Accuracy of Alternate Nonpolarizable Force Fields for the Determination of Protein-Ligand Binding Affinities Dominated by Cation-π Interactions

Optimized Protein-Excipient Interactions in the Martini 3 Force Field

The high doses of drugs required for biotherapeutics, such as monoclonal antibodies (mAbs), and the small volumes that can be administered to patients by subcutaneous injections pose challenges due to high-concentration formulations. The addition of excipients, such as arginine and glutamate, to high-concentration protein formulations can increase solubility and reduce the tendency of protein particle formation. Molecular dynamics (MD) simulations can provide microscopic insights into the mode of action of excipients in mAb formulations but require large system sizes and long time scales that are currently beyond reach at the fully atomistic level. Computationally efficient coarse-grained models such as the Martini 3 force field can tackle this challenge but require careful parametrization, testing, and validation. This study extends the popular Martini 3 force field toward realistic protein-excipient interactions of arginine and glutamate excipients, using the Fab domains of the therapeutic mAbs trastuzumab and omalizumab as model systems. A novel all-atom to coarse-grained mapping of the amino acid excipients is introduced, which explicitly captures the zwitterionic character of the backbone. The Fab-excipient interactions of arginine and glutamate are characterized concerning molecular contacts with the Fabs at the single-residue level. The Martini 3 simulations are compared with results from all-atom simulations as a reference. Our findings reveal an overestimation of Fab-excipient contacts with the default interaction parameters of Martini 3, suggesting a too strong attraction between protein residues and excipients. Therefore, we reparametrized the protein-excipient interaction parameters in Martini 3 against all-atom simulations. The excipient interactions obtained with the new Martini 3 mapping and Lennard-Jones (LJ) interaction parameters, coined Martini 3-exc, agree closely with the all-atom reference data. This work presents an improved parameter set for mAb-arginine and mAb-glutamate interactions in the Martini 3 coarse-grained force field, a key step toward large-scale coarse-grained MD simulations of high-concentration mAb formulations and the stabilizing effects of excipients.

Discovering cryptic pocket opening and binding of a stimulant derivative in a vestibular site of the 5-HT3A receptor

A diverse set of modulators, including stimulants and anesthetics, regulates ion channel function in our nervous system. However, structures of ligand-bound complexes can be difficult to capture by experimental methods, particularly when binding is dynamic. Here, we used computational methods and electrophysiology to identify a possible bound state of a modulatory stimulant derivative in a cryptic vestibular pocket of a mammalian serotonin-3 receptor. We first applied a molecular dynamics simulation-based goal-oriented adaptive sampling method to identify possible open-pocket conformations, followed by Boltzmann docking that combines traditional docking with Markov state modeling. Clustering and analysis of stability and accessibility of docked poses supported a preferred binding site; we further validated this site by mutagenesis and electrophysiology, suggesting a mechanism of potentiation by stabilizing intersubunit contacts. Given the pharmaceutical relevance of serotonin-3 receptors in emesis, psychiatric, and gastrointestinal diseases, characterizing relatively unexplored modulatory sites such as these could open valuable avenues to understanding conformational cycling and designing state-dependent drugs.

Identification of novel inhibitors for epidermal growth factor receptor tyrosine kinase using absolute binding free-energy simulations

