Global motions exhibited by proteins in micro- to milliseconds simulations concur with anisotropic network model predictions

Evaluation of Essential Dynamics and Fixed-Length Coarse Graining for Multidomain Proteins

For multiscale modeling of biomolecules, reliable coarse-grained (CG) models can offer great potential to simulate larger temporal and spatial scales than traditional all-atom (AA) models. In this study, we explore the essential dynamics coarse graining (EDCG) and fixed-length coarse graining (FLCG) approaches for constructing highly coarse-grained models for multidomain proteins (MDPs), with 1 to 10 amino acid residues per CG site. In the studies of 13 MDPs, our data indicate that both EDCG and FLCG can preserve the protein dynamics of MDPs. FLCG, which restricts an equal number of residues in each CG site, represents an excellent approximation to EDCG and a straightforward approach for coarse-graining MDPs. Furthermore, FLCG is tested with a class B G-protein-coupled receptor protein, and the agreement with prior experiments suggests its general application to various MDPs in different environments or conditions. Finally, we demonstrate another application of FLCG through progressive backmapping, showcasing the ability to recover from lower-resolution CG models (6 residues/CG site) to higher-resolution ones (1 residue/CG site). These promising outcomes underscore the broad applicability of FLCG to construct highly or ultra-coarse-grained models of complex biomolecules for multiscale simulations.

Computational analysis of long-range allosteric communications in CFTR

Malfunction of the CFTR protein results in cystic fibrosis, one of the most common hereditary diseases. CFTR functions as an anion channel, the gating of which is controlled by long-range allosteric communications. Allostery also has direct bearings on CF treatment: the most effective CFTR drugs modulate its activity allosterically. Herein, we integrated Gaussian network model, transfer entropy, and anisotropic normal mode-Langevin dynamics and investigated the allosteric communications network of CFTR. The results are in remarkable agreement with experimental observations and mutational analysis and provide extensive novel insight. We identified residues that serve as pivotal allosteric sources and transducers, many of which correspond to disease-causing mutations. We find that in the ATP-free form, dynamic fluctuations of the residues that comprise the ATP-binding sites facilitate the initial binding of the nucleotide. Subsequent binding of ATP then brings to the fore and focuses on dynamic fluctuations that were present in a latent and diffuse form in the absence of ATP. We demonstrate that drugs that potentiate CFTR's conductance do so not by directly acting on the gating residues, but rather by mimicking the allosteric signal sent by the ATP-binding sites. We have also uncovered a previously undiscovered allosteric 'hotspot' located proximal to the docking site of the phosphorylated regulatory (R) domain, thereby establishing a molecular foundation for its phosphorylation-dependent excitatory role. This study unveils the molecular underpinnings of allosteric connectivity within CFTR and highlights a novel allosteric 'hotspot' that could serve as a promising target for the development of novel therapeutic interventions.

Predicting allosteric pockets in protein biological assemblages

MOTIVATION

Allostery enables changes to the dynamic behavior of a protein at distant positions induced by binding. Here, we present APOP, a new allosteric pocket prediction method, which perturbs the pockets formed in the structure by stiffening pairwise interactions in the elastic network across the pocket, to emulate ligand binding. Ranking the pockets based on the shifts in the global mode frequencies, as well as their mean local hydrophobicities, leads to high prediction success when tested on a dataset of allosteric proteins, composed of both monomers and multimeric assemblages.

RESULTS

Out of the 104 test cases, APOP predicts known allosteric pockets for 92 within the top 3 rank out of multiple pockets available in the protein. In addition, we demonstrate that APOP can also find new alternative allosteric pockets in proteins. Particularly interesting findings are the discovery of previously overlooked large pockets located in the centers of many protein biological assemblages; binding of ligands at these sites would likely be particularly effective in changing the protein's global dynamics.

AVAILABILITY AND IMPLEMENTATION

APOP is freely available as an open-source code (https://github.com/Ambuj-UF/APOP) and as a web server at https://apop.bb.iastate.edu/.

Protein dynamics developments for the large scale and cryoEM: case study of ProDy 2.0

New computational biophysics pipelines for analysing the global dynamics of structural ensembles and large, dynamic complexes resolved by cryoEM are reviewed.

Cryo-electron microscopy (cryoEM) has become a well established technique with the potential to produce structures of large and dynamic supramolecular complexes that are not amenable to traditional approaches for studying structure and dynamics. The size and low resolution of such molecular systems often make structural modelling and molecular dynamics simulations challenging and computationally expensive. This, together with the growing wealth of structural data arising from cryoEM and other structural biology methods, has driven a trend in the computational biophysics community towards the development of new pipelines for analysing global dynamics using coarse-grained models and methods. At the centre of this trend has been a return to elastic network models, normal mode analysis (NMA) and ensemble analyses such as principal component analysis, and the growth of hybrid simulation methodologies that make use of them. Here, this field is reviewed with a focus on ProDy, the Python application programming interface for protein dynamics, which has been developed over the last decade. Two key developments in this area are highlighted: (i) ensemble NMA towards extracting and comparing the signature dynamics of homologous structures, aided by the recent SignDy pipeline, and (ii) pseudoatom fitting for more efficient global dynamics analyses of large and low-resolution supramolecular assemblies from cryoEM, revisited in the CryoDy pipeline. It is believed that such a renewal and extension of old models and methods in new pipelines will be critical for driving the field forward into the next cryoEM revolution.

Normal mode analysis of membrane protein dynamics using the vibrational subsystem analysis

The vibrational subsystem analysis is a useful approach that allows for evaluating the spectrum of modes of a given system by integrating out the degrees of freedom accessible to the environment. The approach could be utilized for exploring the collective dynamics of a membrane protein (system) coupled to the lipid bilayer (environment). However, the application to membrane proteins is limited due to high computational costs of modeling a sufficiently large membrane environment unbiased by end effects, which drastically increases the size of the investigated system. We derived a recursive formula for calculating the reduced Hessian of a membrane protein embedded in a lipid bilayer by decomposing the membrane into concentric cylindrical domains with the protein located at the center. The approach allows for the design of a time- and memory-efficient algorithm and a mathematical understanding of the convergence of the reduced Hessian with respect to increasing membrane sizes. The application to the archaeal aspartate transporter Glt_Ph illustrates its utility and efficiency in capturing the transporter's elevator-like movement during its transition between outward-facing and inward-facing states.

