Biomolecular Systems Research Articles

Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies

Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe – Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.

Synthesis, in vitro Anti-HIV-1RT evaluation, molecular modeling, DFT and acute oral toxicity studies of some benzotriazole derivatives

This study synthesized and evaluated a series of benzotriazole derivatives denoted 3(a-j) and 6(a-j) for their anti-HIV-1 RT activities compared to the standard drug efavirenz. Notably, compound 3 h, followed closely by 6 h, exhibited significant anti-HIV-1 RT efficacy relative to the standard drug. In vivo oral toxicity studies were conducted for the most active compound 3 h, confirming its nontoxic nature to ascertain the safety profile. By employing molecular docking techniques, we explored the potential interactions between the synthesized compounds (ligands) and a target biomolecule (protein)(PDB ID 1RT2) at the molecular level. We undertook the molecular dynamics study of 3 h, the most active compound, within the active binding pocket of the cocrystallized structure of HIV-1 RT (PDB ID 1RT2). We aimed to learn more about how biomolecular systems behave, interact, and change at the atomic or molecular level over time. Finally, the DFT-derived HOMO and LUMO orbitals, as well as analysis of the molecular electrostatic potential map, aid in discerning the reactivity characteristics of our molecule.

GENESIS CGDYN: large-scale coarse-grained MD simulation with dynamic load balancing for heterogeneous biomolecular systems.

Residue-level coarse-grained (CG) molecular dynamics (MD) simulation is widely used to investigate slow biological processes that involve multiple proteins, nucleic acids, and their complexes. Biomolecules in a large simulation system are distributed non-uniformly, limiting computational efficiency with conventional methods. Here, we develop a hierarchical domain decomposition scheme with dynamic load balancing for heterogeneous biomolecular systems to keep computational efficiency even after drastic changes in particle distribution. These schemes are applied to the dynamics of intrinsically disordered protein (IDP) droplets. During the fusion of two droplets, we find that the changes in droplet shape correlate with the mixing of IDP chains. Additionally, we simulate large systems with multiple IDP droplets, achieving simulation sizes comparable to those observed in microscopy. In our MD simulations, we directly observe Ostwald ripening, a phenomenon where small droplets dissolve and their molecules redeposit into larger droplets. These methods have been implemented in CGDYN of the GENESIS software, offering a tool for investigating mesoscopic biological processes using the residue-level CG models.

Hydrophobic Clusters Regulate Surface Hydration Dynamics of Bacillus subtilis Lipase A.

The surface hydration diffusivity of Bacillus subtilis Lipase A (BSLA) has been characterized by low-field Overhauser dynamic nuclear polarization (ODNP) relaxometry using a series of spin-labeled constructs. Sites for spin-label incorporation were previously designed via an atomistic computational approach that screened for surface exposure, reflective of the surface hydration comparable to other proteins studied by this method, as well as minimal impact on protein function, dynamics, and structure of BSLA by excluding any surface site that participated in greater than 30% occupancy of a hydrogen bonding network within BSLA. Experimental ODNP relaxometry coupling factor results verify the overall surface hydration behavior for these BSLA spin-labeled sites similar to other globular proteins. Here, by plotting the ODNP parameters of relative diffusive water versus the relative bound water, we introduce an effective "phase-space" analysis, which provides a facile visual comparison of the ODNP parameters of various biomolecular systems studied to date. We find notable differences when comparing BSLA to other systems, as well as when comparing different clusters on the surface of BSLA. Specifically, we find a grouping of sites that correspond to the spin-label surface location within the two main hydrophobic core clusters of the branched aliphatic amino acids isoleucine, leucine, and valine cores observed in the BSLA crystal structure. The results imply that hydrophobic clustering may dictate local surface hydration properties, perhaps through modulation of protein conformations and samplings of the unfolded states, providing insights into how the dynamics of the hydration shell is coupled to protein motion and fluctuations.

Fluorine-19 labeling of the tryptophan residues in the G protein-coupled receptor NK1R using the 5-fluoroindole precursor in Pichia pastoris expression.

