Relative Binding Free Energies Research Articles

Binding Selectivity Analysis from Alchemical Receptor Hopping and Swapping Free Energy Calculations.

We present receptor hopping and receptor swapping free energy estimation protocols based on the Alchemical Transfer Method (ATM) to model the binding selectivity of a set of ligands to two arbitrary receptors. The receptor hopping protocol, where a ligand is alchemically transferred from one receptor to another in one simulation, directly yields the ligand's binding selectivity free energy (BSFE) for the two receptors, which is the difference between the two individual binding free energies. In the receptor swapping protocol, the first ligand of a pair is transferred from one receptor to another while the second ligand is simultaneously transferred in the opposite direction. The receptor swapping free energy yields the differences in binding selectivity free energies of a set of ligands, which, when combined using a generalized DiffNet algorithm, yield the binding selectivity free energies of the ligands. We test these algorithms on host-guest systems and show that they yield results that agree with experimental data and are consistent with differences in absolute and relative binding free energies obtained by conventional methods. Preliminary applications to the selectivity analysis of molecular fragments binding to the trypsin and thrombin serine protease confirm the potential of the receptor swapping technology in structure-based drug discovery. The novel methodologies presented in this work are a first step toward streamlined and computationally efficient protocols for ligand selectivity optimization between mutants and homologous proteins.

Accurate protein-ligand binding free energy estimation using QM/MM on multi-conformers predicted from classical mining minima

Accurate prediction of binding free energy is crucial for the rational design of drug candidates and understanding protein-ligand interactions. To address this, we have developed four protocols that combine QM/MM calculations and the mining minima (M2) method, tested on 9 targets and 203 ligands. Our protocols carry out free energy processing with or without conformational search on the selected conformers obtained from M2 calculations, where their force field atomic charge parameters are substituted with those obtained from a QM/MM calculation. The method achieved a high Pearson’s correlation coefficient (0.81) with experimental binding free energies across diverse targets, demonstrating its generality. Using a differential evolution algorithm with a universal scaling factor of 0.2, we achieved a low mean absolute error of 0.60 kcal mol-1. This performance surpasses many existing methods and is comparable to popular relative binding free energy techniques but at significantly lower computational cost.

The Generation of ROS by Exposure to Trihalomethanes Promotes the IκBα/NF-κB/p65 Complex Dissociation in Human Lung Fibroblast.

Background: Disinfection by-products used to obtain drinking water, including halomethanes (HMs) such as CH2Cl2, CHCl3, and BrCHCl2, induce cytotoxicity and hyperproliferation in human lung fibroblasts (MRC-5). Enzymes such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) modulate these damages through their biotransformation processes, potentially generating toxic metabolites. However, the role of the oxidative stress response in cellular hyperproliferation, modulated by nuclear factor-kappa B (NF-κB), remains unclear. Methods: In this study, MRC-5 cells were treated with these compounds to evaluate reactive oxygen species (ROS) production, lipid peroxidation, phospho-NF-κB/p65 (Ser536) levels, and the activities of SOD, CAT, and GPx. Additionally, the interactions between HMs and ROS with the IκBα/NF-κB/p65 complex were analyzed using molecular docking. Results: Correlation analysis among biomarkers revealed positive relationships between pro-oxidant damage and antioxidant responses, particularly in cells treated with CH2Cl2 and BrCHCl2. Conversely, negative relationships were observed between ROS levels and NF-κB/p65 levels in cells treated with CH2Cl2 and CHCl3. The estimated relative free energy of binding using thermodynamic integration with the p65 subunit of NF-κB was -3.3 kcal/mol for BrCHCl2, -3.5 kcal/mol for both CHCl3 and O2•, and -3.6 kcal/mol for H2O2. Conclusions: Chloride and bromide atoms were found in close contact with IPT domain residues, particularly in the RHD region involved in DNA binding. Ser281 is located within this domain, facilitating the phosphorylation of this protein. Similarly, both ROS interacted with the IPT domain in the RHD region, with H2O2 forming a side-chain oxygen interaction with Leu280 adjacent to the phosphorylation site of p65. However, the negative correlation between ROS and phospho-NF-κB/p65 suggests that steric hindrance by ROS on the C-terminal domain of NF-κB/p65 may play a role in the antioxidant response.

Alchemical Transformations and Beyond: Recent Advances and Real-World Applications of Free Energy Calculations in Drug Discovery.

