Binding Free Energy Differences Research Articles

Study of the Enantioselectivity and Recognition Mechanism of Allyl-β-CD Modified Organic Polymer Monolithic Capillary Column.

Allyl-β-CD was synthesized and used as the chiral functional monomer to prepare chiral organic polymer monolithic columns in capillary HPLC. First, the enantioselectivity of the prepared allyl-β-CD modified organic polymer monolithic capillary columns was investigated. Then, the influences of enantioseparation conditions of chiral drugs were further explored. Finally, the recognition mechanism was studied by molecular docking with AutoDock. Complete enantioseparations of four chiral drugs as well as partial enantioseparations of eight chiral drugs have been achieved. Results showed that the RSD values for run-to-run, day-to-day, and column-to-column variations ranged from 1.2% to 4.6%, 1.4% to 4.7%, and 2.0% to 6.1%, respectively. The enantioselectivity factor rather than resolution is correlated with the binding free energy difference between enantiomers with allyl-β-CD. Furthermore, the abundant ether bonds, hydroxyl groups, and hydrophobic cavities in cyclodextrin are responsible for the enantioseparation ability of the chiral monolithic capillary columns.

Binding characteristics of the doxepin E/Z-isomers to the histamine H1 receptor revealed by receptor-bound ligand analysis and molecular dynamics study.

Doxepin is an antihistamine and tricyclic antidepressant that binds to the histamine H1 receptor (H1R) with high affinity. Doxepin is an 85:15 mixture of the E- and Z-isomers. The Z-isomer is well known to be more effective than the E-isomer, whereas based on the crystal structure of the H1R/doxepin complex, the hydroxyl group of Thr1123.37 is close enough to form a hydrogen bond with the oxygen atom of the E-isomer. The detailed binding characteristics and reasons for the differences remain unclear. In this study, we analyzed doxepin isomers bound to the receptor following extraction from a purified H1R protein complexed with doxepin. The ratio of the E- and Z-isomers bound to wild-type (WT) H1R was 55:45, indicating that the Z-isomer was bound to WT H1R with an approximately 5.2-fold higher affinity than the E-isomer. For the T1123.37V mutant, the E/Z ratio was 89:11, indicating that both isomers have similar affinities. Free energy calculations using molecular dynamics (MD) simulations also reproduced the experimental results of the relative binding free energy differences between the isomers for WT and T1123.37V. Furthermore, MD simulations revealed that the hydroxyl group of T1123.37 did not form hydrogen bonds with the E-isomer, but with the adjacent residues in the binding pocket. Analysis of the receptor-bound doxepin and MD simulations suggested that the hydroxyl group of T1123.37 contributes to the formation of a chemical environment in the binding pocket, which is slightly more favorable for the Z-isomer without hydrogen bonding with doxepin.

Supramolecular Interaction Modulation in Thermosensitive Composites: Enantiomeric Recognition and Chiral Site Regeneration.

Herein, a novel strategy was implemented to modulate the supramolecular interaction between enantiomers and chiral recognition sites (CRSs), effectively resolving the issue of CRS saturation. Randomly methylated-β-cyclodextrin (Rm-β-CD) was used as the CRS (host molecule), and polymerized ionic liquids [poly([vbim]TFSI)] were used as the supramolecular modulator (guest molecule), which self-assembled to generate thermosensitive supramolecular host/guest complexes. The enantiomeric binding capacity and enantioselectivity of chiral separation systems centered on supramolecular host-guest complexes are characterized by a high degree of temperature dependence. Poly([vbim]TFSI) bonded to Rm-β-CD at temperatures between 17 °C ± 3 and 50 °C ± 3 °C, and the binding free energy difference (|ΔΔG|) between the (S)- and (R)-enantiomer was 0.55. Conversely, poly([vbim]TFSI detached from Rm-β-CD at temperatures >50 °C ± 3 °C or <17 °C ± 3 °C, and |ΔΔG| between (S)- and (R)-enantiomer was 0.03. The |ΔΔG| value of the (R)-enantiomer can reach 0.86 in two temperature intervals. Therefore, the binding of poly([vbim]TFSI) to Rm-β-CD afforded the favorable separation of four racemic sample mixtures: mandelic acid (e.e.% = 61.3%), ibuprofen (e.e.% = 21.6%), warfarin (e.e.% = 14.9%), and naproxen (e.e% = 18.2%). The detachment of poly([vbim]TFSI) from Rm-β-CD released the enantiomer bound to CRSs. The decomplexation of mandelic acid reached 75.1%.

