Free Energy Perturbation Method Research Articles

The role of the membrane in driving CLC-ec1 dimerization.

Most membrane proteins oligomerize in the membrane. In the case of the bacterial chloride/proton antiporter CLC-ec1, the role of highly stable homodimers is not understood since individual CLC-ec1 protomers can maintain the chloride/proton transport stoichiometry. In a previous study, we used experimental and computational approaches to show that in C16:0/C18:1 palmitoyl-oleoyl lipid membranes, the monomeric state of CLC-ec1 creates a membrane defect that is ≈ 8 Å thinner than the bulk. However, in the dimer state, the membrane is restored to a near-native bilayer thickness and structure. We hence proposed that the dimerization is driven by the larger free-energy cost of lipid solvation of the dissociated monomers. Here, we carry out coarse-grained molecular dynamics simulations with umbrella sampling and free energy perturbation methods to quantify the membrane's contribution to free energy of dimerization. In the case of CLC-ec1, addition of 30% C12:0 di-lauryl chain lipids stabilizes the free energy of the monomeric state by ≈ 2 kcal/mole, in qualitative agreement with our experimental observations. Therefore, we have a physical model of how changes in lipid composition can regulate self-assembly reactions of membrane proteins in membranes. This work was partially performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-840782.

MemCross: Accelerated Weight Histogram method to assess membrane permeability

Passive permeation events across biological membranes are determining steps in the pharmacokinetics of xenobiotics. To reach an accurate and rapid prediction of membrane permeation coefficients of drugs is a complex challenge, which can efficiently support drug discovery. Such predictions are indeed highly valuable as they may guide the selection of potential leads with optimum bioavailabilities prior to synthesis. Theoretical models exist to predict these coefficients. Many of them are based on molecular dynamics (MD) simulations, which allow calculation of permeation coefficients through the evaluation of both the potential of mean force (PMF) and the diffusivity profiles. However, these simulations still require intensive computational efforts, and novel methodologies should be developed and benchmarked. Free energy perturbation (FEP) method was recently shown to estimate PMF with a significantly reduced computational cost compared to the adaptive biasing force method. This benchmarking was achieved with small molecules, namely short-chain alcohols. Here, we show that to estimate the PMF of bulkier, drug-like xenobiotics, conformational sampling is a critical issue. To reach a sufficient sampling with FEP calculations requires a relatively long time-scale, which can lower the benefits related to the computational gain. In the present work, the Accelerated Weight Histogram (AWH) method was employed for the first time in all-atom membrane models. The AWH-based protocol, named MemCross, appears affordable to estimate PMF profiles of a series of drug-like xenobiotics, compared to other enhanced sampling methods. The continuous exploration of the crossing pathway by MemCross also allows modeling subdiffusion by computing fractional diffusivity profiles. The method is also versatile as its input parameters are largely insensitive to the molecule properties. It also ensures a detailed description of the molecule orientations along the permeation pathway, picturing all intermolecular interactions at an atomic resolution. Here, MemCross was applied on a series of 12 xenobiotics, including four weak acids, and a coherent structure-activity relationship was established.

Identifying pathways to metal-organic framework collapse during solvent activation with molecular simulations.

Metal-organic framework (MOF) materials are a vast family of nanoporous solids with potential applications ranging from drug delivery to environmental remediation. Application of MOFs in these scenarios is hindered, however, by difficulties in MOF 'activation' after initial synthesis - removal of the synthesis solvent from the pores to make the pore space accessible - often leading to framework collapse if improperly performed. While experimental studies have correlated collapse to specific solvent properties and conditions, the mechanism of activation-collapse is currently unknown. Developing this understanding would enable researchers to create better activation protocols for MOFs, accelerating discovery and process intensification. To achieve this goal, we simulated solvent removal using grand-canonical Monte Carlo and free energy perturbation methods. By framing activation as a fluid desorption problem, we investigated activation processes in the isoreticular metal organic framework (IRMOF) family of MOFs for different solvents. We identified two pathways for solvent activation - the solvent either desorbs uniformly from each individual pore or forms coexisting phases during desorption. These mesophases in turn lead to large capillary stresses within the framework, corroborating experimental hypotheses for the cause of activation-collapse. Finally, we found that the activation energy of solvent removal increased with pore size and connectivity due to the increased stability of solvent mesophases, matching experimental findings. Using these simulations, it is possible to screen MOF activation procedures, enabling rapid identification of ideal solvents and conditions and thus enabling faster development of MOFs for practical applications.