Mutations in the kinase domain of the epidermal growth factor receptor (EGFR), a critical biological macromolecule involved in cell growth and division, can lead to drug resistance in patients undergoing chemotherapy with kinase inhibitors. Notably, the emergence of the C797S mutation poses new challenges for targeted EGFR therapy, highlighting the urgent need for agents effective against this triple mutation (L858R/T790M/C797S, EGFR™). Building on our previous finding that sulfonyl and piperidinyl groups significantly contribute to the EGFR™-inhibitor interactions, we have identified the best-in-class inhibitors containing these groups through functional-group-based screening and formally exact absolute binding free-energy calculations. Our new strategy offers greater flexibility than traditional workflows leaning on relative binding free-energy calculations and accommodates ligands with substantial structural variations. The result shows that the top candidate exhibits a binding affinity of -15.8 kcal/mol towards the EGFR™ mutant, surpassing BLU-945, a state-of-the-art fourth-generation inhibitor with a binding free energy of -12.6 kcal/mol. Subsequent free-energy decomposition indicates that the presented top candidate primarily enhances interactions with the K745, D800 and R841 residues, suggesting its potential to overcome resistance from the C797S mutation. Notably, K745 forms highly favorable hydrogen bonds and cation-π interactions with C6. Targeting lysine has emerged as a promising strategy, especially in cases where the C797S mutation renders traditional covalent inhibitors ineffective. We propose that these novel inhibitors represent promising drug candidates for non-small cell lung cancer treatment and offer new strategies to overcome drug resistance caused by EGFR mutation.

Overview on Building Blocks and Applications of Efficient and Robust Extended Tight Binding

The extended tight binding (xTB) family of methods opened many new possibilities in the field of computational chemistry. Within just 5 years, the GFN2-xTB parametrization for all elements up to Z = 86 enabled more than a thousand applications, which were previously not feasible with other electronic structure methods. The xTB methods provide a robust and efficient way to apply quantum mechanics-based approaches for obtaining molecular geometries, computing free energy corrections or describing noncovalent interactions and found applicability for many more targets. A crucial contribution to the success of the xTB methods is the availability within many simulation packages and frameworks, supported by the open source development of its program library and packages. We present a comprehensive summary of the applications and capabilities of xTB methods in different fields of chemistry. Moreover, we consider the main software packages for xTB calculations, covering their current ecosystem, novel features, and usage by the scientific community.

Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface

γ-Aminobutyric acid type A (GABAA) receptors are ligand-gated ion channels in the central nervous system with largely inhibitory function. Despite being a target for drugs including general anesthetics and benzodiazepines, experimental structures have yet to capture an open state of classical synaptic α1β2γ2 GABAA receptors. Here, we use a goal-oriented adaptive sampling strategy in molecular dynamics simulations followed by Markov state modeling to capture an energetically stable putative open state of the receptor. The model conducts chloride ions with comparable conductance as in electrophysiology measurements. Relative to experimental structures, our open model is relatively expanded at both the cytoplasmic (-2') and central (9') gates, coordinated with distinctive rearrangements at the transmembrane αβ subunit interface. Consistent with previous experiments, targeted substitutions disrupting interactions at this interface slowed the open-to-desensitized transition rate. This work demonstrates the capacity of advanced simulation techniques to investigate a computationally and experimentally plausible functionally critical of a complex membrane protein yet to be resolved by experimental methods.

Synthesis, insertion, and characterization of SARS-CoV-2 membrane protein within lipid bilayers

Throughout history, coronaviruses have posed challenges to both public health and the global economy; nevertheless, methods to combat them remain rudimentary, primarily due to the absence of experiments to understand the function of various viral components. Among these, membrane (M) proteins are one of the most elusive because of their small size and challenges with expression. Here, we report the development of an expression system to produce tens to hundreds of milligrams of M protein per liter of Escherichia coli culture. These large yields render many previously inaccessible structural and biophysical experiments feasible. Using cryo-electron microscopy and atomic force microscopy, we image and characterize individual membrane-incorporated M protein dimers and discover membrane thinning in the vicinity, which we validated with molecular dynamics simulations. Our results suggest that the resulting line tension, along with predicted induction of local membrane curvature, could ultimately drive viral assembly and budding.