Nonspecific vs. specific DNA binding free energetics of a transcription factor domain protein

Transcription factor (TF) proteins regulate gene expression by binding to specific sites on the genome. In the facilitated diffusion model, an optimized search process is achieved by the TF alternating between 3D diffusion in the bulk and 1D diffusion along DNA. While undergoing 1D diffusion, the protein can switch from a search mode for fast diffusion along nonspecific DNA to a recognition mode for stable binding to specific DNA. It was recently noticed that, for a small TF domain protein, reorientations on DNA happen between the nonspecific and specific DNA binding. We here conducted all-atom molecular dynamics simulations with steering forces to reveal the protein-DNA binding free energetics, confirming that the search and recognition modes are distinguished primarily by protein orientations on the DNA. As the binding free energy difference between the specific and nonspecific DNA system slightly deviates from that being estimated directly from dissociation constants on 15-bp DNA constructs, we hypothesize that the discrepancy can come from DNA sequences flanking the 6-bp central binding sites that impact on the dissociation kinetics measurements. The hypothesis is supported by a simplified spherical protein-DNA model along with stochastic simulations and kinetic modeling.

Dynamics and recognition of homeodomain containing protein-DNA complex of IRX4.

Iroquois Homeobox 4 (IRX4) belongs to a family of homeobox TFs having roles in embryogenesis, cell specification, and organ development. Recently, large scale genome-wide association studies and epigenetic studies have highlighted the role of IRX4 and its associated variants in prostate cancer. No studies have investigated and characterized the structural aspect of the IRX4 homeodomain and its potential to bind to DNA. The current study uses sequence analysis, homology modeling, and molecular dynamics simulations to explore IRX4 homeodomain-DNA recognition mechanisms and the role of somatic mutations affecting these interactions. Using publicly available databases, gene expression of IRX4 was found in different tissues, including prostate, heart, skin, vagina, and the protein expression was found in cancer cell lines (HCT166, HEK293), B cells, ascitic fluid, and brain. Sequence conservation of the homeodomain shed light on the importance of N- and C-terminal residues involved in DNA binding. The specificity of IRX4 homodimer bound to consensus human DNA sequence was confirmed by molecular dynamics simulations, representing the role of conserved amino acids including R145, A194, N195, S190, R198, and R199 in binding to DNA. Additional N-terminal residues like T144 and G143 were also found to have specific interactions highlighting the importance of N-terminus of the homeodomain in DNA recognition. Additionally, the effects of somatic mutations, including the conserved Arginine (R145, R198, and R199) residues on DNA binding elucidated the importance of these residues in stabilizing the protein-DNA complex. Secondary structure and hydrogen bonding analysis showed the roles of specific residues (R145, T191, A194, N195, R198, and R199) in maintaining the homogeneity of the structure and its interaction with DNA. The differences in relative binding free energies of all the mutants shed light on the structural modularity of this protein and the dynamics behind protein-DNA interaction. We also have predicted that the C-terminal sequence of the IRX4 homeodomain could act as a potential cell-penetrating peptide, emphasizing the role these small peptides could play in targeting homeobox TFs.

Calculations of Absolute Solvation Free Energies with Transformato─Application to the FreeSolv Database Using the CGenFF Force Field.

We recently introduced transformato, an open-source Python package for the automated setup of large-scale calculations of relative solvation and binding free energy differences. Here, we extend the capabilities of transformato to the calculation of absolute solvation free energy differences. After careful validation against the literature results and reference calculations with the PERT module of CHARMM, we used transformato to compute absolute solvation free energies for most molecules in the FreeSolv database (621 out of 642). The force field parameters were obtained with the program cgenff (v2.5.1), which derives missing parameters from the CHARMM general force field (CGenFF v4.6). A long-range correction for the Lennard-Jones interactions was added to all computed solvation free energies. The mean absolute error compared to the experimental data is 1.12 kcal/mol. Our results allow a detailed comparison between the AMBER and CHARMM general force fields and provide a more in-depth understanding of the capabilities and limitations of the CGenFF small molecule parameters.

Chiral covalent organic framework incorporated organic polymer monolithic capillary column for enantioseparations.

