NbIT--a new information theory-based analysis of allosteric mechanisms reveals residues that underlie function in the leucine transporter LeuT

Dynamically driven correlations in elastic net models reveal sequence of events and causality in proteins

An explicit analytic solution is given for the Langevin equation applied to the Gaussian Network Model of a protein subjected to both a random and a deterministic periodic force. Synchronous and asynchronous components of time correlation functions are derived and an expression for phase differences in the time correlations of residue pairs is obtained. The synchronous component enables the determination of dynamic communities within the protein structure. The asynchronous component reveals causality, where the time correlation function between residues i and j differs depending on whether i is observed before j or vice versa, resulting in directional information flow. Driver and driven residues in the allosteric process of cyclophilin A and human NAD-dependent isocitrate dehydrogenase are determined by a perturbation-scanning technique. Factors affecting phase differences between fluctuations of residues, such as network topology, connectivity, and residue centrality, are identified. Within the constraints of the isotropic Gaussian Network Model, our results show that asynchronicity increases with viscosity and distance between residues, decreases with increasing connectivity, and decreases with increasing levels of eigenvector centrality.

Synergy and anti-cooperativity in allostery: Molecular dynamics study of WT and oncogenic KRAS-RGL1

This study focuses on investigating the effects of an oncogenic mutation (G12V) on the stability and interactions within the KRAS-RGL1 protein complex. The KRAS-RGL1 complex is of particular interest due to its relevance to KRAS-associated cancers and the potential for developing targeted drugs against the KRAS system. The stability of the complex and the allosteric effects of specific residues are examined to understand their roles as modulators of complex stability and function. Using molecular dynamics simulations, we calculate the mutual information, MI, between two neighboring residues at the interface of the KRAS-RGL1 complex, and employ the concept of interaction information, II, to measure the contribution of a third residue to the interaction between interface residue pairs. Negative II indicates synergy, where the presence of the third residue strengthens the interaction, while positive II suggests anti-cooperativity. Our findings reveal that MI serves as a dominant factor in determining the results, with the G12V mutation increasing the MI between interface residues, indicating enhanced correlations due to the formation of a more compact structure in the complex. Interestingly, although II plays a role in understanding three-body interactions and the impact of distant residues, it is not significant enough to outweigh the influence of MI in determining the overall stability of the complex. Nevertheless, II may nonetheless be a relevant factor to consider in future drug design efforts. This study provides valuable insights into the mechanisms of complex stability and function, highlighting the significance of three-body interactions and the impact of distant residues on the binding stability of the complex. Additionally, our findings demonstrate that constraining the fluctuations of a third residue consistently increases the stability of the G12V variant, making it challenging to weaken complex formation of the mutated species through allosteric manipulation. The novel perspective offered by this approach on protein dynamics, function, and allostery has potential implications for understanding and targeting other protein complexes involved in vital cellular processes. The results contribute to our understanding of the effects of oncogenic mutations on protein-protein interactions and provide a foundation for future therapeutic interventions in the context of KRAS-associated cancers and beyond.

Substrate binding-induced conformational transitions in the omega-3 fatty acid transporter MFSD2A

Major Facilitator Superfamily Domain containing 2 A (MFSD2A) is a transporter that is highly enriched at the blood-brain and blood-retinal barriers, where it mediates Na+-dependent uptake of ω-3 fatty acids in the form of lysolipids into the brain and eyes, respectively. Despite recent structural insights, it remains unclear how this process is initiated, and driven by Na+. Here, we perform Molecular Dynamics simulations which demonstrate that substrates enter outward facing MFSD2A from the outer leaflet of the membrane via lateral openings between transmembrane helices 5/8 and 2/11. The substrate headgroup enters first and engages in Na+ -bridged interactions with a conserved glutamic acid, while the tail is surrounded by hydrophobic residues. This binding mode is consistent with a "trap-and-flip" mechanism and triggers transition to an occluded conformation. Furthermore, using machine learning analysis, we identify key elements that enable these transitions. These results advance our molecular understanding of the MFSD2A transport cycle.

Allosterically coupled conformational dynamics in solution prepare the sterol transfer protein StarD4 to release its cargo upon interaction with target membranes

Complex mechanisms regulate the cellular distribution of cholesterol, a critical component of eukaryote membranes involved in regulation of membrane protein functions directly and through the physiochemical properties of membranes. StarD4, a member of the steroidogenic acute regulator-related lipid-transfer (StART) domain (StARD)-containing protein family, is a highly efficient sterol-specific transfer protein involved in cholesterol homeostasis. Its mechanism of cargo loading and release remains unknown despite recent insights into the key role of phosphatidylinositol phosphates in modulating its interactions with target membranes. We have used large-scale atomistic Molecular dynamics (MD) simulations to study how the dynamics of cholesterol bound to the StarD4 protein can affect interaction with target membranes, and cargo delivery. We identify the two major cholesterol (CHL) binding modes in the hydrophobic pocket of StarD4, one near S136&S147 (the Ser-mode), and another closer to the putative release gate located near W171, R92&Y117 (the Trp-mode). We show that conformational changes of StarD4 associated directly with the transition between these binding modes facilitate the opening of the gate. To understand the dynamics of this connection we apply a machine-learning algorithm for the detection of rare events in MD trajectories (RED), which reveals the structural motifs involved in the opening of a front gate and a back corridor in the StarD4 structure occurring together with the spontaneous transition of CHL from the Ser-mode of binding to the Trp-mode. Further analysis of MD trajectory data with the information-theory based NbIT method reveals the allosteric network connecting the CHL binding site to the functionally important structural components of the gate and corridor. Mutations of residues in the allosteric network are shown to affect the performance of the allosteric connection. These findings outline an allosteric mechanism which prepares the CHL-bound StarD4 to release and deliver the cargo when it is bound to the target membrane.

