Side-chain Modeling Research Articles

Interaction potential for coarse-grained models of bottlebrush polymers

Bottlebrush polymers are a class of highly branched macromolecules that show promise for applications such as self-assembled photonic materials and tunable elastomers. However, computational studies of bottlebrush polymer solutions and melts remain challenging due to the high computational cost involved in explicitly accounting for the presence of side chains. Here, we consider a coarse-grained molecular model of bottlebrush polymers where the side chains are modeled implicitly, with the aim of expediting simulations by accessing longer length and time scales. The key ingredients of this model are the size of a coarse-grained segment and a suitably coarse-grained interaction potential between the non-bonded segments. Prior studies have not focused on developing explicit forms of such potentials, instead, relying on scaling arguments to model non-bonded interactions. Here, we show how to systematically calculate an interaction potential between the coarse-grained segments of bottlebrush from finer grained explicit side chain models using Monte Carlo and Brownian dynamics and then incorporate it into an implicit side chain model. We compare the predictions from our coarse-grained implicit side chain model with those obtained from models with explicit side chains in terms of the potential of mean force, the osmotic second virial coefficient, and the interpenetration function, highlighting the range of applicability and limitations of the coarse-grained representation. Although presented in the context of homopolymer bottlebrushes in athermal solvents, our proposed method can be extended to other solvent conditions as well as to different monomer chemistries. We expect that our implicit side chain model will prove useful for accelerating large-scale simulations of bottlebrush solutions and assembly.

OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.

Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer library, which may have limitations on their accuracies and usages. In this study, we report an open-source toolkit for protein side-chain modeling, named OPUS-Rota4. It consists of three modules: OPUS-RotaNN2, which predicts protein side-chain dihedral angles; OPUS-RotaCM, which measures the distance and orientation information between the side chain of different residue pairs and OPUS-Fold2, which applies the constraints derived from the first two modules to guide side-chain modeling. OPUS-Rota4 adopts the dihedral angles predicted by OPUS-RotaNN2 as its initial states, and uses OPUS-Fold2 to refine the side-chain conformation with the side-chain contact map constraints derived from OPUS-RotaCM. Therefore, we convert the side-chain modeling problem into a side-chain contact map prediction problem. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to include other differentiable energy terms. OPUS-Rota4 also provides a platform in which the side-chain conformation can be dynamically adjusted under the influence of other processes. We apply OPUS-Rota4 on 15 FM predictions submitted by AlphaFold2 on CASP14, the results show that the side chains modeled by OPUS-Rota4 are closer to their native counterparts than those predicted by AlphaFold2 (e.g. the residue-wise RMSD for all residues and core residues are 0.588 and 0.472 for AlphaFold2, and 0.535 and 0.407 for OPUS-Rota4).

Reaction of dirhodium and diruthenium paddlewheel tetraacetate complexes with nucleophilic protein sites: A computational study

The biomolecular affinity of three paddlewheel dinuclear complexes Rh2(µ-O2CCH3)4(H2O)2, Ru2(µ-O2CCH3)4(H2O)Cl, [Ru2(µ-O2CCH3)4(H2O)2]+ for the binding at cancer-specific protein targets was determined by means of DFT approaches. Thermodynamics of axial ligand substitution reaction by models of suitable protein sites was investigated in order to assess the binding selectivity displayed by the paddlewheel complexes. Both Rh2(µ-O2CCH3)4(H2O)2 and Ru2(µ-O2CCH3)4(H2O)Cl resulted to react favorably with most of the examined models of the protein side chains, with higher exergodicity demonstrated in the reaction of Arg, Cys, His, Lys, Sec, thus showing a limited selectivity. On the other hand, we identified Sec and His as the most suitable targets of the examined paddlewheel complexes, while Arg and Lys are expected to be also targetable at higher pH. Therefore, our calculations showed how both dirhodium and, majorly, diruthenium examined complexes undergo to a certain degree of destabilization upon the binding at nucleophilic protein sites. The presented computational results allowed us to shed light onto the protein sites’ affinity and on the therapeutic potential of both Rh2(µ-O2CCH3)4(H2O)2 and Ru2(µ-O2CCH3)4(H2O)Cl, and provided for a structural basis for the development of newly designed paddlewheel complexes.

