Structure of the MRAS-SHOC2-PP1C phosphatase complex.

RAS-MAPK signalling is fundamental for cell proliferation and is altered in most human cancers1-3. However, our mechanistic understanding of how RAS signals through RAF is still incomplete. Although studies revealed snapshots for autoinhibited and active RAF-MEK1-14-3-3 complexes4, the intermediate steps that lead to RAF activation remain unclear. The MRAS-SHOC2-PP1C holophosphatase dephosphorylates RAF at serine 259, resulting in the partial displacement of 14-3-3 and RAF-RAS association3,5,6. MRAS, SHOC2 and PP1C are mutated in rasopathies-developmental syndromes caused by aberrant MAPK pathway activation6-14-and SHOC2 itself has emerged as potential target in receptor tyrosine kinase (RTK)-RAS-driven tumours15-18. Despite its importance, structural understanding of the SHOC2 holophosphatase is lacking. Here we determine, using X-ray crystallography, the structure of the MRAS-SHOC2-PP1C complex. SHOC2 bridges PP1C and MRAS through its concave surface and enables reciprocal interactions between all three subunits. Biophysical characterization indicates a cooperative assembly driven by the MRAS GTP-bound active state, an observation that is extendible to other RAS isoforms. Our findings support the concept of a RAS-driven and multi-molecular model for RAF activation in which individual RAS-GTP molecules recruit RAF-14-3-3 and SHOC2-PP1C to produce downstream pathway activation. Importantly, we find that rasopathy and cancer mutations reside at protein-protein interfaces within the holophosphatase, resulting in enhanced affinities and function. Collectively, our findings shed light on a fundamental mechanism of RAS biology and on mechanisms of clinically observed enhanced RAS-MAPK signalling, therefore providing the structural basis for therapeutic interventions.

Rational design of a new antibiotic class for drug-resistant infections.

The development of new antibiotics to treat infections caused by drug-resistant Gram-negative pathogens is of paramount importance as antibiotic resistance continues to increase worldwide1. Here we describe a strategy for the rational design of diazabicyclooctane inhibitors of penicillin-binding proteins from Gram-negative bacteria to overcome multiple mechanisms of resistance, including ß-lactamase enzymes, stringent response and outer membrane permeation. Diazabicyclooctane inhibitors retain activity in the presence of ß-lactamases, the primary resistance mechanism associated with ß-lactam therapy in Gram-negative bacteria2,3. Although the target spectrum of an initial lead was successfully re-engineered to gain in vivo efficacy, its ability to permeate across bacterial outer membranes was insufficient for further development. Notably, the features that enhanced target potency were found to preclude compound uptake. An improved optimization strategy leveraged porin permeation properties concomitant with biochemical potency in the lead-optimization stage. This resulted in ETX0462, which has potent in vitro and in vivo activity against Pseudomonas aeruginosa plus all other Gram-negative ESKAPE pathogens, Stenotrophomonas maltophilia and biothreat pathogens. These attributes, along with a favourable preclinical safety profile, hold promise for the successful clinical development of the first novel Gram-negative chemotype to treat life-threatening antibiotic-resistant infections in more than 25 years.

Revealing Molecular Determinants of hERG Blocker and Activator Binding.

The Kv11.1 potassium channel, encoded by the human ether-a-go-go-related gene (hERG), plays an essential role in the cardiac action potential. hERG blockade by small molecules can induce "torsade de pointes" arrhythmias and sudden death; as such, it is an important off-target to avoid during drug discovery. Recently, a cryo-EM structure of the open channel state of hERG was reported, opening the door to in silico docking analyses and interpretation of hERG structure-activity relationships, with a view to avoiding blocking activity. Despite this, docking directly to this cryo-EM structure has been reported to yield binding modes that are unable to explain known mutagenesis data. In this work, we use molecular dynamics simulations to sample a range of channel conformations and run ensemble docking campaigns at the known hERG binding site below the selectivity filter, composed of the central cavity and the four deep hydrophobic pockets. We identify a hERG conformational state allowing discrimination of blockers vs nonblockers from docking; furthermore, the binding pocket agrees with mutagenesis data, and blocker binding modes fit the hERG blocker pharmacophore. We then use the same protocol to identify a binding pocket in the hERG channel pore for hERG activators, again agreeing with the reported mutagenesis. Our approach may be useful in drug discovery campaigns to prioritize candidate compounds based on hERG liability via virtual docking screens.

Time-averaged distributions of solute and solvent motions: exploring proton wires of GFP and PfM2DH.