Structural mechanism of a drug-binding process involving a large conformational change of the protein target

Proteins often undergo large conformational changes when binding small molecules, but atomic-level descriptions of such events have been elusive. Here, we report unguided molecular dynamics simulations of Abl kinase binding to the cancer drug imatinib. In the simulations, imatinib first selectively engages Abl kinase in its autoinhibitory conformation. Consistent with inferences drawn from previous experimental studies, imatinib then induces a large conformational change of the protein to reach a bound complex that closely resembles published crystal structures. Moreover, the simulations reveal a surprising local structural instability in the C-terminal lobe of Abl kinase during binding. The unstable region includes a number of residues that, when mutated, confer imatinib resistance by an unknown mechanism. Based on the simulations, NMR spectra, hydrogen-deuterium exchange measurements, and thermostability measurements and estimates, we suggest that these mutations confer imatinib resistance by exacerbating structural instability in the C-terminal lobe, rendering the imatinib-bound state energetically unfavorable.

Mutual information analysis of mutation, nonlinearity, and triple interactions in proteins

Mutations are the cause of several diseases as well as the underlying force of evolution. A thorough understanding of their biophysical consequences is essential. We present a computational framework for evaluating different levels of mutual information (MI) and its dependence on mutation. We used molecular dynamics trajectories of the third PDZ domain and its different mutations. Nonlinear MI between all residue pairs are calculated by tensor Hermite polynomials up to the fifth order and compared with results from multivariate Gaussian distribution of joint probabilities. We show that MI is written as the sum of a Gaussian and a nonlinear component. Results for the PDZ domain show that the Gaussian term gives a sufficiently accurate representation of MI when compared with nonlinear terms up to the fifth order. Changes in MI between residue pairs show the characteristic patterns resulting from specific mutations. Emergence of new peaks in the MI versus residue index plots of mutated PDZ shows how mutation may change allosteric pathways. Triple correlations are characterized by evaluating MI between triplets of residues. We observed that certain triplets are strongly affected by mutation. Susceptibility of residues to perturbation is obtained by MI and discussed in terms of linear response theory.

Metadynamics simulations leveraged by statistical analyses and artificial intelligence-based tools to inform the discovery of G protein-coupled receptor ligands

G Protein-Coupled Receptors (GPCRs) are a large family of membrane proteins with pluridimensional signaling profiles. They undergo ligand-specific conformational changes, which in turn lead to the differential activation of intracellular signaling proteins and the consequent triggering of a variety of biological responses. This conformational plasticity directly impacts our understanding of GPCR signaling and therapeutic implications, as do ligand-specific kinetic differences in GPCR-induced transducer activation/coupling or GPCR-transducer complex stability. High-resolution experimental structures of ligand-bound GPCRs in the presence or absence of interacting transducers provide important, yet limited, insights into the highly dynamic process of ligand-induced activation or inhibition of these receptors. We and others have complemented these studies with computational strategies aimed at characterizing increasingly accurate metastable conformations of GPCRs using a combination of metadynamics simulations, state-of-the-art algorithms for statistical analyses of simulation data, and artificial intelligence-based tools. This minireview provides an overview of these approaches as well as lessons learned from them towards the identification of conformational states that may be difficult or even impossible to characterize experimentally and yet important to discover new GPCR ligands.

Dual-Reporter System for Real-Time Monitoring of SARS-CoV-2 Main Protease Activity in Live Cells Enables Identification of an Allosteric Inhibition Path

The SARS-CoV-2 pandemic is an ongoing threat to global health, and the continuing emergence of contagious variants highlights the urgent need for additional antiviral therapy to attenuate COVID-19 disease. The SARS-CoV-2 main protease (3CL^pro) presents an attractive target for such therapy due to its high sequence conservation and key role in the viral life cycle. In this study, we designed a fluorescent-luminescent cell-based reporter for the detection and quantification of 3CL^pro intracellular activity. Employing this platform, we examined the efficiency of known protease inhibitors against 3CL^pro and further identified potent inhibitors through high-throughput chemical screening. Computational analysis confirmed a direct interaction of the lead compounds with the protease catalytic site and identified a prototype for efficient allosteric inhibition. These developments address a pressing need for a convenient sensor and specific targets for both virus detection and rapid discovery of potential inhibitors.

The allosteric mechanism leading to an open-groove lipid conductive state of the TMEM16F scramblase

TMEM16F is a Ca²⁺-activated phospholipid scramblase in the TMEM16 family of membrane proteins. Unlike other TMEM16s exhibiting a membrane-exposed hydrophilic groove that serves as a translocation pathway for lipids, the experimentally determined structures of TMEM16F shows the groove in a closed conformation even under conditions of maximal scramblase activity. It is currently unknown if/how TMEM16F groove can open for lipid scrambling. Here we describe the analysis of ~400 µs all-atom molecular dynamics (MD) simulations of the TMEM16F revealing an allosteric mechanism leading to an open-groove, lipid scrambling competent state of the protein. The groove opens into a continuous hydrophilic conduit that is highly similar in structure to that seen in other activated scramblases. The allosteric pathway connects this opening to an observed destabilization of the Ca²⁺ ion bound at the distal site near the dimer interface, to the dynamics of specific protein regions that produces the open-groove state to scramble phospholipids.

Molecular dynamics simulations reveal the allosteric mechanism leading to an open, lipid scrambling competent state of a mammalian TMEM16F.