A chiral covalent organic framework was synthesized, characterized, and incorporated into organic polymer monolithic capillary columns to provide chiral stationary phases for enantioseparations. The prepared monolithic capillary columns were characterized by scanning electron microscopy and elemental analysis. To obtain better enantioseparations, the columns' preparation conditions, and enantioseparation conditions were optimized. Baseline resolutions of several chiral compounds were obtained with good reproducibility and stability. Furthermore, the mechanism of chiral recognition was investigated using molecular docking with AutoDock. Docking results showed that the enantioselectivity factor rather than resolution is correlated with the binding free energy difference between enantiomers with the chiral covalent organic framework. And abundant acetoxy and nitrile groups as well as benzene rings in the chiral covalent organic framework are responsible for the enantioseparation ability of the chiral monolithic capillary columns.

Non-specific vs. specific DNA binding free energetics of a transcription factor domain protein between search and recognition.

Transcription factor (TF) proteins are key in genetic regulation by locating specific sites on the genome. It has been proposed that an optimized search can be achieved by protein alternating between 3D diffusion in the bulk and 1D diffusion along DNA in the facilitated diffusion model. While undergoing 1D diffusion, the protein can switch from a “search” mode for fast diffusion along non-specific DNA, to a “recognition” mode for protein stable binding to specific DNA. Though it was regarded that protein conformation transitions enable the search to recognition transitions, it was recently noticed that for a small TF domain protein, re-orientation of the protein on the DNA, without protein conformational changes, happens between the non-specific and specific DNA binding. We further conducted all-atom molecular dynamics simulations on the TF domain protein bound to a nonspecific or specific DNA site, to energetically confirm that the protein-DNA binding free energetics between the two systems is consistent with the “search” and “recognition”. Using both the Jarzynski equality and umbrella sampling methods pulling protein away from DNA, we obtained protein binding free energetics and a free energy difference of about 10 kBT between the two systems. However, the binding free energy difference estimated from experimental measurements was about 4 kBT on 15-bp DNA. We suggest that the discrepancy between the experimental and computational measurements can be due to DNA sequences flanking the 6-bp central specific and nonspecific binding sites. Such a proposal was also investigated through a highly simplified spherical protein model along with stochastic simulations, which well supported that flanking DNA sequences impact on overall protein dissociation kinetics and therefore on measuring binding affinity variations with specific or non-specific DNA in the central binding site.

A comparative study of receptor interactions between SARS-CoV and SARS-CoV-2 from molecular modeling

The pandemic of COVID-19 severe acute respiratory syndrome, which was fatal for millions of people worldwide, triggered the race to understand in detail the molecular mechanisms of this disease. In this work, the differences of interactions between the SARS-CoV/SARS-CoV-2 Receptor binding domain (RBD) and the human Angiotensin Converting Enzyme 2 (ACE2) receptor were studied using in silico tools. Our results show that SARS-CoV-2 RBD is more stable and forms more interactions with ACE2 than SARS-CoV. At its interface, three stable binding patterns are observed and named red-K31, green-K353 and blue-M82 according to the central ACE2 binding residue. In SARS-CoV instead, only the first two binding patches are persistently formed during the MD simulation. Our MM/GBSA calculations indicate the binding free energy difference of about 2.5 kcal/mol between SARS-CoV-2 and SARS-CoV which is compatible with the experiments. The binding free energy decomposition points out that SARS-CoV-2 RBD–ACE2 interactions of the red-K31 (-23.5~pm ~0.2~kcal/mol) and blue-M82 (-9.1~pm ~0.1~kcal/mol) patterns contribute more to the binding affinity than in SARS-CoV (-1.8~pm ~0.02~kcal/mol for red-K31), while the contribution of the green-K353 pattern is very similar in the two strains (-17.8~pm ~0.2~kcal/mol and -22.7~pm ~0.1~kcal/mol for SARS-CoV-2 and SARS-CoV, respectively). Five groups of mutations draw our attention at the RBD–ACE2 binding interface, among them, the mutation –PPA469-471/GVEG482-485 has the most important and favorable impact on SARS-CoV-2 binding to the ACE2 receptor. These results, highlighting the molecular differences in the binding between the two viruses, contribute to the common knowledge about the new corona virus and to the development of appropriate antiviral treatments, addressing the necessity of ongoing pandemics.

Relative binding free energy calculations with transformato: A molecular dynamics engine-independent tool.