Conserved Conformational Hierarchy across Functionally Divergent Glycosyltransferases of the GT-B Structural Superfamily as Determined from Microsecond Molecular Dynamics

It has long been understood that some proteins undergo conformational transitions en route to the Michaelis Complex to allow chemistry. Examination of crystal structures of glycosyltransferase enzymes in the GT-B structural class reveals that the presence of ligand in the active site triggers an open-to-closed conformation transition, necessary for their catalytic functions. Herein, we describe microsecond molecular dynamics simulations of two distantly related glycosyltransferases that are part of the GT-B structural superfamily, HepI and GtfA. Simulations were performed using the open and closed conformations of these unbound proteins, respectively, and we sought to identify the major dynamical modes and communication networks that interconnect the open and closed structures. We provide the first reported evidence within the scope of our simulation parameters that the interconversion between open and closed conformations is a hierarchical multistep process which can be a conserved feature of enzymes of the same structural superfamily. Each of these motions involves of a collection of smaller molecular reorientations distributed across both domains, highlighting the complexities of protein dynamic involved in the interconversion process. Additionally, dynamic cross-correlation analysis was employed to explore the potential effect of distal residues on the catalytic efficiency of HepI. Multiple distal nonionizable residues of the C-terminal domain exhibit motions anticorrelated to positively charged residues in the active site in the N-terminal domain involved in substrate binding. Mutations of these residues resulted in a reduction in negatively correlated motions and an altered enzymatic efficiency that is dominated by lower K_m values with k_cat effectively unchanged. The findings suggest that residues with opposing conformational motions involved in the opening and closing of the bidomain HepI protein can allosterically alter the population and conformation of the “closed” state, essential to the formation of the Michaelis complex. The stabilization effects of these mutations likely equally influence the energetics of both the ground state and the transition state of the catalytic reaction, leading to the unaltered k_cat. Our study provides new insights into the role of conformational dynamics in glycosyltransferase’s function and new modality to modulate enzymatic efficiency.

Coarse-grained nucleic acid-protein model for hybrid nanotechnology

The emerging field of hybrid DNA-protein nanotechnology brings with it the potential for many novel materials which combine the addressability of DNA nanotechnology with the versatility of protein interactions. However, the design and computational study of these hybrid structures is difficult due to the system sizes involved. To aid in the design and in silico analysis process, we introduce here a coarse-grained DNA/RNA-protein model that extends the oxDNA/oxRNA models of DNA/RNA with a coarse-grained model of proteins based on an anisotropic network model representation. Fully equipped with analysis scripts and visualization, our model aims to facilitate hybrid nanomaterial design towards eventual experimental realization, as well as enabling study of biological complexes. We further demonstrate its usage by simulating DNA-protein nanocage, DNA wrapped around histones, and a nascent RNA in polymerase.

Insight into Shared Properties and Differential Dynamics and Specificity of Secretory Phospholipase A2 Family Members

Understanding generic mechanisms of functions shared by the secretory phospholipase A₂ (sPLA₂) family involved in the lipid metabolism and cell signaling and the molecular basis of function specificity for family members is an intriguing but challenging problem for biologists. Here, we explore the issue through extensive analyses using a combination of structure-based methods and bioinformatics tools on130 sPLA₂ family members. The principal component analysis of the structure ensemble reveals that the enzyme has an open-close motion which helps widen the substrate binding channel, facilitating its binding to phospholipid. Performing elastic network model and sequence analyses found that the residues critical for family functions, such as cysteine and catalytic residues, are highly conserved and undergo minimal movements, which is evolutionarily essential as their perturbation would impact the function, while the four residue regions involved in the association with the calcium ion/membrane are lowly conserved and of high mobility and large variations in low-to-intermediate frequency modes, which reflects the specificity of members. The analyses from perturbation response scanning also reveal that the above four regions with high sensitivity to an external perturbation are member-specific, suggesting their different roles in allosteric modulation, while the minimal sensitive residues are the shared characteristics across family members, which play an important role in maintaining structural stability as the folding core. This study is helpful for understanding how sequences, structures, and dynamics of sPLA₂ family members evolve to ensure their common and specific functions and can provide a guide for accurate design of proteins with finely tuned activities.

The high-energy transition state of the glutamate transporter homologue GltPh

Membrane transporters mediate cellular uptake of nutrients, signaling molecules, and drugs. Their overall mechanisms are often well understood, but the structural features setting their rates are mostly unknown. Earlier single-molecule fluorescence imaging of the archaeal model glutamate transporter homologue GltPh from Pyrococcus horikoshii suggested that the slow conformational transition from the outward- to the inward-facing state, when the bound substrate is translocated from the extracellular to the cytoplasmic side of the membrane, is rate limiting to transport. Here, we provide insight into the structure of the high-energy transition state of GltPh that limits the rate of the substrate translocation process. Using bioinformatics, we identified GltPh gain-of-function mutations in the flexible helical hairpin domain HP2 and applied linear free energy relationship analysis to infer that the transition state structurally resembles the inward-facing conformation. Based on these analyses, we propose an approach to search for allosteric modulators for transporters.

Mechanochemical enzymes and protein machines as hydrodynamic force dipoles: the active dimer model

Mechanochemically active enzymes change their shapes within every turnover cycle. Therefore, they induce circulating flows in the solvent around them and behave as oscillating hydrodynamic force dipoles. Because of non-equilibrium fluctuating flows collectively generated by the enzymes, mixing in the solution and diffusion of passive particles within it are expected to get enhanced. Here, we investigate the intensity and statistical properties of such force dipoles in the minimal active dimer model of a mechanochemical enzyme. In the framework of this model, novel estimates for hydrodynamic collective effects in solution and in lipid bilayers under rapid rotational diffusion are derived, and available experimental and computational data is examined.