Proton translocation pathways of selected variants of the green fluorescent protein (GFP) and Pseudomonas fluorescens mannitol 2-dehydrogenase (PfM2DH) were investigated via an explicit solvent molecular dynamics-based analysis protocol that allows for direct quantitative relationship between a crystal structure and its time-averaged solute-solvent structure obtained from simulation. Our study of GFP is in good agreement with previous research suggesting that the proton released from the chromophore upon photoexcitation can diffuse through an extended internal hydrogen bonding network that allows for the proton to exit to bulk or be recaptured by the anionic chromophore. Conversely for PfM2DH, we identified the most probable ionization states of key residues along the proton escape channel from the catalytic site to bulk solvent, wherein the solute and high-density solvent crystal structures of binary and ternary complexes were properly reproduced. Furthermore, we proposed a plausible mechanism for this proton translocation process that is consistent with the state-dependent structural shifts observed in our analysis. The time-averaged structures generated from our analyses facilitate validation of MD simulation results and provide a comprehensive profile of the dynamic all-occupancy solvation network within and around a flexible solute, from which detailed hydrogen-bonding networks can be inferred. In this way, potential drawbacks arising from the elucidation of these networks by examination of static crystal structures or via alternate rigid-protein solvation analysis procedures can be overcome. Complementary studies aimed at the effective use of our methodology for alternate implementations (e.g., ligand design) are currently underway.

Dissecting the Interaction Fingerprints and Binding Affinity of BYL719 Analogs Targeting PI3Kα.

Phosphatidylinositol-3-kinase Alpha (PI3Kα) is a lipid kinase which regulates signaling pathways involved in cell proliferation. Dysregulation of these pathways promotes several human cancers, pushing for the development of anticancer drugs to target PI3Kα. One such medicinal chemistry campaign at Novartis led to the discovery of BYL719 (Piqray, Alpelicib), a PI3Kα inhibitor approved by the FDA in 2019 for treatment of HR+/HER2-advanced breast cancer with a PIK3CA mutation. Structure-based drug design played a key role in compound design and optimization throughout the discovery process. However, further characterization of potency drivers via structural dynamics and energetic analyses can be advantageous for ensuing PI3Kα programs. Here, our goal is to employ various in-silico techniques, including molecular simulations and machine learning, to characterize 14 ligands from the BYL719 analogs and predict their binding affinities. The structural insights from molecular simulations suggest that although the ligand-hinge interaction is the primary driver of ligand stability at the pocket, the R group positioning at C2 or C6 of pyridine/pyrimidine also plays a major role. Binding affinities predicted via thermodynamic integration (TI) are in good agreement with previously reported IC50s. Yet, computationally demanding techniques such as TI might not always be the most efficient approach for affinity prediction, as in our case study, fast high-throughput techniques were capable of classifying compounds as active or inactive, and one docking approach showed accuracy comparable to TI.

Overcoming dissipation in the calculation of standard binding free energies by ligand extraction.

This article addresses calculations of the standard free energy of binding from molecular simulations in which a bound ligand is extracted from its binding site by steered molecular dynamics (MD) simulations or equilibrium umbrella sampling (US). Host-guest systems are used as test beds to examine the requirements for obtaining the reversible work of ligand extraction. We find that, for both steered MD and US, marked irreversibilities can occur when the guest molecule crosses an energy barrier and suddenly jumps to a new position, causing dissipation of energy stored in the stretched molecule(s). For flexible molecules, this occurs even when a stiff pulling spring is used, and it is difficult to suppress in calculations where the spring is attached to the molecules by single, fixed attachment points. We, therefore, introduce and test a method, fluctuation-guided pulling, which adaptively adjusts the spring's attachment points based on the guest's atomic fluctuations relative to the host. This adaptive approach is found to substantially improve the reversibility of both steered MD and US calculations for the present systems. The results are then used to estimate standard binding free energies within a comprehensive framework, termed attach-pull-release, which recognizes that the standard free energy of binding must include not only the pulling work itself, but also the work of attaching and then releasing the spring, where the release work includes an accounting of the standard concentration to which the ligand is discharged.

N-terminal ß-strand in YAP is critical for stronger binding to scalloped relative to TEAD transcription factor.