The Second Generation Type II JAK2 Inhibitor, AJ1-10502, Demonstrates Enhanced Selectivity, Improved Therapeutic Efficacy and Reduced Mutant Cell Fraction Compared to Type I JAK2 Inhibitors in Models of Myeloproliferative Neoplasms (MPNs)

Type I JAK inhibition (JAKi) represents a mainstay therapy for myelofibrosis and hydroxyurea-resistant high-risk polycythemia vera. Current type I JAKi, including ruxolitinib (RUX) and fedratinib, improve symptoms and outcomes in MPNs; however, JAK2VF allele burden remains essentially unchanged, and efficacy wanes over time. Sustained JAK/STAT signaling plays a critical role in MPN cell persistence in the setting of type I inhibition. CHZ868, a type II JAKi that binds the inactive conformation of the kinase domain, overcomes RUX persistence in vitro and reduces Jak2VF allele fraction in vivo suggesting improved JAK2 targeting might enhance clinical efficacy. However, current type II JAKi, including CHZ868, are limited by lack of kinome specificity and off-target toxicity. We therefore sought to develop novel type II JAK2i with improved potency and selectivity. Computational free energy perturbation and structure-activity relationship-based methods were used to identify lead type II inhibitor compounds. This work, followed by Absorption, Distribution, Metabolism and Excretion modeling, led to the development of AJ1-10502. Kinome selectivity profiling of AJ1-10502 revealed potent JAK2 selectivity with minimal kinase cross-reactivity compared to CHZ868, including among other JAK family tyrosine kinases (Figure 1A). Assessment of in vitro efficacy of AJ1-10502 in SET2 inhibitor naïve and SET2 RUX persistence (RUXper) cells revealed concentration-dependent inhibition of proliferation of RUXper cells comparable to that of CHZ868. The IC50 for AJ1-10502 in RUXper cells was similar to the IC50 observed in inhibitor naïve cells. We next evaluated AJ1-10502 in vivo using a novel dual Dre/Cre-recombinase Jak2VF knock-in/knock-out model allowing for the comparison of JAKi to Jak2VF genetic deletion. AJ1-10502 demonstrated reductions in leukocytosis comparable to that of RUX (K/uL: VEH 18.7 vs. RUX 10.1 vs. AJ1-10502 9.3) but dose-dependent improvements in hematocrit, platelet levels, and spleen weights superior to RUX, with reductions in spleen weights on par to that of Jak2VF deletion (mg: VEH 480 vs. RUX 255 vs. AJ1-10502 145 vs. del 107, p<0.05). A greater degree of restoration of splenic architecture was also observed with AJ1-10502 compared to type I JAKi. Critically, we observed reductions in peripheral blood (PB) and bone marrow (BM) mutant allele fraction with AJ1-10502 not observed with RUX, including within Mac1+Gr1+ myeloid cell fractions (VEH 94% vs. RUX 92% vs. AJ1-10502 78.5%, p<0.05), consistent with a mutant-biased reduction in myeloid output. In a separate series of competitive transplants using a Cre-inducible human JAK2VF transgenic mouse line, we validated the phenotypic changes in regard to leukocytosis, hematocrit, and spleen weight reduction seen with the DreCre model. Most importantly, we confirmed significant reductions in mutant cell fraction within the hematopoietic stem (HSC) compartment of BM and spleen, including among granulocytic-monocytic progenitor (GMP) and long-term HSC (LT-HSC) populations (Figure 1B). Finally, a separate study comparing AJ1-10502 to CHZ868 revealed no significant weight loss with AJ1-10502 (-0.5g) compared to CHZ868 (-2.2g, p<0.05) despite similar reductions in Jak2VF allele fraction suggesting comparable efficacy without systemic toxicity. In sum, AJ1-10502 is a potent, selective type II JAK2i with improved efficacy compared to RUX and an enhanced safety profile compared to previous non-selective type II JAKi. Most importantly, AJ1-10502 results in superior reductions in PB and BM mutant cell fraction in vivo not observed with type I JAKi. These data demonstrate the preclinical utility of type II JAKi with AJ1-10502 and inform a path to clinical development of type II JAKi for MPN patients. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Partition of the Reactive Species of the Suzuki-Miyaura Reaction between Aqueous and Micellar Environments.