The Discovery of a Putative Allosteric Site in the SARS-CoV-2 Spike Protein Using an Integrated Structural/Dynamic Approach

SARS-CoV-2 has caused the largest pandemic of the twenty-first century (COVID-19), threatening the life and economy of all countries in the world. The identification of novel therapies and vaccines that can mitigate or control this global health threat is among the most important challenges facing biomedical sciences. To construct a long-term strategy to fight both SARS-CoV-2 and other possible future threats from coronaviruses, it is critical to understand the molecular mechanisms underlying the virus action. The viral entry and associated infectivity stems from the formation of the SARS-CoV-2 spike protein complex with angiotensin-converting enzyme 2 (ACE2). The detection of putative allosteric sites on the viral spike protein molecule can be used to elucidate the molecular pathways that can be targeted with allosteric drugs to weaken the spike-ACE2 interaction and, thus, reduce viral infectivity. In this study, we present the results of the application of different computational methods aimed at detecting allosteric sites on the SARS-CoV-2 spike protein. The adopted tools consisted of the protein contact networks (PCNs), SEPAS (Affinity by Flexibility), and perturbation response scanning (PRS) based on elastic network modes. All of these methods were applied to the ACE2 complex with both the SARS-CoV2 and SARS-CoV spike proteins. All of the adopted analyses converged toward a specific region (allosteric modulation region [AMR]), present in both complexes and predicted to act as an allosteric site modulating the binding of the spike protein with ACE2. Preliminary results on hepcidin (a molecule with strong structural and sequence with AMR) indicated an inhibitory effect on the binding affinity of the spike protein toward the ACE2 protein.

Adaptability and specificity: how do proteins balance opposing needs to achieve function?

Many proteins select from a small repertoire of 3-dimensional folds retained over evolutional timescales and recruited for different functions, with changes in local structure and sequence to enable specificity. Recent studies have revealed the evolutionary constraints on protein dynamics to achieve function. The significance of protein dynamics in simultaneously satisfying conformational flexibility/malleability and stability/precision requirements becomes clear upon dissecting the spectrum of equilibrium motions accessible to fold families. Accessibility to highly conserved global modes of motions shared by family members, to low-to-intermediate-frequency modes that distinguish subfamilies and confer specificity, and to conserved high-frequency modes ensuring chemical precision and core stability underlies functional specialization while exploiting highly versatile folds. These design principles are illustrated for the family of PDZ domains.

Conformational transition of SARS-CoV-2 spike glycoprotein between its closed and open states

In 2020, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide and caused the coronavirus disease 2019 (COVID-19). Spike (S) glycoproteins on the viral membrane bind to ACE2 receptors on the host cell membrane and initiate fusion, and S protein is currently among the primary drug target to inhibit viral entry. The S protein can be in a receptor inaccessible (closed) or accessible (open) state based on down and up positions of its receptor-binding domain (RBD), respectively. However, conformational dynamics and the transition pathway between closed to open states remain unexplored. Here, we performed all-atom molecular dynamics (MD) simulations starting from closed and open states of the S protein trimer in the presence of explicit water and ions. MD simulations showed that RBD forms a higher number of interdomain interactions and exhibits lower mobility in its down position than its up position. MD simulations starting from intermediate conformations between the open and closed states indicated that RBD switches to the up position through a semi-open intermediate that potentially reduces the free energy barrier between the closed and open states. Free energy landscapes were constructed, and a minimum energy pathway connecting the closed and open states was proposed. Because RBD-ACE2 binding is compatible with the semi-open state, but not with the closed state of the S protein, we propose that the formation of the intermediate state is a prerequisite for the host cell recognition.

Structural basis of the activation of a metabotropic GABA receptor

Metabotropic γ-aminobutyric acid receptors (GABA_B) are involved in the modulation of synaptic responses in the central nervous system and are implicated in various neuropsychological conditions, ranging from addiction to psychosis¹. GABA_B belongs to G protein-coupled receptor class C, and its functional entity consists of an obligate heterodimer composed of GB1 and GB2². Each subunit possesses an extracellular Venus flytrap domain, connected to a canonical seven-transmembrane domain. Here, we present four cryo-EM structures of the human full-length GB1-GB2 heterodimer in its inactive apo, two intermediate agonist-bound, and active agonist/positive allosteric modulator bound forms. The structures reveal startling differences, shedding light onto the complex motions underlying the unique activation mechanism of GABA_B. Our results show that agonist binding in the GB1 Venus flytrap domain triggers a series of transitions, first rearranging and bringing the two transmembrane domains into close contact along transmembrane helix 6 and ultimately inducing conformational rearrangements in the GB2 transmembrane domain via a lever-like mechanism, potentiated by a positive allosteric modulator binding at the dimerization interface, to initiate downstream signaling.

Spectral analysis of molecular dynamics simulations on PDZ: MD sectors

The idea of protein "sectors" posits that sparse subsets of amino acid residues form cooperative networks that are key elements of protein stability, ligand binding, and allosterism. To date, protein sectors have been calculated by the statistical coupling analysis (SCA) method of Ranganathan and co-workers via the spectral analysis of conservation-weighted evolutionary covariance matrices obtained from a multiple sequence alignments of homologous families of proteins. SCA sectors, a knowledge-based protocol, have been indentified with functional properties and allosterism for a number of systems. In this study, we investigate the utility of the sector idea for the analysis of physics-based molecular dynamics (MD) trajectories of proteins. Our test case for this procedure is PSD95- PDZ3, one of the smallest proteins for which allosterism has been observed. It has served previously as a model system for a number of prediction algorithms, and is well characterized by X-ray crystallography, NMR spectroscopy and site specific mutagenisis. All-atom MD simulations were performed for a total of 500 nanoseconds using AMBER, and MD-calculated covariance matrices for the fluctuations of residue displacements and non-bonded interaction energies were subjected to spectral analysis in a manner analogous to that of SCA. The composition of MD sectors was compared with results from SCA, site specific mutagenesis, and allosterism. The concordance indicates that MD sectors are a viable protocol for analyzing MD trajectories and provide insight into the physical origin of the phenomenon.Communicated by Ramaswamy H. Sarma.

Essential site scanning analysis: A new approach for detecting sites that modulate the dispersion of protein global motions

Despite the wealth of methods developed for exploring the molecular basis of allostery in biomolecular systems, there is still a need for structure-based predictive tools that can efficiently detect susceptible sites for triggering allosteric responses. Toward this goal, we introduce here an elastic network model (ENM)-based method, Essential Site Scanning Analysis (ESSA). Essential sites are here defined as residues that would significantly alter the protein's global dynamics if bound to a ligand. To mimic the crowding induced upon substrate binding, the heavy atoms of each residue are incorporated as additional network nodes into the α-carbon-based ENM, and the resulting shifts in soft mode frequencies are used as a metric for evaluating the essentiality of each residue. Results on a dataset of monomeric proteins indicate the enrichment of allosteric and orthosteric binding sites, as well as global hinge regions among essential residues, highlighting the significant role of these sites in controlling the overall structural dynamics. Further integration of ESSA with information on predicted pockets and their local hydrophobicity density enables successful predictions of allosteric pockets for both ligand-bound and -unbound structures. ESSA can be efficiently applied to large multimeric systems. Three case studies, namely (i) G-protein binding to a GPCR, (ii) heterotrimeric assembly of the Ser/Thr protein phosphatase PP2A, and (iii) allo-targeting of AMPA receptor, demonstrate the utility of ESSA for identifying essential sites and narrowing down target allosteric sites identified by druggability simulations.