Inferring metal binding sites in flexible regions of proteins.

Metal ions are central to the molecular function of many proteins. Thus their knowledge in experimentally determined structure is important; however, such structures often lose bound metal ions during sample preparation. Identification of these metal-binding site(s) becomes difficult when the receptor is novel and/or their conformations differ in the bound/unbound states. Locating such sites in theoretical models also poses a challenge due to the uncertainties with side-chain modeling. We address the problem by employing the Geometric Hashing algorithm to create a template library of functionally important binding sites and match query structures with the available templates. The matching is done on the structure ensemble obtained from coarse-grained molecular dynamics simulation, where metal-specific amino acids are screened to infer the true site. Test on 1347 non-redundant monomer protein structures show that Ca2+ , Zn2+ , Mg2+ , Cu2+ , and Fe3+ binding site residues can be classified at 0.92, 0.95, 0.80, 0.90, and 0.92 aggregate performance (out of 1) across all possible thresholds. The performance for Ca2+ and Zn2+ is notably superior in comparison to state-of-the-art methods like IonCom and MIB. Specific case studies show that additionally predicted metal-binding site residues in proteins have features necessary for ion binding. These include new sites not predicted by other methods. The use of coarse-grained dynamics thus provides a generalized approach to improve metal-binding site prediction. The work is expected to contribute to improving our ability to correctly predict protein molecular function where knowledge of metal binding is a key requirement.

Implicit Side-Chain Model and Experimental Characterization of Bottlebrush Block Copolymer Solution Assembly

Bottlebrush polymers are a class of macromolecules with linear backbones and densely grafted side chains, possessing unique physical properties due to strong steric interactions between the side ch...

ProMod3-A versatile homology modelling toolbox.

Computational methods for protein structure modelling are routinely used to complement experimental structure determination, thus they help to address a broad spectrum of scientific questions in biomedical research. The most accurate methods today are based on homology modelling, i.e. detecting a homologue to the desired target sequence that can be used as a template for modelling. Here we present a versatile open source homology modelling toolbox as foundation for flexible and computationally efficient modelling workflows. ProMod3 is a fully scriptable software platform that can perform all steps required to generate a protein model by homology. Its modular design aims at fast prototyping of novel algorithms and implementing flexible modelling pipelines. Common modelling tasks, such as loop modelling, sidechain modelling or generating a full protein model by homology, are provided as production ready pipelines, forming the starting point for own developments and enhancements. ProMod3 is the central software component of the widely used SWISS-MODEL web-server.

OPUS-Rota3: Improving Protein Side-Chain Modeling by Deep Neural Networks and Ensemble Methods.

Side-chain modeling is critical for protein structure prediction since the uniqueness of the protein structure is largely determined by its side-chain packing conformation. In this paper, differing from most approaches that rely on rotamer library sampling, we first propose a novel side-chain rotamer prediction method based on deep neural networks, named OPUS-RotaNN. Then, on the basis of our previous work OPUS-Rota2, we propose an open-source side-chain modeling framework, OPUS-Rota3, which integrates the results of different methods into its rotamer library as the sampling candidates. By including OPUS-RotaNN into OPUS-Rota3, we conduct our experiments on three native backbone test sets and one non-native backbone test set. On the native backbone test set, CAMEO-Hard61 for example, OPUS-Rota3 successfully predicts 51.14% of all side-chain dihedral angles with a tolerance criterion of 20° and outperforms OSCAR-star (50.87%), SCWRL4 (50.40%), and FASPR (49.85%). On the non-native backbone test set DB379-ITASSER, the accuracy of OPUS-Rota3 is 52.49%, better than OSCAR-star (48.95%), FASPR (48.69%), and SCWRL4 (48.29%). All the source codes including the training codes and the data we used are available at https://github.com/thuxugang/opus_rota3.