The yes-associated protein (YAP) regulates the transcriptional activity of the TEAD transcription factors that are key in the control of organ morphogenesis. YAP interacts with TEAD via three secondary structure elements: a ß-strand, an α-helix, and an Ω-loop. Earlier results have shown that the ß-strand has only a marginal contribution in the YAP:TEAD interaction, but we show here that it significantly enhances the affinity of YAP for the Drosophila homolog of TEAD, scalloped (Sd). Nuclear magnetic resonance shows that the ß-strand adopts a more rigid conformation once bound to Sd; pre-steady state kinetic measurements show that the YAP:Sd complex is more stable. Although the crystal structures of the YAP:TEAD and YAP:Sd complexes reveal no differences at the binding interface that could explain these results. Molecular Dynamics simulations are in line with our experimental findings regarding ß-strand stability and overall binding affinity of YAP to TEAD and Sd. In particular, RMSF, correlated motion and MMGBSA analyses suggest that ß-sheet fluctuations play a relevant role in YAP53-57 ß-strand dissociation from TEAD4 and contribute to the lower affinity of YAP for TEAD4. Identifying a clear mechanism leading to the difference in YAP's ß-strand stability proved to be challenging, pointing to the potential relevance of multiple modest structural changes or fluctuations for regulation of binding affinity.

Martini 3 Force Field Parameters for Protein Lipidation Post-Translational Modifications.

Protein lipidations are vital co/post-translational modifications that tether lipid tails to specific protein amino acids, allowing them to anchor to biological membranes, switch their subcellular localization, and modulate association with other proteins. Such lipidations are thus crucial for multiple biological processes including signal transduction, protein trafficking, and membrane localization and are implicated in various diseases as well. Examples of lipid-anchored proteins include the Ras family of proteins that undergo farnesylation; actin and gelsolin that are myristoylated; phospholipase D that is palmitoylated; glycosylphosphatidylinositol-anchored proteins; and others. Here, we develop parameters for cysteine-targeting farnesylation, geranylgeranylation, and palmitoylation, as well as glycine-targeting myristoylation for the latest version of the Martini 3 coarse-grained force field. The parameters are developed using the CHARMM36m all-atom force field parameters as reference. The behavior of the coarse-grained models is consistent with that of the all-atom force field for all lipidations and reproduces key dynamical and structural features of lipid-anchored peptides, such as the solvent-accessible surface area, bilayer penetration depth, and representative conformations of the anchors. The parameters are also validated in simulations of the lipid-anchored peripheral membrane proteins Rheb and Arf1, after comparison with independent all-atom simulations. The parameters, along with mapping schemes for the popular martinize2 tool, are available for download at 10.5281/zenodo.7849262 and also as supporting information.

Membrane Composition and Raf[CRD]-Membrane Attachment Are Driving Forces for K-Ras4B Dimer Stability.

Ras proteins are membrane-anchored GTPases that regulate key cellular signaling networks. It has been recently shown that different anionic lipid types can affect the properties of Ras in terms of dimerization/clustering on the cell membrane. To understand the effects of anionic lipids on key spatiotemporal properties of dimeric K-Ras4B, we perform all-atom molecular dynamics simulations of the dimer K-Ras4B in the presence and absence of Raf[RBD/CRD] effectors on two model anionic lipid membranes: one containing 78% mol DOPC, 20% mol DOPS, and 2% mol PIP2 and another one with enhanced concentration of anionic lipids containing 50% mol DOPC, 40% mol DOPS, and 10% mol PIP2. Analysis of our results unveils the orientational space of dimeric K-Ras4B and shows that the stability of the dimer is enhanced on the membrane containing a high concentration of anionic lipids in the absence of Raf effectors. This enhanced stability is also observed in the presence of Raf[RBD/CRD] effectors although it is not influenced by the concentration of anionic lipids in the membrane, but rather on the ability of Raf[CRD] to anchor to the membrane. We generate dominant K-Ras4B conformations by Markov state modeling and yield the population of states according to the K-Ras4B orientation on the membrane. For the membrane containing anionic lipids, we observe correlations between the diffusion of K-Ras4B and PIP2 and anchoring of anionic lipids to the Raf[CRD] domain. We conclude that the presence of effectors with the Raf[CRD] domain anchoring on the membrane as well as the membrane composition both influence the conformational stability of the K-Ras4B dimer, enabling the preservation of crucial interface interactions.

Evaluating the Efficiency of the Martini Force Field to Study Protein Dimerization in Aqueous and Membrane Environments.