Dynamical comparison between Drosha and Dicer reveals functional motion similarities and dissimilarities

Drosha and Dicer are RNase III family members of classes II and III, respectively, which play a major role in the maturation of micro-RNAs. The two proteins share similar domain arrangement and overall fold despite no apparent sequence homology. The overall structural and catalytic reaction similarity of both proteins, on the one hand, and differences in the substrate and its binding mechanisms, on the other, suggest that both proteins also share dynamic similarities and dissimilarities. Since dynamics is essential for protein function, a comparison at their dynamics level is fundamental for a complete understanding of the overall relations between these proteins. In this study, we present a dynamical comparison between human Drosha and Giardia Dicer. Gaussian Network Model and Anisotropic Network Model modes of motion of the proteins are calculated. Dynamical comparison is performed using global and local dynamic programming algorithms for aligning modes of motion. These algorithms were recently developed based on the commonly used Needleman-Wunsch and Smith-Waterman algorithms for global and local sequence alignment. The slowest mode of Drosha is different from that of Dicer due to its more bended posture and allow the motion of the double-stranded RNA-binding domain toward and away from its substrate. Among the five slowest modes dynamics similarity exists only for the second slow mode of motion of Drosha and Dicer. In addition, high local dynamics similarity is observed at the catalytic domains, in the vicinity of the catalytic residues. The results suggest that the proteins exert a similar catalytic mechanism using similar motions, especially at the catalytic sites.

Stochastic modeling of macromolecules in solution. I. Relaxation processes

A framework for the stochastic description of relaxation processes in flexible macromolecules, including dissipative effects, is introduced from an atomistic point of view. Projection-operator techniques are employed to obtain multidimensional Fokker-Planck operators governing the relaxation of internal coordinates and global degrees of freedom and depending upon parameters fully recoverable from classic force fields (energetics) and continuum models (friction tensors). A hierarchy of approaches of different complexity is proposed in this unified context, aimed primarily at the interpretation of magnetic resonance relaxation experiments. In particular, a model based on a harmonic internal Hamiltonian is discussed as a test case.

Dynamics based clustering of globin family members

A methodology to cluster proteins based on their dynamics’ similarity is presented. For each pair of proteins from a dataset, the structures are superimposed, and the Anisotropic Network Model modes of motions are calculated. The twelve slowest modes from each protein are matched using a local mode alignment algorithm based on the local sequence alignment algorithm of Smith–Waterman. The dynamical similarity distance matrix is calculated based on the top scoring matches of each pair and the proteins are clustered using a hierarchical clustering algorithm. The utility of this method is exemplified on a dataset of protein chains from the globin family and a dataset of tetrameric hemoglobins. The results demonstrate the effect of the quaternary structure of globin members on their intrinsic dynamics and show good ability to distinguish between different states of hemoglobin, revealing the dynamical relations between them.

Dynamical comparison between myoglobin and hemoglobin

Myoglobin and hemoglobin are globular hemeproteins, when the former is a monomer and the latter a heterotetramer. Despite the structural similarity of myoglobin to α and β subunits of hemoglobin, there is a functional difference between the two proteins, owing to the quaternary structure of hemoglobin. The effect of the quaternary structure of hemoglobin on the intrinsic dynamics of its subunits is explored by dynamical comparison of the two proteins. Anisotropic Network Model modes of motion were calculated for hemoglobin and myoglobin. Dynamical comparison between the proteins was performed using global and local Anisotropic Network Model mode alignment algorithms based on the algorithms of Smith-Waterman and Needleman-Wunsch for sequence comparison. The results indicate that the quaternary structure of hemoglobin substantially alters the intrinsic dynamics of its subunits, an effect that may contribute to the functional difference between the two proteins. Local dynamics similarity between the proteins is still observed at the major exit route of the ligand.

Molecular dynamics simulations of site point mutations in the TPR domain of cyclophilin 40 identify conformational states with distinct dynamic and enzymatic properties

Cyclophilin 40 (Cyp40) is a member of the immunophilin family that acts as a peptidyl-prolyl-isomerase enzyme and binds to the heat shock protein 90 (Hsp90). Its structure comprises an N-terminal cyclophilin domain and a C-terminal tetratricopeptide (TPR) domain. Cyp40 is overexpressed in prostate cancer and certain T-cell lymphomas. The groove for Hsp90 binding on the TPR domain includes residues Lys227 and Lys308, referred to as the carboxylate clamp, and is essential for Cyp40-Hsp90 binding. In this study, the effect of two mutations, K227A and K308A, and their combinative mutant was investigated by performing a total of 5.76 μs of all-atom molecular dynamics (MD) simulations in explicit solvent. All simulations, except the K308A mutant, were found to adopt two distinct (extended or compact) conformers defined by different cyclophilin-TPR interdomain distances. The K308A mutant was only observed in the extended form which is observed in the Cyp40 X-ray structure. The wild-type, K227A, and combined mutant also showed bimodal distributions. The experimental melting temperature, Tm, values of the mutants correlate with the degree of compactness with the K308A extended mutant having a marginally lower melting temperature. Another novel measure of compactness determined from the MD data, the "coordination shell volume," also shows a direct correlation with Tm. In addition, the MD simulations show an allosteric effect with the mutations in the remote TPR domain having a pronounced effect on the molecular motions of the enzymatic cyclophilin domain which helps rationalise the experimentally observed increase in enzyme activity measured for all three mutations.