Experimental and Theoretical Investigation of Intrinsic Pyridine Isomer Effects on Physical Property Tuning of Metallo Supramolecular Polymers Bearing Multiple Pyridine Ligands

Coordinative polymers have gained great attention over the last two decades because of the potential versatile modification and functionalization of their physical properties. The pyridine isomer effects on metallo-supramolecular materials, where metal salts are blended with the polymers bearing pyridine coordinative ligands, have been frequently argued based only on steric effects. Here the pyridine isomer effects are investigated by both experimental and computational approaches. In the experimental approach, ZnCl2 was blended with amorphous polyesters uniformly bearing either 4-vinylpyridine (4VP)- or 2-vinylpyridine (2VP)-type ligands at the side groups. In addition, a polyester bearing both ligand types was also used to prepare blends with ZnCl2, which enabled deeper understanding of the pyridine isomer effects on the pyridine–metal coordination. Experimental characterizations by Fourier transform infrared spectroscropy, differential scanning calorimetry, and rheological measurements first revealed that the coordination of ZnCl2 occurs more predominantly on 4VP ligands. Such pyridine isomer effects on the coordination are further investigated by density functional theory computation for complexes of ZnCl2 with side chain models of 4VP or 2VP. On the basis of the obtained complex structures and stabilities, ZnCl2-complexation with two 4VP units was energetically more favored than for those with two 2VP units or 4VP/2VP mixtures. The coordination preference of the 4VP to ZnCl2 was also confirmed by the stabilization of the interaction between the natural bond orbitals of the Zn-pyridyl N pair. Therefore, the theoretical approach can be applied to demonstrate the experimentally found unique isomeric effects of pyridine on metallo-supramolecular matrix, which will bring important insights into the practical application of coordinative polymers.

Reactions of cisplatin and cis-[PtI2(NH3)2] with molecular models of relevant protein sidechains: A comparative analysis

Quite surprisingly, cisplatin and cis-[PtI2(NH3)2] were found to manifest significant differences in their reactions with the model protein lysozyme. We decided to explore whether these differences recur when reacting these two Pt compounds with other proteins. Notably, ESI-MS measurements carried out on cytochrome c nicely confirmed the reaction pattern observed for lysozyme. This prompted us to exploit a computational DFT approach to disclose the molecular basis of such behavior. We analyzed comparatively the reactions of cis-[PtCl2(NH3)2] and cis-[PtI2(NH3)2] with appropriate molecular models (Ls) of the sidechains of relevant aminoacids. We found that when Pt(II) complexes are reacted with sulfur ligands both quickly lose their halide ligands and then the resulting cis-[Pt(L)2(NH3)2] species loses ammonia upon reaction with a ligand excess. In the case of imidazole, again cis-[PtCl2(NH3)2] and cis-[PtI2(NH3)2] quickly lose their halide ligands but the resulting cis-[Pt(L)2(NH3)2] species does not lose ammonia by reaction with excess imidazole. These results imply that the two platinum complexes manifest a significantly different behavior in their reaction with representative small molecules in agreement with what observed in the case of model proteins. It follows that the protein itself must play a crucial role in triggering the peculiar reactivity of cis-[PtI2(NH3)2] and in governing the nature of the formed protein adducts. The probable reasons for the observed behavior are critically commented and discussed.

Urea-water solvation of protein side chain models

Aqueous urea stabilizes the unfolded states of protein due to their ability to solvate both hydrophilic and hydrophobic residues favorably. The nature of interactions that stabilize different types of amino acid side chains in their solvent exposed state is still not understood. To gain insights into the molecular level details of urea interactions with proteins in their unfolded states, we have performed atomistic molecular dynamics simulations and free energy calculations using the thermodynamic integration method on model systems representing side chains of all amino acids in different solvent environments (water and varying concentrations of aqueous urea). A systematic analysis of structural, energetic and dynamic parameters has been done to understand the detailed atomistic mechanism. The main aim of the current study is to unravel the nature of urea-amino acid interactions by emphasizing on the chemical nature of amino acid side chain models. The preferential interactions of urea over water with each side chain and backbone model systems in various concentrations of aqueous urea were quantified using the two-domain model, and it is validated by mean lifetime calculations. Interestingly, almost all amino acids showed a preference for urea over water. The order of preferences depending on the chemical nature of the amino acids is obtained with the aromatic groups exhibiting the highest preferences followed by hydrophobic groups, followed by amides and basic groups, and the least by nucleophilic groups. The extensive energetic analysis revealed, these preferential interactions are enthalpically and entropically driven and are dominated by dispersion effects. Spatial density distributions and radial distribution analyses provide insights to understand the different modes and urea orientation towards preferred sites of interactions by which urea-protein interactions stabilize proteins in their unfolded states by forming favorable interactions with exposed amino acids side chains.