Computational methods constitute efficient strategies for screening and optimizing potential drug molecules. A critical factor in this process is the binding affinity between candidate molecules and targets, quantified as binding free energy. Among various estimation methods, alchemical transformation methods stand out for their theoretical rigor. Despite challenges in force field accuracy and sampling efficiency, advancements in algorithms, software, and hardware have increased the application of free energy perturbation (FEP) calculations in the pharmaceutical industry. Here, we review the practical applications of FEP in drug discovery projects since 2018, covering both ligand-centric and residue-centric transformations. We show that relative binding free energy calculations have steadily achieved chemical accuracy in real-world applications. In addition, we discuss alternative physics-based simulation methods and the incorporation of deep learning into free energy calculations.

In-silico analysis of ethanol peel extract of Citrus sinensis on mercury chloride-induced prefrontal cortex damage in Wistar rat

This study evaluated the effect of ethanolic extract of Citrus sinensis peel on mercury chloride-induced changes in the prefrontal cortex of adult Wistar rats. Twenty-five Wistar rats were purchased and divided into five groups containing five animals in each group. Group 1 was administered with distilled water, Group 2, Group 3, Group 4, and Group 5 were administered with 5 mg/kg of mercury chloride only, 5 mg/kg of mercury chloride and 140 mg/kg Silymarin, 5 mg/kg mercury chloride and 1000 mg/kg of ethanoic extract of orange peel, and 5 mg/kg mercury chloride and 1500 mg/kg of ethanoic extract of orange peel. All administration was done orally and the administration lasted for 14 days. The animals were sacrificed humanely using 75 mg/kg ketamine intraperitoneally and prefrontal was dissected out. Part was homogenized in 0.1M phosphate buffered saline for the estimation of superoxide dismutase (SOD), and catalase (CAT) activities, and Malondialdehyde (MDA) level and the other part was fixed by immersion in 10 neutral buffered formal-saline for histological evaluation. The chemical structure of sixteen compounds from Citrus sinensis peel obtained from GC-MS analysis reported in the literature were retrieved from the PubChem compound database and the crystal structure of human peroxisome proliferator- activated receptor gamma (PPARγ; PDB:ID: 2P4Y) reported to increase the expression of catalase gene, human extracellular copper-zinc superoxide dismutase enzyme (PDB ID: 2JLP) and mammalian 15-lipoxygenase - 1 enzyme (PDB ID: 2P0M) responsible for the production of lipid peroxidation were retrieved from the PDB database. Ligands and protein preparation, docking and MM-GBSA relative binding free energy calculation were done in Maestro 2023.1. Data obtained was analyzed using the IBM SPSS (version 25) using one-way ANOVA and p-value < 0.05 was considered statistically significant. The results indicate that the MDA level in control Group(13.29±1.183 μmol) is statistically significantly lower compared to the Group 2 (21.88±1.96 μmol), group 3 (27.44±3.52 μmol), Group 4 (22.20±1.16 μmol) and Group 5 (25.40±3.13 μmol). No statistically significant difference was observed in SOD activity. The CAT activities in control group (53.51±6.83 nmol/ml) was statistically significantly lower compared to the group 2 (26.21±3.70 nmol/ml), Group 3 (27.17±5.32 nmol/ml), Group 4 (25.30±4.24 nmol/ml) and Group5 (26.59±4.22 nmol/ml).The present study suggests, ethanolic extract of Citrus sinensis peel have protective effects on mercury-induced changes in prelimbic part of the prefrontal cortex of adult Wistar rats.

A Method for Treating Significant Conformational Changes in Alchemical Free Energy Simulations of Protein-Ligand Binding.

Relative binding free energy (RBFE) simulation is a rigorous approach to the calculation of quantitatively accurate binding free energy values for protein-ligand binding in which a reference binder is gradually converted to a target binder through alchemical transformation during the simulation. The success of such simulations relies on being able to accurately sample the correct conformational phase space for each alchemical state; however, this becomes a challenge when a significant conformation change occurs between the reference and target binder-receptor complexes. Increasing the simulation time and using enhanced sampling methods can be helpful, but effects can be limited, especially when the free energy barrier between conformations is high or when the correct target complex conformation is difficult to find and maintain. Current RBFE protocols seed the reference complex structure into every alchemical window of the simulation. In our study, we describe an improved protocol in which the reference structure is seeded into the first half of the alchemical windows, and the target structure is seeded into the second half of the alchemical windows. By applying information about the relevant correct end point conformations to different simulation windows from the beginning, the need for large barrier crossings or simulation prediction of the correct structures during an alchemical simulation is in many cases obviated. In the diverse cases we examine below, the simulations yielded free energy predictions that are satisfactory as compared to experiment and superior to running the simulations utilizing the conventional protocol. The method is straightforward to implement for publicly available FEP workflows.