Concerted motions and large-scale structural fluctuations of Trichoderma reesei Cel7A cellobiohydrolase

Cellobiohydrolases (CBHs) are key enzymes for the saccharification of cellulose and play major roles in industrial settings for biofuel production. The catalytic core domain of these enzymes exhibits a long and narrow binding tunnel capable of binding glucan chains from crystalline cellulose and processively hydrolyze them. The binding cleft is topped by a set of loops, which are believed to play key roles in substrate binding and cleavage processivity. Here, we present an analysis of the loop motions of the Trichoderma reesei Cel7A catalytic core domain (TrCel7A) using conventional and accelerated molecular dynamics simulations. We observe that the loops exhibit highly coupled fluctuations and cannot move independently of each other. In the absence of a substrate, the characteristic large amplitude dynamics of TrCel7A consists of breathing motions, where the loops undergo open-and-close fluctuations. Upon substrate binding, the open-close fluctuations of the loops are quenched and one of the loops moves parallel to the binding site, possibly to allow processive motion along the glucan chain. Using microsecond accelerated molecular dynamics, we observe large-scale fluctuations of the loops (up to 37 Å) and the entire exposure of the TrCel7A binding site in the absence of the substrate, resembling an endoglucanase. These results suggest that the initial CBH-substrate contact and substrate recognition by the enzyme are similar to that of endoglucanases and, once bound to the substrate, the loops remain closed for proper enzymatic activity.

Activation and desensitization of ionotropic glutamate receptors by selectively triggering pre-existing motions

Ionotropic glutamate receptors (iGluRs) are ligand-gated ion channels that are key players in synaptic transmission and plasticity. They are composed of four subunits, each containing four functional domains, the quaternary packing and collective structural dynamics of which are important determinants of their molecular mechanism of function. With the explosion of structural studies on different members of the family, including the structures of activated open channels, the mechanisms of action of these central signaling machines are now being elucidated. We review the current state of computational studies on two major members of the family, AMPA and NMDA receptors, with focus on molecular simulations and elastic network model analyses that have provided insights into the coupled movements of extracellular and transmembrane domains. We describe the newly emerging mechanisms of activation, allosteric signaling and desensitization, as mainly a selective triggering of pre-existing soft motions, as deduced from computational models and analyses that leverage structural data on intact AMPA and NMDA receptors in different states.

Computational Exploration of Conformational Transitions in Protein Drug Targets

Protein drug targets vary from highly structured to completely disordered; either way dynamics governs function. Hence, understanding the dynamical aspects of how protein targets function can enable improved interventions with drug molecules. Computational approaches offer highly detailed structural models of protein dynamics which are becoming more predictive as model quality and sampling power improve. However, the most advanced and popular models still have errors owing to imperfect parameter sets and often cannot access longer timescales of many crucial biological processes. Experimental approaches offer more certainty but can struggle to detect and measure lightly populated conformations of target proteins and subtle allostery. An emerging solution is to integrate available experimental data into advanced molecular simulations. In the future, molecular simulation in combination with experimental data may be able to offer detailed models of important drug targets such that improved functional mechanisms or selectivity can be accessed.

Energy Landscape of the Substrate Translocation Equilibrium of Plasma-Membrane Glutamate Transporters

Glutamate transporters maintain a large glutamate concentration gradient across synaptic membranes and are, thus, critical for functioning of the excitatory synapse. Mammalian glutamate transporters concentrate glutamate inside cells through energetic coupling of glutamate flux to the transmembrane concentration gradient of Na⁺. Structural models based on an archeal homologue, GltPh, suggest an elevator-like carrier mechanism. However, the energetic determinants of this carrier-based movement are not well understood. Although electrostatics play an important role in governing these energetics, their implication on transport dynamics has not been studied. Here, we combine a pre-steady-state kinetic analysis of the translocation equilibrium with electrostatic computations to gain insight into the energetics of the translocation process. Our results show the biphasic nature of translocation, consistent with the existence of an intermediate on the translocation pathway. In the absence of voltage, the equilibrium is shifted to the outward-facing configuration. Electrostatic computations confirm the intermediate state and show that the elevator-like movement is energetically feasible in the presence of bound Na⁺ ions, whereas a substrate-hopping model is energetically prohibitive. Our results highlight the critical contribution of charge compensation to transport and add to results from previous molecular dynamics simulations for improved understanding of the glutamate translocation process.

Elastic network model of learned maintained contacts to predict protein motion

We present a novel elastic network model, lmcENM, to determine protein motion even for localized functional motions that involve substantial changes in the protein's contact topology. Existing elastic network models assume that the contact topology remains unchanged throughout the motion and are thus most appropriate to simulate highly collective function-related movements. lmcENM uses machine learning to differentiate breaking from maintained contacts. We show that lmcENM accurately captures functional transitions unexplained by the classical ENM and three reference ENM variants, while preserving the simplicity of classical ENM. We demonstrate the effectiveness of our approach on a large set of proteins covering different motion types. Our results suggest that accurately predicting a "deformation-invariant" contact topology offers a promising route to increase the general applicability of ENMs. We also find that to correctly predict this contact topology a combination of several features seems to be relevant which may vary slightly depending on the protein. Additionally, we present case studies of two biologically interesting systems, Ferric Citrate membrane transporter FecA and Arachidonate 15-Lipoxygenase.

Dynamical differences of hemoglobin and the ionotropic glutamate receptor in different states revealed by a new dynamics alignment method

A new algorithm for comparison of protein dynamics is presented. Compared protein structures are superposed and their modes of motions are calculated using the anisotropic network model. The obtained modes are aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. Dynamical comparison of hemoglobin in the T and R2 states reveals that the dynamics of the allosteric effector 2,3-bisphosphoglycerate binding site is different in the two states. These differences can contribute to the selectivity of the effector to the T state. Similar comparison of the ionotropic glutamate receptor in the kainate+(R,R)-2b and ZK bound states reveals that the kainate+(R,R)-2b bound states slow modes describe upward motions of ligand binding domain and the transmembrane domain regions. Such motions may lead to the opening of the receptor. The upper lobes of the LBDs of the ZK bound state have a smaller interface with the amino terminal domains above them and have a better ability to move together. The present study exemplifies the use of dynamics comparison as a tool to study protein function. Proteins 2017; 85:1507-1517. © 2014 Wiley Periodicals, Inc.

Effect of Dimerization on the Dynamics of Neurotransmitter:Sodium Symporters

Dimerization is a common feature among the members of the neurotransmitter:sodium symporter (NSS) family of membrane proteins. Yet, the effect of dimerization on the mechanism of action of NSS members is not fully understood. In this study, we examined the collective dynamics of two members of the family, leucine transporter (LeuT) and dopamine transporter (DAT), to assess the significance of dimerization in modulating the functional motions of the monomers. We used to this aim the anisotropic network model (ANM), an efficient and robust method for modeling the intrinsic motions of proteins and their complexes. Transporters belonging to the NSS family are known to alternate between outward-facing (OF) and inward-facing (IF) states, which enables the uptake and release of their substrate (neurotransmitter) respectively, as the substrate is transported from the exterior to the interior of the cell. In both LeuT and DAT, dimerization is found to alter the collective motions intrinsically accessible to the individual monomers in favor of the functional transitions (OF ↔ IF), suggesting that dimerization may play a role in facilitating transport.

