Molecular Simulation Protocol Research Articles

HSADab: A comprehensive database for human serum albumin

Human Serum Albumin (HSA), the most abundant protein in human body fluids, plays a crucial role in the transportation, absorption, metabolism, distribution, and excretion of drugs, significantly influencing their therapeutic efficacy. Despite the importance of HSA as a drug target, the available data on its interactions with external agents, such as drug-like molecules and antibodies, are limited, posing challenges for molecular modeling investigations and the development of empirical scoring functions or machine learning predictors for this target. Furthermore, the reported entries in existing databases often contain major inconsistencies due to varied experiments and conditions, raising concerns about data quality. To address these issues, a pioneering database, HSADab, was established through an extensive review of >30,000 scientific publications published between 1987 and 2023. The database encompasses over 5000 affinity data points at multiple temperatures and >130 crystal structures, including both ligand-bound and apo forms. The current HSADab resource (www.hsadab.cn) serves as a reliable foundation for validating molecular simulation protocols, such as traditional virtual screening workflows using docking, end-point, and al-chemical free energy techniques. Additionally, it provides a valuable data source for the implementation of machine learning predictors, including plasma protein binding models and plasma protein-based drug design models.

Molecular Dynamics Simulation of Silicone Oil Polymerization from Combined QM/MM Modeling.

We outline a molecular simulation protocol for elucidating the formation of silicone oil from trimethlyl- and dimethlysilanediole precursor mixtures. While the fundamental condensation reactions are effectively described by quantum mechanical calculations, this is combined with molecular mechanics models in order to assess the extended relaxation processes. Within a small series of different precursor mixtures used as starting points, we demonstrate the evolution of the curing degree and heat formation in the course of polymer chain growth. Despite the increasing complexity of the amorphous agglomerate of polymer chains, our approach shows an appealing performance for tackling both elastic and viscous relaxation. Indeed, the finally obtained polymer systems feature 99% curing and thus offer realistic insights into the growth mechanisms of coexisting/competing polymer strands.

Structural basis for the mechanism of interaction of SARS-CoV-2 B.1.640.2 variant RBD with the host receptors hACE2 and GRP78

The inflicted chaos instigated by the SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) globally continues with the emergence of novel variants. The current global outbreak is aggravated by the manifestation of novel variants, which affect the effectiveness of the vaccine, attachment with hACE2 (human Angiotensin-converting enzyme 2) and immune evasion. Recently, a new variant named University Hospital Institute (IHU) (B.1.640.2) was reported in France in November 2021 and is spreading globally affecting public healthcare. The B.1.640.2 SARS-CoV-2 strain revealed 14 mutations and 9 deletions in spike protein. Thus, it is important to understand how these variations in the spike protein impact the communication with the host. A protein coupling approach along with molecular simulation protocols was used to interpret the variation in the binding of the wild type (WT) and B.1.640.2 variant with hACE2 and Glucose-regulating protein 78 (GRP78) receptors. The initial docking scores revealed a stronger binding of the B.1.640.2-RBD with both the hACE2 and GRP78. To further understand the crucial dynamic changes, we looked at the structural and dynamic characteristics and also explored the variations in the bonding networks between the WT and B.1.640.2-RBD (receptor-binding domain) in association with hACE2 and GRP78, respectively. Our findings revealed that the variant complex demonstrated distinct dynamic properties in contrast to the wild type due to the acquired mutations. Finally, to provide conclusive evidence on the higher binding by the B.1.640.2 variant the TBE was computed for each complex. For the WT with hACE2 the TBE was quantified to be-61.38 ± 0.96 kcal/mol and for B.1.640.2 variant the TBE was estimated to be −70.47 ± 1.00 kcal/mol. For the WT-RBD-GRP78 the TBE -was computed to be 32.32 ± 0.56 kcal/mol and for the B.1.640.2-RBD a TBE of −50.39 ± 0.88 kcal/mol was reported. This show that these mutations are the basis for higher binding and infectivity produced by B.1.640.2 variant and can be targeted for drug designing against it. Communicated by Ramaswamy H. Sarma

Molecular simulation of layered GO membranes with amorphous structure for heavy metal ions separation