Effect of Protein-Polarized Ligand Charges on Relative Protein Ligand Binding Affinities.

A major challenge in computer-aided drug design is predicting relative binding energies of different molecules to a target protein using fast and accurate free-energy calculation methods. Free-energy calculations are primarily computed by utilizing classical molecular dynamics simulations based on all-atom force fields (FF) to model the interactions in the system. The present standard classical all-atom FFs contain fixed partial charges on the atoms, and hence electrostatic interactions are modeled between them. The parametrization process to determine these partial charges usually relies on quantum mechanics or semiempirical calculations of the molecule in the gas phase or homogeneous water surrounding. These present standard parametrization schemes of the partial charges neglect, therefore, polarization effects from the protein surrounding. The absence of protein polarization effects can lead to significant errors in free-energy calculations in proteins. We present a parametrization scheme for the partial charges of ligands, named protein-induced polarization (PIP) charges, which account for the electrostatic polarization due to the protein surrounding. The scheme involves single-point quantum mechanics/molecular mechanics calculations of the ligand charges in the protein/water surrounding. Using PIP ligand partial charges, we have calculated the relative binding free energies (RBFEs) of well-studied protein-ligand systems. We show here that RBFEs computed with PIP charges are either significantly improved or at least comparable to those computed with nonpolarized standard GAFF charges. Overall, we present a simple-to-use parametrization scheme to include protein polarization in any type of binding free-energy calculations. The parametrization scheme increases the accuracy in RBFE calculations, while it does not add significant computation time to standard parametrization procedures.

Improvements in Precision of Relative Binding Free Energy Calculations Afforded by the Alchemical Enhanced Sampling (ACES) Approach.

Accurate in silico predictions of how strongly small molecules bind to proteins, such as those afforded by relative binding free energy (RBFE) calculations, can greatly increase the efficiency of the hit-to-lead and lead optimization stages of the drug discovery process. The success of such calculations, however, relies heavily on their precision. Here, we show that a recently developed alchemical enhanced sampling (ACES) approach can consistently improve the precision of RBFE calculations on a large and diverse set of proteins and small molecule ligands. The addition of ACES to conventional RBFE calculations lowered the average hysteresis by over 35% (0.3-0.4 kcal/mol) and the average replicate spread by over 25% (0.2-0.3 kcal/mol) across a set of 10 protein targets and 213 small molecules while maintaining similar or improved accuracy. We show in atomic detail how ACES improved convergence of several representative RBFE calculations through enhancing the sampling of important slowly transitioning ligand degrees of freedom.

Hit-to-Lead Optimization of Heterocyclic Carbonyloxycarboximidamides as Selective Antagonists at Human Adenosine A3 Receptor.

Antagonism of the human adenosine A3 receptor (hA3R) has potential therapeutic application. Alchemical relative binding free energy calculations of K18 and K32 suggested that the combination of a 3-(2,6-dichlorophenyl)-isoxazolyl group with 2-pyridinyl at the ends of a carbonyloxycarboximidamide group should improve hA3R affinity. Of the 25 new analogues synthesized, 37 and 74 showed improved hA3R affinity compared to K18 (and K32). This was further improved through the addition of a bromine group to the 2-pyridinyl at the 5-position, generating compound 39. Alchemical relative binding free energy calculations, mutagenesis studies and MD simulations supported the compounds' binding pattern while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, so highlighting the importance of rigidification of the carbonyloxycarboximidamide moiety. MD simulations highlighted the importance of rigidification of the carbonyloxycarboximidamide, while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, which was supported through mutagenesis studies 39 also selectively antagonized endogenously expressed hA3R in nonsmall cell lung carcinoma cells, while pharmacokinetic studies indicated low toxicity enabling in vivo evaluation. We therefore suggest that 39 has potential for further development as a high-affinity hA3R antagonist.

Massively parallel free energy calculations for in silico affinity maturation of designed miniproteins.

