The intrinsic dynamics of enzymes plays a dominant role in determining the structural changes induced upon inhibitor binding

Explaining Conformational Diversity in Protein Families through Molecular Motions

Proteins play a central role in biological processes, and understanding their conformational variability is crucial for unraveling their functional mechanisms. Recent advancements in high-throughput technologies have enhanced our knowledge of protein structures, yet predicting their multiple conformational states and motions remains challenging. This study introduces Dimensionality Analysis for protein Conformational Exploration (DANCE) for a systematic and comprehensive description of protein families conformational variability. DANCE accommodates both experimental and predicted structures. It is suitable for analysing anything from single proteins to superfamilies. Employing it, we clustered all experimentally resolved protein structures available in the Protein Data Bank into conformational collections and characterized them as sets of linear motions. The resource facilitates access and exploitation of the multiple states adopted by a protein and its homologs. Beyond descriptive analysis, we assessed classical dimensionality reduction techniques for sampling unseen states on a representative benchmark. This work improves our understanding of how proteins deform to perform their functions and opens ways to a standardised evaluation of methods designed to sample and generate protein conformations.

MDFF_NM: Improved Molecular Dynamics Flexible Fitting into Cryo-EM Density Maps with a Multireplica Normal Mode-Based Search

Molecular Dynamics Flexible Fitting (MDFF) is a widely used tool to refine high-resolution structures into cryo-EM density maps. Despite many successful applications, MDFF is still limited by its high computational cost, overfitting, accuracy, and performance issues due to entrapment within wrong local minima. Modern ensemble-based MDFF tools have generated promising results in the past decade. In line with these studies, we present MDFF_NM, a stochastic hybrid flexible fitting algorithm combining Normal Mode Analysis (NMA) and simulation-based flexible fitting. Initial tests reveal that, besides accelerating the fitting process, MDFF_NM increases the diversity of fitting routes leading to the target, uncovering ensembles of conformations in closer agreement with experimental data. The potential integration of MDFF_NM with other existing methods and integrative modeling pipelines is also discussed.

Scalable computation of anisotropic vibrations for large macromolecular assemblies

The Normal Mode Analysis (NMA) is a standard approach to elucidate the anisotropic vibrations of macromolecules at their folded states, where low-frequency collective motions can reveal rearrangements of domains and changes in the exposed surface of macromolecules. Recent advances in structural biology have enabled the resolution of megascale macromolecules with millions of atoms. However, the calculation of their vibrational modes remains elusive due to the prohibitive cost associated with constructing and diagonalizing the underlying eigenproblem and the current approaches to NMA are not readily adaptable for efficient parallel computing on graphic processing unit (GPU). Here, we present eigenproblem construction and diagonalization approach that implements level-structure bandwidth-reducing algorithms to transform the sparse computation in NMA to a globally-sparse-yet-locally-dense computation, allowing batched tensor products to be most efficiently executed on GPU. We map, optimize, and compare several low-complexity Krylov-subspace eigensolvers, supplemented by techniques such as Chebyshev filtering, sum decomposition, external explicit deflation and shift-and-inverse, to allow fast GPU-resident calculations. The method allows accurate calculation of the first 1000 vibrational modes of some largest structures in PDB ( > 2.4 million atoms) at least 250 times faster than existing methods.

Multilevel superposition for deciphering the conformational variability of protein ensembles

The dynamics and variability of protein conformations are directly linked to their functions. Many comparative studies of X-ray protein structures have been conducted to elucidate the relevant conformational changes, dynamics and heterogeneity. The rapid increase in the number of experimentally determined structures has made comparison an effective tool for investigating protein structures. For example, it is now possible to compare structural ensembles formed by enzyme species, variants or the type of ligands bound to them. In this study, the author developed a multilevel model for estimating two covariance matrices that represent inter- and intra-ensemble variability in the Cartesian coordinate space. Principal component analysis using the two estimated covariance matrices identified the inter-/intra-enzyme variabilities, which seemed to be important for the enzyme functions, with the illustrative examples of cytochrome P450 family 2 enzymes and class A $\beta$-lactamases. In P450, in which each enzyme has its own active site of a distinct size, an active-site motion shared universally between the enzymes was captured as the first principal mode of the intra-enzyme covariance matrix. In this case, the method was useful for understanding the conformational variability after adjusting for the differences between enzyme sizes. The developed method is advantageous in small ensemble-size problems and hence promising for use in comparative studies on experimentally determined structures where ensemble sizes are smaller than those generated, for example, by molecular dynamics simulations.