The Suzuki-Miyaura reaction between the aryl halide (1) and the phenyl boronic acid (2), in the presence of the palladium(0) complex (3) as catalyst, gives the cross-coupling product (4) in quantitative yield when performed in basic aqueous solution of the nonionic surfactant Kolliphor-EL (K-EL). The partition between the aqueous and micellar environments of the species of this reaction has been investigated by means of Molecular Dynamics (MD) simulations. Starting from the K-EL molecules dispersed in water, a micelle model has been generated by MD simulations, adopting the 2016H66 force field. Reagent and product species have been described with the same force field, once the reliability of this force field has been tested comparing the n-octanol/water partition free energies calculated from the MD and Free Energy Perturbation (FEP) method with those obtained from the quantum-mechanical SMD method. The potential of mean force for the transfer process between water and the micellar phase of the different species has been calculated by the MD simulations and the Umbrella Sampling (US) method. The overall picture that emerges from these results confirms that the molecular species involved in this reaction prefers the micellar environment and concentrates in different but close zones of the micelle. This supports the experimental evidence that the use of suitable surfactant agents promotes reactivity, allowing micelles to behave as nanoreactors in which reactive species are solubilized and enhance their local concentration.

Hydrophilic Versus Hydrophobic Coupling in the Pressure Dependence of the Chemical Potential of Alkali Metal and Halide Ions in Water.

We computed the chemical potential for some alkali metal ions (K+, Rb+, and Cs+) and two halide ions (Br- and I-) in aqueous solution at ambient T and various pressures in the range 1-8000 atm. Results were obtained from classic Monte Carlo simulations in the NPT ensemble by means of the free energy perturbation method. Here, the chemical potential is computed as the sum of a term relative to a Lennard-Jones solute and a term relative to the process in which this solute is transformed into the ion. Hydrophobic and hydrophilic features of these two components of the chemical potential show opposite behaviors under isothermal compression. The increase in pressure determines an increase in the hydrophobic component, which becomes more positive with a stronger effect for larger ions. Correspondingly, the values of the hydrophilic component become more negative for alkali ions, whereas they are only slightly affected by compression for halide ions. Hydrophobic-hydrophilic quasi-compensation in the slopes is observed for Rb+. For a smaller ion, such as K+, the dependence on pressure of the hydrophilic component is slightly dominant. For a larger ion, as observed in the cases of Cs+, Br-, and I-, the hydrophobic component assumes the determinant role. Pressure dependence of the chemical potential is little affected by corrections introduced for molecular potential truncation. This view can change for possible boundary artifacts that could have affected the static electrostatic potential. Some inference is obtained from comparison with experimental data at 1 atm on the free energy of hydration. Discrepancies show the characteristic asymmetry between cations and anions. The further addition of a correction based on the static potential significantly reduces these discrepancies with important error cancellation on the sum of chemical potentials of ions of opposite charge. The correction is applied also at higher pressures, and results are compared with those obtained by adding an alternative correction that is based on the water number density. Regardless of the ion, changes of the chemical potential induced by an increase in pressure appear to be dominated by the hydrophobic component, in particular when using the alternative correction. For bromide and iodide electrolytes, the two corrections give chemical potentials in good agreement.

