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

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.

N-terminal β-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 β-strand, an α-helix, and an Ω-loop. Earlier results have shown that the β-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 β-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 β-strand stability and overall binding affinity of YAP to TEAD and Sd. In particular, RMSF, correlated motion and MMGBSA analyses suggest that β-sheet fluctuations play a relevant role in YAP53-57 β-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 β-strand stability proved to be challenging, pointing to the potential relevance of multiple modest structural changes or fluctuations for regulation of binding affinity.

Relative Binding Free-Energy Calculations at Lipid-Exposed Sites: Deciphering Hot Spots

Relative binding free-energy (RBFE) calculations are experiencing resurgence in the computer-aided drug design of novel small molecules due to performance gains allowed by cutting-edge molecular mechanic force fields and computer hardware. Application of RBFE to soluble proteins is becoming a routine, while recent studies outline necessary steps to successfully apply RBFE at the orthosteric site of membrane-embedded G-protein-coupled receptors (GPCRs). In this work, we apply RBFE to a congeneric series of antagonists that bind to a lipid-exposed, extra-helical site of the P2Y1 receptor. We find promising performance of RBFE, such that it may be applied in a predictive manner on drug discovery programs targeting lipid-exposed sites. Further, by the application of the microkinetic model, binding at a lipid-exposed site can be split into (1) membrane partitioning of the drug molecule followed by (2) binding at the extra-helical site. We find that RBFE can be applied to calculate the free energy of each step, allowing the uncoupling of observed binding free energy from the influence of membrane affinity. This protocol may be used to identify binding hot spots at extra-helical sites and guide drug discovery programs toward optimizing intrinsic activity at the target.

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 β-lactamase enzymes, stringent response and outer membrane permeation. Diazabicyclooctane inhibitors retain activity in the presence of β-lactamases, the primary resistance mechanism associated with β-lactam therapy in Gram-negative bacteria^2,3. 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.

Identification of a PCSK9-LDLR disruptor peptide with in vivo function

Proprotein convertase subtilisin/kexin type 9 (PCSK9) regulates plasma low-density lipoprotein cholesterol (LDL-C) levels by promoting hepatic LDL receptor (LDLR) degradation. Therapeutic antibodies that disrupt PCSK9-LDLR binding reduce LDL-C concentrations and cardiovascular disease risk. The epidermal growth factor precursor homology domain A (EGF-A) of the LDLR serves as a primary contact with PCSK9 via a flat interface, presenting a challenge for identifying small molecule PCSK9-LDLR disruptors. We employ an affinity-based screen of 10¹³in vitro-translated macrocyclic peptides to identify high-affinity PCSK9 ligands that utilize a unique, induced-fit pocket and partially disrupt the PCSK9-LDLR interaction. Structure-based design led to molecules with enhanced function and pharmacokinetic properties (e.g., ₁₃PCSK9i). In mice, ₁₃PCSK9i reduces plasma cholesterol levels and increases hepatic LDLR density in a dose-dependent manner. ₁₃PCSK9i functions by a unique, allosteric mechanism and is the smallest molecule identified to date with in vivo PCSK9-LDLR disruptor function.

Probing the Dynamic Structure-Function and Structure-Free Energy Relationships of the Coronavirus Main Protease with Biodynamics Theory

The SARS-CoV-2 main protease (M^pro) is of major interest as an antiviral drug target. Structure-based virtual screening efforts, fueled by a growing list of apo and inhibitor-bound SARS-CoV/CoV-2 M^pro crystal structures, are underway in many laboratories. However, little is known about the dynamic enzyme mechanism, which is needed to inform both assay development and structure-based inhibitor design. Here, we apply biodynamics theory to characterize the structural dynamics of substrate-induced M^pro activation under nonequilibrium conditions. The catalytic cycle is governed by concerted dynamic structural rearrangements of domain 3 and the m-shaped loop (residues 132–147) on which Cys145 (comprising the thiolate nucleophile and half of the oxyanion hole) and Gly143 (comprising the second half of the oxyanion hole) reside. In particular, we observed the following: (1) Domain 3 undergoes dynamic rigid-body rotation about the domain 2–3 linker, alternately visiting two primary conformational states (denoted as M₁^pro ↔ M₂^pro); (2) The Gly143-containing crest of the m-shaped loop undergoes up and down translations caused by conformational changes within the rising stem of the loop (Lys137–Asn142) in response to domain 3 rotation and dimerization (denoted as M_1/down^pro ↔ 2·M_2/up^pro) (noting that the Cys145-containing crest is fixed in the up position). We propose that substrates associate to the M_1/down^pro state, which promotes the M_2/down^pro state, dimerization (denoted as 2·M_2/up^pro–substrate), and catalysis. Here, we explore the state transitions of M^pro under nonequilibrium conditions, the mechanisms by which they are powered, and the implications thereof for efficacious inhibition under in vivo conditions.

