Molecular Dynamics Free Energy Perturbation Research Articles

Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability.

Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.

Uncovering the Critical Factors that Enable Extractive Desulfurization of Fuels in Ionic Liquids and Deep Eutectic Solvents from Simulations.

Environmental regulatory agencies have implemented stringent restrictions on the permissible levels of sulfur compounds in fuel to reduce harmful emissions and improve air quality. Problematically, traditional desulfurization methods have shown low effectiveness in the removal of refractory sulfur compounds, e.g., thiophene (TS), dibenzothiophene (DBT), and 4-methyldibenzothiophene (MDBT). In this work, molecular dynamics (MD) simulations and free energy perturbation (FEP) have been applied to investigate the use of ionic liquids (ILs) and deep eutectic solvents (DESs) as efficient TS/DBT/MDBT extractants. For the IL simulations, the selected cation was 1-butyl-3-methylimidazolium [BMIM] and the anions included chloride [Cl], thiocyanate [SCN], tetrafluoroborate [BF4], hexafluorophosphate [PF6], and bis(trifluoromethylsulfonyl)amide [NTf2]. The DESs were composed of choline chloride with ethylene glycol (CCEtg) or with glycerol (CCGly). Calculation of excess chemical potentials predicted the ILs to be more promising extractants with energies lower by 1-3 kcal/mol compared to DESs. Increasing IL anion size was positively correlated to enhanced solvation of S-compounds, which was influenced by energetically dominant solute-anion interactions and favorable solute-[BMIM] π-π stacking. For the DESs, the solvent components offered a range of synergistic, yet comparatively weaker, electrostatic interactions that included hydrogen bonding and cation-π interactions. An in-depth analysis of the structure of IL and DES systems is presented, along with a discussion of the critical factors behind experimental trends of S-compound extraction efficiency.

Machine learning reveals the critical interactions for SARS-CoV-2 spike protein binding to ACE2

A novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread throughout the world. SARS-CoV-2 is less deadly but more transmissible than SARS-CoV, which appeared in late 2002. Both viruses first engage with their host by binding to the same target protein, ACE2. Receptor-binding domain (RBD) is the key that allows the virus to dock to the targeted host protein, ACE2, to gain entry into cells. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses.

Surface salt bridges contribute to the extreme thermal stability of an FN3-like domain from a thermophilic bacterium.

This study uses differential scanning calorimetry, X-ray crystallography, and molecular dynamics simulations to investigate the structural basis for the high thermal stability (melting temperature 97.5°C) of a FN3-like protein domain from thermophilic bacteria Thermoanaerobacter tengcongensis (FN3tt). FN3tt adopts a typical FN3 fold with a three-stranded beta sheet packing against a four-stranded beta sheet. We identified three solvent exposed arginine residues (R23, R25, and R72), which stabilize the protein through salt bridge interactions with glutamic acid residues on adjacent strands. Alanine mutation of the three arginine residues reduced melting temperature by up to 22°C. Crystal structures of the wild type (WT) and a thermally destabilized (∆Tm -19.7°C) triple mutant (R23L/R25T/R72I) were found to be nearly identical, suggesting that the destabilization is due to interactions of the arginine residues. Molecular dynamics simulations showed that the salt bridge interactions in the WT were stable and provided a dynamical explanation for the cooperativity observed between R23 and R25 based on calorimetry measurements. In addition, folding free energy changes computed using free energy perturbation molecular dynamics simulations showed high correlation with melting temperature changes. This work is another example of surface salt bridges contributing to the enhanced thermal stability of thermophilic proteins. The molecular dynamics simulation methods employed in this study may be broadly useful for in silico surface charge engineering of proteins.