Residue-resolved insights into the stabilization of therapeutic proteins by excipients: A case study of two monoclonal antibodies with arginine and glutamate

Protein formulation development relies on the selection of excipients that inhibit protein-protein interactions preventing aggregation. Empirical strategies involve screening many excipient and buffer combinations by physicochemical characterization using forced degradation or temperature-induced stress, mostly under accelerated conditions. Such methods do not readily provide information on the inter- and intramolecular interactions responsible for the effects of excipients. Here, we describe a combined experimental and computational approach for investigating the effect of protein-excipient interactions on formulation stability, which allows the identification of preferential interaction sites and thus can aid in the selection of excipients to be experimentally screened. Model systems composed of two marketed therapeutic IgG1 monoclonal antibodies with identical Fc domain sequences, trastuzumab and omalizumab, were investigated with commonly used excipients arginine, glutamate, and equimolar arginine/glutamate mixtures. Protein-excipient interactions were studied using all-atom molecular dynamics (MD) simulations, which show accumulation of the excipients at specific antibody regions. Preferential excipient-interaction sites were particularly found for charged and aromatic residues and in the complementary-determining regions, with more pronounced arginine contacts for omalizumab than trastuzumab. These computational findings are in line with the more pronounced stabilizing effects of arginine observed in the long-term storage stability study. Furthermore, the aggregation and solubility propensity predicted by commonly used in silico tools do not align with the preferential excipient-interaction sites identified by the MD simulations, suggesting that different physicochemical mechanisms are at play.

Binding Thermodynamics of Fourth-Generation EGFR Inhibitors Revealed by Absolute Binding Free Energy Calculations

The overexpression or mutation of the kinase domain of the epidermal growth factor receptor (EGFR) is strongly associated with non-small-cell lung cancer (NSCLC). EGFR tyrosine kinase inhibitors (TKIs) have proven to be effective in treating NSCLC patients. However, EGFR mutations can result in drug resistance. To elucidate the mechanisms underlying this resistance and inform future drug development, we examined the binding affinities of BLU-945, a recently reported fourth-generation TKI, to wild-type EGFR (EGFRWT) and its double-mutant (L858R/T790M; EGFRDM) and triple-mutant (L858R/T790M/C797S; EGFRTM) forms. We compared the binding affinities of BLU-945, BLU-945 analogues, CH7233163 (another fourth-generation TKI), and erlotinib (a first-generation TKI) using absolute binding free energy calculations. Our findings reveal that BLU-945 and CH7233163 exhibit binding affinities to both EGFRDM and EGFRTM stronger than those of erlotinib, corroborating experimental data. We identified K745 and T854 as the key residues in the binding of fourth-generation EGFR TKIs. Electrostatic forces were the predominant driving force for the binding of fourth-generation TKIs to EGFR mutants. Furthermore, we discovered that the incorporation of piperidinol and sulfone groups in BLU-945 substantially enhanced its binding capacity to EGFR mutants. Our study offers valuable theoretical insights for optimizing fourth-generation EGFR TKIs.

Structural basis for ligand recognition and signaling of hydroxy-carboxylic acid receptor 2

Hydroxycarboxylic acid receptors (HCAR1, HCAR2, and HCAR3) transduce Gi/o signaling upon biding to molecules such as lactic acid, butyric acid and 3-hydroxyoctanoic acid, which are associated with lipolytic and atherogenic activity, and neuroinflammation. Although many reports have elucidated the function of HCAR2 and its potential as a therapeutic target for treating not only dyslipidemia but also neuroimmune disorders such as multiple sclerosis and Parkinson's disease, the structural basis of ligand recognition and ligand-induced Gi-coupling remains unclear. Here we report three cryo-EM structures of the human HCAR2-Gi signaling complex, each bound with different ligands: niacin, acipimox or GSK256073. All three agonists are held in a deep pocket lined by residues that are not conserved in HCAR1 and HCAR3. A distinct hairpin loop at the HCAR2 N-terminus and extra-cellular loop 2 (ECL2) completely enclose the ligand. These structures also reveal the agonist-induced conformational changes propagated to the G-protein-coupling interface during activation. Collectively, the structures presented here are expected to help in the design of ligands specific for HCAR2, leading to new drugs for the treatment of various diseases such as dyslipidemia and inflammation.