Toward in vivo relevant drug design

Current early and preclinical drug discovery are rooted in decades-old empirical principles describing structure-free energy and structure-function relationships under equilibrium conditions that frequently break down under in vivo conditions. Improved prediction of efficacy and toxicity depends on a paradigm shift to in vivo-relevant principles describing the true nonequilibrium/nonlinear dynamic (NLD) nature of cellular systems. Here, we outline a holistic, in vivo-relevant first principles theory ('Biodynamics'), in which cellular function/dysfunction, and pharmaco-/toxicodynamic effects are considered as emergent behaviors of multimolecular systems powered by covalent and noncovalent free energy sources. The reduction to practice of Biodynamics theory consists of in silico simulations performed at the atomistic and molecular systems levels, versus empirical models fit to in vitro data under the classical paradigm.

Applications of water molecules for analysis of macromolecule properties

Water molecules maintain proteins' structures, functions, stabilities and dynamics. They can occupy certain positions or pass quickly via a protein's interior. Regardless of their behaviour, water molecules can be used for the analysis of proteins' structural features and biochemical properties. Here, we present a list of several software programs that use the information provided by water molecules to: i) analyse protein structures and provide the optimal positions of water molecules for protein hydration, ii) identify high-occupancy water sites in order to analyse ligand binding modes, and iii) detect and describe tunnels and cavities. The analysis of water molecules' distribution and trajectories sheds a light on proteins' interactions with small molecules, on the dynamics of tunnels and cavities, on protein composition and also on the functionality, transportation network and location of functionally relevant residues. Finally, the correct placement of water molecules in protein crystal structures can significantly improve the reliability of molecular dynamics simulations.

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.

Allele-Specific Mechanisms of Activation of MEK1 Mutants Determine Their Properties

Mutations at multiple sites in MEK1 occur in cancer, suggesting that their mechanisms of activation might be different. We analyzed 17 tumor-associated MEK1 mutants and found that they drove ERK signaling autonomously or in a RAS/RAF-dependent manner. The latter are sensitive to feedback inhibition of RAF, which limits their functional output, and often cooccur with RAS or RAF mutations. They act as amplifiers of RAF signaling. In contrast, another class of mutants deletes a hitherto unrecognized negative regulatory segment of MEK1, is RAF- and phosphorylation-independent, is unaffected by feedback inhibition of upstream signaling, and drives high ERK output and transformation in the absence of RAF activity. Moreover, these RAF-independent mutants are insensitive to allosteric MEK inhibitors, which preferentially bind to the inactivated form of MEK1. All the mutants are sensitive to an ATP-competitive MEK inhibitor. Thus, our study comprises a novel therapeutic strategy for tumors driven by RAF-independent MEK1 mutants.Significance: Mutants with which MEK1 mutants coexist and their sensitivity to inhibitors are determined by allele-specific properties. This study shows the importance of functional characterization of mutant alleles in single oncogenes and identifies a new class of MEK1 mutants, insensitive to current MEK1 inhibitors but treatable with a new ATP-competitive inhibitor. Cancer Discov; 8(5); 648-61. ©2018 AACR.See related commentary by Maust et al., p. 534This article is highlighted in the In This Issue feature, p. 517.

ETX2514 is a broad-spectrum β-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 β-lactamases, enzymes that inactivate β-lactams, a class of antibiotics that has been a therapeutic mainstay for decades. Although several new β-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 β-lactamase inhibitors that potently inhibit clinically relevant class A, C and D β-lactamases and penicillin-binding proteins, resulting in intrinsic antibacterial activity against Enterobacteriaceae and restoration of β-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.

Proton Wire Dynamics in the Green Fluorescent Protein

Inside proteins, protons move on proton wires (PWs). Starting from the highest resolution X-ray structure available, we conduct a 306 ns molecular dynamics simulation of the (A-state) wild-type (wt) green fluorescent protein (GFP) to study how its PWs change with time. We find that the PW from the chromophore via Ser205 to Glu222, observed in all X-ray structures, undergoes rapid water molecule insertion between Ser205 and Glu222. Sometimes, an alternate Ser205-bypassing PW exists. Side chain rotations of Thr203 and Ser205 play an important role in shaping the PW network in the chromophore region. Thr203, with its bulkier side chain, exhibits slower transitions between its three rotameric states. Ser205 experiences more frequent rotations, slowing down when the Thr203 methyl group is close by. The combined states of both residues affect the PW probabilities. A random walk search for PWs from the chromophore reveals several exit points to the bulk, one being a direct water wire (WW) from the chromophore to the bulk. A longer WW connects the "bottom" of the GFP barrel with a "water pool" (WP1) situated below Glu222. These two WWs were not observed in X-ray structures of wt-GFP, but their analogues have been reported in related fluorescent proteins. Surprisingly, the high-resolution X-ray structure utilized herein shows that Glu222 is protonated at low temperatures. At higher temperatures, we suggest ion pairing between anionic Glu222 and a proton hosted in WP1. Upon photoexcitation, these two recombine, while a second proton dissociates from the chromophore and either exits the protein using the short WW or migrates along the GFP-barrel axis on the long WW. This mechanism reconciles the conflicting experimental and theoretical data on proton motion within GFP.