Energy landscape of LeuT from molecular simulations

The bacterial sodium-coupled leucine transporter (LeuT) has been broadly used as a structural model for understanding the structure-dynamics-function of mammalian neurotransmitter transporters as well as other solute carriers that share the same fold (LeuT fold), as the first member of the family crystallographically resolved in multiple states: outward-facing open, outward-facing occluded, and inward-facing open. Yet, a complete picture of the energy landscape of (sub)states visited along the LeuT transport cycle has been elusive. In an attempt to visualize the conformational spectrum of LeuT, we performed extensive simulations of LeuT dimer dynamics in the presence of substrate (Ala or Leu) and co-transported Na(+) ions, in explicit membrane and water. We used both conventional molecular dynamics (MD) simulations (with Anton supercomputing machine) and a recently introduced method, collective MD, that takes advantage of collective modes of motions predicted by the anisotropic network model. Free energy landscapes constructed based on ∼40 μs trajectories reveal multiple substates occluded to the extracellular (EC) and/or intracellular (IC) media, varying in the levels of exposure of LeuT to EC or IC vestibules. The IC-facing transmembrane (TM) helical segment TM1a shows an opening, albeit to a smaller extent and in a slightly different direction than that observed in the inward-facing open crystal structure. The study provides insights into the spectrum of conformational substates and paths accessible to LeuT and highlights the differences between Ala- and Leu-bound substates.

Computational approaches to investigating allostery

Allosteric regulation plays a key role in many biological processes, such as signal transduction, transcriptional regulation, and many more. It is rooted in fundamental thermodynamic and dynamic properties of macromolecular systems that are still poorly understood and are moreover modulated by the cellular context. Here we review the computational approaches used in the investigation of allosteric processes in protein systems. We outline how the models of allostery have evolved from their initial formulation in the sixties to the current views, which more fully account for the roles of the thermodynamic and dynamic properties of the system. We then describe the major classes of computational approaches employed to elucidate the mechanisms of allostery, the insights they have provided, as well as their limitations. We complement this analysis by highlighting the role of computational approaches in promising practical applications, such as the engineering of regulatory modules and identifying allosteric binding sites.

Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

Protein conformational changes are key to a wide range of cellular functions but remain difficult to access experimentally. Here the authors describe eBDIMS, a novel approach to predict intermediates observed in structural transition pathways from experimental ensembles.

Controlling Allosteric Networks in Proteins

Allosteric transition, defined as conformational changes induced by ligand binding, is one of the fundamental properties of proteins. Allostery has been observed and characterized in many proteins, and has been recently utilized to control protein function via regulation of protein activity. Here, we review the physical and evolutionary origin of protein allostery, as well as its importance to protein regulation, drug discovery, and biological processes in living systems. We describe recently developed approaches to identify allosteric pathways, connected sets of pairwise interactions that are responsible for propagation of conformational change from the ligand-binding site to a distal functional site. We then present experimental and computational protein engineering approaches for control of protein function by modulation of allosteric sites. As an example of application of these approaches, we describe a synergistic computational and experimental approach to rescue the cystic-fibrosis-associated protein cystic fibrosis transmembrane conductance regulator, which upon deletion of a single residue misfolds and causes disease. This example demonstrates the power of allosteric manipulation in proteins to both elucidate mechanisms of molecular function and to develop therapeutic strategies that rescue those functions. Allosteric control of proteins provides a tool to shine a light on the complex cascades of cellular processes and facilitate unprecedented interrogation of biological systems.

Revealing an outward-facing open conformational state in a CLC Cl(-)/H(+) exchange transporter

CLC secondary active transporters exchange Cl^- for H⁺. Crystal structures have suggested that the conformational change from occluded to outward-facing states is unusually simple, involving only the rotation of a conserved glutamate (Glu_ex) upon its protonation. Using ¹⁹F NMR, we show that as [H⁺] is increased to protonate Glu_ex and enrich the outward-facing state, a residue ~20 Å away from Glu_ex, near the subunit interface, moves from buried to solvent-exposed. Consistent with functional relevance of this motion, constriction via inter-subunit cross-linking reduces transport. Molecular dynamics simulations indicate that the cross-link dampens extracellular gate-opening motions. In support of this model, mutations that decrease steric contact between Helix N (part of the extracellular gate) and Helix P (at the subunit interface) remove the inhibitory effect of the cross-link. Together, these results demonstrate the formation of a previously uncharacterized 'outward-facing open' state, and highlight the relevance of global structural changes in CLC function.

DOI:http://dx.doi.org/10.7554/eLife.11189.001

Cells have transporter proteins on their surface to carry molecules in and out of the cell. For example, the CLC family of transporters move two chloride ions in one direction at the same time as moving one hydrogen ion in the opposite direction.

To be able to move these ions in opposite directions, transporters have to cycle through a series of shapes in which the ions can only access alternate sides of the membrane. First, the transporter adopts an 'outward-facing' shape when the ions first bind to the transporter, then it switches into the 'occluded' shape to move the ions through the membrane. Finally, the transporter takes on the 'inward-facing' shape to release the ions on the other side of the membrane. However, structural studies of CLCs suggest that the structures of these proteins do not change much while they are moving ions, which suggests that they might work in a different way.

Khantwal, Abraham et al. have now used techniques called “nuclear magnetic resonance” and "double electron-electron resonance" to investigate how a CLC from a bacterium moves ions. The experiments suggest that when the transporter adopts the outward-facing shape, points on the protein known as Y419 and D417 shift their positions. Chemically linking two regions of the CLC prevented this movement and inhibited the transport of chloride ions across the membrane.

Khantwal, Abraham et al. then used a computer simulation to model how the protein changes shape in more detail. This model predicts that two regions of the transporter undergo major rearrangements resulting in a gate-opening motion that widens a passage to allow the chloride ions to bind to the protein. Khantwal, Abraham et al.’s findings will prompt future studies to reveal the other shapes and how CLCs transition between them.

DOI:http://dx.doi.org/10.7554/eLife.11189.002

New generation of elastic network models

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation.