Molecular determinants of pH sensing in the proton-activated chloride channel

In response to acidic pH, the widely expressed proton-activated chloride (PAC) channel opens and conducts anions across cellular membranes. By doing so, PAC plays an important role in both cellular physiology (endosome acidification) and diseases associated with tissue acidosis (acid-induced cell death). Despite the available structural information, how proton binding in the extracellular domain (ECD) leads to PAC channel opening remains largely unknown. Here, through comprehensive mutagenesis and electrophysiological studies, we identified several critical titratable residues, including two histidine residues (H130 and H131) and an aspartic acid residue (D269) at the distal end of the ECD, together with the previously characterized H98 at the transmembrane domain-ECD interface, as potential pH sensors for human PAC. Mutations of these residues resulted in significant changes in pH sensitivity. Some combined mutants also exhibited large basal PAC channel activities at neutral pH. By combining molecular dynamics simulations with structural and functional analysis, we further found that the β12 strand at the intersubunit interface and the associated "joint region" connecting the upper and lower ECDs allosterically regulate the proton-dependent PAC activation. Our studies suggest a distinct pH-sensing and gating mechanism of this new family of ion channels sensitive to acidic environment.

Information Flow and Allosteric Communication in Proteins

Based on Schreiber's work on transfer entropy, a molecular theory of nonlinear information transfer in proteins is developed. The joint distribution function for residue fluctuations is expressed in terms of tensor Hermite polynomials which conveniently separate harmonic and nonlinear contributions to information transfer. The harmonic part of information transfer is expressed as the difference between time dependent and independent mutual information. Third order nonlinearities are discussed in detail. Amount and speed of information transfer between residues, important for understanding allosteric activity in proteins, are discussed. While mutual information shows the maximum amount of information that may be transferred between two residues, it does not explain the actual amount of transfer nor the transfer rate of information. For this, dynamic equations of the system are needed. The solution of the Langevin equation and molecular dynamics trajectories are used in the present work for this purpose. Allosteric communication in Human NAD-dependent isocitrate dehydrogenase is studied as an example. Calculations show that several paths contribute collectively to information transfer. Important residues on these paths are identified. Time resolved information transfer between these residues, their amplitudes and transfer rates, which are in agreement with time resolved ultraviolet resonance Raman measurements in general, are estimated. Estimated transfer rates are in the order of 1-20 megabits per second. Information transfer from third order contributions are one to two orders of magnitude smaller than the harmonic terms, showing that harmonic analysis is a good approximation to information transfer.

Atomistic mechanisms of human TRPA1 activation by electrophile irritants through molecular dynamics simulation and mutual information analysis

The ion channel TRPA1 is a promiscuous chemosensor, with reported response to a wide spectrum of noxious electrophilic irritants, as well as cold, heat, and mechanosensation. It is also implicated in the inception of itch and pain and has hence been investigated as a drug target for novel analgesics. The mechanism of electrophilic activation for TRPA1 is therefore of broad interest. TRPA1 structures with the pore in both open and closed states have recently been published as well as covalent binding modes for electrophile agonists. However, the detailed mechanism of coupling between electrophile binding sites and the pore remains speculative. In addition, while two different cysteine residues (C621 and C665) have been identified as critical for electrophile bonding and activation, the bound geometry has only been resolved at C621. Here, we use molecular dynamics simulations of TRPA1 in both pore-open and pore-closed states to explore the allosteric link between the electrophile binding sites and pore stability. Our simulations reveal that an open pore is structurally stable in the presence of open ‘pockets’ in the C621/C665 region, but rapidly collapses and closes when these pockets are shut. Binding of electrophiles at either C621 or C665 provides stabilisation of the pore-open state, but molecules bound at C665 are shown to be able to rotate in and out of the pocket, allowing for immediate stabilisation of transient open states. Finally, mutual information analysis of trajectories reveals an informational path linking the electrophile binding site pocket to the pore via the voltage-sensing-like domain, giving a detailed insight into the how the pore is stabilized in the open state.

Targetable HER3 functions driving tumorigenic signaling in HER2-amplified cancers

Effective inactivation of the HER2-HER3 tumor driver has remained elusive because of the challenging attributes of the pseudokinase HER3. We report a structure-function study of constitutive HER2-HER3 signaling to identify opportunities for targeting. The allosteric activation of the HER2 kinase domain (KD) by the HER3 KD is required for tumorigenic signaling and can potentially be targeted by allosteric inhibitors. ATP binding within the catalytically inactive HER3 KD provides structural rigidity that is important for signaling, but this is mimicked, not opposed, by small molecule ATP analogs, reported here in a bosutinib-bound crystal structure. Mutational disruption of ATP binding and molecular dynamics simulation of the apo KD of HER3 identify a conformational coupling of the ATP pocket with a hydrophobic AP-2 pocket, analogous to EGFR, that is critical for tumorigenic signaling and feasible for targeting. The value of these potential target sites is confirmed in tumor growth assays using gene replacement techniques.

Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have noncanonical and "long-distance" outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions ("toggle"), ten nonconserved positions showed progressive changes from a range of substitutions ("rheostat"), and three nonconserved positions tolerated almost all substitutions ("neutral"). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.

Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol

Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins, and the effects of ligand binding. The need for, and successes of, MD simulations in providing this type of essential information are well documented, but so are the challenges presented by the size of the resulting datasets encoding the desired information. The difficulty of extracting information on mechanistically important state-to-state transitions in response to ligand binding and other interactions is compounded by these being rare events in the MD trajectories of complex molecular machines, such as G-protein-coupled receptors (GPCRs). To address this problem, we have developed a protocol for the efficient detection of such events. We show that the novel Rare Event Detection (RED) protocol reveals functionally relevant and pharmacologically discriminating responses to the binding of different ligands to the 5-HT_2AR orthosteric site in terms of clearly defined, structurally coherent, and temporally ordered conformational transitions. This information from the RED protocol offers new insights into specific ligand-determined functional mechanisms encoded in the MD trajectories, which opens a new and rigorously reproducible path to understanding drug activity with application in drug discovery.