Adhesion of Bis-Salphen-Based Coordination Polymers to Graphene: Insights from Free Energy Perturbation Study.

Manipulation of nanoscale objects using molecular self-assembly is a potent tool to achieve large scale nanopatterning with small effort. Coordination polymers of bis-salphen compounds based on zinc have demonstrated their ability to align carbon nanotubes into micro-scale networks with an unusual "rings-and-rods" pattern. This paper investigates how the compounds interact with pristine and functionalized graphene using density functional theory calculations and molecular dynamic simulations. Using the free energy perturbation method we will show how the addition of phenyl side groups to the core compound and functionalization of graphene affect the stability, mobility and conformation adopted by a dimer of bis-(Zn)salphen compound adsorbed on graphene surface and what it can reveal about the arrangement of chains of bis-(Zn)salphen polymer around carbon nanotubes during the self-assembly of microscale networks.

Potential of Mean Force for Face-Face Interactions between Pairs of 2:1 Clay Mineral Platelets.

Bottom-up modeling of clay behavior from the molecular scale requires a detailed understanding of the free energy between pairs of clay platelets. We investigate the potential of mean force (PMF) for hydrated clays in face-to-face interactions with free energy perturbation (FEP) methods through molecular dynamics simulations using simple overlap sampling (SOS). We show that PMF results for open systems with one finite in-plane dimension are affected by migration of counterions from within the interlayer space compared with fully confined closed system conditions. We compare PMFs for two common 2:1 clay sheet minerals Illite (IMt-1) and Na-smectite. The PMFs for the open illite systems exhibit a strong attractive energy well at a basal layer separation, d = 11 Å and interlayer water content, wIL = ∼0.4% while the attractive minimum for the closed system occurs at d = 12 Å, wIL = 3.5%. In contrast, net repulsion occurs between pairs of Na-smectite platelets for both open and closed systems (for d < 15-16 Å). The free energy is closely related to the distribution of counterions; while K+ ions are bound closely to the surfaces of the illite platelets, Na+ ions are more spatially disperse. This PMF results contradict prior findings for Na-smectite and prompted further comparisons with other published results. We find that most of the published results do not represent accurately the free energy for face-face interactions between pairs of clay platelets that are effectively infinite (with width/thickness O[104]). The PMF results presented in this paper form a reliable basis for mesoscale, coarse-grained modeling of illite and smectite particle assemblies. We show that the Gay-Berne potential provides a reasonable first-order model for upscaling, while the solvation potential proposed by Masoumi enables a more accurate representation of the computed PMFs.

Modeling receptor flexibility in the structure-based design of KRASG12C inhibitors.

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRASG12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRASG12C—sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRASG12C. In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRASG12C, we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRASG12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10822-022-00467-0.

Free energy calculation of crystalline solids using normalizing flows

Taking advantage of the advances in generative deep learning, particularly normalizing flow, a framework, called Boltzmann generator, has recently been proposed to generate equilibrium atomic configurations from the canonical ensemble and determining the associated free energy. In this work, we revisit Boltzmann generator to motivate the construction of the loss function from the statistical mechanical point of view and to cast the training of the normalizing flow model in a purely unsupervised manner that does not require any sample of the atomic configurations from the equilibrium ensemble. We further show that the normalizing flow framework furnishes a reference thermodynamic system, very close to the real thermodynamic system under consideration, that is suitable for the well-established free energy perturbation methods to determine accurate free energy of solids. We then apply the normalizing flow to two problems: temperature-dependent Gibbs free energy of perfect crystal and formation free energy of monovacancy defect in a model system of diamond cubic Si. The results obtained from the normalizing flow are shown to be in good agreement with that obtained from independent well-established free energy methods.

Binding Studies and Lead Generation of Pteridin-7(8H)-one Derivatives Targeting FLT3.