In NMR spectroscopy of biomolecular systems, the use of fluorine-19 probes benefits from a clean background and high sensitivity. Therefore, 19F-labeling procedures are of wide-spread interest. Here, we use 5-fluoroindole as a precursor for cost-effective residue-specific introduction of 5-fluorotryptophan (5F-Trp) into G protein-coupled receptors (GPCRs) expressed in Pichia pastoris. The method was successfully implemented with the neurokinin 1 receptor (NK1R). The 19F-NMR spectra of 5F-Trp-labeled NK1R showed one well-separated high field-shifted resonance, which was assigned by mutational studies to the "toggle switch tryptophan". Residue-selective labeling thus enables site-specific investigations of this functionally important residue. The method described here is inexpensive, requires minimal genetic manipulation and can be expected to be applicable for yeast expression of GPCRs at large.

Multilevel Framework for Analysis of Protein Folding Involving Disulfide Bond Formation.

In this study, a three-layered multicenter ONIOM approach is implemented to characterize the naive folding pathway of bovine pancreatic trypsin inhibitor (BPTI). Each layer represents a distinct level of theory, where the initial layer, encompassing the entire protein, is modeled by a general all-atom force-field GFN-FF. An intermediate electronic structure layer consisting of three multicenter fragments is introduced with the state-of-the-art semiempirical tight-binding method GFN2-xTB. Higher accuracy, specifically addressing the breaking and formation of the three disulfide bonds, is achieved at the innermost layer using the composite DFT method r2SCAN-3c. Our analysis sheds light on the structural stability of BPTI, particularly the significance of interlinking disulfide bonds. The accuracy and efficiency of the multicenter QM/SQM/MM approach are benchmarked using the oxidative formation of cystine. For the folding pathway of BPTI, relative stabilities are investigated through the calculation of free energy contributions for selected intermediates, focusing on the impact of the disulfide bond. Our results highlight the intricate trade-off between accuracy and computational cost, demonstrating that the multicenter ONIOM approach provides a well-balanced and comprehensive solution to describe electronic structure effects in biomolecular systems. We conclude that multiscale energy landscape exploration provides a robust methodology for the study of intriguing biological targets.

ELViM: Exploring Biomolecular Energy Landscapes through Multidimensional Visualization.

Molecular dynamics (MD) simulations provide a powerful means of exploring the dynamic behavior of biomolecular systems at the atomic level. However, analyzing the vast data sets generated by MD simulations poses significant challenges. This article discusses the energy landscape visualization method (ELViM), a multidimensional reduction technique inspired by the energy landscape theory. ELViM transcends one-dimensional representations, offering a comprehensive analysis of the effective conformational phase space without the need for predefined reaction coordinates. We apply the ELViM to study the folding landscape of the antimicrobial peptide Polybia-MP1, showcasing its versatility in capturing complex biomolecular dynamics. Using dissimilarity matrices and a force-scheme approach, the ELViM provides intuitive visualizations, revealing structural correlations and local conformational signatures. The method is demonstrated to be adaptable, robust, and applicable to various biomolecular systems.

Constant-pH Simulations with the Polarizable Atomic Multipole AMOEBA Force Field.

Accurately predicting protein behavior across diverse pH environments remains a significant challenge in biomolecular simulations. Existing constant-pH molecular dynamics (CpHMD) algorithms are limited to fixed-charge force fields, hindering their application to biomolecular systems described by permanent atomic multipoles or induced dipoles. This work overcomes these limitations by introducing the first polarizable CpHMD algorithm in the context of the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) force field. Additionally, our implementation in the open-source Force Field X (FFX) software has the unique ability to handle titration state changes for crystalline systems including flexible support for all 230 space groups. The evaluation of constant-pH molecular dynamics (CpHMD) with the AMOEBA force field was performed on 11 crystalline peptide systems that span the titrating amino acids (Asp, Glu, His, Lys, and Cys). Titration states were correctly predicted for 15 out of the 16 amino acids present in the 11 systems, including for the coordination of Zn2+ by cysteines. The lone exception was for a HIS-ALA peptide where CpHMD predicted both neutral histidine tautomers to be equally populated, whereas the experimental model did not consider multiple conformers and diffraction data are unavailable for rerefinement. This work demonstrates the promise polarizable CpHMD simulations for pKa predictions, the study of biochemical mechanisms such as the catalytic triad of proteases, and for improved protein-ligand binding affinity accuracy in the context of pharmaceutical lead optimization.

