and the ligand, i.e., solvent molecules will be shared by PTP1B and 2HB1/2QBP. The active site pocket of the protein was also found to be well-hydrated. P–L binding results in partial dehydration of the pocket, which is connected with the displacement of part of the water from the pocket by the ligand. The results show the presence of two/seven waters inside the pocket for PTP1B-2HB1/2QBP. Location of the most tightly bound two/three waters in the PTP1B-2HB1/2QBP complex is coinsiding with the PDB data. Among tightly bound waters, only two molecules are “bridging” ones, i.e., forming simultaneously H-bonds with pocket residues and ligands. In addition, all possible H-bonds between the ligand, pocket amino acid residues and water are discussed for both complexes. The data obtained are necessary for understanding the molecular mechanisms of the PTP1B functioning and the creation of selective regulators of its activity.

Theoretical Analysis of the Role of Water in Ligand Binding to Cucurbit[n]uril of Different Sizes.

The role of water in host-ligand binding was investigated using a combination of molecular dynamics simulation and three-dimensional reference interaction site model theory. Three different hosts were selected (CB6, CB7, and CB8). Six organic molecules were used as representative ligands: dimethyl sulfoxide (DMSO), N,N-dimethylformamide (DMF), acetone, 2,3-diazabicyclo[2.2.2]oct-2-ene (DBO), cyclopentanone (CPN), and pyrrole. From the binding free energy and its components, we divided the ligands into two groups: those with relatively small molecular size (DMSO, DMF, acetone, and pyrrole) and those with relatively large molecular size (DBO and CPN). We established that the solvent water in the CB6 cavity can be completely displaced by small ligands, resulting in a greater binding affinity compared with larger CBs, except in the case of the small pyrrole ligand, due to outstanding intrinsic properties such as the relatively high hydrophobicity and low dipole moment. In the case of the large ligands, the solvent water can be displaced by DBO and CPN in both CB6 and CB7; there were similar tendencies in their binding affinities, with the greatest affinity in the CB7 complexes. However, the tendencies of the binding affinity components are completely different due to the difference between the complex structure and the solvation structure when a ligand binds with a CB structure. The binding affinities suggest that the size fit between the ligand and CB cannot guarantee the greatest binding affinity gain because the binding structure and intrinsic properties of CB and ligand equally play a crucial role.

Aggregation propensities of proteins with varying degrees of disorder.

The hydration thermodynamics of a globular protein (AcP), three intrinsically disordered protein regions (1CD3, 1MVF, 1F0R) and a fully disordered protein (α-synuclein) is studied by an approach that combines an all-atom explicit water molecular dynamics simulations and three-dimensional reference interaction site model (3D-RISM) theory. The variation in hydration free energy with percentage disorder of the selected proteins is investigated through its nonelectrostatic and electrostatic components. A decrease in hydration free energy is observed with an increase in percentage disorder, indicating favorable interactions of the disordered proteins with the solvent. This confirms the role of percentage disorder in determining the aggregation propensity of proteins which is measured in terms of the hydration free energy in addition to their respective mean net charge and mean hydrophobicity. The hydration free energy is decoupled into energetic and entropic terms. A residue-wise decomposition analysis of the hydration free energy for the selected proteins is evaluated. The decomposition shows that the disordered regions contribute more than the ordered ones for the intrinsically disordered protein regions. The dominant role of electrostatic interactions is confirmed from the residue-wise decomposition of the hydration free energy. The results depict that the negatively charged residues contribute more to the total hydration free energy for the proteins with negative mean net charge, while the positively charged residues contribute more for proteins with positive mean net charge.