Heteromeric Solute Carriers: Function, Structure, Pathology and Pharmacology

Solute carriers form one of three major superfamilies of membrane transporters in humans, and include uniporters, exchangers and symporters. Following several decades of molecular characterisation, multiple solute carriers that form obligatory heteromers with unrelated subunits are emerging as a distinctive principle of membrane transporter assembly. Here we comprehensively review experimentally established heteromeric solute carriers: SLC3-SLC7 amino acid exchangers, SLC16 monocarboxylate/H⁺ symporters and basigin/embigin, SLC4A1 (AE1) and glycophorin A exchanger, SLC51 heteromer Ost α-Ost β uniporter, and SLC6 heteromeric symporters. The review covers the history of the heteromer discovery, transporter physiology, structure, disease associations and pharmacology - all with a focus on the heteromeric assembly. The cellular locations, requirements for complex formation, and the functional role of dimerization are extensively detailed, including analysis of the first complete heteromer structures, the SLC7-SLC3 family transporters LAT1-4F2hc, b^0,+AT-rBAT and the SLC6 family heteromer B⁰AT1-ACE2. We present a systematic analysis of the structural and functional aspects of heteromeric solute carriers and conclude with common principles of their functional roles and structural architecture.

A non-helical region in transmembrane helix 6 of hydrophobic amino acid transporter MhsT mediates substrate recognition

MhsT of Bacillus halodurans is a transporter of hydrophobic amino acids and a homologue of the eukaryotic SLC6 family of Na+ -dependent symporters for amino acids, neurotransmitters, osmolytes, or creatine. The broad range of transported amino acids by MhsT prompted the investigation of the substrate recognition mechanism. Here, we report six new substrate-bound structures of MhsT, which, in conjunction with functional studies, reveal how the flexibility of a Gly-Met-Gly (GMG) motif in the unwound region of transmembrane segment 6 (TM6) is central for the recognition of substrates of different size by tailoring the binding site shape and volume. MhsT mutants, harboring substitutions within the unwound GMG loop and substrate binding pocket that mimick the binding sites of eukaryotic SLC6A18/B0AT3 and SLC6A19/B0AT1 transporters of neutral amino acids, exhibited impaired transport of aromatic amino acids that require a large binding site volume. Conservation of a general (G/A/C)ΦG motif among eukaryotic members of SLC6 family suggests a role for this loop in a common mechanism for substrate recognition and translocation by SLC6 transporters of broad substrate specificity.

Allosteric Pathways Originating at Cysteine Residues in Regulators of G-Protein Signaling Proteins

Regulators of G-protein signaling (RGS) proteins play a central role in modulating signaling via G-protein coupled receptors (GPCRs). Specifically, RGS proteins bind to activated Gα subunits in G-proteins, accelerate the GTP hydrolysis, and thereby rapidly dampen GPCR signaling. Therefore, covalent molecules targeting conserved cysteine residues among RGS proteins have emerged as potential candidates to inhibit the RGS/Gα protein-protein interaction and enhance GPCR signaling. Although these inhibitors bind to conserved cysteine residues among RGS proteins, we have previously suggested [J. Am. Chem. Soc. 2018;140:3454–3460] that their potencies and specificities are related to differential protein dynamics among RGS proteins. Using data from all-atom molecular dynamics simulations, we reveal these differences in dynamics of RGS proteins by partitioning the protein structural space into a network of communities that allow allosteric signals to propagate along unique pathways originating at inhibitor binding sites and terminating at the RGS/Gα protein-protein interface.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

Aromatic interactions with membrane modulate human BK channel activation

Large-conductance potassium (BK) channels are transmembrane (TM) proteins that can be synergistically and independently activated by membrane voltage and intracellular Ca²⁺. The only covalent connection between the cytosolic Ca²⁺ sensing domain and the TM pore and voltage sensing domains is a 15-residue ‘C-linker’. To determine the linker’s role in human BK activation, we designed a series of linker sequence scrambling mutants to suppress potential complex interplay of specific interactions with the rest of the protein. The results revealed a surprising sensitivity of BK activation to the linker sequence. Combining atomistic simulations and further mutagenesis experiments, we demonstrated that nonspecific interactions of the linker with membrane alone could directly modulate BK activation. The C-linker thus plays more direct roles in mediating allosteric coupling between BK domains than previously assumed. Our results suggest that covalent linkers could directly modulate TM protein function and should be considered an integral component of the sensing apparatus.

The Amino Terminus of LeuT Changes Conformation in an Environment Sensitive Manner

Neurotransmitter:sodium symporters are highly expressed in the human brain and catalyze the uptake of substrate through the plasma membrane by using the electrochemical gradient of sodium as the energy source. The bacterial homolog LeuT, a small amino acid transporter isolated from the bacteria Aquifex aeolicus, is the founding member of the family and has been crystallized in three conformations. The N-terminus is structurally well defined and strongly interacts with the transporter core in the outward-facing conformations. However, it could not be resolved in the inward-facing conformation, which indicates enhanced mobility. Here we investigate conformations and dynamics of the N-terminus, by combining molecular dynamics simulations with experimental verification using distance measurements and accessibility studies. We found strongly increased dynamics of the N-terminus, but also that helix TM1A is subject to enhanced mobility. TM1A moves towards the transporter core in the membrane environment, reaching a conformation that is closer to the structure of LeuT with wild type sequence, indicating that the mutation introduced to create the inward-facing structure might have altered the position of helix TM1A. The mobile N-terminus avoids entering the open vestibule of the inward-facing state, as accessibility studies do not show any reduction of quenching by iodide of a fluorophore attached to the N-terminus.

Allosteric communication in molecular machines via information exchange: what can be learned from dynamical modeling

Allosteric regulation is crucial for the operation of protein machines and molecular motors. A major challenge is to characterize and quantify the information exchange underlying allosteric communication between remote functional sites in a protein, and to identify the involved relevant pathways. We review applications of two topical approaches of dynamical protein modeling, a kinetic-based single-molecule stochastic model, which employs information thermodynamics to quantify allosteric interactions, and structure-based coarse-grained modeling to characterize intra-molecular couplings in terms of conformational motions and propagating mechanical strain. Both descriptions resolve the directionality of allosteric responses within a protein, emphasizing the concept of causality as the principal hallmark of protein allostery. We discuss the application of techniques from information thermodynamics to dynamic protein elastic networks and evolutionary designed model structures, and the ramifications for protein allostery.