Exploring Free Energies of Specific Protein Conformations Using the Martini Force Field.

Coarse-grained (CG) level molecular dynamics simulations are routinely used to study various biomolecular processes. The Martini force field is currently the most widely adopted parameter set for such simulations. The functional form of this and several other CG force fields enforces secondary protein structure support by employing a variety of harmonic potentials or restraints that favor the protein's native conformation. We propose a straightforward method to calculate the energetic consequences of transitions between predefined conformational states in systems in which multiple factors can affect protein conformational equilibria. This method is designed for use within the Martini force field and involves imposing conformational transitions by linking a Martini-inherent elastic network to the coupling parameter λ. We demonstrate the applicability of our method using the example of five biomolecular systems that undergo experimentally characterized conformational transitions between well-defined structures (Staphylococcal nuclease, C-terminal segment of surfactant protein B, LAH4 peptide, and β2-adrenergic receptor) as well as between folded and unfolded states (GCN4 leucine zipper protein). The results show that the relative free energy changes associated with protein conformational transitions, which are affected by various factors, such as pH, mutations, solvent, and lipid membrane composition, are correctly reproduced. The proposed method may be a valuable tool for understanding how different conditions and modifications affect conformational equilibria in proteins.

PROBLEMS OF BIOLOGICAL, MEDICAL AND PHARMACEUTICAL CHEMISTRY

Introduction. Flavonoids are a family of biologically active substances, representatives of which are often found in the human diet, in particular quercetin, rutin, and morin. When ingested with food, these compounds exhibit their antioxidant properties within the biomolecular system, where α-tocopherol is an important component. Systems formed by antioxidants are characterized by a certain total antioxidant effect, which often differs from the simple sum of their antioxidant capacities to a greater extent in the case of synergy or to a lesser extent in the case of subadditive interaction. From this point of view, the nature of the studied flavonoid's interaction with the endogenous antioxidant α-tocopherol is interesting. The identified inter-action effects can serve as a basis for improved antioxidant formulations, as well as the subsequent study of the cooperation mechanisms in vivo. Aim. The study aims to determine the interaction effects of the α-tocopherol compositions with quercetin, rutin, and morin at their different ratios. Material and methods. Solutions of individual substances and flavonoid–α-tocopherol compositions in ratios from 1:1 to 1:20 were assessed. The antioxidant capacity was evaluated by the ABTS/PP method, implemented in the form of decolorization and kinetic approaches. Results. The values of the TEAC index of the studied flavonoids obtained by the decolorization and kinetic method are close and lie in the range of 0.85–3.73 (decolorization) and 0.94–3.22 (kinetic method). Antioxidant capacity increased in the next order: α-tocopherol, rutin, morin, and quercetin. In the first 10 minutes of incubation, flavonoids captured 50–80% of the total number of ABTS•+ radical cations, while α-tocopherol showed the maximum of its antioxidant capacity already in the 1st minute. The composition effects were additive and slightly subadditive for the studied compositions of ru-tin, morin, and quercetin with α-tocopherol demonstrating maximum values up to –13% in the composition of morin–α-tocopherol 1:10 and quercetin–α-tocopherol 1:20. No dependence of the component’s ratios on the composition effect was found. Conclusions. The studied compositions of bioflavonoids and α-tocopherol exhibit additive and minor subadditive effects.

Efficient Sampling of Cavity Hydration in Proteins with Nonequilibrium Grand Canonical Monte Carlo and Polarizable Force Fields.