We present the software package transformato for the setup of large-scale relative binding free energy calculations. Transformato is written in Python as an open source project (https://github.com/wiederm/transformato); in contrast to comparable tools, it is not closely tied to a particular molecular dynamics engine to carry out the underlying simulations. Instead of alchemically transforming a ligand L 1 directly into another L 2, the two ligands are mutated to a common core. Thus, while dummy atoms are required at intermediate states, in particular at the common core state, none are present at the physical endstates. To validate the method, we calculated 76 relative binding free energy differences for five protein–ligand systems. The overall root mean squared error to experimental binding free energies is 1.17 kcal/mol with a Pearson correlation coefficient of 0.73. For selected cases, we checked that the relative binding free energy differences between pairs of ligands do not depend on the choice of the intermediate common core structure. Additionally, we report results with and without hydrogen mass reweighting. The code currently supports OpenMM, CHARMM, and CHARMM/OpenMM directly. Since the program logic to choose and construct alchemical transformation paths is separated from the generation of input and topology/parameter files, extending transformato to support additional molecular dynamics engines is straightforward.

Wetting Properties of Clathrate Hydrates in the Presence of Polycyclic Aromatic Compounds: Evidence of Ion-Specific Effects

Polycyclic aromatic hydrocarbons (PAHs) have attracted remarkable multidisciplinary attention due to their intriguing π–π stacking configurations, showing enormous opportunity for their use in a variety of advanced applications. To secure progress, detailed knowledge on PAHs’ interfacial properties is required. Employing molecular dynamics, we probe the wetting properties of brine droplets (KCl, NaCl, and CaCl2) on sII methane–ethane hydrate surfaces immersed in various oil solvents. Our simulations show synergistic effects due to the presence of PAHs compounded by ion-specific effects. Our analysis reveals phenomenological correlations between the wetting properties and a combination of the binding free-energy difference and entropy changes upon oil solvation for PAHs at oil/brine and oil/hydrate interfaces. The detailed thermodynamic analysis conducted upon the interactions between PAHs and various interfaces identifies molecular-level mechanisms responsible for wettability alterations, which could be applicable for advancing applications in optics, microfluidics, biotechnology, medicine, as well as hydrate management.

SARS-CoV-2 and MERS-CoV Spike Protein Binding Studies Support Stable Mimic of Bound 9-O-Acetylated Sialic Acids.

Many disease-causing viruses target sialic acids (Sias), a class of nine-carbon sugars known to coat the surface of many cells, including those in the lungs. Human beta coronaviridae, known for causing respiratory tract diseases, often bind Sias, and some preferentially bind to those with 9-O-Ac-modification. Currently, co-binding of SARS-CoV-2, a beta coronavirus responsible for the COVID-19 pandemic, to human Sias has been reported and its preference towards α2-3-linked Neu5Ac has been shown. Nevertheless, O-acetylated Sias-protein binding studies are difficult to perform, due to the ester lability. We studied the binding free energy differences between Neu5,9Ac2α2-3GalβpNP and its more stable 9-NAc mimic binding to SARS-CoV-2 spike protein using molecular dynamics and alchemical free energy simulations. We identified multiple Sia-binding pockets, including two novel sites, with similar binding affinities to those of MERS-CoV, a known co-binder of sialic acid. In our binding poses, 9-NAc and 9-OAc Sias bind similarly, suggesting an experimentally reasonable mimic to probe viral mechanisms.

The performance of ensemble-based free energy protocols in computing binding affinities to ROS1 kinase

Optimization of binding affinities for compounds to their target protein is a primary objective in drug discovery. Herein we report on a collaborative study that evaluates a set of compounds binding to ROS1 kinase. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to rank the binding free energies. The predicted binding free energies from ESMACS simulations show good correlations with experimental data for subsets of the compounds. Consistent binding free energy differences are generated for TIES and ESMACS. Although an unexplained overestimation exists, we obtain excellent statistical rankings across the set of compounds from the TIES protocol, with a Pearson correlation coefficient of 0.90 between calculated and experimental activities.

Improved Binding Affinity of Omicron's Spike Protein for the Human Angiotensin-Converting Enzyme 2 Receptor Is the Key behind Its Increased Virulence.