Dynamics and allostery of the ionotropic glutamate receptors and the ligand binding domain

The dynamics of the ligand-binding domain (LBD) and the intact ionotropic glutamate receptor (iGluR) were studied using Gaussian Network Model (GNM) analysis. The dynamics of LBDs with various allosteric modulators is compared using a novel method of multiple alignment of GNM modes of motion. The analysis reveals that allosteric effectors change the dynamics of amino acids at the upper lobe interface of the LBD dimer as well as at the hinge region between the upper- and lower- lobes. For the intact glutamate receptor the analysis show that the clamshell-like movement of the LBD upper and lower lobes is coupled to the bending of the trans-membrane domain (TMD) helices which may open the channel pore. The results offer a new insight on the mechanism of action of allosteric modulators on the iGluR and support the notion of TMD helices bending as a possible mechanism for channel opening. In addition, the study validates the methodology of multiple GNM modes alignment as a useful tool to study allosteric effect and its relation to proteins dynamics.

A human transcription factor in search mode

Transcription factors (TF) can change shape to bind and recognize DNA, shifting the energy landscape from a weak binding, rapid search mode to a higher affinity recognition mode. However, the mechanism(s) driving this conformational change remains unresolved and in most cases high-resolution structures of the non-specific complexes are unavailable. Here, we investigate the conformational switch of the human mitochondrial transcription termination factor MTERF1, which has a modular, superhelical topology complementary to DNA. Our goal was to characterize the details of the non-specific search mode to complement the crystal structure of the specific binding complex, providing a basis for understanding the recognition mechanism. In the specific complex, MTERF1 binds a significantly distorted and unwound DNA structure, exhibiting a protein conformation incompatible with binding to B-form DNA. In contrast, our simulations of apo MTERF1 revealed significant flexibility, sampling structures with superhelical pitch and radius complementary to the major groove of B-DNA. Docking these structures to B-DNA followed by unrestrained MD simulations led to a stable complex in which MTERF1 was observed to undergo spontaneous diffusion on the DNA. Overall, the data support an MTERF1-DNA binding and recognition mechanism driven by intrinsic dynamics of the MTERF1 superhelical topology.

Computational Studies of Glutamate Transporters

Glutamate is the major excitatory neurotransmitter in the human brain whose binding to receptors on neurons excites them while excess glutamate are removed from synapses via transporter proteins. Determination of the crystal structures of bacterial aspartate transporters has paved the way for computational investigation of their function and dynamics at the molecular level. Here, we review molecular dynamics and free energy calculation methods used in these computational studies and discuss the recent applications to glutamate transporters. The focus of the review is on the insights gained on the transport mechanism through computational methods, which otherwise is not directly accessible by experimental probes. Recent efforts to model the mammalian glutamate and other amino acid transporters, whose crystal structures have not been solved yet, are included in the review.

Comparison of the Internal Dynamics of Metalloproteases Provides New Insights on Their Function and Evolution

Metalloproteases have evolved in a vast number of biological systems, being one of the most diverse types of proteases and presenting a wide range of folds and catalytic metal ions. Given the increasing understanding of protein internal dynamics and its role in enzyme function, we are interested in assessing how the structural heterogeneity of metalloproteases translates into their dynamics. Therefore, the dynamical profile of the clan MA type protein thermolysin, derived from an Elastic Network Model of protein structure, was evaluated against those obtained from a set of experimental structures and molecular dynamics simulation trajectories. A close correspondence was obtained between modes derived from the coarse-grained model and the subspace of functionally-relevant motions observed experimentally, the later being shown to be encoded in the internal dynamics of the protein. This prompted the use of dynamics-based comparison methods that employ such coarse-grained models in a representative set of clan members, allowing for its quantitative description in terms of structural and dynamical variability. Although members show structural similarity, they nonetheless present distinct dynamical profiles, with no apparent correlation between structural and dynamical relatedness. However, previously unnoticed dynamical similarity was found between the relevant members Carboxypeptidase Pfu, Leishmanolysin, and Botulinum Neurotoxin Type A, despite sharing no structural similarity. Inspection of the respective alignments shows that dynamical similarity has a functional basis, namely the need for maintaining proper intermolecular interactions with the respective substrates. These results suggest that distinct selective pressure mechanisms act on metalloproteases at structural and dynamical levels through the course of their evolution. This work shows how new insights on metalloprotease function and evolution can be assessed with comparison schemes that incorporate information on protein dynamics. The integration of these newly developed tools, if applied to other protein families, can lead to more accurate and descriptive protein classification systems.

Hierarchical Conformational Analysis of Native Lysozyme Based on Sub-Millisecond Molecular Dynamics Simulations

Hierarchical organization of free energy landscape (FEL) for native globular proteins has been widely accepted by the biophysics community. However, FEL of native proteins is usually projected onto one or a few dimensions. Here we generated collectively 0.2 milli-second molecular dynamics simulation trajectories in explicit solvent for hen egg white lysozyme (HEWL), and carried out detailed conformational analysis based on backbone torsional degrees of freedom (DOF). Our results demonstrated that at micro-second and coarser temporal resolutions, FEL of HEWL exhibits hub-like topology with crystal structures occupying the dominant structural ensemble that serves as the hub of conformational transitions. However, at 100ns and finer temporal resolutions, conformational substates of HEWL exhibit network-like topology, crystal structures are associated with kinetic traps that are important but not dominant ensembles. Backbone torsional state transitions on time scales ranging from nanoseconds to beyond microseconds were found to be associated with various types of molecular interactions. Even at nanoseconds temporal resolution, the number of conformational substates that are of statistical significance is quite limited. These observations suggest that detailed analysis of conformational substates at multiple temporal resolutions is both important and feasible. Transition state ensembles among various conformational substates at microsecond temporal resolution were observed to be considerably disordered. Life times of these transition state ensembles are found to be nearly independent of the time scales of the participating torsional DOFs.