The impact of wheat (Triticum aestivum L.) bran on wheat starch gelatinization: A differential scanning calorimetry study

The effect of wheat bran on starch gelatinization temperature was investigated. Dynamic water vapour sorption and water retention capacity experiments showed that bran bound up to 3 times more water than starch. However, examining starch gelatinization in starch-bran-water mixtures with differential scanning calorimetry showed that the effect of substituting starch by bran differed from that of moving into a regime of limiting water. Modelling the effect of the mixture composition on starch gelatinization behavior indicated that the onset (To) and peak (Tp) gelatinization temperatures were positively impacted by the bran concentration in water. The conclusion temperature (Tc) was negatively affected by the water content. Fractionation experiments demonstrated that the increased To and Tp were mainly caused by the extractable wheat bran components, such as potassium and phosphorus, which decrease the plasticization capacity of the solvent. The mechanism behind our observations was explained with the side-chain liquid-crystalline polymeric model for starch.

Comparative Modeling, Characterization and Energy Minimization Studies of Aquaporin 9: An Exclusive Target Protein for Rheumatoid Arthritis

Background: In the absence of the experimentally determined structure, computer aided protein structure prediction, evaluation and their energetically stable structure identification is the only way out of the problem. The main objective of the study was to perform the structure prediction of Aquaporin 9 (APQ9) the most targeted protein for rheumatoid arthritis, using in-silico methodology and validate the generated models. Methods: Secondary structure prediction of AQP9 was performed using GOR4, SOPMA and CFSSP algorithm. This was followed by the three-dimensional structure identification from MODELLER, LOMETS and MUSTER server. Many models were built and the best amongst them was identified on the basis of their DOPE score. RAMPAGE was used to validate these models and finally the selected model was energetically stabilized. Results: Amongst the 4 predicted models, model predicted using MODELLER software with 1FX8 PDB template (MODELER MODEL 2) was selected as the best. This model showed the best results in Ramachandran plot validation. In the Ramachandran Plot, 223 residues (95.7%) were found to be in the favored region, 9 residues (3.9%) in the Allowed region and the rest 1 residue (0.4%) in the Outlier region. Energy minimization calculations were also done for the four models using SPBDV software and Modeler Model 2 model showed the least energy (E= 3484.038 KJ/mol). Conclusion: The accurate three-dimensional structure prediction of proteins is a grand challenge now. Massive amount of sequence and structural data is available now with low cost. The choice of one or other method depends solely on the type of protein sequence and the quality of the predicted structure. The accurate structure prediction, fold recognition, energy calculation, side chain modeling and target template identification are the crucial edges of the molecular modeling process which need to be scrutinized for the best predicted model.

Near-Complete Structure and Model of Tel1ATM from Chaetomium thermophilum Reveals a Robust Autoinhibited ATP State

Tel1 (ATM in humans) is a large kinase that resides in the cell in an autoinhibited dimeric state and upon activation orchestrates the cellular response to DNA damage. We report the structure of an endogenous Tel1 dimer from Chaetomium thermophilum. Major parts are at 2.8 Å resolution, including the kinase active site with ATPγS bound, and two different N-terminal solenoid conformations are at 3.4Å and 3.6Å, providing a side-chain model for 90% of the Tel1 polypeptide. We show that the N-terminal solenoid has DNA binding activity, but that its movements are not coupled to kinase activation. Although ATPγS and catalytic residues are poised for catalysis, the kinase resides in an autoinhibited state. The PIKK regulatory domain acts as a pseudo-substrate, blocking direct access to the site of catalysis. The structure allows mapping of human cancer mutations and defines mechanisms of autoinhibition at near-atomic resolution.