Ligand modification by substituting chemical groups within the binding pocket is a popular strategy for kinase drug development. In this study, a series of pteridin-7(8H)-one derivatives targeting wild-type FMS-like tyrosine kinase-3 (FLT3) and its D835Y mutant (FL3D835Y) were studied using a combination of molecular modeling techniques, such as docking, molecular dynamics (MD), binding energy calculation, and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies. We determined the protein–ligand binding affinity by employing molecular mechanics Poisson–Boltzmann/generalized Born surface area (MM-PB/GBSA), fast pulling ligand (FPL) simulation, linear interaction energy (LIE), umbrella sampling (US), and free energy perturbation (FEP) scoring functions. The structure–activity relationship (SAR) study was conducted using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), and the results were emphasized as a SAR scheme. In both the CoMFA and CoMSIA models, satisfactory correlation statistics were obtained between the observed and predicted inhibitory activity. The MD and SAR models were co-utilized to design several new compounds, and their inhibitory activities were anticipated using the CoMSIA model. The designed compounds with higher predicted pIC50 values than the most active compound were carried out for binding free energy evaluation to wild-type and mutant receptors using MM-PB/GBSA, LIE, and FEP methods.

Binding Affinity Calculations of Gluten Peptides to HLA Risk Modifiers: DQ2.5 versus DQ7.5.

Free energy perturbation (FEP) calculations can predict relative binding affinities of an antigen and its point mutants to the same human leukocyte antigen (HLA) with high accuracy (e.g., within 1.0 kcal/mol to experiment); however, a more challenging task is to compare binding affinities of wholly different antigens binding to completely different HLAs using FEP. Researchers have used a variety of different FEP schemes to compute and compare absolute binding affinities, with varied success. Here, we propose and assess a unifying scheme to compute the relative binding affinities of different antigens binding to completely different HLAs using absolute binding affinity FEP calculations. We apply our affinity calculation technique to HLA-antigen-T-cell receptor (TCR) systems relevant to celiac disease (CeD) by investigating binding affinity differences between HLA-DQ2.5 (enhanced CeD risk) and HLA-DQ7.5 (CeD protective) in the binary (HLA-gliadin) and ternary (HLA-gliadin-TCR) binding complexes for three gliadin derived epitopes: glia-α1, glia-α2, and glia-ω1. Based on FEP calculations with our carefully designed thermodynamic cycles, we demonstrate that HLA-DQ2.5 has higher binding affinity than HLA-DQ7.5 for gliadin and enhanced binding affinity with a common TCR, agreeing with known results that the HLA-DQ2.5 serotype exhibits increased risk for CeD. Our findings reveal that our proposed absolute binding affinity FEP method is appropriate for predicting HLA binding for disparate antigens with different genotypes. We also discuss atomic-level details of HLA genotypes interacting with gluten peptides and TCRs in regard to the pathogenesis of CeD.

Effect of electric field on water free energy in graphene nanochannel

Graphene nanochannels and nanostructures have been of great interest to applications like nanofluidics and solar-thermal evaporation since nanoconfinement can lead to altered liquid properties. In this article, we employ molecular dynamics simulations combined with the free energy perturbation method to study the influence of external electric fields on the free energy of water molecules in graphene nanochannels. We observe a decrease in the water free energy difference (ΔG1−0=G0−G1, where 0 is the reference vacuum state and 1 is the solvated state) with the increasing electric field, suggesting that the application of an electric field may reduce the thermal energy needed to evaporate water from graphene nanochannels. Our analysis reveals that the reduction in free energy difference is related to more aligned water molecules along the electric field direction in the nanochannels, which leads to a decrease in the water inter-molecular potential energy and, thus, reduces the free energy difference.

Competitive Binding of Ozanimod and Other Sphingosine 1-Phosphate Receptor Modulators at Receptor Subtypes 1 and 5.