Protein-protein complex assembly is one of the major drivers of biological response. Understanding the mechanisms of protein oligomerization/dimerization would allow one to elucidate how these complexes participate in biological activities and could ultimately lead to new approaches in designing novel therapeutic agents. However, determining the exact association pathways and structures of such complexes remains a challenge. Here, we use parallel tempering metadynamics simulations in the well-tempered ensemble to evaluate the performance of Martini 2.2P and Martini open-beta 3 (Martini 3) force fields in reproducing the structure and energetics of the dimerization process of membrane proteins and proteins in an aqueous solution in reasonable accuracy and throughput. We find that Martini 2.2P systematically overestimates the free energy of association by estimating large barriers in distinct areas, which likely leads to overaggregation when multiple monomers are present. In comparison, the less viscous Martini 3 results in a systematic underestimation of the free energy of association for proteins in solution, while it performs well in describing the association of membrane proteins. In all cases, the near-native dimer complexes are identified as minima in the free energy surface albeit not always as the lowest minima. In the case of Martini 3, we find that the spurious supramolecular protein aggregation present in Martini 2.2P multimer simulations is alleviated and thus this force field may be more suitable for the study of protein oligomerization. We propose that the use of enhanced sampling simulations with a refined coarse-grained force field and appropriately defined collective variables is a robust approach for studying the protein dimerization process, although one should be cautious of the ranking of energy minima.

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease.

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of Mpro, a cysteine protease, have been determined, facilitating structure-based drug design. Mpro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, Mpro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nucleophile Cys145 have been debated in previous studies of SARS-CoV Mpro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 Mpro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of Mpro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 Mpro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Kinetics and mechanism of the unfolding native-to-loop transition of Trp-cage in explicit solvent via optimized forward flux sampling simulations.

The native-to-loop (N-L) unfolding transition of Trp-cage protein was studied via optimized forward flux sampling (FFS) methods with trajectories evolved using molecular dynamics. The rate constant calculated from our simulations is in good agreement with the experimental value for the native-to-unfolded transition of this protein; furthermore, the trajectories sampled a phase region consistent with that reported in previous studies for the N-L transition using transition path sampling and transition interface sampling. A new variant of FFS is proposed and implemented that allows a better control of a constant flux of partial paths. A reaction coordinate model was obtained, at no extra cost, from the transition path ensemble generated by FFS, through iterative use of the FFS-least-square estimation method [E. E. Borrero and F. A. Escobedo, J. Chem. Phys. 127, 164101 (2007)] and an adaptive staging optimization algorithm [E. E. Borrero and F. A. Escobedo, J. Chem. Phys. 129, 024115 (2008)]. Finally, we further elucidate the unfolding mechanism by correlating the unfolding progress with changes in the root mean square deviation from the α carbons of the native state, the root mean square deviation from an ideal α-helix, and other structural properties of the protein.

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease.

The main protease (M pro ) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of M pro , a cysteine protease, have been determined, facilitating structure-based drug design. M pro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41-Cys145, M pro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nu-cleophile Cys145 have been debated in previous studies of SARS-CoV M pro , but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 M pro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of M pro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α -ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N δ (HD) and N ϵ (HE) protonation of His41 and His164, respectively, the α -ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 M pro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

Simulated mutagenesis of the hypervariable loops of a llama VHH domain for the recovery of canonical conformations.

In this work, wildtype and mutated hypervariable regions of an anti-hCG llama VHH antibody were simulated via a molecular dynamics replica exchange method (REM). Seven mutants were simulated with the goal of identifying structural determinants that return the noncanonical H1 loop of the wildtype antibody to the type 1 canonical structure predicted by database methods formulated for conventional antibodies. Two cases with three point mutations yielded a stable type 1 H1 structure. In addition, other mutants with fewer mutations showed evidence of such conformations. Overall, the mutagenesis results suggest a marked influence of interloop interactions on the attainment of canonical conformations for this antibody. On the methodological front, a novel REM scheme was developed to quickly screen diverse mutants based on their relative propensities for attaining favorable structures. This multimutant REM (MMREM) was used to successfully identify mutations that stabilize a canonical H1 loop grafted on the llama antibody scaffold. The use of MMREM and REM for screening mutants and assessing structural stability may be useful in the rational design of antibody hypervariable loops.

Kinetics and reaction coordinate for the isomerization of alanine dipeptide by a forward flux sampling protocol.

Forward flux sampling (FFS) simulations were used to study the kinetics of alanine dipeptide both in vacuum and in explicit solvent. The recently proposed FFS least-squares estimation approach and an algorithm that optimizes the position of the interfaces were implemented to determine a reaction coordinate that adequately describes the transition dynamics. A new method is also introduced to try to ensure that the ensemble of "starting points" (for the trial trajectories) is properly sampled. The rate constant estimates for the C7(eq)-->C5 transition of alanine dipeptide in vacuum were used to demonstrate the consistency between Monte Carlo and molecular dynamics (MD) simulations. FFS-MD simulations were then performed for the study of the beta(2)/alpha(R)-->C5/C7(eq) transition in explicit solvent. The kinetic results for both systems in vacuum and explicit solvent are in general agreement with previous experimental and computational studies for this peptide. In vacuum, an additional dihedral angle besides the one typically used as order parameter is identified as a significant variable in the reaction coordinate model. In solution, several dihedral angles and variables that describe the solvent action on the molecule's dynamics are found to play a significant role in the description of the system's dynamics.