Drude polarizable force field for cation-π interactions of alkali and quaternary ammonium ions with aromatic amino acid side chains.

Cation-π interactions play important roles in molecular recognition and in the stability and function of proteins. However, accurate description of the structure and energetics of cation-π interactions presents a challenge to both additive and polarizable force fields, which are rarely designed to account for the complexation of charged groups with aromatic moieties. We calibrate the Drude polarizable force field for complexes of alkali metal ions (Li+ , Na+ , K+ , Rb+ , Cs+ ), ammonium (NH4+ ), tetramethylammonium (TMA+ ), and tetraethylammonium (TEA+ ) with aromatic amino acid side chain model compounds (benzene, toluene, 4-methylphenol, 3-methylindole) using high-level ab initio quantum chemical properties of these complexes. Molecular dynamics simulations reveal that cation-π complexes of the hard and tightly coordinated Li+ and Na+ ions are not stable in water but that larger ions form stable complexes, with binding free energies ranging between -0.8 and -2.9 kcal/mol. Like in gas phase, all complexes at equilibrium adopt an "en-face" complexation mode in water. The optimized Drude polarizable model provides an accurate description of the cation-π interactions involving small ions and proteins. © 2019 Wiley Periodicals, Inc.

OPUS-Rota2: An Improved Fast and Accurate Side-Chain Modeling Method.

Side-chain modeling plays a critical role in protein structure prediction. However, in many current methods, balancing the speed and accuracy is still challenging. In this paper, on the basis of our previous work OPUS-Rota (Protein Sci. 2008, 17, 1576-1585), we introduce a new side-chain modeling method, OPUS-Rota2, which is tested on both a 65-protein test set (DB65) in the OPUS-Rota paper and a 379-protein test set (DB379) in the SCWRL4 paper. If the main chain is native, OPUS-Rota2 is more accurate than OPUS-Rota, SCWRL4, and OSCAR-star but slightly less accurate than OSCAR-o. Also, if the main chain is non-native, OPUS-Rota2 is more accurate than any other method. Moreover, OPUS-Rota2 is significantly faster than any other method, in particular, 2 orders of magnitude faster than OSCAR-o. Thus, the combination of higher accuracy and speed of OPUS-Rota2 in modeling side chains on both the native and non-native main chains makes OPUS-Rota2 a very useful tool in protein structure modeling.

Flexible and modular 3D-printed peptide models.

A flexible and modular peptide modeling set was designed using freely available software tools. The set consists of space-filling models of all 20 naturally occurring amino acid side chains and a modular kit for constructing peptides employing C-alpha carbons and amide bond groups. Connectors that allow free rotation about phi and psi angles on the peptide, together with explicit representation of peptide backbone hydrogen bond donor and acceptors allows for the construction of a wide range of protein secondary structure motifs. The space-filling side chain models highlight the steric, acid-base, and polarity of these groups. These models were printed using relatively affordable commercially available fused filament fabrication printers with minimal postprinting processing. Use of these models in student group activities focused on amino acids and protein secondary structural features is described. © 2019 International Union of Biochemistry and Molecular Biology, 47(4):432-437, 2019.

Gamma radiolysis of perfluorosulfonic acid ionomers and their side chain model compounds in water

Aqueous solutions of perfluorinated sulfonic acid (PFSA) ionomers and their side chain model compounds were irradiated with cobalt-60 gamma rays and their reaction products were analyzed by ion chromatography, liquid chromatography with mass spectrometry, and nuclear magnetic resonance spectroscopy. Radiolytic yields of fluoride and sulfate anions from trifluoromethane sulfonate (TFMS) were very low and attributed to a direct effect. The higher degradation rate of perfluoro-2-ethoxyethane-sulfonate (PFEES) in N2O-saturated samples compared with those under air saturation was attributed to an impurity containing a hydrogen atom. The intrinsic reactivity of PFEES toward hydroxyl was comparable to TFMS. Degradation products retaining the side chain structure were detected after gamma irradiation of long and short side chain PFSA ionomers. Based on the low reactivity of the side chain model compounds and the absence of an N2O saturation effect, dissociative electron attachment likely is responsible for their formation after the direct effect of ionizing radiation on the PFSA ionomers.