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation

Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

Microseconds simulations reveal a new sodium-binding site and the mechanism of sodium-coupled substrate uptake by LeuT

The bacterial sodium-coupled leucine/alanine transporter LeuT is broadly used as a model system for studying the transport mechanism of neurotransmitters because of its structural and functional homology to mammalian transporters such as serotonin, dopamine, or norepinephrine transporters, and because of the resolution of its structure in different states. Although the binding sites (S1 for substrate, and Na1 and Na2 for two co-transported sodium ions) have been resolved, we still lack a mechanistic understanding of coupled Na(+)- and substrate-binding events. We present here results from extensive (>20 μs) unbiased molecular dynamics simulations generated using the latest computing technology. Simulations show that sodium binds initially the Na1 site, but not Na2, and, consistently, sodium unbinding/escape to the extracellular (EC) region first takes place at Na2, succeeded by Na1. Na2 diffusion back to the EC medium requires prior dissociation of substrate from S1. Significantly, Na(+) binding (and unbinding) consistently involves a transient binding to a newly discovered site, Na1″, near S1, as an intermediate state. A robust sequence of substrate uptake events coupled to sodium bindings and translocations between those sites assisted by hydration emerges from the simulations: (i) bindings of a first Na(+) to Na1″, translocation to Na1, a second Na(+) to vacated Na1″ and then to Na2, and substrate to S1; (ii) rotation of Phe(253) aromatic group to seclude the substrate from the EC region; and (iii) concerted tilting of TM1b and TM6a toward TM3 and TM8 to close the EC vestibule.

Study, by use of coarse-grained models, of the functionally crucial residues and allosteric pathway of anesthetic regulation of the Gloeobacter violaceus ligand-gated ion channel

Although pentameric ligand-gated ion channels (pLGICs) have been found to be the targets of general anesthetics, the mechanism of the effects of anesthetics on pLGICs remains elusive. pLGICs from Gloeobacter violaceus (GLIC) can be inhibited by the anesthetic ketamine. X-ray crystallography has shown that the ketamine binding site is distant from the channel gate of the GLIC. It is still not clear how ketamine controls the function of the GLIC by long-range allosteric regulation. In this work, the functionally crucial residues and allosteric pathway of anesthetic regulation of the GLIC were identified by use of a coarse-grained thermodynamic method developed by our group. In our method, the functionally crucial sites were identified as the residues thermodynamically coupled with binding of ketamine. The results from calculation were highly consistent with experimental data. Our study aids understanding of the mechanism of the anesthetic action of ketamine on the GLIC by long-range allosteric modulation.

Probing the global and local dynamics of aminoacyl-tRNA synthetases using all-atom and coarse-grained simulations

Coarse-grained simulations have emerged as invaluable tools for studying conformational changes in biomolecules. To evaluate the effectiveness of computationally inexpensive coarse-grained models in studying global and local dynamics of large protein systems like aminoacyl-tRNA synthetases, we have performed coarse-grained normal mode analysis, as well as principle component analysis on trajectories of all-atom and coarse-grained molecular dynamics simulations for three aminoacyl-tRNA synthetases—Escherichia coli methionyl-tRNA synthetase, Thermus thermophilus leucyl-tRNA synthetase, and Enterococcus faecium prolyl-tRNA synthetase. In the present study, comparison of predicted dynamics based on B-factor and overlap calculations revealed that coarse-grained methods are comparable to the all-atom simulations in depicting the intrinsic global dynamics of the three enzymes. However, the principal component analyses of the motions obtained from the all-atom molecular dynamics simulations provide a superior description of the local fluctuations of these enzymes. In particular, the all-atom model was able to capture the functionally relevant substrate-induced dynamical changes in prolyl-tRNA synthetase. The alteration in the coupled dynamics between the catalytically important proline-binding loop and its neighboring structural elements due to substrate binding has been characterized and reported for the first time. Taken together, the study portrays comparable and contrasting situations in studying the functional dynamics of large multi-domain aminoacyl-tRNA synthetases using coarse-grained and all-atom simulation methods.

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Exploring the conformational transitions of biomolecular systems using a simple two-state anisotropic network model

Biomolecular conformational transitions are essential to biological functions. Most experimental methods report on the long-lived functional states of biomolecules, but information about the transition pathways between these stable states is generally scarce. Such transitions involve short-lived conformational states that are difficult to detect experimentally. For this reason, computational methods are needed to produce plausible hypothetical transition pathways that can then be probed experimentally. Here we propose a simple and computationally efficient method, called ANMPathway, for constructing a physically reasonable pathway between two endpoints of a conformational transition. We adopt a coarse-grained representation of the protein and construct a two-state potential by combining two elastic network models (ENMs) representative of the experimental structures resolved for the endpoints. The two-state potential has a cusp hypersurface in the configuration space where the energies from both the ENMs are equal. We first search for the minimum energy structure on the cusp hypersurface and then treat it as the transition state. The continuous pathway is subsequently constructed by following the steepest descent energy minimization trajectories starting from the transition state on each side of the cusp hypersurface. Application to several systems of broad biological interest such as adenylate kinase, ATP-driven calcium pump SERCA, leucine transporter and glutamate transporter shows that ANMPathway yields results in good agreement with those from other similar methods and with data obtained from all-atom molecular dynamics simulations, in support of the utility of this simple and efficient approach. Notably the method provides experimentally testable predictions, including the formation of non-native contacts during the transition which we were able to detect in two of the systems we studied. An open-access web server has been created to deliver ANMPathway results.

Many biomolecules are like tiny molecular machines that need to change their shapes and visit many states to perform their biological functions. For a complete molecular understanding of a biological process, one needs to have information on the relevant stable states of the system in question, as well as the pathways by which the system travels from one state to another. We report here an efficient computational method that uses the knowledge of experimental structures of a pair of stable states in order to construct an energetically favoravle pathway between them. We adopt a simple representation of the molecular system by replacing the atoms with beads connected by springs and constructing an energy function with two minima around the end-states. We searched for the structure with highest energy that the system is most likely to visit during the transition and created two paths starting from this structure and proceeding toward the end-states. The combined result of these two paths is the minimum energy pathway between the two stable states. We apply this method to study important structural changes in one enzyme and three large proteins that transport small molecules and ions across the cell membrane.

Computational approaches to mapping allosteric pathways

Allosteric signaling occurs when chemical and/or physical changes at an allosteric site alter the activity of a primary orthosteric site often many Ångströms distant. A number of recently developed computational techniques, including dynamical network analysis, novel topological and molecular dynamics methods, and hybrids of these methods, are useful for elucidating allosteric signaling pathways at the atomistic level. No single method prevails as best to identify allosteric signal propagation path(s), rather each has particular strengths in characterizing signals that occur over specific timescale ranges and magnitudes of conformational fluctuation. With continued improvement in accuracy and predictive power, these computational techniques aim to become useful drug discovery tools that will allow researchers to identify allostery critical residues for subsequent pharmacological targeting.