Whole-Cell-Based Assay To Evaluate Structure Permeation Relationships for Carbapenem Passage through the Pseudomonas aeruginosa Porin OprD.

The global emergence of antibiotic resistance, especially in Gram-negative bacteria, is an urgent threat to public health. Discovery of novel classes of antibiotics with activity against these pathogens has been impeded by a fundamental lack of understanding of the molecular drivers underlying small molecule uptake. Although it is well-known that outer membrane porins represent the main route of entry for small, hydrophilic molecules across the Gram-negative cell envelope, the structure-permeation relationship for porin passage has yet to be defined. To address this knowledge gap, we developed a sensitive and specific whole-cell approach in Escherichia coli called titrable outer membrane permeability assay system (TOMAS). We used TOMAS to characterize the structure porin-permeation relationships of a set of novel carbapenem analogues through the Pseudomonas aeruginosa porin OprD. Our results show that small structural modifications, especially the number and nature of charges and their position, have dramatic effects on the ability of these molecules to permeate cells through OprD. This is the first demonstration of a defined relationship between specific molecular changes in a substrate and permeation through an isolated porin. Understanding the molecular mechanisms that impact antibiotic transit through porins should provide valuable insights to antibacterial medicinal chemistry and may ultimately allow for the rational design of porin-mediated uptake of small molecules into Gram-negative bacteria.

Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT.

ETX2514 is a broad-spectrum ß-lactamase inhibitor for the treatment of drug-resistant Gram-negative bacteria including Acinetobacter baumannii.

Multidrug-resistant (MDR) bacterial infections are a serious threat to public health. Among the most alarming resistance trends is the rapid rise in the number and diversity of ß-lactamases, enzymes that inactivate ß-lactams, a class of antibiotics that has been a therapeutic mainstay for decades. Although several new ß-lactamase inhibitors have been approved or are in clinical trials, their spectra of activity do not address MDR pathogens such as Acinetobacter baumannii. This report describes the rational design and characterization of expanded-spectrum serine ß-lactamase inhibitors that potently inhibit clinically relevant class A, C and D ß-lactamases and penicillin-binding proteins, resulting in intrinsic antibacterial activity against Enterobacteriaceae and restoration of ß-lactam activity in a broad range of MDR Gram-negative pathogens. One of the most promising combinations is sulbactam-ETX2514, whose potent antibacterial activity, in vivo efficacy against MDR A. baumannii infections and promising preclinical safety demonstrate its potential to address this significant unmet medical need.

Uncoupling the Structure-Activity Relationships of ß2 Adrenergic Receptor Ligands from Membrane Binding.

Ligand binding to membrane proteins may be significantly influenced by the interaction of ligands with the membrane. In particular, the microscopic ligand concentration within the membrane surface solvation layer may exceed that in bulk solvent, resulting in overestimation of the intrinsic protein-ligand binding contribution to the apparent/measured affinity. Using published binding data for a set of small molecules with the ß2 adrenergic receptor, we demonstrate that deconvolution of membrane and protein binding contributions allows for improved structure-activity relationship analysis and structure-based drug design. Molecular dynamics simulations of ligand bound membrane protein complexes were used to validate binding poses, allowing analysis of key interactions and binding site solvation to develop structure-activity relationships of ß2 ligand binding. The resulting relationships are consistent with intrinsic binding affinity (corrected for membrane interaction). The successful structure-based design of ligands targeting membrane proteins may require an assessment of membrane affinity to uncouple protein binding from membrane interactions.

Estimation of Solvation Entropy and Enthalpy via Analysis of Water Oxygen-Hydrogen Correlations.

A statistical-mechanical framework for estimation of solvation entropies and enthalpies is proposed, which is based on the analysis of water as a mixture of correlated water oxygens and water hydrogens. Entropic contributions of increasing order are cast in terms of a Mutual Information Expansion that is evaluated to pairwise interactions. In turn, the enthalpy is computed directly from a distance-based hydrogen bonding energy algorithm. The resulting expressions are employed for grid-based analyses of Molecular Dynamics simulations. In this first assessment of the methodology, we obtained global estimates of the excess entropy and enthalpy of water that are in good agreement with experiment and examined the method's ability to enable detailed elucidation of solvation thermodynamic structures, which can provide valuable knowledge toward molecular design.