Ozanimod, a sphingosine 1-phosphate (S1P) receptor modulator, binds with high affinity selectively to S1P receptor subtypes 1 (S1P1) and 5 (S1P5), and is approved in multiple countries for treating adults with relapsing forms of multiple sclerosis (MS) or moderately to severely active ulcerative colitis (UC). Other S1P receptor modulators have been approved for the treatment of MS or are in clinical development for MS or UC, but it is unknown whether these compounds bind competitively with each other to S1P1 or S1P5. We developed a competitive radioligand binding assay using tritiated ozanimod and demonstrate full displacement of ozanimod by S1P (endogenous ligand), suggesting that ozanimod binds to the S1P1 and S1P5 orthosteric binding sites. S1P receptor modulators FTY720-p, siponimod, etrasimod, ponesimod, KRP-203-p, and amiselimod-p also completely displacing radiolabeled ozanimod; thus, on a macroscopic level, all bind to the same site. Molecular docking studies support these results and predict the binding of each molecule to the orthosteric site of the receptors, creating similar interactions within S1P1 and S1P5. The absolute free energy perturbation method further validated key proposed binding modes. Functional potency tightly aligned with binding affinities across S1P1 and S1P5 and all compounds elicited S1P1-mediated β-arrestin recruitment. Since all the S1P modulators included in this study display similar receptor pharmacology and compete for binding at the same site, they can be considered interchangeable with one another. The choice of any one particular agent should therefore be made on the basis of overall therapeutic profile, and patients can be offered the opportunity to switch S1P medications without the potential concern of additive S1P pharmacology.

Modified Hamiltonian in FEP Calculations for Reducing the Computational Cost of Electrostatic Interactions.

The free-energy perturbation (FEP) method predicts relative and absolute free-energy changes of biomolecules in solvation and binding with other molecules. FEP is, therefore, one of the most essential tools in in silico drug design. In conventional FEP, to smoothly connect two thermodynamic states, the potential energy is modified as a linear combination of the end-state potential energies by introducing scaling factors. When the particle mesh Ewald is used for electrostatic calculations, conventional FEP requires two reciprocal-space calculations per time step, which largely decreases the computational performance. To overcome this problem, we propose a new FEP scheme by introducing a modified Hamiltonian instead of interpolation of the end-state potential energies. The scheme introduces nonuniform scaling into the electrostatic potential as used in Replica Exchange with Solute Tempering 2 (REST2) and does not require additional reciprocal-space calculations. We tested this modified Hamiltonian in FEP calculations in several biomolecular systems. In all cases, the calculated free-energy changes with the current scheme are in good agreement with those from conventional FEP. The modified Hamiltonian in FEP greatly improves the computational performance, which is particularly marked for large biomolecular systems whose reciprocal-space calculations are the major bottleneck of total computational time.

Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision, and Reproducibility.

The binding free energy between a ligand and its target protein is an essential quantity to know at all stages of the drug discovery pipeline. Assessing this value computationally can offer insight into where efforts should be focused in the pursuit of effective therapeutics to treat a myriad of diseases. In this work, we examine the computation of alchemical relative binding free energies with an eye for assessing reproducibility across popular molecular dynamics packages and free energy estimators. The focus of this work is on 54 ligand transformations from a diverse set of protein targets: MCL1, PTP1B, TYK2, CDK2, and thrombin. These targets are studied with three popular molecular dynamics packages: OpenMM, NAMD2, and NAMD3 alpha. Trajectories collected with these packages are used to compare relative binding free energies calculated with thermodynamic integration and free energy perturbation methods. The resulting binding free energies show good agreement between molecular dynamics packages with an average mean unsigned error between them of 0.50 kcal/mol. The correlation between packages is very good, with the lowest Spearman’s, Pearson’s and Kendall’s tau correlation coefficients being 0.92, 0.91, and 0.76, respectively. Agreement between thermodynamic integration and free energy perturbation is shown to be very good when using ensemble averaging.

Exploring the Activity Profile of TbrPDEB1 and hPDE4 Inhibitors Using Free Energy Perturbation.