Computational protein design efforts continue to make remarkable advances, yet the discovery of high-affinity binders typically requires large-scale experimental screening of site-saturated mutant (SSM) libraries. Here, we explore how massively parallel free energy methods can be used for in silico affinity maturation of de novo designed binding proteins. Using an expanded ensemble (EE) approach, we perform exhaustive relative binding free energy calculations for SSM variants of three miniproteins designed to bind influenza A H1 hemagglutinin by Chevalier et al. (2017). We compare our predictions to experimental ΔΔ G values inferred from a Bayesian analysis of the high-throughput sequencing data, and to state-of-the-art predictions made using the Flex ddG Rosetta protocol. A systematic comparison reveals prediction accuracies around 2 kcal/mol, and identifies net charge changes, large numbers of alchemical atoms, and slow side chain conformational dynamics as key contributors to the uncertainty of the EE predictions. Flex ddG predictions are more accurate on average, but highly conservative. In contrast, EE predictions can better classify stabilizing and destabilizing mutations. We also explored the ability of SSM scans to rationalize known affinity-matured variants containing multiple mutations, which are non-additive due to epistatic effects. Simple electrostatic models fail to explain non-additivity, but observed mutations are found at positions with higher Shannon entropies. Overall, this work suggests that simulation-based free energy methods can provide predictive information for in silico affinity maturation of designed miniproteins, with many feasible improvements to the efficiency and accuracy within reach.

Adsorption of Flavonoids in a Transcriptional Regulator TtgR: Relative Binding Free Energies and Intermolecular Interactions.

Antimicrobial resistance in bacteria often arises from their ability to actively identify and expel toxic compounds. The bacterium strain Pseudomonas putida DOT-T1E utilizes its TtgABC efflux pump to confer robust resistance against antibiotics, flavonoids, and organic solvents. This resistance mechanism is intricately regulated at the transcriptional level by the TtgR protein. Through molecular dynamics and alchemical free energy simulations, we systematically examine the binding of seven flavonoids and their derivatives with the TtgR transcriptional regulator. Our simulations reveal distinct binding geometries and free energies for the flavonoids in the active site of the protein, which are driven by a range of noncovalent forces encompassing van der Waals, electrostatic, and hydrogen bonding interactions. The interplay of molecular structures, substituent patterns, and intermolecular interactions effectively stabilizes the bound flavonoids, confining their movements within the TtgR binding pocket. These findings yield valuable insights into the molecular determinants that govern ligand recognition in TtgR and shed light on the mechanism of antimicrobial resistance in P. putida DOT-T1E.

Probing Dual Covalent Irreversible Inhibition of EGFR/FGFR4 by Electrophilic-Based Natural Compounds to Overcome Resistance and Enhance Combination Therapeutic Potentials and Management of Hepatocellular Carcinoma (HCC).

Hepatocellular carcinoma (HCC) is one of the most prevalent cancer types in the world and accounts for the majority of cases of primary liver cancer. A crucial part of the carcinogenesis of HCC involves aberrant stimulation of the FGF19-FGFR4 signaling pathway. Therefore, FGFR4 inhibition has become a strategic therapeutic approach for the treatment of HCC. However, the clinical treatment procedure is significantly hampered by the prevalence of kinase inhibitors resistance. It was recently established that the activation of EGFR signaling was found to be one of the primary mechanisms mediating the acquired resistance to FGFR4 inhibitors, moreover, sensitivity to FGFR4 inhibitors was effectively restored by inhibiting EGFR. These results provide compelling evidence that dual inhibition of EGFR and FGFR4 could represent a viable therapeutic approach to overcome resistance, hence enhanced management of HCC. To this end, we proposed a dual irreversible inhibition strategy through covalent binding by naturally occurring electrophilic warhead-bearing compounds (curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A and andrographolide) to covalently target both EGFR and FGFR4 through cysteine residues, Cys797 and Cys552, respectively. Covalent docking and covalent molecular dynamics (MM/MDcov) simulations combined with thermodynamic binding free energy calculations were performed, and the results were compared against known potent and selective covalent EGFR and FGFR4 inhibitors with available X-ray crystal structures, Afatinib and BLU9931, respectively. Curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A, and andrographolide showed relative binding free energies of -22.85, -17.14, -12.98, -21.81, and - 19.00kcal/mol against EGFR and - 41.06, -29.45, -24.76, -40.11, and - 37.55kcal/mol against FGFR4, respectively. The mechanisms of binding were emphasized by hydrogen bonding and binding forces analysis as well as active site physicochemical profiling. The findings of this study identified that curcumin, syringolin A and andrographolide-but not eupalmerin acetate or deoxyelephantopin -could be viable dual EGFR and FGFR4 covalent irreversible inhibitors and could be implemented in HCC combination therapy protocols alone or in conjunction with other chemotherapeutic agents. Investigations of this study conclusively indicate dual blockade of EGFR and FGFR4 may be a promising future therapeutic strategy for enhanced management of HCC.