Allosteric modulation of serotonin and dopamine transporters: New insights from computations and experiments

Human monoamine transporters (MATs) are critical to regulating monoaminergic neurotransmission by translocating their substrates from the synaptic space back into the presynaptic neurons. As such, their primary substrate binding site S1 has been targeted by a wide range of compounds for treating neuropsychiatric and neurodegenerative disorders including depression, ADHD, neuropathic pain, and anxiety disorders. We present here a comparative study of the structural dynamics and ligand-binding properties of two MATs, dopamine transporter (DAT) and serotonin transporter (SERT), with focus on the allosteric modulation of their transport function by drugs or substrates that consistently bind a secondary site S2, proposed to serve as an allosteric site. Our systematic analysis of the conformational space and dynamics of a dataset of 50 structures resolved for DAT and SERT in the presence of one or more ligands/drugs reveals the specific residues playing a consistent role in coordinating the small molecules bound to subsites S2-I and S2-II within S2, such as R476 and Y481 in dDAT and E494, P561, and F556 in hSERT. Further analysis reveals how DAT and SERT differ in their two principal modes of structural changes, PC1 and PC2. Notably, PC1 underlies the transition between outward- and inward-facing states of the transporters as well as their gating; whereas PC2 supports the rearrangements of TM helices near the S2 site. Finally, the examination of cross-correlations between structural elements lining the respective sites S1 and S2 point to the crucial role of coupled motions between TM6a and TM10. In particular, we note the involvement of hSERT residues F335 and G338, and E493-E494-T497 belonging to these two respective helices, in establishing the allosteric communication between S1 and S2. These results help understand the molecular basis of the action of drugs that bind to the S2 site of DAT or SERT. They also provide a basis for designing allosteric modulators that may provide better control of specific interactions and cellular pathways, rather than indiscriminately inhibiting the transporter by targeting its orthosteric site.

Convergence and equilibrium in molecular dynamics simulations

Molecular dynamics is a powerful tool that has been long used for the simulation of biomolecules. It complements experiments, by providing detailed information about individual atomic motions. But there is an essential and often overlooked assumption that, left unchecked, could invalidate any results from it: is the simulated trajectory long enough, so that the system has reached thermodynamic equilibrium, and the measured properties are converged? Previous studies showed mixed results in relation to this assumption. This has profound implications, as the resulting simulated trajectories may not be reliable in predicting equilibrium properties. Yet, this is precisely what most molecular dynamics studies do. So the question arises: are these studies even valid?Here, we present a thorough analysis of up to a hundred microseconds long trajectories, of several system with varying size, to probe the convergence of different structural, dynamical and cumulative properties, and elaborate on the relevance of the concept of equilibrium, and its physical and biological meaning. The results show that properties with the most biological interest tend to converge in multi-microsecond trajectories, although other properties-like transition rates to low probability conformations-may require more time.

Structural and pKa Estimation of the Amphipathic HR1 in SARS-CoV-2: Insights from Constant pH MD, Linear vs. Nonlinear Normal Mode Analysis

A comprehensive understanding of molecular interactions and functions is imperative for unraveling the intricacies of viral protein behavior and conformational dynamics during cellular entry. Focusing on the SARS-CoV-2 spike protein (SARS-CoV-2 sp), a Principal Component Analysis (PCA) on a subset comprising 131 A-chain structures in presence of various inhibitors was conducted. Our analyses unveiled a compelling correlation between PCA modes and Anisotropic Network Model (ANM) modes, underscoring the reliability and functional significance of low-frequency modes in adapting to diverse inhibitor binding scenarios. The role of HR1 in viral processing, both linear Normal Mode Analysis (NMA) and Nonlinear NMA were implemented. Linear NMA exhibited substantial inter-structure variability, as evident from a higher Root Mean Square Deviation (RMSD) range (7.30 Å), nonlinear NMA show stability throughout the simulations (RMSD 4.85 Å). Frequency analysis further emphasized that the energy requirements for conformational changes in nonlinear modes are notably lower compared to their linear counterparts. Using simulations of molecular dynamics at constant pH (cpH-MD), we successfully predicted the pKa order of the interconnected residues within the HR1 mutations at lower pH values, suggesting a transition to a post-fusion structure. The pKa determination study illustrates the profound effects of pH variations on protein structure. Key results include pKa values of 9.5179 for lys-921 in the D936H mutant, 9.50 for the D950N mutant, and a slightly higher value of 10.49 for the D936Y variant. To further understand the behavior and physicochemical characteristics of the protein in a biologically relevant setting, we also examine hydrophobic regions in the prefused states of the HR1 protein mutants D950N, D936Y, and D936H in our study. This analysis was conducted to ascertain the hydrophobic moment of the protein within a lipid environment, shedding light on its behavior and physicochemical properties in a biologically relevant context.