Protein 3D Hydration: A Case of Bovine Pancreatic Trypsin Inhibitor

Characterization of the hydrated state of a protein is crucial for understanding its structural stability and function. In the present study, we have investigated the 3D hydration structure of the protein BPTI (bovine pancreatic trypsin inhibitor) by molecular dynamics (MD) and the integral equation method in the three-dimensional reference interaction site model (3D-RISM) approach. Both methods have found a well-defined hydration layer around the protein and revealed the localization of BPTI buried water molecules corresponding to the X-ray crystallography data. Moreover, under 3D-RISM calculations, the obtained positions of waters bound firmly to the BPTI sites are in reasonable agreement with the experimental results mentioned above for the BPTI crystal form. The analysis of the 3D hydration structure (thickness of hydration shell and hydration numbers) was performed for the entire protein and its polar and non-polar parts using various cut-off distances taken from the literature as well as by a straightforward procedure proposed here for determining the thickness of the hydration layer. Using the thickness of the hydration shell from this procedure allows for calculating the total hydration number of biomolecules properly under both methods. Following this approach, we have obtained the thickness of the BPTI hydration layer of 3.6 Å with 369 water molecules in the case of MD simulation and 3.9 Å with 333 water molecules in the case of the 3D-RISM approach. The above procedure was also applied for a more detailed description of the BPTI hydration structure near the polar charged and uncharged radicals as well as non-polar radicals. The results presented for the BPTI as an example bring new knowledge to the understanding of protein hydration.

Molecular simulations of liquid aliphatic carboxylic acids (C1-C6) using the 3D-RISM-KH molecular solvation theory

The liquid structures of short straight chain aliphatic carboxylic acids (C1-C6) and halogenated acetic acids (trifluoro and trichloro) are analyzed with molecular dynamics simulations, three-dimensional reference interaction site model, and density functional theory calculations. The neat acids are found to exist in multimeric ordered form consisting of both open chain and cyclic oligomers. Introduction of water breaks the hydrogen bonding networks between adjacent acetic acid molecules by inserting water as a bridging molecule. The electronic structure calculations confirm the formation of chain and ring type structures in the liquid state.

Gr Predictor: A Deep Learning Model for Predicting the Hydration Structures around Proteins.

Among the factors affecting biological processes such as protein folding and ligand binding, hydration, which is represented by a three-dimensional water site distribution function around the protein, is crucial. The typical methods for computing the distribution functions, including molecular dynamics simulations and the three-dimensional reference interaction site model (3D-RISM) theory, require a long computation time ranging from hours to tens of hours. Here, we propose a deep learning (DL) model that rapidly estimates the distribution functions around proteins obtained using the 3D-RISM theory from the protein 3D structure. The distribution functions predicted using our DL model are in good agreement with those obtained using the 3D-RISM theory. Particularly, the coefficient of determination between the distribution function obtained by the DL model and that obtained using the 3D-RISM theory is approximately 0.98. Furthermore, using a graphics processing unit, the prediction by the DL model is completed in less than 1 min, more than 2 orders of magnitude faster than the calculation time of the 3D-RISM theory. The position of water molecules around the protein was estimated based on the distribution function obtained by our DL model, and the position of waters estimated by our DL model was in good agreement with that of water molecules estimated using the 3D-RISM theory and of crystallographic waters. Therefore, our DL model provides a practical and efficient way to calculate the three-dimensional water site distribution functions and to estimate the position of water molecules around the protein. The program called "gr Predictor" is available under the GNU General Public License from https://github.com/YoshidomeGroup-Hydration/gr-predictor.

Theoretical Analysis on the Stability of 1-Pyrenebutanoic Acid Succinimidyl Ester Adsorbed on Graphene.

The adsorbed structure of 1-pyrenebutanoic acid succinimidyl ester (PASE) on graphene was investigated based on density functional theory. We found two locally stable structures: a straight structure with the chainlike part of butanoic acid succinimidyl ester (BSE) lying down and a bent structure with the BSE part directed away from graphene, keeping the pyrene (Py) part adsorbed on graphene. Then, to elucidate the adsorption mechanism, we separately estimated the contributions of the Py and BSE parts to the entire PASE adsorption, and the adsorption effect of the BSE part was found to be secondary in comparison to the contribution of the Py. Next, the mobility of the BSE part at room temperature was confirmed by the activation energy barrier between straight and bent structures. To take account of the external environment, we considered the presence of amino acids and the hydration effect by a three-dimensional reference interaction site model. The contributions of glycine molecules and the solvent environment to stabilizing the bent PASE structure relative to the straight PASE structure were found. Therefore, the effect of the external environment around PASE is of importance when the standing-up process of the BSE part from graphene is considered.