Transmembrane helix 6b links proton and metal release pathways and drives conformational change in an Nramp-family transition metal transporter

The natural resistance-associated macrophage protein (Nramp) family encompasses transition metal and proton cotransporters that are present in many organisms from bacteria to humans. Recent structures of Deinococcus radiodurans Nramp (DraNramp) in multiple conformations revealed the intramolecular rearrangements required for alternating access of the metal-binding site to the external or cytosolic environment. Here, using recombinant proteins and metal transport and cysteine accessibility assays, we demonstrate that two parallel cytoplasm-accessible networks of conserved hydrophilic residues in DraNramp, one lining the wide intracellular vestibule for metal release and the other forming a narrow proton transport pathway, are essential for metal transport. We further show that mutagenic or posttranslational modifications of transmembrane helix (TM) 6b, which structurally links these two pathways, impede normal conformational cycling and metal transport. TM6b contains two highly conserved histidines, His²³² and His²³⁷ We found that different mutagenic perturbations of His²³², just below the metal-binding site along the proton exit route, differentially affect DraNramp's conformational state, suggesting that His²³² serves as a pivot point for conformational changes. In contrast, any replacement of His²³⁷, lining the metal exit route, locked the transporter in a transport-inactive outward-closed state. We conclude that these two histidines, and TM6b more broadly, help trigger the bulk rearrangement of DraNramp to the inward-open state upon metal binding and facilitate return of the empty transporter to an outward-open state upon metal release.

The allosteric mechanism of substrate-specific transport in SLC6 is mediated by a volumetric sensor

Neurotransmitter:sodium symporters (NSSs) in the SLC6 family terminate neurotransmission by coupling the thermodynamically favorable transport of ions to the thermodynamically unfavorable transport of neurotransmitter back into presynaptic neurons. Results from many structural, functional, and computational studies on LeuT, a bacterial NSS homolog, have provided critical insight into the mechanism of sodium-coupled transport, but the mechanism underlying substrate-specific transport rates is still not understood. We present a combination of molecular dynamics simulations, single-molecule fluorescence resonance energy transfer (smFRET) imaging, and measurements of Na+ binding and substrate transport that reveals an allosteric substrate specificity mechanism. In this mechanism, residues F259 and I359 in the substrate binding pocket couple the binding of substrate to Na+ release from the Na2 site by allosterically modulating the stability of a partially open, inward-facing state. We propose a model for transport selectivity in which residues F259 and I359 act as a volumetric sensor that inhibits the transport of bulky amino acids.

A Machine Learning Approach for the Discovery of Ligand-Specific Functional Mechanisms of GPCRs

G protein-coupled receptors (GPCRs) play a key role in many cellular signaling mechanisms, and must select among multiple coupling possibilities in a ligand-specific manner in order to carry out a myriad of functions in diverse cellular contexts. Much has been learned about the molecular mechanisms of ligand-GPCR complexes from Molecular Dynamics (MD) simulations. However, to explore ligand-specific differences in the response of a GPCR to diverse ligands, as is required to understand ligand bias and functional selectivity, necessitates creating very large amounts of data from the needed large-scale simulations. This becomes a Big Data problem for the high dimensionality analysis of the accumulated trajectories. Here we describe a new machine learning (ML) approach to the problem that is based on transforming the analysis of GPCR function-related, ligand-specific differences encoded in the MD simulation trajectories into a representation recognizable by state-of-the-art deep learning object recognition technology. We illustrate this method by applying it to recognize the pharmacological classification of ligands bound to the 5-HT_2A and D2 subtypes of class-A GPCRs from the serotonin and dopamine families. The ML-based approach is shown to perform the classification task with high accuracy, and we identify the molecular determinants of the classifications in the context of GPCR structure and function. This study builds a framework for the efficient computational analysis of MD Big Data collected for the purpose of understanding ligand-specific GPCR activity.

An efficient strategy to estimate thermodynamics and kinetics of G protein-coupled receptor activation using metadynamics and maximum caliber

Computational strategies aimed at unveiling the thermodynamic and kinetic properties of G Protein-Coupled Receptor (GPCR) activation require extensive molecular dynamics simulations of the receptor embedded in an explicit lipid-water environment. A possible method for efficiently sampling the conformational space of such a complex system is metadynamics (MetaD) with path collective variables (CVs). Here, we applied well-tempered MetaD with path CVs to one of the few GPCRs for which both inactive and fully active experimental structures are available, the μ-opioid receptor (MOR), and assessed the ability of this enhanced sampling method to estimate the thermodynamic properties of receptor activation in line with those obtained by more computationally expensive adaptive sampling protocols. While n-body information theory analysis of these simulations confirmed that MetaD can efficiently characterize ligand-induced allosteric communication across the receptor, standard MetaD cannot be used directly to derive kinetic rates because transitions are accelerated by a bias potential. Applying the principle of Maximum Caliber (MaxCal) to the free-energy landscape of morphine-bound MOR reconstructed from MetaD, we obtained Markov state models that yield kinetic rates of MOR activation in agreement with those obtained by adaptive sampling. Taken together, these results suggest that the MetaD-MaxCal combination creates an efficient strategy for estimating the thermodynamic and kinetic properties of GPCR activation at an affordable computational cost.