Contributions of the membrane dipole potential to the function of voltage-gated cation channels and modulation by small molecule potentiators

The membrane dipole potential (Ψ_d) constitutes one of three electrical potentials generated by cell membranes. Ψ_d arises from the unfavorable parallel alignment of phospholipid and water dipoles, and varies in magnitude both longitudinally and laterally across the bilayer according to membrane composition and phospholipid packing density. In this work, we propose that dynamic counter-balancing between Ψ_d and the transmembrane potential (ΔΨ_m) governs the conformational state transitions of voltage-gated ion channels. Ψ_d consists of 1) static outer, and dynamic inner leaflet components (Ψ_d(extra) and Ψ_d(intra), respectively); and 2) a transmembrane component (ΔΨ_{d(inner-outer)}), ariing from differences in intra- and extracellular leaflet composition. Ψ_d(intra), which transitions between high and low energy states (Ψ_{d(intra, high)} and Ψ_{d(intra, low)}) as a function of channel conformation, is transduced by the pore domain. ΔΨ_{d(inner-outer)} is transduced by the voltage-sensing (VS) domain in summation with ΔΨ_m. Potentiation of voltage-gated ion channels is of interest for the treatment of cardiac, neuronal, and other disorders arising from inherited/acquired ion channel dysfunction. Potentiators are widely believed to alter the rates and voltage-dependencies of channel gating transitions by binding to pockets in the membrane-facing and other regions of ion channel targets. Here, we propose that potentiators alter Ψ_d(intra) and/or Ψ_d(extra), thereby increasing or decreasing the energy barriers governing channel gating transitions. We used quantum mechanical and molecular dynamics (MD) simulations to predict the overall Ψ_d-modulating effects of a series of published positive hERG potentiators partitioned into model DOPC bilayers. Our findings suggest a strong correlation between the magnitude of Ψ_d-lowering and positive hERG potentiation across the series.

Solvation thermodynamic mapping of molecular surfaces in AmberTools: GIST

The expulsion of water from surfaces upon molecular recognition and nonspecific association makes a major contribution to the free energy changes of these processes. In order to facilitate the characterization of water structure and thermodynamics on surfaces, we have incorporated Grid Inhomogeneous Solvation Theory (GIST) into the CPPTRAJ toolset of AmberTools. GIST is a grid-based implementation of Inhomogeneous Fluid Solvation Theory, which analyzes the output from molecular dynamics simulations to map out solvation thermodynamic and structural properties on a high-resolution, three-dimensional grid. The CPPTRAJ implementation, called GIST-cpptraj, has a simple, easy-to-use command line interface, and is open source and freely distributed. We have also developed a set of open-source tools, called GISTPP, which facilitate the analysis of GIST output grids. Tutorials for both GIST-cpptraj and GISTPP can be found at ambermd.org. © 2016 Wiley Periodicals, Inc.

Uncoupling the Structure-Activity Relationships of β2 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 β2 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 β2 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.

Toward Automated Benchmarking of Atomistic Force Fields: Neat Liquid Densities and Static Dielectric Constants from the ThermoML Data Archive

Atomistic molecular simulations are a powerful way to make quantitative predictions, but the accuracy of these predictions depends entirely on the quality of the force field employed. Although experimental measurements of fundamental physical properties offer a straightforward approach for evaluating force field quality, the bulk of this information has been tied up in formats that are not machine-readable. Compiling benchmark data sets of physical properties from non-machine-readable sources requires substantial human effort and is prone to the accumulation of human errors, hindering the development of reproducible benchmarks of force-field accuracy. Here, we examine the feasibility of benchmarking atomistic force fields against the NIST ThermoML data archive of physicochemical measurements, which aggregates thousands of experimental measurements in a portable, machine-readable, self-annotating IUPAC-standard format. As a proof of concept, we present a detailed benchmark of the generalized Amber small-molecule force field (GAFF) using the AM1-BCC charge model against experimental measurements (specifically, bulk liquid densities and static dielectric constants at ambient pressure) automatically extracted from the archive and discuss the extent of data available for use in larger scale (or continuously performed) benchmarks. The results of even this limited initial benchmark highlight a general problem with fixed-charge force fields in the representation low-dielectric environments, such as those seen in binding cavities or biological membranes.