The new variant of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), Omicron, has been quickly spreading in many countries worldwide. Compared to the original virus, Omicron is characterized by several mutations in its genomic region, including the spike protein’s receptor-binding domain (RBD). We have computationally investigated the interaction between the RBD of both the wild type and Omicron variant of SARS-CoV-2 with the human angiotensin-converting enzyme 2 (hACE2) receptor using molecular dynamics and molecular mechanics-generalized Born surface area (MM-GBSA)-based binding free energy calculations. The mode of the interaction between Omicron’s RBD with the hACE2 receptor is similar to the original SARS-CoV-2 RBD except for a few key differences. The binding free energy difference shows that the spike protein of Omicron has an increased affinity for the hACE2 receptor. The mutated residues in the RBD showed strong interactions with a few amino acid residues of hACE2. More specifically, strong electrostatic interactions (salt bridges) and hydrogen bonding were observed between R493 and R498 residues of the Omicron RBD with D30/E35 and D38 residues of the hACE2, respectively. Other mutated amino acids in the Omicron RBD, e.g., S496 and H505, also exhibited hydrogen bonding with the hACE2 receptor. A pi-stacking interaction was also observed between tyrosine residues (RBD-Tyr501: hACE2-Tyr41) in the complex, which contributes majorly to the binding free energies and suggests that this is one of the key interactions stabilizing the formation of the complex. The resulting structural insights into the RBD:hACE2 complex, the binding mode information within it, and residue-wise contributions to the free energy provide insight into the increased transmissibility of Omicron and pave the way to design and optimize novel antiviral agents.

SARS-CoV-2 Membrane Protein: From Genomic Data to Structural New Insights.

Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) is composed of four structural proteins and several accessory non-structural proteins. SARS-CoV-2’s most abundant structural protein, Membrane (M) protein, has a pivotal role both during viral infection cycle and host interferon antagonism. This is a highly conserved viral protein, thus an interesting and suitable target for drug discovery. In this paper, we explain the structural nature of M protein homodimer. To do so, we developed and applied a detailed and robust in silico workflow to predict M protein dimeric structure, membrane orientation, and interface characterization. Single Nucleotide Polymorphisms (SNPs) in M protein were retrieved from over 1.2 M SARS-CoV-2 genomes and proteins from the Global Initiative on Sharing All Influenza Data (GISAID) database, 91 of which were located at the predicted dimer interface. Among those, we identified SNPs in Variants of Concern (VOC) and Variants of Interest (VOI). Binding free energy differences were evaluated for dimer interfacial SNPs to infer mutant protein stabilities. A few high-prevalent mutated residues were found to be especially relevant in VOC and VOI. This realization may be a game-changer to structure-driven formulation of new therapeutics for SARS-CoV-2.

Computational prediction of the effect of mutations in the receptor-binding domain on the interaction between SARS-CoV-2 and human ACE2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 continues to mutate. Numerous studies have indicated that this viral mutation, particularly in the receptor-binding domain area, may increase the viral affinity for human angiotensin-converting enzyme 2 (hACE2), the receptor for viral entry into host cells, thereby increasing viral virulence and transmission. In this study, we investigated the binding affinity of SARS-CoV-2 variants (Delta plus, Iota, Kappa, Mu, Lambda, and C.1.2) on hACE2 using computational modeling with a protein-protein docking approach. The simulation results indicated that there were differences in the interactions between the RBD and hACE2, including hydrogen bonding, salt bridge interactions, non-bonded interactions, and binding free energy differences among these variants. Molecular dynamics simulations revealed that mutations in the RBD increase the stability of the hACE2-spike protein complex relative to the wild type, following the global stability trend and increasing the binding affinity. The value of binding-free energy calculated using molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) indicated that all mutations in the spike protein increased the contagiousness of SARS-CoV-2 variants. The findings of this study provide a foundation for developing effective interventions against these variants. Computational modeling elucidates that the spike protein of SARS-CoV-2 variants binds considerably stronger than the wild-type to hACE2.

Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7.

New variants of SARS-CoV-2 are being reported worldwide. The World Health Organization has reported Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2) and Omicron (B.1.1.529) as the variants of concern. There are speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19 occurs through the interaction of the spike protein's receptor-binding domain (RBD) with the peptidase domain of the human ACE-2 (hACE-2) receptor. This study aims to get a molecular-level understanding of the mechanism behind the increased infection rate in the alpha variant. We have computationally studied the spike protein interaction in both the wild-type and B.1.1.7 variant with the hACE-2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The binding free energy difference shows that the mutant variant of the spike protein has increased binding affinity for the hACE-2 receptor (i.e. ΔG(N501Y,A570D) is in the range -7.2 to -7.6 kcal mol-1) and the results were validated using Density functional theory. We demonstrate that with the use of state-of-the-art computational approaches, we can, in advance, predict the virulent nature of variants of SARS-CoV-2 and alert the world healthcare system.