Correlation Between Allosteric and Orthosteric Sites

Correlation between an allosteric site and its orthosteric site refers to the phenomenon that perturbations like ligand binding, mutation, or posttranslational modifications at the allosteric site leverage variation in the orthosteric site. Understanding this kind of correlation not only helps to disclose how information is transmitted in allosteric regulation but also provides clues for allosteric drug discovery. This chapter starts with an overview of correlation studies on allosteric and orthosteric sites and then introduces recent progress in evolutionary and simulation-based dynamic studies. Discussions and perspectives on future directions are also given.

Computation-guided analysis of paroxetine binding to hSERT reveals functionally important structural elements and dynamics

The serotonin transporter (SERT) is one of the primary targets for medications to treat neuropsychiatric disorders and functions by exploiting pre-existing ion gradients of Na⁺, Cl^-, and K⁺ to translocate serotonin from the synaptic cleft into the presynaptic neuron. Although recent hSERT crystal structures represent a milestone for structure-function analyses of mammalian neurotransmitter:sodium symporters, they are all derived from thermostabilized but transport-deficient constructs. Two of these structures are in complex with paroxetine, the most potent selective serotonin reuptake inhibitor known. In this study, by carrying out and analyzing the results of extensive and comparative molecular dynamics simulations while also re-evaluating the transport and binding properties of the thermostabilized constructs, we identified functionally important structural elements that are perturbed by these mutations, revealed unexpected dynamics in the central primary binding site of SERT, and uncovered a conceivable ambiguity in paroxetine's binding orientation. We propose that the favored entropy contribution plays a significant role in paroxetine's extraordinarily high affinity for SERT. Our findings lay the foundation for future mechanistic studies and rational design of high-affinity SERT inhibitors. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.

"Infostery" analysis of short molecular dynamics simulations identifies highly sensitive residues and predicts deleterious mutations

Characterizing a protein mutational landscape is a very challenging problem in Biology. Many disease-associated mutations do not seem to produce any effect on the global shape nor motions of the protein. Here, we use relatively short all-atom biomolecular simulations to predict mutational outcomes and we quantitatively assess the predictions on several hundreds of mutants. We perform simulations of the wild type and 175 mutants of PSD95’s third PDZ domain in complex with its cognate ligand. By recording residue displacements correlations and interactions, we identify “communication pathways” and quantify them to predict the severity of the mutations. Moreover, we show that by exploiting simulations of the wild type, one can detect 80% of the positions highly sensitive to mutations with a precision of 89%. Importantly, our analysis describes the role of these positions in the inter-residue communication and dynamical architecture of the complex. We assess our approach on three different systems using data from deep mutational scanning experiments and high-throughput exome sequencing. We refer to our analysis as “infostery”, from “info” - information - and “steric” - arrangement of residues in space. We provide a fully automated tool, COMMA2 (www.lcqb.upmc.fr/COMMA2), that can be used to guide medicinal research by selecting important positions/mutations.

Allosteric Effects of the Proton Donor on the Microbial Proton Pump Proteorhodopsin

Proteorhodopsin (PR) is a microbial proton pump that is ubiquitous in marine environments and may play an important role in the oceanic carbon cycle. Photoisomerization of the retinal chromophore in PR leads to a series of proton transfers between specific acidic amino acid residues and the Schiff base of retinal, culminating in a proton motive force to facilitate ATP synthesis. The proton donor in a similar retinal protein, bacteriorhodopsin, acts as a latch to allow the influx of bulk water. However, it is unclear if the proton donor in PR, E108, utilizes the same latch mechanism to become internally hydrated. Here, we used molecular dynamics simulations to model the changes in internal hydration of the blue variant of PR during photoactivation with the proton donor in protonated and deprotonated states. We find that there is a stark contrast in the levels of internal hydration of the cytoplasmic half of PR based on the protonation state of E108. Instead of a latch mechanism, deprotonation of E108 acts as a gate, taking advantage of a nearby polar residue (S61) to promote the formation of a stable water wire from bulk cytoplasm to the retinal-binding pocket over hundreds of nanoseconds. No large-scale conformational changes occur in PR over the microsecond timescale. This subtle yet clear difference in the effect of deprotonation of the proton donor in PR may help explain why the photointermediates that involve the proton donor (i.e., M and N states) have timescales that are orders of magnitude different from the archaeal proton pump, bacteriorhodopsin. In general, our study highlights the importance of understanding how structural fluctuations lead to differences in the way that retinal proteins accomplish the same task.

The LeuT-fold neurotransmitter:sodium symporter MhsT has two substrate sites

Crystal structures of the neurotransmitter:sodium symporter MhsT revealed occluded inward-facing states with one substrate (Trp) bound in the primary substrate (S1) site and a collapsed extracellular vestibule, which in LeuT contains the second substrate (S2) site. In n-dodecyl-β-d-maltoside, the detergent used to prepare MhsT for crystallization, the substrate-to-protein binding stoichiometry was determined by using scintillation proximity to be 1 Trp:MhsT. Here, using the same experimental approach, as well as equilibrium dialysis, we report that in n-decyl-β-d-maltoside, or after reconstitution in lipid, MhsT, like LeuT, can simultaneously bind two Trp substrate molecules. Trp binding to the S2 site sterically blocks access to a substituted Cys at position 33 in the S2 site, as well as access to the deeper S1 site. Mutation of either the S1 or S2 site disrupts transport, consistent with previous studies in LeuT showing that substrate binding to the S2 site is an essential component of the transport mechanism.

Gating interaction maps reveal a noncanonical electromechanical coupling mode in the Shaker K+ channel

Membrane potential regulates the activity of voltage-dependent ion channels via specialized voltage-sensing modules but the mechanisms involved in coupling voltage-sensor movement to pore opening remain unclear due to lack of resting state structures and robust methods to identify allosteric pathways. Here, using a newly developed interaction energy analysis, we probe the interfaces of the voltage-sensing and pore modules in the drosophila Shaker K⁺ channel. Our measurements reveal unexpectedly strong equilibrium gating interactions between contacts at the S4 and S5 helices in addition to those between S6 and S4–S5 linker. Network analysis of MD trajectories shows that the voltage-sensor and pore motions are linked by two distinct pathways- canonical one through the S4–S5 linker and a hitherto unknown pathway akin to rack and pinion coupling involving S4 and S5 helices. Our findings highlight the central role of the S5 helix in electromechanical transduction in the VGIC superfamily.