Structure and dynamics of differential ligand binding in the human ρ-type GABAA receptor

The neurotransmitter γ-aminobutyric acid (GABA) drives critical inhibitory processes in and beyond the nervous system, partly via ionotropic type-A receptors (GABAARs). Pharmacological properties of ρ-type GABAARs are particularly distinctive, yet the structural basis for their specialization remains unclear. Here, we present cryo-EM structures of a lipid-embedded human ρ1 GABAAR, including a partial intracellular domain, under apo, inhibited, and desensitized conditions. An apparent resting state, determined first in the absence of modulators, was recapitulated with the specific inhibitor (1,2,5,6-tetrahydropyridin-4-yl)methylphosphinic acid and blocker picrotoxin and provided a rationale for bicuculline insensitivity. Comparative structures, mutant recordings, and molecular simulations with and without GABA further explained the sensitized but slower activation of ρ1 relative to canonical subtypes. Combining GABA with picrotoxin also captured an apparent uncoupled intermediate state. This work reveals structural mechanisms of gating and modulation with applications to ρ-specific pharmaceutical design and to our biophysical understanding of ligand-gated ion channels.

Modern non-polarizable force fields diverge in modeling the enzyme-substrate complex of a canonical serine protease

Classical molecular dynamics simulation is a powerful and established method of modern computational chemistry. Being able to obtain accurate information on molecular behavior is crucial to get valuable insights into structure-function relationships that translate into fundamental findings and practical applications. Active sites of enzymes are known to be particularly intricate, therefore, simpler non-polarizable force fields may provide an inaccurate description. In this work, we addressed this hypothesis in a case of a canonical serine triad protease trypsin in its complex with a substrate-mimicking inhibitor. We tested six modern and popular force fields to find that significantly diverging results may be obtained. Amber FB-15 and OPLS-AA/M turned out to model the active site incorrectly. Amber ff19sb and ff15ipq demonstrated mixed performance. The best performing force fields were CHARMM36m and Amber ff99sb-ildn, therefore, they are recommended for use with this and related systems. We speculate that a similar lack of cross-force field convergence may be characteristic of other enzymatic systems. Therefore, we advocate for careful consideration of different force fields in any study within the field of computational enzymology.

Conformational dynamics and putative substrate extrusion pathways of the N-glycosylated outer membrane factor CmeC from Campylobacter jejuni

The outer membrane factor CmeC of the efflux machinery CmeABC plays an important role in conferring antibiotic and bile resistance to Campylobacter jejuni. Curiously, the protein is N-glycosylated, with the glycans playing a key role in the effective function of this system. In this work we have employed atomistic equilibrium molecular dynamics simulations of CmeC in a representative model of the C. jejuni outer membrane to characterise the dynamics of the protein and its associated glycans. We show that the glycans are more conformationally labile than had previously been thought. The extracellular loops of CmeC visit the open and closed states freely suggesting the absence of a gating mechanism on this side, while the narrow periplasmic entrance remains tightly closed, regulated via coordination to solvated cations. We identify several cation binding sites on the interior surface of the protein. Additionally, we used steered molecular dynamics simulations to elucidate translocation pathways for a bile acid and a macrolide antibiotic. These, and additional equilibrium simulations suggest that the anionic bile acid utilises multivalent cations to climb the ladder of acidic residues that line the interior surface of the protein.

Meta-Analysis Reveals That Absolute Binding Free-Energy Calculations Approach Chemical Accuracy

Systematic and quantitative analysis of the reliability of formally exact methods that in silico calculate absolute protein-ligand binding free energies remains lacking. Here, we provide, for the first time, evidence-based information on the reliability of these methods by statistically studying 853 cases from 34 different research groups through meta-analysis. The results show that formally exact methods approach chemical accuracy (error = 1.58 kcal/mol), even if people are challenging difficult tasks such as blind drug screening in recent years. The geometrical-pathway-based methods prove to possess a better convergence ability than the alchemical ones, while the latter have a larger application range. We also reveal the importance of always using the latest force fields to guarantee reliability and discuss the pros and cons of turning to an implicit solvent model in absolute binding free-energy calculations. Moreover, based on the meta-analysis, an evidence-based guideline for in silico binding free-energy calculations is provided.