The development of an Amber-compatible organosilane force field for drug-like small molecules.

As members of the group IVA elements, silicon and carbon have long been thought of as isosteres of each other in drug design. However, the lack of silicon parameters in current main stream force fields hinders the computational study of this important element in drug discovery. Thus, in this study, we attempted to supplement the parameters of organosilanes in the General Amber Force Field (GAFF2). The parameters have been designed following the principles of GAFF2 to make it compatible with the Amber force field family. The accuracy of the parameters was discussed by comparing the pair interaction energy, the liquid properties, and the structures and alchemical binding free energy differences for a set of protein-ligand complexes.

Quantum chemical calculations for elucidating chiral resolution mechanism of chiral covalent organic frameworks 6 chromatographic stationary phase

With the aim of exploring the chiral resolution mechanism of the chiral covalent organic frameworks 6 (CCOF6) chromatographic stationary phase, the ORCA program was used to optimize the structures of CCOF6 and four pairs of enantiomers. Then the molecular docking of CCOF6 with each enantiomer was performed by AutoDock program to obtain the initial interaction configurations of CCOF6 with four pairs of enantiomers. Energy calculations of the initial configurations were performed by ORCA program (B3LYP functional with DFT-D3 correction, def2-TZVP orbital basis set, def2/J auxiliary basis set, and RIJCOSX used to accelerate the calculation) to determine the interaction configurations of CCOF6 with four pairs of enantiomers and to obtain the corresponding binding free energy and binding free energy difference. Wave function analyses of ORCA calculation results were performed by Multiwfn program, and the weak interactions between CCOF6 and the four pairs of enantiomers were visualized by Visual Molecular Dynamics program. The results showed the following:① for calculating the binding free energies of CCOF6 and the four pairs of enantiomers, the ORCA method with the solvation effect was more accurate than the AutoDock method as well as the ORCA method without the solvation effect; ② the greater the absolute value of the binding free energy difference between the CCOF6 stationary phase and enantiomers, the greater was the selectivity factor of the enantiomers but not the resolution of the enantiomers; ③ the hydroxyl group of S-1-phenyl-1-propanol interacted with the ether bond of CCOF6, but the hydroxyl groups of the other enantiomers all interacted with the carbonyl groups of CCOF6, and the binding force between S-1-phenyl-1-propanol and CCOF6 was the weakest; ④ from the peak time of the enantiomer and its binding free energy with CCOF6, it was confirmed that the elution ability of n-hexane/isopropanol for 1-phenyl-1-propanol was the weakest, followed by the elution ability for 1-phenyl-2-propanol; ⑤ the peak time of S-1-phenyl-1-propanol was longer than that of R-1-phenyl-1-propanol, while for the other enantiomers, the peak time of the R-enantiomers was longer than that of the S-enantiomers.

Optimizing enzymatic catalysts for rapid turnover of substrates with low enzyme sequestration.

Enzymes are central to both metabolism and information processing in cells. In both cases, an enzyme's ability to accelerate a reaction without being consumed in the reaction is crucial. Nevertheless, enzymes are transiently sequestered when they bind to their substrates; this sequestration limits activity and potentially compromises information processing and signal transduction. In this article, we analyse the mechanism of enzyme-substrate catalysis from the perspective of minimizing the load on the enzymes through sequestration, while maintaining at least a minimum reaction flux. In particular, we ask: which binding free energies of the enzyme-substrate and enzyme-product reaction intermediates minimize the fraction of enzymes sequestered in complexes, while sustaining a certain minimal flux? Under reasonable biophysical assumptions, we find that the optimal design will saturate the bound on the minimal flux and reflects a basic trade-off in catalytic operation. If both binding free energies are too high, there is low sequestration, but the effective progress of the reaction is hampered. If both binding free energies are too low, there is high sequestration, and the reaction flux may also be suppressed in extreme cases. The optimal binding free energies are therefore neither too high nor too low, but in fact moderate. Moreover, the optimal difference in substrate and product binding free energies, which contributes to the thermodynamic driving force of the reaction, is in general strongly constrained by the intrinsic free-energy difference between products and reactants. Both the strategies of using a negative binding free-energy difference to drive the catalyst-bound reaction forward and of using a positive binding free-energy difference to enhance detachment of the product are limited in their efficacy.