Opportunities and Challenges in the Discovery of Allosteric Modulators of GPCRs

From the pharmacological point of view, allosteric modulators may present numerous advantages over orthosteric ligands. Growing availability of novel tools and experimental data provides a tempting opportunity to apply computational methods to improve known modulators and design novel ones. However, recent progress in understanding of complexity of allostery increases awareness of problems involved in design of modulators with desired properties. Deeper insight into phenomena such as probe dependence, altering signaling bias with minor changes in ligand structure, as well as influence of subtle endogenous allosteric factors turns out to be fundamental. These effects make the design of a modulator with precise pharmacological outcome a very challenging task, and need to be taken into consideration throughout the design process. In this chapter, we focus on nuances of targeting GPCR allosteric sites in computational drug design efforts, in particular with application of docking, virtual screening, and molecular dynamics.

Investigating Small-Molecule Ligand Binding to G Protein-Coupled Receptors with Biased or Unbiased Molecular Dynamics Simulations

An increasing number of G protein-coupled receptor (GPCR) crystal structures provide important-albeit static-pictures of how small molecules or peptides interact with their receptors. These high-resolution structures represent a tremendous opportunity to apply molecular dynamics (MD) simulations to capture atomic-level dynamical information that is not easy to obtain experimentally. Understanding ligand binding and unbinding processes, as well as the related responses of the receptor, is crucial to the design of better drugs targeting GPCRs. Here, we discuss possible ways to study the dynamics involved in the binding of small molecules to GPCRs, using long timescale MD simulations or metadynamics-based approaches.

Thermodynamic Coupling Function Analysis of Allosteric Mechanisms in the Human Dopamine Transporter

Allostery plays a crucial role in the mechanism of neurotransmitter-sodium symporters, such as the human dopamine transporter. To investigate the molecular mechanism that couples the transport-associated inward release of the Na⁺ ion from the Na2 site to intracellular gating, we applied a combination of the thermodynamic coupling function (TCF) formalism and Markov state model analysis to a 50-μs data set of molecular dynamics trajectories of the human dopamine transporter, in which multiple spontaneous Na⁺ release events were observed. Our TCF approach reveals a complex landscape of thermodynamic coupling between Na⁺ release and inward-opening, and identifies diverse, yet well-defined roles for different Na⁺-coordinating residues. In particular, we identify a prominent role in the allosteric coupling for the Na⁺-coordinating residue D421, where mutation has previously been associated with neurological disorders. Our results highlight the power of the TCF analysis to elucidate the molecular mechanism of complex allosteric processes in large biomolecular systems.

Conformational landscapes of membrane proteins delineated by enhanced sampling molecular dynamics simulations

The expansion of computational power, better parameterization of force fields, and the development of novel algorithms to enhance the sampling of the free energy landscapes of proteins have allowed molecular dynamics (MD) simulations to become an indispensable tool to understand the function of biomolecules. The temporal and spatial resolution of MD simulations allows for the study of a vast number of processes of interest. Here, we review the computational efforts to uncover the conformational free energy landscapes of a subset of membrane proteins: ion channels, transporters and G-protein coupled receptors. We focus on the various enhanced sampling techniques used to study these questions, how the conclusions come together to build a coherent picture, and the relationship between simulation outcomes and experimental observables.

Identification of perturbed signaling pathways from gene expression data using information divergence

Abnormal regulation of signaling pathways is the key causative factor in several diseases. Although many methods have been proposed to identify significantly differential pathways between two conditions via microarray gene expression datasets, most of them concentrate on differences in the pathway components-either the differential expression or the correlation of genes in a given pathway. However, as biological functional units, signaling pathways may have diverse activity patterns across different biological contexts. In order to detect overall changes in pathways, we propose an analysis model called SPAID (Signaling Pathway Analysis based on Information Divergence). SPAID is based on the concept of information divergence, which can be used to compare two conditions by computing the differential probability distribution of the regulation capacity. We compared SPAID with several classical algorithms using different datasets, and the results indicate that SPAID produces higher repeatability, has better performance and universality, and extracts more comprehensive information regarding the underlying biological processes. In conclusion, by introducing the idea of information divergence, our study measures differences in pathways from an overall perspective and will provide a complementary analysis framework for pathway analysis.

The Isomeric Preference of an Atypical Dopamine Transporter Inhibitor Contributes to Its Selection of the Transporter Conformation

Cocaine, a widely abused psychostimulant, inhibits the dopamine transporter (DAT) by trapping the protein in an outward-open conformation, whereas atypical DAT inhibitors such as benztropine have low abuse liability and prefer less outward-open conformations. Here, we use a spectrum of computational modeling and simulation approaches to obtain the underlying molecular mechanism in atomistic detail. Interestingly, our quantum mechanical calculations and molecular dynamics (MD) simulations suggest that a benztropine derivative JHW007 prefers a different stereoisomeric conformation of tropane in binding to DAT compared to that of a cocaine derivative, CFT. To further investigate the different inhibition mechanisms of DAT, we carried out MD simulations in combination with Markov state modeling analysis of wild-type and Y156F DAT in the absence of any ligand or the presence of CFT or JHW007. Our results indicate that the Y156F mutation and CFT shift the conformational equilibrium toward an outward-open conformation, whereas JHW007 prefers an inward-occluded conformation. Our findings reveal the mechanistic details of DAT inhibition by JHW007 at the atomistic level, which provide clues for rational design of atypical inhibitors.