Molecular dynamic insight into solubility of H2S in ionic liquids [emim][BF4], [emim][OTf] and [emim][Tf2N

Natural gas sweetening is one of the important processes in petroleum industry. Ionic liquids (ILs) as a new class of compounds are an alternative to conventional solvents to achieve this goal. In this study, the solubility of H2S gas in ionic liquids 1-Ethyl-3-methylimidazolium tetrafluoroborate ([emim][BF4]), 1-Ethyl-3-methylimidazolium trifluoromethanesulfonate ([emim][OTf]) and 1-Ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide was calculated based on the excess chemical potential energy by molecular dynamics free energy perturbation (FEP) technique. In this regard, validation was carried out for force fields of gas and ILs. Two force fields, All-Atom (A-A) and United-Atom (U-A), were compared to calculate the H2S solubility in the ILs. The performance of A-A force field was better for [emim][BF4] and [emim][OTf]; whereas, that of U-A force field for [emim][Tf2N]. The calculated Henry’s constant and chemical potential energy were in a good agreement with experimental data. The results showed that higher negative potential energy resulted in higher molar fraction and the ionic liquid [emim][BF4] had the best performance for H2S removal from a gas stream.

Machine Learning Reveals the Critical Interactions for SARS-CoV-2 Spike Protein Binding to ACE2.

SARS-CoV and SARS-CoV-2 bind to the human ACE2 receptor in practically identical conformations, although several residues of the receptor-binding domain (RBD) differ between them. Herein, we have used molecular dynamics (MD) simulations, machine learning (ML), and free-energy perturbation (FEP) calculations to elucidate the differences in binding by the two viruses. Although only subtle differences were observed from the initial MD simulations of the two RBD–ACE2 complexes, ML identified the individual residues with the most distinctive ACE2 interactions, many of which have been highlighted in previous experimental studies. FEP calculations quantified the corresponding differences in binding free energies to ACE2, and examination of MD trajectories provided structural explanations for these differences. Lastly, the energetics of emerging SARS-CoV-2 mutations were studied, showing that the affinity of the RBD for ACE2 is increased by N501Y and E484K mutations but is slightly decreased by K417N.

Toward Physics-Based Solubility Computation for Pharmaceuticals to Rival Informatics.

We demonstrate that physics-based calculations of intrinsic aqueous solubility can rival cheminformatics-based machine learning predictions. A proof-of-concept was developed for a physics-based approach via a sublimation thermodynamic cycle, building upon previous work that relied upon several thermodynamic approximations, notably the 2RT approximation, and limited conformational sampling. Here, we apply improvements to our sublimation free-energy model with the use of crystal phonon mode calculations to capture the contributions of the vibrational modes of the crystal. Including these improvements with lattice energies computed using the model-potential-based Ψmol method leads to accurate estimates of sublimation free energy. Combining these with hydration free energies obtained from either molecular dynamics free-energy perturbation simulations or density functional theory calculations, solubilities comparable to both experiment and informatics predictions are obtained. The application to coronene, succinic acid, and the pharmaceutical desloratadine shows how the methods must be adapted for the adoption of different conformations in different phases. The approach has the flexibility to extend to applications that cannot be covered by informatics methods.

Inositol Phospholipid Interactions with Inward Rectifier Potassium Channels and Their Role in Disease

Ion channels are frequently modulated by specific protein-lipid interactions in the phospholipid bilayer. The activation of human inward rectifying potassium (hKir) channels by phosphoinositides (PI) has been well characterised in biophysical studies. Here, we provide an extensive application of a coarse-grained molecular dynamics free-energy perturbation (CG-MD-FEP) methodology to capture the energetics of binding of PI lipids to hKir channels. By using either a single- or multi-step protocol, we establish a consistent value for the binding of PIP2 to hKir channels, relative to the binding of the bulk phosphatidylcholine phospholipid and in the presence of anionic phospholipid such as phosphatidylserine (PS). By perturbing amino acid side chains on hKir6.2, we show that the neonatal diabetes mutation E179K has increased PIP2 affinity, while the congenital hyperinsulinism mutation K67N results in a reduced affinity. This is in good agreement with electrophysiological studies showing the E179K mutant exhibits a reduction in neomycin sensitivity, which implies that PIP2 binds more tightly to E179K mutant channels. We conclude that our application provides a valuable method to compare affinities between lipid species, and for annotating amino acid side chains within lipid-binding pockets.