Ligand Binding Affinity Prediction for Membrane Proteins with Alchemical Free Energy Calculation Methods.

Alchemical relative binding free energy (ΔΔG) calculations have shown high accuracy in predicting ligand binding affinity and have been used as important tools in computer-aided drug discovery and design. However, there has been limited research on the application of ΔΔG methods to membrane proteins despite the fact that these proteins represent a significant proportion of drug targets, play crucial roles in biological processes, and are implicated in numerous diseases. In this study, to predict the binding affinity of ligands to G protein-coupled receptors (GPCRs), we employed two ΔΔG calculation methods: thermodynamic integration (TI) with AMBER and the alchemical transfer method (AToM) with OpenMM. We calculated ΔΔG values for 53 transformations involving four class A GPCRs and evaluated the performance of AMBER-TI and AToM-OpenMM. In addition, we conducted tests using different numbers of windows and varying simulation times to achieve reliable ΔΔG results and to optimize resource utilization. Overall, both AMBER-TI and AToM-OpenMM show good agreement with the experimental data. Our results validate the applicability of AMBER-TI and AToM-OpenMM for optimization of lead compounds targeting membrane proteins.

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.

Current State of Open Source Force Fields in Protein-Ligand Binding Affinity Predictions.

In drug discovery, the in silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations are nowadays a popular approach for the accurate affinity ranking of compounds. MD simulations rely on empirical force field parameters, which strongly influence the accuracy of the predicted affinities. Here, we evaluate the ability of six different small-molecule force fields to predict experimental protein-ligand binding affinities in RBFE calculations on a set of 598 ligands and 22 protein targets. The public force fields OpenFF Parsley and Sage, GAFF, and CGenFF show comparable accuracy, while OPLS3e is significantly more accurate. However, a consensus approach using Sage, GAFF, and CGenFF leads to accuracy comparable to OPLS3e. While Parsley and Sage are performing comparably based on aggregated statistics across the whole dataset, there are differences in terms of outliers. Analysis of the force field reveals that improved parameters lead to significant improvement in the accuracy of affinity predictions on subsets of the dataset involving those parameters. Lower accuracy can not only be attributed to the force field parameters but is also dependent on input preparation and sampling convergence of the calculations. Especially large perturbations and nonconverged simulations lead to less accurate predictions. The input structures, Gromacs force field files, as well as the analysis Python notebooks are available on GitHub.

Peptide Drug Design Using Alchemical Free Energy Calculation: An Application and Validation on Agonists of Ghrelin Receptor.

With recent large-scale applications and validations, the relative binding free energy (RBFE) calculated using alchemical free energy methods has been proven to be an accurate measure to probe the binding of small-molecule drug candidates. On the other hand, given the flexibility of peptides, it is of great interest to find out whether sufficient sampling could be achieved within the typical time scale of such calculation, and a similar level of accuracy could be reached for peptide drugs. However, the systematic evaluation of such calculations on protein-peptide systems has been less reported. Most reported studies of peptides were restricted to a limited number of data points or lacking experimental support. To demonstrate the applicability of the alchemical free energy method for protein-peptide systems in a typical real-world drug discovery project, we report an application of the thermodynamic integration (TI) method to the RBFE calculation of ghrelin receptor and its peptide agonists. Along with the calculation, the synthesis and in vitro EC50 activity of relamorelin and 17 new peptide derivatives were also reported. A cost-effective criterion to determine the data collection time was proposed for peptides in the TI simulation. The average of three TI repeats yielded a mean absolute error of 0.98 kcal/mol and Pearson's correlation coefficient (R) of 0.77 against the experimental free energy derived from the in vitro EC50 activity, showing good repeatability of the proposed method and a slightly better agreement than the results obtained from the arbitrary time frames up to 20 ns. Although it is limited by having one target and a deduced binding pose, we hope that this study can add some insights into alchemical free energy calculation of protein-peptide systems, providing theoretical assistance to the development of peptide drugs.