Currently, layered graphene oxide (GO) membranes have gained considerable attention due to their high separation efficiency in water treatment. However, a molecular-level separation mechanism remains elusive due to the complex irregular stacking feature of GO nanoscale flakes in actual GO membranes. Most existing molecular simulation studies using idealized GO membrane models might largely ignore the membrane structural heterogeneity. In this work, a molecular simulation protocol was applied to construct a non-idealized amorphous GO membrane model, and its structural morphology and property fit well with the realistic GO membranes. For the first time, the actual structure-oriented GO membrane model was used to study the separation behavior of heavy metal ions from aqueous solutions. The effects of the stacking structures and morphologies for the amorphous membranes on the water permeation and ion rejection were investigated. The constituent GO flakes with varied sheet sizes and oxidization degrees were considered. Our simulations demonstrate that the GO-based amorphous membranes with different-sized GO sheets can exhibit distinct ion rejection mechanisms and water penetration behavior. This finding has not been observed in previous idealized membrane models. Our simulation study provides novel insight into the separation mechanisms and improves the microscopic understanding of layered GO membranes.

Study of interfacial properties of water + methane + oil three-phase systems by a simple molecular simulation protocol

A straightforward molecular simulation protocol has been proposed to study the interfacial properties of the three-phase fluid systems. With this protocol, the interfctcial tension (IFT) can be calculated based on the pressure tensor of the entire simulation box of the two-phase systems split from the three-phase system without calculating the debatable pressure tensor profile. Water + methane + oil (decane, hexadecane, and toluene) three-phase systems was studied at different temperatures (323–423 K) and pressures (up to around 20 MPa). Reasonable agreement was found among the results obtained from molecular simulation, density gradient theory with the cubic-plus-association equation of state, and available experimental data in the literature. The IFT of the aqueous phase + vapor phase in the three-phase systems is smaller than the IFT in water + methane two-phase systems. Importantly, the reduction of IFT of aqueous phase + vapor phase in the three-phase systems containing decane or hexadecane is moderate while that in the three-phase systems containing toluene is significant, which can be explained by the stronger enrichment of toluene in the interfacial region in contrast to that of decane or hexadecane. Meanwhile, methane accumulates in the interfacial region of the aqueous phase + decane/hexadecane-rich phase in the three-phase systems, which causes the reduction of IFT with pressure while the opposite pressure effect was reported in the water + decane/hexadecane two-phase systems. The interfacial properties of the oil-rich phase + vapor phase in the three-phase systems are hardly affected by water due to the small amount of dissolved water. Furthermore, the calculated spreading coefficient of different types of oil in contact with water + methane under three-phase conditions follows this order: toluene > decane > hexadecane.

An Efficient Computational Assay for β-Lactam Antibiotic Breakdown by Class A β-Lactamases.

Class A β-lactamases cause clinically relevant resistance to β-lactam antibiotics. Carbapenem degradation is a particular concern. We present an efficient QM/MM molecular simulation protocol that accurately predicts the activity of β-lactamases against carbapenems. Simulations take less than 24 CPU hours, a greater than 99% reduction, and do not require fitting against experimental data or significant parametrization. This computational assay also reveals mechanistic details of β-lactam breakdown and should assist in evaluating emerging β-lactamase variants and developing new antibiotics.

A molecular simulation protocol for swelling and organic solvent nanofiltration of polymer membranes

Polymer membranes have received considerable interest for organic solvent nanofiltration (OSN). The OSN performance is governed by many complex factors and quantitative understanding is experimentally challenging. In addition, it is a prerequisite to characterize membrane swelling in solvents prior to nanofiltration. A molecular simulation protocol is developed herein to investigate the swelling of three polymer membranes namely polybenzimidazole (PBI), polyimide (PI) and polymer of intrinsic microporosity (PIM-1) in four organic solvents (methanol, ethanol, acetonitrile and acetone), and then examine the OSN through the swollen membranes. The simulation protocol can highly efficiently simulate membrane swelling, which is approximately one order of magnitude faster than normal simulation method. The predicted swelling degrees of the three polymer membranes follow experimentally measured trend, exhibit good relationships with the polymer-solvent solubility parameter differences and the mean pore sizes of swollen membranes. For the OSN of a dye (methylene blue) in the four organic solvents, 100% rejection is found by the swollen PBI, PI and PIM-1 membranes. The predicted solvent permeabilities through PIM-1 and PI membranes match fairly well with experimental data, and their dependences on solvent viscosity, pore size and polymer-solvent interaction are examined. From this simulation study, the microscopic insights into the swelling of polymer membranes and the permeation of organic solvents are provided, which are useful for the development of new membranes for high-performance OSN.