Evaluating inositol phospholipid interactions with inward rectifier potassium channels and characterising their role in disease

Membrane proteins are frequently modulated by specific protein-lipid interactions. The activation of human inward rectifying potassium (hKir) channels by phosphoinositides (PI) has been well characterised. Here, we apply a coarse-grained molecular dynamics free-energy perturbation (CG-FEP) protocol to capture the energetics of binding of PI lipids to hKir channels. By using either a single- or multi-step approach, we establish a consistent value for the binding of PIP2 to hKir channels, relative to the binding of the bulk phosphatidylcholine phospholipid. Furthermore, by perturbing amino acid side chains on hKir6.2, we show that the neonatal diabetes mutation E179K increases PIP2 affinity, while the congenital hyperinsulinism mutation K67N results in a reduced affinity. We show good agreement with electrophysiological data where E179K exhibits a reduction in neomycin sensitivity, implying that PIP2 binds more tightly E179K channels. This illustrates the application of CG-FEP to compare affinities between lipid species, and for annotating amino acid residues.

CHARMM-GUI Free Energy Calculator for Absolute and Relative Ligand Solvation and Binding Free Energy Simulations.

Alchemical free energy simulations have long been utilized to predict free energy changes for binding affinity and solubility of small molecules. However, while the theoretical foundation of these methods is well established, seamlessly handling many of the practical aspects regarding the preparation of the different thermodynamic end states of complex molecular systems and the numerous processing scripts often remains a burden for successful applications. In this work, we present CHARMM-GUI Free Energy Calculator (http://www.charmm-gui.org/input/fec) that provides various alchemical free energy perturbation molecular dynamics (FEP/MD) systems with input and post-processing scripts for NAMD and GENESIS. Four submodules are available: Absolute Ligand Binder (for absolute ligand binding FEP/MD), Relative Ligand Binder (for relative ligand binding FEP/MD), Absolute Ligand Solvator (for absolute ligand solvation FEP/MD), and Relative Ligand Solvator (for relative ligand solvation FEP/MD). Each module is designed to build multiple systems of a set of selected ligands at once for high-throughput FEP/MD simulations. The capability of Free Energy Calculator is illustrated by absolute and relative solvation FEP/MD of a set of ligands and absolute and relative binding FEP/MD of a set of ligands for T4-lysozyme in solution and the adenosine A2A receptor in a membrane. The calculated free energy values are overall consistent with the experimental and published free energy results (within ∼1 kcal/mol). We hope that Free Energy Calculator is useful to carry out high-throughput FEP/MD simulations in the field of biomolecular sciences and drug discovery.

Discovery of Novel Tankyrase Inhibitors through Molecular Docking-Based Virtual Screening and Molecular Dynamics Simulation Studies.

Tankyrase enzymes (TNKS), a core part of the canonical Wnt pathway, are a promising target in the search for potential anti-cancer agents. Although several hundreds of the TNKS inhibitors are currently known, identification of their novel chemotypes attracts considerable interest. In this study, the molecular docking and machine learning-based virtual screening techniques combined with the physico-chemical and ADMET (absorption, distribution, metabolism, excretion, toxicity) profile prediction and molecular dynamics simulations were applied to a subset of the ZINC database containing about 1.7 M commercially available compounds. Out of seven candidate compounds biologically evaluated in vitro for their inhibition of the TNKS2 enzyme using immunochemical assay, two compounds have shown a decent level of inhibitory activity with the IC50 values of less than 10 nM and 10 μM. Relatively simple scores based on molecular docking or MM-PBSA (molecular mechanics, Poisson-Boltzmann, surface area) methods proved unsuitable for predicting the effect of structural modification or for accurate ranking of the compounds based on their binding energies. On the other hand, the molecular dynamics simulations and Free Energy Perturbation (FEP) calculations allowed us to further decipher the structure-activity relationships and retrospectively analyze the docking-based virtual screening performance. This approach can be applied at the subsequent lead optimization stages.

Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase.