Reprogramming cellular functions with engineered membrane proteins

Taking inspiration from Nature, synthetic biology utilizes and modifies biological components to expand the range of biological functions for engineering new practical devices and therapeutics. While early breakthroughs mainly concerned the design of gene circuits, recent efforts have focused on engineering signaling pathways to reprogram cellular functions. Since signal transduction across cell membranes initiates and controls intracellular signaling, membrane receptors have been targeted by diverse protein engineering approaches despite limited mechanistic understanding of their function. The modular architecture of several receptor families has enabled the empirical construction of chimeric receptors combining domains from distinct native receptors which have found successful immunotherapeutic applications. Meanwhile, progress in membrane protein structure determination, computational modeling and rational design promise to foster the engineering of a broader range of membrane receptor functions. Marrying empirical and rational membrane protein engineering approaches should enable the reprogramming of cells with widely diverse fine-tuned functions.

Toward high-resolution computational design of the structure and function of helical membrane proteins

The computational design of α-helical membrane proteins is still in its infancy but has already made great progress. De novo design allows stable, specific and active minimal oligomeric systems to be obtained. Computational reengineering can improve the stability and function of naturally occurring membrane proteins. Currently, the major hurdle for the field is the experimental characterization of the designs. The emergence of new structural methods for membrane proteins will accelerate progress.

Insights into the function of opioid receptors from molecular dynamics simulations of available crystal structures

The opioid receptors are key targets in the treatment of acute and chronic pain, and the development of novel analgesics with reduced side effects is crucial in the search for more effective medications. The crystal structures of opioid receptors have provided a wealth of knowledge on many aspects of opioid receptor pharmacology and function, including ligand binding poses, location of the sodium allosteric binding site, conformational changes associated with activation and putative dimeric interfaces. These crystal structures also offer a starting point for molecular dynamics (MD) simulations to capture one aspect of drug design that static structures cannot resolve, namely protein dynamics. With the increase in computing power, MD simulations of crystal structures have become an influential tool in understanding the function of GPCRs in general. Here, we discuss lessons learned from MD simulations of opioid receptor crystal structures with reference to (i) the binding pathway of sodium to its crystallographic allosteric site, (ii) the dynamics of ligand-receptor and receptor-receptor interactions, both at the ligand- and G protein-binding sites, (iii) the binding pathway and binding pose of novel ligands, and (iv) opioid receptor oligomerization.

LINKED ARTICLES

This article is part of a themed section on Emerging Areas of Opioid Pharmacology. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.14/issuetoc.

Applications of Normal Mode Analysis Methods in Computational Protein Design

Recent advances in coarse-grained normal mode analysis methods make possible the large-scale prediction of the effect of mutations on protein stability and dynamics as well as the generation of biologically relevant conformational ensembles. Given the interplay between flexibility and enzymatic activity, the combined analysis of stability and dynamics using the Elastic Network Contact Model (ENCoM) method has ample applications in protein engineering in industrial and medical applications such as in computational antibody design. Here, we present a detailed tutorial on how to perform such calculations using ENCoM.

Alternating access mechanisms of LeuT-fold transporters: trailblazing towards the promised energy landscapes

Secondary active transporters couple the uphill translocation of substrates to electrochemical ion gradients. Transporter conformational motion, generically referred to as alternating access, enables a central ligand binding site to change its orientation relative to the membrane. Here we review themes of alternating access and the transduction of ion gradient energy to power this process in the LeuT-fold class of transporters where crystallographic, computational and spectroscopic approaches have converged to yield detailed models of transport cycles. Specifically, we compare findings for the Na⁺-coupled amino acid transporter LeuT and the Na⁺-coupled hydantoin transporter Mhp1. Although these studies have illuminated multiple aspects of transporter structures and dynamics, a number of questions remain unresolved that so far hinder understanding transport mechanisms in an energy landscape perspective.

The Allostery Landscape: Quantifying Thermodynamic Couplings in Biomolecular Systems

Allostery plays a fundamental role in most biological processes. However, little theory is available to describe it outside of two-state models. Here we use a statistical mechanical approach to show that the allosteric coupling between two collective variables is not a single number, but instead a two-dimensional thermodynamic coupling function that is directly related to the mutual information from information theory and the copula density function from probability theory. On this basis, we demonstrate how to quantify the contribution of specific energy terms to this thermodynamic coupling function, enabling an approximate decomposition that reveals the mechanism of allostery. We illustrate the thermodynamic coupling function and its use by showing how allosteric coupling in the alanine dipeptide molecule contributes to the overall shape of the Φ/Ψ free energy surface, and by identifying the interactions that are necessary for this coupling.

Vibrational resonance, allostery, and activation in rhodopsin-like G protein-coupled receptors

G protein-coupled receptors are a large family of membrane proteins activated by a variety of structurally diverse ligands making them highly adaptable signaling molecules. Despite recent advances in the structural biology of this protein family, the mechanism by which ligands induce allosteric changes in protein structure and dynamics for its signaling function remains a mystery. Here, we propose the use of terahertz spectroscopy combined with molecular dynamics simulation and protein evolutionary network modeling to address the mechanism of activation by directly probing the concerted fluctuations of retinal ligand and transmembrane helices in rhodopsin. This approach allows us to examine the role of conformational heterogeneity in the selection and stabilization of specific signaling pathways in the photo-activation of the receptor. We demonstrate that ligand-induced shifts in the conformational equilibrium prompt vibrational resonances in the protein structure that link the dynamics of conserved interactions with fluctuations of the active-state ligand. The connection of vibrational modes creates an allosteric association of coupled fluctuations that forms a coherent signaling pathway from the receptor ligand-binding pocket to the G-protein activation region. Our evolutionary analysis of rhodopsin-like GPCRs suggest that specific allosteric sites play a pivotal role in activating structural fluctuations that allosterically modulate functional signals.