Prediction of the hydration levels of protein cavities and active sites is important to both mechanistic analysis and ligand design. Due to the unique microscopic environment of these buried water molecules, a polarizable model is expected to be crucial for an accurate treatment of protein internal hydration in simulations. Here we adapt a nonequilibrium candidate Monte Carlo approach for conducting grand canonical Monte Carlo simulations with the Drude polarizable force field. The GPU implementation enables the efficient sampling of internal cavity hydration levels in biomolecular systems. We also develop an enhanced sampling approach referred to as B-walking, which satisfies detailed balance and readily combines with grand canonical integration to efficiently calculate quantitative binding free energies of water to protein cavities. Applications of these developments are illustrated in a solvent box and the polar ligand binding site in trypsin. Our simulation results show that including electronic polarization leads to a modest but clear improvement in the description of water position and occupancy compared to the crystal structure. The B-walking approach enhances the range of water sampling in different chemical potential windows and thus improves the accuracy of water binding free energy calculations.

Data-Efficient Generation of Protein Conformational Ensembles with Backbone-to-Side-Chain Transformers.

Excitement at the prospect of using data-driven generative models to sample configurational ensembles of biomolecular systems stems from the extraordinary success of these models on a diverse set of high-dimensional sampling tasks. Unlike image generation or even the closely related problem of protein structure prediction, there are currently no data sources with sufficient breadth to parametrize generative models for conformational ensembles. To enable discovery, a fundamentally different approach to building generative models is required: models should be able to propose rare, albeit physical, conformations that may not arise in even the largest data sets. Here we introduce a modular strategy to generate conformations based on "backmapping" from a fixed protein backbone that (1) maintains conformational diversity of the side chains and (2) couples the side-chain fluctuations using global information about the protein conformation. Our model combines simple statistical models of side-chain conformations based on rotamer libraries with the now ubiquitous transformer architecture to sample with atomistic accuracy. Together, these ingredients provide a strategy for rapid data acquisition and hence a crucial ingredient for scalable physical simulation with generative neural networks.

Cooperative control of a DNA origami force sensor

Biomolecular systems are dependent on a complex interplay of forces. Modern force spectroscopy techniques provide means of interrogating these forces, but they are not optimized for studies in constrained environments as they require attachment to micron-scale probes such as beads or cantilevers. Nanomechanical devices are a promising alternative, but this requires versatile designs that can be tuned to respond to a wide range of forces. We investigate the properties of a nanoscale force sensitive DNA origami device which is highly customizable in geometry, functionalization, and mechanical properties. The device, referred to as the NanoDyn, has a binary (open or closed) response to an applied force by undergoing a reversible structural transition. The transition force is tuned with minor alterations of 1 to 3 DNA oligonucleotides and spans tens of picoNewtons (pN). The DNA oligonucleotide design parameters also strongly influence the efficiency of resetting the initial state, with higher stability devices (≳10 pN) resetting more reliably during repeated force-loading cycles. Finally, we show the opening force is tunable in real time by adding a single DNA oligonucleotide. These results establish the potential of the NanoDyn as a versatile force sensor and provide fundamental insights into how design parameters modulate mechanical and dynamic properties.

Development of a universal method for vibrational analysis of the terminal alkyne C≡C stretch.

The terminal alkyne C≡C stretch has a large Raman scattering cross section in the "silent" region for biomolecules. This has led to many Raman tag and probe studies using this moiety to study biomolecular systems. A computational investigation of these systems is vital to aid in the interpretation of these results. In this work, we develop a method for computing terminal alkyne vibrational frequencies and isotropic transition polarizabilities that can easily and accurately be applied to any terminal alkyne molecule. We apply the discrete variable representation method to a localized version of the C≡C stretch normal mode. The errors of (1) vibrational localization to the terminal alkyne moiety, (2) anharmonic normal mode isolation, and (3) discretization of the Born-Oppenheimer potential energy surface are quantified and found to be generally small and cancel each other. This results in a method with low error compared to other anharmonic vibrational methods like second-order vibrational perturbation theory and to experiments. Several density functionals are tested using the method, and TPSS-D3, an inexpensive nonempirical density functional with dispersion corrections, is found to perform surprisingly well. Diffuse basis functions are found to be important for the accuracy of computed frequencies. Finally, the computation of vibrational properties like isotropic transition polarizabilities and the universality of the localized normal mode for terminal alkynes are demonstrated.