Modeling induction phenomena in amino acid cation– $$\pi $$ π interactions

Cation– $$\pi $$ interactions are widely recognized as an important class of interactions, notably in biology and supramolecular chemistry, participating in molecular recognition and association phenomena. Numerical simulations relying on additive force fields perform usually poorly in modeling precisely these interactions. It is now well established that accurate reproduction of the interaction energy of a positively charged group bound to the $$\pi $$ -electron cloud of an aromatic ring requires an explicit treatment of induction effects by means of polarizable potentials. In this contribution, we compare critically the ability of the CHARMM Drude polarizable force field to describe a series of prototypical cation– $$\pi $$ interactions observed in proteins with that of the pairwise additive CHARMM36 force field. Toward this end, potentials of mean force characterizing the binding of amino acid side-chain models, namely ammonium and guanidinium cations, on the one hand, and toluene, para-cresol and 3-methylindole, on the other hand, have been determined within the extended adaptive biasing force framework.

Evaluating the London Dispersion Coefficients of Protein Force Fields Using the Exchange-Hole Dipole Moment Model

London dispersion is one of the fundamental interactions involved in protein folding and dynamics. The popular CHARMM36, Amber ff14sb, and OPLS-AA force fields represent these interactions through the C6/ r6 term of the Lennard-Jones potential, where the C6 parameters are assigned empirically. Here, dispersion coefficients of these three force fields are shown to be roughly 50% larger than values calculated using the quantum mechanically derived exchange-hole dipole moment (XDM) model. The CHARMM36 and Amber OL15 force fields for nucleic acids also exhibit this trend. The hydration energies of the side-chain models were calculated using REMD-TI for the CHARMM36, Amber ff14sb, and OPLS-AA force fields. These force fields predict side-chain hydration energies that are in generally good agreement with the experimental values, which suggests that the total strength of aqueous dispersion interactions is correct, despite C6 coefficients that are considerably larger than XDM predicts. An analytical expression for the dispersion hydration energy using XDM coefficients shows that higher-order dispersion terms (i.e., C8 and C10) account for roughly 37.5% of the hydration energy of methane. This suggests that the C6 dispersion coefficients used in contemporary force fields are elevated to account for the neglected higher-order terms.

Interaction of Tyrosine Analogues with Quaternary Ammonium Head Groups at the Micelle/Water Interface and Contrasting Effect of Molecular Folding on the Hydrophobic Outcome and End-Cap Geometry.

The surface property of the cationic micelles of cetyltrimethylammonium bromide (CTAB) in an aqueous medium is highly modified in the presence of tyrosineoctyl ester (TYOE) and tyrosinedodecyl ester (TYDE), the models for aromatic amino acid side chains of transmembrane proteins. While the synergistic interaction between the quaternary ammonium head group of CTAB and the π-electron cloud of aromatic amino acid ester is influenced by the relative orientation and the unusual molecular geometry of the latter, this eventually triggers a morphology transition of the spherical micelle to cylindrical/wormlike micelles and imparts a strong viscoelasticity in the medium. Physical characteristics of the elongated micelles have been investigated by high resolution transmission electron microscopy (HRTEM) and the small angle neutron scattering (SANS) technique; the complex fluidic nature of the system is investigated by a dynamic rheological measurement. The intermolecular interactions have been recognized via 1H NMR and 2D nuclear Overhauser effect spectroscopy (NOESY), and the unambiguous geometry of the end-caps of the rods has been ascertained for the first time. While the interplay between lipids and transmembrane proteins is thought to be crucial in controlling the membrane shape of the cells during many vital events such as cellular fission, fusion, and virus entry, the observed tuning of the micellar surface curvature via the cation-π interaction involving tyrosine analogues is thought provoking and opens up an avenue for new physical chemistry research on a vital biological phenomena.