A molecular simulation protocol for membrane pervaporation

Pervaporation (PV) has emerged as a robust membrane-based separation technology for liquid mixtures. For the development of high-performance PV membranes, it is crucial to quantitatively understand the separation mechanism from a molecular level. Nevertheless, molecular simulation of PV is challenging due to the practical requirements of preserving a vapor-liquid equilibrium (VLE) in the feed side, and simultaneously an extremely low permeate pressure throughout the simulation. In this study, we develop a molecular simulation protocol for PV by rigorously incorporating these two practical requirements and demonstrate its applications in three separations: (1) Seawater desalination through a zeolitic-imidazolate framework (ZIF-8) membrane. Water permeability and salt rejection predicted are in excellent agreement with experiment. (2) Ethanol/water separation through a polymer of intrinsic microporosity (PIM-1). The normalized-fluxes of ethanol and water match remarkably well with experimental data. (3) Ethanol/water separation through a zeolite (MFI) membrane. The separation factors of ethanol/water agree fairly well with measured data. In all the three separations, a VLE is preserved in the feed side, while a vanishingly low pressure is maintained in the permeate side (< 10 mbar as in experiments). The simulation protocol reliably mimics practical PV processes and can be generally applied to simulate the PV separations of other liquid mixtures.

Structure-affinity properties of a high-affinity ligand of FKBP12 studied by molecular simulations of a binding intermediate.

With a view to explaining the structure-affinity properties of the ligands of the protein FKBP12, we characterized a binding intermediate state between this protein and a high-affinity ligand. Indeed, the nature and extent of the intermolecular contacts developed in such a species may play a role on its stability and, hence, on the overall association rate. To find the binding intermediate, a molecular simulation protocol was used to unbind the ligand by gradually decreasing the biasing forces introduced. The intermediate was subsequently refined with 17 independent stochastic boundary molecular dynamics simulations that provide a consistent picture of the intermediate state. In this state, the core region of the ligand remains stable, notably because of the two anchoring oxygen atoms that correspond to recurrent motifs found in all FKBP12 ligand core structures. Besides, the non-core regions participate in numerous transient intermolecular and intramolecular contacts. The dynamic aspect of most of the contacts seems important both for the ligand to retain at least a part of its configurational entropy and for avoiding a trapped state along the binding pathway. Since the transient and anchoring contacts contribute to increasing the stability of the intermediate, as a corollary, the dissociation rate constant of this intermediate should be decreased, resulting in an increase of the affinity constant . The present results support our previous conclusions and provide a coherent rationale for explaining the prevalence in high-affinity ligands of (i) the two oxygen atoms found in carbonyl or sulfonyl groups of dissimilar core structures and of (ii) symmetric or pseudo-symmetric mobile groups of atoms found as non-core moieties. Another interesting aspect of the intermediate is the distortion of the flexible 80 s loop of the protein, mainly in its tip region, that promotes the accessibility to the bound state.

A molecular simulation protocol to avoid sampling redundancy and discover new states

BackgroundFor biomacromolecules or their assemblies, experimental knowledge is often restricted to specific states. Ambiguity pervades simulations of these complex systems because there is no prior knowledge of relevant phase space domains, and sampling recurrence is difficult to achieve. In molecular dynamics methods, ruggedness of the free energy surface exacerbates this problem by slowing down the unbiased exploration of phase space. Sampling is inefficient if dwell times in metastable states are large. MethodsWe suggest a heuristic algorithm to terminate and reseed trajectories run in multiple copies in parallel. It uses a recent method to order snapshots, which provides notions of “interesting” and “unique” for individual simulations. We define criteria to guide the reseeding of runs from more “interesting” points if they sample overlapping regions of phase space. ResultsUsing a pedagogical example and an α-helical peptide, the approach is demonstrated to amplify the rate of exploration of phase space and to discover metastable states not found by conventional sampling schemes. Evidence is provided that accurate kinetics and pathways can be extracted from the simulations. ConclusionsThe method, termed PIGS for Progress Index Guided Sampling, proceeds in unsupervised fashion, is scalable, and benefits synergistically from larger numbers of replicas. Results confirm that the underlying ideas are appropriate and sufficient to enhance sampling. General SignificanceIn molecular simulations, errors caused by not exploring relevant domains in phase space are always unquantifiable and can be arbitrarily large. Our protocol adds to the toolkit available to researchers in reducing these types of errors. This article is part of a Special Issue entitled “Recent Developments of Molecular Dynamics.”