Free Energy and Solvation Structure Analysis for Adsorption of Aromatic Molecules at Pt(111)/Water Interface by 3D-RISM Theory

Abstract The free energy change of aromatic molecules adsorbed at a Pt(111)/water interface was analyzed using the three-dimensional reference interaction site model (3D-RISM) theory with density functional theory (DFT), compared with the reported experimental data. The changes in the solvation structure induced by molecular adsorption were discussed.

Reaction Entropies in Solution from Analytical Three-Dimensional Reference Interaction Site Model Derivatives with Application to Redox and Spin-Crossover Processes.

An analytical approach to compute the excess entropy of solvation at constant pressure in three-dimensional reference interaction site model (3D-RISM) calculations is presented. It includes the changes in the macroscopic dielectric constant of the solvent upon variation of temperature and density. The approach is exact within the framework of force-field descriptions of the solute and gives reasonable results for self-consistently determined electrostatics as used in the 3D-RISM-self-consistent field approach, particularly for entropy differences. The new method is applied to simple examples of reaction entropies of iron complexes in aqueous solution, for which simple gas-phase calculations and many other approaches give unreliable estimates. For both redox half-reactions and spin-crossover processes, (semi)quantitative agreement with experimental reaction entropies can be achieved out of the box.

Computational Analysis of the SARS-CoV-2 RBD-ACE2-Binding Process Based on MD and the 3D-RISM Theory.

The binding process of angiotensin-converting enzyme 2 (ACE2) to the receptor-binding domain (RBD) of the severe acute respiratory syndrome-like coronavirus 2 spike protein was investigated using molecular dynamics simulation and the three-dimensional reference interaction-site model theory. The results suggested that the protein-binding process consists of a protein–protein approaching step, followed by a local structural rearrangement step. In the approaching step, the interprotein interaction energy decreased as the proteins approached each other, whereas the solvation free energy increased. As the proteins approached, the glycan of ACE2 first established a hydrogen bond with the RBD. Thereafter, the number of interprotein hydrogen bonds increased rapidly. The solvation free energy increased because of the desolvation of the protein as it approached its partner. The spatial distribution function of the solvent revealed the presence of hydrogen bonds bridged by water molecules on the RBD–ACE2 interface. Finally, principal component analysis revealed that ACE2 showed a pronounced conformational change, whereas there was no significant change in RBD.

Implementation of solvent polarization in three-dimensional reference interaction-site model self-consistent field theory

The three-dimensional reference interaction-site model self-consistent field (3D-RISM-SCF) theory is an electronic structure theory of solvated molecules, which can handle the electronic polarization of the solute molecule induced by the interaction with the solvent, whereas the electronic polarization of solvent molecules is ignored. Here, the solvent-polarizable model is implemented to take into account the electronic polarization of solvent molecules. It is applied to the water molecule in an aqueous solution and the p-nitroaniline molecule in an aqueous solution, and the effects of the solvent polarization on the properties of these solutes are demonstrated.

Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex.

The entry of the SARS-CoV-2, a causative agent of COVID-19, into human host cells is mediated by the SARS-CoV-2 spike (S) glycoprotein, which critically depends on the formation of complexes involving the spike protein receptor-binding domain (RBD) and the human cellular membrane receptor angiotensin-converting enzyme 2 (hACE2). Using classical site density functional theory (SDFT) and structural bioinformatics methods, we investigate binding and conformational properties of these complexes and study the overlooked role of water-mediated interactions. Analysis of the three-dimensional reference interaction site model (3DRISM) of SDFT indicates that water mediated interactions in the form of additional water bridges strongly increases the binding between SARS-CoV-2 spike protein and hACE2 compared to SARS-CoV-1-hACE2 complex. By analyzing structures of SARS-CoV-2 and SARS-CoV-1, we find that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) has expanded in size, indicating large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits stronger intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction causes a significant structural rigidification of the spike protein, favoring proteolytic processing of the S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification of the RBD dynamics and their impact on infectivity.