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations.

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

Adenine Adsorption on Ag Doped Graphene : A Theoretical Insight

The adsorption phenomenon of Adenine on silver (Ag) doped graphene extensively studied by using density functional theory (DFT) method to insight the role of DNA nucleobase adenine as adsorbent. Our theoretical findings suggest that the structural and electronic properties of the complex system of graphene-adenine (Gr-Ade) strong depends on Silver (Ag) atom. The DNA base adenine molecule is adsorbed on pristine graphene, while there is strong chemisorption phenomenon is observed on Ag-doped graphene. We successfully reported the Dipole moment, HOMO-LUMO and density of states (DOS). The complex biomolecular system (Gr-Ag-Ade) studied could be used to assemble DNA based biosensors in different fields as well.

Controlling the Fluctuating Tip-Enhanced Raman Spectra of Chloramben on Silver Nanocubes.

Tip-enhanced Raman (TER) scattering from molecules residing at plasmonic junctions can be used to detect, identify, and image single molecules. This is most evident for flat molecules interrogated under conditions of extreme temperatures and pressure. It is also the case for (bio)molecular systems that feature preferred orientations/conformations under ambient laboratory conditions. More complex molecules that can adopt multiple conformations and/or feature different protonation or charge states give rise to complex TER spectra. We illustrate how the latter can be controlled in the case of chloramben molecules coated onto plasmonic silver nanocubes. We show that characteristic molecular Raman spectra cannot be obtained when tunneling plasmons are operative, i.e., when the tip is in direct contact with the chemically functionalized plasmonic nanoparticles. We rationalize these observations and propose an approach to less invasive and hence more analytical TER spectral imaging.

Enhanced sampling simulations of biomolecular systems

Enhanced sampling simulations of biomolecular systems

Pulse Dipolar Electron Paramagnetic Resonance Spectroscopy Distance Measurements at Low Nanomolar Concentrations: The CuII-Trityl Case.

Recent sensitivity enhancements in pulse dipolar electron paramagnetic resonance spectroscopy (PDS) have afforded distance measurements at submicromolar spin concentrations. This development opens the path for new science as more biomolecular systems can be investigated at their respective physiological concentrations. Here, we demonstrate that the combination of orthogonal spin-labeling using CuII ions and trityl yields a >3-fold increase in sensitivity compared to that of the established CuII-nitroxide labeling strategy. Application of the recently developed variable-time relaxation-induced dipolar modulation enhancement (RIDME) method yields a further ∼2.5-fold increase compared to the commonly used constant-time RIDME. This overall increase in sensitivity of almost an order of magnitude makes distance measurements in the range of 3 nm with protein concentrations as low as 10 nM feasible, >2 times lower than the previously reported concentration. We expect that experiments at single-digit nanomolar concentrations are imminent, which have the potential to transform biological PDS applications.

Martini on the Rocks: Can a Coarse-Grained Force Field Model Crystals?

Computational chemistry is an important tool in numerous scientific disciplines, including drug discovery and structural biology. Coarse-grained models offer simple representations of molecular systems that enable simulations of large-scale systems. Because there has been an increase in the adoption of such models for simulations of biomolecular systems, critical evaluation is warranted. Here, the stability of the amyloid peptide and organic crystals is evaluated using the Martini 3 coarse-grained force field. The crystals change shape drastically during the simulations. Radial distribution functions show that the distance between backbone beads in β-sheets increases by ∼1 Å, breaking the crystals. The melting points of organic compounds are much too low in the Martini force field. This suggests that Martini 3 lacks the specific interactions needed to accurately simulate peptides or organic crystals without imposing artificial restraints. The problems may be exacerbated by the use of the 12-6 potential, suggesting that a softer potential could improve this model for crystal simulations.