Starting from late 2019, the coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures, and supporting apparatuses. Recently, because of its positive results in clinical trials, remdesivir was approved by the Food and Drug Administration to treat COVID-19 through Emergency Use Authorization. Here, we used molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). We first constructed the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identity of 95.8%). We then built a putative preinsertion binding structure by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp without the RNA template. The putative binding structure was further optimized with molecular dynamics simulations. The resulting stable preinsertion state of remdesivir appeared to form hydrogen bonds with the RNA template when aligned with the newly solved cryo-EM structure of SARS-CoV-2 RdRp. The relative binding free energy between remdesivir and ATP was calculated to be −2.80 ± 0.84 kcal/mol, where remdesivir bound much stronger to SARS-CoV-2 RdRp than the natural substrate ATP. The ∼100-fold improvement in the Kd from remdesivir over ATP indicates an effective replacement of ATP in blocking of the RdRp preinsertion site. Key residues D618, S549, and R555 are found to be the contributors to the binding affinity of remdesivir. These findings suggest that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA replication, with key residues also identified for future lead optimization and/or drug resistance studies.

Evolution of Angiotensin Peptides and Peptidomimetics as Angiotensin II Receptor Type 2 (AT2) Receptor Agonists.

Angiotensin II receptor type 1 and 2 (AT1R and AT2R) are two G-protein coupled receptors that mediate most biological functions of the octapeptide Angiotensin II (Ang II). AT2R is upregulated upon tissue damage and its activation by selective AT2R agonists has become a promising approach in the search for new classes of pharmaceutical agents. We herein analyzed the chemical evolution of AT2R agonists starting from octapeptides, through shorter peptides and peptidomimetics to the first drug-like AT2R-selective agonist, C21, which is in Phase II clinical trials and aimed for idiopathic pulmonary fibrosis. Based on the recent crystal structures of AT1R and AT2R in complex with sarile, we identified a common binding model for a series of 11 selected AT2R agonists, consisting of peptides and peptidomimetics of different length, affinity towards AT2R and selectivity versus AT1R. Subsequent molecular dynamics simulations and free energy perturbation (FEP) calculations of binding affinities allowed the identification of the bioactive conformation and common pharmacophoric points, responsible for the key interactions with the receptor, which are maintained by the drug-like agonists. The results of this study should be helpful and facilitate the search for improved and even more potent AT2R-selective drug-like agonists.

Inhibition Mechanisms of Rhodococcus Erythropolis 2'-Hydroxybiphenyl-2-sulfinate Desulfinase (DszB).

Naturally occurring enzymatic pathways enable highly specific, rapid thiophenic sulfur cleavage occurring at ambient temperature and pressure, which may be harnessed for the desulfurization of petroleum-based fuel. One pathway found in bacteria is a four-step catabolic pathway (the 4S pathway) converting dibenzothiophene (DBT), a common crude oil contaminant, into 2-hydroxybiphenyl (HBP) without disrupting the carbon-carbon bonds. 2'-Hydroxybiphenyl-2-sulfinate desulfinase (DszB), the rate-limiting enzyme in the enzyme cascade, is capable of selectively cleaving carbon-sulfur bonds. Accordingly, understanding the molecular mechanisms of DszB activity may enable development of the cascade as industrial biotechnology. Based on crystallographic evidence, we hypothesized that DszB undergoes an active site conformational change associated with the catalytic mechanism. Moreover, we anticipated this conformational change is responsible, in part, for enhancing product inhibition. Rhodococcus erythropolis IGTS8 DszB was recombinantly produced and purified via Escherichia coli BL21 to test these hypotheses. Activity and the resulting conformational change of DszB in the presence of HBP were evaluated. The activity of recombinant DszB was comparable to the natively expressed enzyme and was inhibited via competitive binding of the product, HBP. Using circular dichroism, global changes in DszB conformation were monitored in response to HBP concentration, which indicated that both product and substrate produced similar structural changes. Molecular dynamics (MD) simulations and free energy perturbation with Hamiltonian replica exchange molecular dynamics (FEP/λ-REMD) calculations were used to investigate the molecular-level phenomena underlying the connection between conformation change and kinetic inhibition. In addition to the HBP, MD simulations of DszB bound to common, yet structurally diverse, crude oil contaminants 2',2-biphenol (BIPH), 1,8-naphthosultam (NTAM), 2-biphenyl carboxylic acid (BCA), and 1,8-naphthosultone (NAPO) were performed. Analysis of the simulation trajectories, including root-mean-square fluctuation (RMSF), center of mass (COM) distances, and strength of nonbonded interactions, when compared with FEP/λ-REMD calculations of ligand binding free energy, showed excellent agreement with experimentally determined inhibition constants. Together, the results show that the combination of a molecule's hydrophobicity and nonspecific interactions with nearby functional groups contributes to a competitive inhibition mechanism that locks DszB in a closed conformation and precludes substrate access to the active site.