Structure of SARS-CoV-2 membrane protein essential for virus assembly

The coronavirus membrane protein (M) is the most abundant viral structural protein and plays a central role in virus assembly and morphogenesis. However, the process of M protein-driven virus assembly are largely unknown. Here, we report the cryo-electron microscopy structure of the SARS-CoV-2 M protein in two different conformations. M protein forms a mushroom-shaped dimer, composed of two transmembrane domain-swapped three-helix bundles and two intravirion domains. M protein further assembles into higher-order oligomers. A highly conserved hinge region is key for conformational changes. The M protein dimer is unexpectedly similar to SARS-CoV-2 ORF3a, a viral ion channel. Moreover, the interaction analyses of M protein with nucleocapsid protein (N) and RNA suggest that the M protein mediates the concerted recruitment of these components through the positively charged intravirion domain. Our data shed light on the M protein-driven virus assembly mechanism and provide a structural basis for therapeutic intervention targeting M protein.

Accurate Description of Solvent-Exposed Salt Bridges with a Non-polarizable Force Field Incorporating Solvent Effects

The strength of salt bridges resulting from the interaction of cations and anions is modulated by their environment. However, polarization of the solvent molecules by the charged moieties makes the accurate description of cation-anion interactions in an aqueous solution by means of a pairwise additive potential energy function and classical combination rules particularly challenging. In this contribution, aiming at improving the representation of solvent-exposed salt-bridge interactions with an all-atom non-polarizable force field, we put forth here a parametrization strategy. First, the interaction of a cation and an anion is characterized by hybrid quantum mechanical/molecular mechanics (QM/MM) potential of mean force (PMF) calculations, whereby constantly exchanging solvent molecules around the ions are treated at the quantum mechanical level. The Lennard-Jones (LJ) parameters describing the salt-bridge ion pairs are then optimized to match the reference QM/MM PMFs through the so-called nonbonded FIX, or NBFIX, feature of the CHARMM force field. We apply the new set of parameters, coined CHARMM36m-SBFIX, to the calculation of association constants for the ammonium-acetate and guanidinium-acetate complexes, the osmotic pressures for glycine zwitterions, guanidinium, and acetate ions, and to the simulation of both folded and intrinsically disordered proteins. Our findings indicate that CHARMM36m-SBFIX improves the description of solvent-exposed salt-bridge interactions, both structurally and thermodynamically. However, application of this force field to the standard binding free-energy calculation of a protein-ligand complex featuring solvent-excluded salt-bridge interactions leads to a poor reproduction of the experimental value, suggesting that the parameters optimized in an aqueous solution cannot be readily transferred to describe solvent-excluded salt-bridge interactions. Put together, owing to their sensitivity to the environment, modeling salt-bridge interactions by means of a single, universal set of LJ parameters remains a daunting theoretical challenge.

Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations

Designing a reliable computational methodology to calculate protein:ligand standard binding free energies is extremely challenging. The large change in configurational enthalpy and entropy that accompanies the association of ligand and protein is notoriously difficult to capture in naive brute-force simulations. Addressing this issue, the present protocol rests upon a rigorous statistical mechanical framework for the determination of protein:ligand binding affinities together with the comprehensive Binding Free-Energy Estimator 2 (BFEE2) application software. With the knowledge of the bound state, available from experiments or docking, application of the BFEE2 protocol with a reliable force field supplies in a matter of days standard binding free energies within chemical accuracy, for a broad range of protein:ligand complexes. Limiting undesirable human intervention, BFEE2 assists the end user in preparing all the necessary input files and performing the post-treatment of the simulations towards the final estimate of the binding affinity.