Human African trypanosomiasis (HAT) is a neglected tropical disease caused by the parasite Trypanosoma brucei (T.b.). A validated target for the treatment of HAT is the parasitic T.b. cyclic nucleotide phosphodiesterase B1 (TbrPDEB1). Although nanomolar TbrPDEB1 inhibitors have been obtained, their activity against the off-target human PDE4 (hPDE4) is likely to lead to undesirable clinical side effects, such as nausea, emesis, and immune suppression. Thus, new and more selective TbrPDEB1 inhibitors are still needed. This retrospective study evaluated the free energy perturbation (FEP+) method to predict the affinity profiles of TbrPDEB1 inhibitors against hPDE4. We demonstrate that FEP+ can be used to accurately predict the activity profiles of these homologous proteins. Moreover, we show how FEP+ can overcome challenges like protein flexibility and high sequence conservation. This also implies that the method can be applied prospectively for the lead optimization campaigns to design new and more selective TbrPDEB1 inhibitors.

Structure–activity relationship and in silico development of c‐Met kinase inhibitors

AbstractOverexpression and concomitant drug resistance of c‐Met kinase are strongly associated with poor prognosis in gastric carcinoma. This needs the further development of existing lead compounds against c‐Met. Herein, we conducted molecular modeling studies of 4‐phenoxypyridine derivatives as c‐Met kinase inhibitors using docking, molecular dynamics (MD), and binding energy estimation to examine receptor–ligand interaction, complex stability, and binding affinity. We developed statistically significant three‐dimensional structure–activity relationship models (3D‐QSAR) to correlate the physicochemical characteristics of the inhibitors with their biological activities. The field effects of the chemical descriptors were determined as contour polyhedrons and emphasized as SAR. Thirty new compounds were designed according to the SAR scheme, and their activities were predicted using the 3D‐QSAR model. The designed compounds with higher predicted pIC50 values than the most active compounds in the dataset were subjected to absolute binding free‐energy evaluation by free energy perturbation (FEP) method.

Diffusion coefficient and solvation free energy of sucrose in water: a molecular dynamics study

In this work, we have carried out Molecular Dynamics Simulation technique to study the diffusion coefficients, radial distribution functions and solvation free energy of sucrose (C12H22O11) at different temperatures ranging from 298.15 K to 318.15 K. We have taken 2 molecules of sucrose in 1343 molecules of extended simple point charge (SPC/E) water model. The self-diffusion coefficients are obtained by applying linear best fit to the mean squaredisplacement (MSD) plot and binary diffusion coefficients are obtained by using Darken’s relation. Arrhenius equation has been used to show a linear relationship between natural logarithm of binary diffusion coefficient and reciprocal of temperature. The structural analysis of the solution has been carried out with the help of radial distribution functions (RDFs) of its constituents. The solvation free energy of sucrose is studied at 300 K by using free energy perturbation method like Bennett Acceptance Ratio (BAR). The results of binary diffusion coefficients obtained from this simulation work agree very well with the previously reported experimental data.

Binding free energy calculation of human beta defensin 3 with negatively charged lipid bilayer using free energy perturbation method

Human β defensin type 3 (hBD-3) is a cationic peptide having strong antimicrobial activities even at high salt concentrations. The conserved sequence is believed to contribute to its unique antibacterial activities. To design novel drugs based on hBD-3, predicting the binding free energy contribution of each residue on hBD-3 with bacterial membrane is important. Firstly, the stable binding structure of hBD-3 dimer in analog form bound on POPG lipid bilayer was predicted using NAMD simulations, which was confirmed by RMSD, buried surface area, hydrogen bonds, distance map, and insertion depth map calculations. Then, free energy perturbation (FEP) method was applied to calculate the binding free energy of each residue by mutating it into Alanine. It was found that the positively charged residues on the tail region of hBD-3 contribute significantly to its binding with membrane. The result emphasized the importance of electrostatic interactions to hBD-3's binding with bacterial membrane.