Ranking Reversible Covalent Drugs: From Free Energy Perturbation to Fragment Docking.

Reversible covalent inhibitors have drawn increasing attention in drug design, as they are likely more potent than noncovalent inhibitors and less toxic than covalent inhibitors. Despite those advantages, the computational prediction of reversible covalent binding presents a formidable challenge because the binding process consists of multiple steps and quantum mechanics (QM) level calculation is needed to estimate the covalent binding free energy. It has been shown that the dissociation rates and the equilibrium dissociation constants vary significantly even with similar warheads, due to noncovalent interactions. We have previously used a simplistic two-state model for predicting the relative binding selectivity of reversible covalent inhibitors ( J. Am. Chem. Soc. 2017, 139 , 17945 ). Here we go beyond binding selectivity and demonstrate that it is possible to use free energy perturbation (FEP) molecular dynamics (MD) to calculate the overall reversible covalent binding using a specially designed thermodynamic cycle. We show that FEP can predict the varying binding free energies of the analogs sharing a common warhead. More importantly, our results revealed that the chemical modification away from warhead alters the binding affinity at both noncovalent and covalent binding states, and the computational prediction can be improved by considering the binding free energy of both states. Furthermore, we explored the possibility of using a more rapid computational method, site-identification by ligand competitive saturation (SILCS), to rank the same set of reversible covalent inhibitors. We found that the fragment docking to a set of precomputed fragment maps produces a reasonable ranking. In conclusion, two independent approaches provided consistent results that the covalent binding state is suitable for the initial ranking of the reversible covalent drug candidates. For lead-optimization, the FEP approach designed here can provide more rigorous and detailed information regarding how much the covalent and noncovalent binding states are contributing to the overall binding affinity, thus offering a new avenue for fine-tuning the noncovalent interactions for optimizing reversible covalent drugs.

Lanosterol Disrupts Aggregation of Human γD-Crystallin by Binding to the Hydrophobic Dimerization Interface.

Cataracts are a leading cause of vision impairment, which stem from the misfolding and aggregation of crystallins in the eye lens. Despite its prevalence and severity, the detailed mechanism by which misfolded crystallins aggregate into cataracts remains elusive. Recently, in vitro and in vivo experiments demonstrated that lanosterol, a steroid-type compound found in human and animal eyes, can not onlyprevent cataract formation but also reverse the formation. Inspired by these experimental observations, we investigate the preventive activity of lanosterol in the aggregate formation of human γD-crystallins (HγD-Crys) using all atom molecular dynamics (MD) simulation and free energy perturbation (FEP) techniques. Our results reveal that lanosterol preferentially binds to the HγD-Crys hydrophobic dimerization interface, in particular, to the structured C-terminus (near residues 135-165) with a stronger binding affinity than the unfolded N-terminus. Furthermore, we observe that the C-terminal binding is more favorable than lanosterol self-aggregation, further attesting to lanosterol's efficacy. Finally, we compare the binding free energy of lanosterol with cholesterol using alchemical transformation and discuss the possible correlation of the molecular geometry of steroids with binding affinity.

Estimating Atomic Contributions to Hydration and Binding Using Free Energy Perturbation.

We present a general method called atom-wise free energy perturbation (AFEP), which extends a conventional molecular dynamics free energy perturbation (FEP) simulation to give the contribution to a free energy change from each atom. AFEP is derived from an expansion of the Zwanzig equation used in the exponential averaging method by defining that the system total energy can be partitioned into contributions from each atom. A partitioning method is assumed and used to group terms in the expansion to correspond to individual atoms. AFEP is applied to six example free energy changes to demonstrate the method. Firstly, the hydration free energies of methane, methanol, methylamine, methanethiol, and caffeine in water. AFEP highlights the atoms in the molecules that interact favorably or unfavorably with water. Finally AFEP is applied to the binding free energy of human immunodeficiency virus type 1 protease to lopinavir, and AFEP reveals the contribution of each atom to the binding free energy, indicating candidate areas of the molecule to improve to produce a more strongly binding inhibitor. FEP gives a single value for the free energy change and is already a very useful method. AFEP gives a free energy change for each "part" of the system being simulated, where part can mean individual atoms, chemical groups, amino acids, or larger partitions depending on what the user is trying to measure. This method should have various applications in molecular dynamics studies of physical, chemical, or biochemical phenomena, specifically in the field of computational drug discovery.