Discovery of highly potent phosphodiesterase-1 inhibitors by a combined-structure free energy perturbation approach

Accurate receptor/ligand binding free energy calculations can greatly accelerate drug discovery by identifying highly potent ligands. By simulating the change from one compound structure to another, the relative binding free energy (RBFE) change can be calculated based on the theoretically rigorous free energy perturbation (FEP) method. However, existing FEP-RBFE approaches may face convergence challenges due to difficulties in simulating non-physical intermediate states, which can lead to increased computational costs to obtain the converged results. To fundamentally overcome these issues and accelerate drug discovery, a new combined-structure RBFE (CS-FEP) calculation strategy was proposed, which solved the existing issues by constructing a new alchemical pathway, smoothed the alchemical transformation, increased the phase-space overlap between adjacent states, and thus significantly increased the convergence and accelerated the relative binding free energy calculations. This method was extensively tested in a practical drug discovery effort by targeting phosphodiesterase-1 (PDE1). Starting from a PDE1 inhibitor (compound 9, IC50 = 16.8 μmol/L), the CS-FEP guided hit-to-lead optimizations resulted in a promising lead (11b and its mesylate salt formulation 11b-Mesylate, IC50 = 7.0 nmol/L), with ∼2400-fold improved inhibitory activity. Further experimental studies revealed that the lead showed reasonable metabolic stability and significant anti-fibrotic effects in vivo.

Impact of protein conformations on binding free energy calculations in the beta-secretase 1 system.

In binding free energy calculations, simulations must sample all relevant conformations of the system in order to obtain unbiased results. For instance, different ligands can bind to different metastable states of a protein, and if these protein conformational changes are not sampled in relative binding free energy calculations, the contribution of these states to binding is not accounted for and thus calculated binding free energies are inaccurate. In this work, we investigate the impact of different beta-sectretase 1 (BACE1) protein conformations obtained from x-ray crystallography on the binding of BACE1 inhibitors. We highlight how these conformational changes are not adequately sampled in typical molecular dynamics simulations. Furthermore, we show that insufficient sampling of relevant conformations induces substantial error in relative binding free energy calculations, as judged by a variation in calculated relative binding free energies up to 2kcal/mol depending on the starting protein conformation. These results emphasize the importance of protein conformational sampling and pose this BACE1 system as a challenge case for further method development in the area of enhanced protein conformational sampling, either in combination with binding calculations or as an endpoint correction.

Development of a Series of Pyrrolopyridone MAT2A Inhibitors.

The optimization of an allosteric fragment, discovered by differential scanning fluorimetry, to an in vivo MAT2a tool inhibitor is discussed. The structure-based drug discovery approach, aided by relative binding free energy calculations, resulted in AZ'9567 (21), a potent inhibitor in vitro with excellent preclinical pharmacokinetic properties. This tool showed a selective antiproliferative effect on methylthioadenosine phosphorylase (MTAP) KO cells, both in vitro and in vivo, providing further evidence to support the utility of MAT2a inhibitors as potential anticancer therapies for MTAP-deficient tumors.

Flexibility of Binding Site is Essential to the Ca2+ Selectivity in EF-Hand Calcium-Binding Proteins.

High binding affinity and selectivity of metal ions are essential to the function of metalloproteins. Thus, understanding the factors that determine these binding characteristics is of major interest for both fundamental mechanistic investigations and guiding of the design of novel metalloproteins. In this work, we perform QM cluster model calculations and quantum mechanics/molecular mechanics (QM/MM) free energy simulations to understand the binding selectivity of Ca2+ and Mg2+ in the wild-type carp parvalbumin and its mutant. While a nonpolarizable MM model (CHARMM36) does not lead to the correct experimental trend, treatment of the metal binding site with the DFTB3 model in a QM/MM framework leads to relative binding free energies (ΔΔGbind) comparable with experimental data. For the wild-type (WT) protein, the calculated ΔΔGbind is ∼6.6 kcal/mol in comparison with the experimental value of 5.6 kcal/mol. The good agreement highlights the value of a QM description of the metal binding site and supports the role of electronic polarization and charge transfer to metal binding selectivity. For the D51A/E101D/F102W mutant, different binding site models lead to considerable variations in computed binding affinities. With a coordination number of seven for Ca2+, which is shown by QM/MM metadynamics simulations to be the dominant coordination number for the mutant, the calculated relative binding affinity is ∼4.8 kcal/mol, in fair agreement with the experimental value of 1.6 kcal/mol. The WT protein is observed to feature a flexible binding site that accommodates a range of coordination numbers for Ca2+, which is essential to the high binding selectivity for Ca2+ over Mg2+. In the mutant, the E101D mutation reduces the flexibility of the binding site and limits the dominant coordination number of Ca2+ to be seven, thereby leading to reduced binding selectivity against Mg2+. Our results highlight that the binding selectivity of metal ions depends on both the structural and dynamical properties of the protein binding site.