Biomimetic design of affinity peptide ligands for human IgG based on protein A-IgG complex

Staphylococcal protein A (SpA) has been widely used as an affinity ligand for the purification of immunoglobulin G (IgG). Based on the affinity motif of SpA, we have herein developed a biomimetic design strategy for affinity peptide ligands of IgG. First, according to the distribution of the six hot spots of the SpA affinity motif determined previously, the number of residues that should be inserted into between the hot spots was determined. Cysteine was introduced as one of the middle inserted residues of the peptide for later immobilization. Then, amino acid location was performed to identify other amino acid residues for insertion, leading to the construction of a peptide library. The library was screened by using different molecular simulation protocols, resulting in the selection of 15 peptide candidates. Thereafter, molecular dynamics simulations were performed to validate the dynamics of the affinity interactions between the candidates and IgG, and 14 of them were found to keep high affinities. Finally, the affinity and specificity of the top one ligand FYWHCLDE were exemplified by protein chromatography and IgG purification. The results indicate that the design strategy was successful and the affinity peptide ligand for IgG is promising for application in antibody purifications.

Nano tools for macro problems: multiscale molecular modeling of nanostructured polymer systems

A current challenge of physical, chemical, and engineering sciences is to develop theoretical tools for predicting structure and properties of complex materials from the knowledge of a few input parameters. In this work, we present a general multiscale molecular simulation protocol for predicting morphologies and properties of nanostructured polymer systems and we apply it to three examples of industrial relevance. The first example is of general importance for the polymer industry and is related to the enhancement of mechanical and barrier properties, if a nanofiller is dispersed into a polymer matrix: the role of multiscale modeling for the development of the material in the stage of screening, the best design is evidenced. The second example, important for the optoelectronic industry, is related to the prediction of the dispersion of gold nanoparticles into a diblock copolymer system forming different nanostructures (lamellae, cylinders, …). In this case, it is relevant to understand how it is possible to influence the self-assembly of the nanoparticles in different regions of the diblock copolymer structure. The third example is of interest to automotive and polymer industries and involves inorganic nanoparticles grafted with organic side chains. The assembly is dispersed in a polymeric matrix and it is interesting to predict the effect of the chain length and grafting density on the nanostructure.

A Simple QM/MM Approach for Capturing Polarization Effects in Protein−Ligand Binding Free Energy Calculations

We present a molecular simulation protocol to compute free energies of binding, which combines a QM/MM correction term with rigorous classical free energy techniques, thereby accounting for electronic polarization effects. Relative free energies of binding are first computed using classical force fields, Monte Carlo sampling, and replica exchange thermodynamic integration. Snapshots of the configurations at the end points of the perturbation are then subjected to DFT-QM/MM single-point calculations using the B3LYP functional and a range of basis sets. The resulting quantum mechanical energies are then processed using the Zwanzig equation to give free energies incorporating electronic polarization. Our approach is conceptually simple and does not require tightly coupled QM and MM software. The method has been validated by calculating the relative free energies of hydration of methane and water and the relative free energy of binding of two inhibitors of cyclooxygenase-2. Closed thermodynamic cycles are obtained across different pathways, demonstrating the correctness of the technique, although significantly more sampling is required for the protein-ligand system. Our method offers a simple and effective way to incorporate quantum mechanical effects into computed free energies of binding.

Molecular Dynamics Simulations of Proteins with Chemically Modified Disulfide Bonds

Proteins that are used as therapeutic drugs act in the extracellular microenvironment. They usually have a small number of intramolecular disulfide bonds to help maintain their tertiary structure in the vascular circulation. In general, most cysteine residues are part of a disulfide bond with free sulfhydrals being uncommon. We have studied whether the site-specific chemical reduction of disulfides and the incorporation of a 3-carbon methylene bridge between the cysteines in interferon-α 2a would change the structure of this protein. Bridging of both of the disulfide bonds of interferon-α 2a was studied using two different molecular simulation protocols: (1) molecular dynamics, and (2) stochastic dynamics. We have shown that the disulfide bonds in interferon-α 2a can be reduced and chemically modified without significantly altering the tertiary structure of the protein. This offers the novel possibility of chemically modifying therapeutically important proteins without affecting their biological properties.