Investigating the effect of mutation on the thermo stability of GB1 protein

The thermo stability of wild-type and mutants of the B1 domain of Protein G (GB1 protein) have been studied using molecular dynamics simulation and free energy perturbation simulation. This research is aimed to examine what residue or what interaction that has a major role in the thermo stability of GB1 protein thermo stability by using the point mutation method. Based on the analysis, the unfolding of wild-type protein occurred in 500 K simulation at 704 ps. The mutations were chosen based on the changes in some analysis parameters and the calculated net solvation free energy change. It was found that a simple replacement of a positively charged residue in the β-sheet (K4S) decreases the stability of GB1 protein (unfolding at 452 ps), while the replacement of a negatively charged residue in the α-helix (E27G) increases the stability (unfolding at 846 ps). It was also found that the K4A mutation will break the α-helix and all β-sheet into the coil and turn. All those results suggest that the non-bonded interaction has the major role in the thermo stability of GB1 protein with the β-sheets were identified as the most important structure in the thermo stability of GB1 protein..

Predicting Binding Free Energies of PDE2 Inhibitors. The Difficulties of Protein Conformation

A congeneric series of 21 phosphodiesterase 2 (PDE2) inhibitors are reported. Crystal structures show how the molecules can occupy a ‘top-pocket’ of the active site. Molecules with small substituents do not enter the pocket, a critical leucine (Leu770) is closed and water molecules are present. Large substituents enter the pocket, opening the Leu770 conformation and displacing the waters. We also report an X-ray structure revealing a new conformation of the PDE2 active site domain. The relative binding affinities of these compounds were studied with free energy perturbation (FEP) methods and it represents an attractive real-world test case. In general, the calculations could predict the energy of small-to-small, or large-to-large molecule perturbations. However, accurately capturing the transition from small-to-large proved challenging. Only when using alternative protein conformations did results improve. The new X-ray structure, along with a modelled dimer, conferred stability to the catalytic domain during the FEP molecular dynamics (MD) simulations, increasing the convergence and thereby improving the prediction of ΔΔG of binding for some small-to-large transitions. In summary, we found the most significant improvement in results when using different protein structures, and this data set is useful for future free energy validation studies.

Origin of Ion Specificity of Telomeric DNA G-Quadruplexes Investigated by Free-Energy Simulations

Telomeric DNA consists of tandem repeats of the sequence d(TTAGGG) that form G-quadruplex structures made of stacked guanines with monovalent cations bound at a central cavity. Although different ions can stabilize a G-quadruplex structure, the preferred bound ions are typically K+ or Na+. Several different strand-folding topologies have been reported for Q-quadruplexes formed from telomeric repeats depending on DNA length and ion solution condition. This suggests a possible dependence of the ion selectivity of the central pore on the folding topology of the quadruplex. Molecular dynamics free energy perturbation has been employed to systematically study the relative affinity of the central quadruplex pore for different cation types and the associated energetic and solvation contributions to ion selectivity. The calculations have been performed on two different common quadruplex folding topologies. For both topologies, the same ion selectivity was found with a preference for K+ followed by Rb+ and Na+, which agrees with the experimentally determined preference for most investigated quadruplexes. The selectivity is determined by a balance between attractive Coulomb interactions and loss of hydration but also modulated by van der Waals contributions. Specificity is mediated by the central guanines and no significant contribution of the nucleic acid backbone. The simulations indicate that different topologies might be stabilized by ions bound at the surface or alternative sites of the quadruplex because the ion specificity of the central pore does not depend on the strand folding topology.