A small non-interface surface epitope in human IL18 mediates the dynamics and self-assembly of IL18-IL18BP heterodimers

Interleukin 18 (IL18) is a pro-inflammatory cytokine that modulates innate and adaptive immune responses. IL18 activity is tightly controlled by the constitutively secreted IL18 binding protein (IL18BP). PDB structures of human IL18 showed that a short stretch of amino acids between 68 and 81 adopted a disordered conformation in all IL18-IL18BP complexes while adopting a 3₁₀ helical structure in other IL18 structures, including the receptor complexes. The C74 of human IL18, which was reported to form a novel intermolecular disulfide bond in the human tetrameric assembly, is also located in this short epitope. These observations reflected the importance of this short surface epitope for the structure and dynamics of the IL18-IL18BP heterodimers. We have analyzed all known IL18-IL18BP complexes in the PDB by all-atom MD simulations. The analysis also included two computed complex models adopting a helical structure for the surface epitope. Heterodimer simulations showed a stabilizing impact of the small surface region at the helical form by reducing flexibility of the complex backbone. Analysis of the symmetry-related human IL18-IL18BP tetramer showed that the unfolding of this small surface region also contributed to the IL18-IL18BP stability through a completely exposed C74 sidechain to form an intermolecular disulfide bond in the self-assembled human IL18-IL18BP dimer. Our findings showed how the conformation of the short IL18 epitope between amino acids 68 and 81 would affect IL18 activity by mediating the intermolecular interactions of IL18.

Functional insight into Cordyceps militaris sugar transporters by structure modeling, network analysis and allosteric regulation

Insights into the structures, functions and dynamics of Cordyceps militaris (C. militaris) sugar transporters are necessary for understanding their versatile metabolic capability for fungal growth. The sequence-function relationship study of 85 C. militaris sugar transporters showed that there is a gap between phylogenetic-based subfamily classification and their functions. Beyond protein sequences, structural modeling and principal component analysis of the structural ensemble revealed the different folds of the Car and Org subfamilies. Performing channel detection and network analysis found that the Alp and Hex subfamilies can be specifically distinguished from others by the betweenness of channel residues. Signature dynamics analysis further suggested that the Hex subfamily demonstrates different dynamics, with high flexibility at the H1 region in TM11. Furthermore, the H1 region as an allosteric site was examined by network parameter calculations that guided allosteric pathways between this region and the channel cavity. Together with gene expression data of C. militaris, e.g., Hex06741 in the Hex subfamily, it was promisingly expressed when sugar utilization was altered. This work demonstrates an in silico framework for investigating C. militaris sugar transporters as an example case study of the allosteric activity of the Hex subfamily and can facilitate sugar transporter engineering design that can further optimize the preferable sugar utilization and fermentation process of C. militaris.

Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions

The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.

Mutually beneficial confluence of structure-based modeling of protein dynamics and machine learning methods

Proteins sample an ensemble of conformers under physiological conditions, having access to a spectrum of modes of motions, also called intrinsic dynamics. These motions ensure the adaptation to various interactions in the cell, and largely assist in, if not determine, viable mechanisms of biological function. In recent years, machine learning frameworks have proven uniquely useful in structural biology, and recent studies further provide evidence to the utility and/or necessity of considering intrinsic dynamics for increasing their predictive ability. Efficient quantification of dynamics-based attributes by recently developed physics-based theories and models such as elastic network models provides a unique opportunity to generate data on dynamics for training ML models towards inferring mechanisms of protein function, assessing pathogenicity, or estimating binding affinities.

Histone tail electrostatics modulate E2-E3 enzyme dynamics: a gateway to regulate ubiquitination machinery

BRCA1 (Breast Cancer-Associated Protein 1) is a human tumor suppressor that functions as an ubiquitin (Ub) ligase enzyme (E3) and plays a key role in genomic stability and DNA repair. Heterodimerization of BRCA1 with BARD1 (BRCA1-associated RING domain protein 1) is known to increase its Ub ligase activity and is important for its stability, and cooperative activation of UbcH5c (Ub conjugating enzyme (E2)). Recent studies demonstrate the importance of ubiquitination of the nucleosomal H2A C-terminal tail by BRCA1/BARD1-UbcH5c in which its mutations inhibit ubiquitination, predispose cells to chromosomal instability and greatly increase the likelihood of breast and ovarian cancer development. Due to the lack of molecular-level insight on the flexible and dis-ordered H2A C-tail, its ubiquitination mechanism by BRCA1/BARD1-UbcH5c and its function and relationship to cancer susceptibility remain elusive. Here, we use molecular dynamics simulations to provide molecular-level insights into the dynamics of the less-studied H2A C-tail and BRCA1/BARD1-UbcH5c on the nucleosome surface and their effect on ubiquitination. Our results precisely identify the key interactions and residues that trigger conformational transitions of BRCA1/BARD1-UbcH5c, and characterize the important role of histone electrostatics in their dynamics. We provide a mechanistic basis for the H2A C-tail lysine approach to UbcH5c and show the role of H2A C-tail and UbcH5c dynamics in lysine ubiquitination. Furthermore, our data demonstrate the potential for ubiquitination based on the lysine position of the C-tail. Altogether, the findings of this study provide unrevealed insights into the mechanism of H2A C-tail ubiquitination and help us understand the communication between Ub ligase/Ub conjugating enzymes (E3/E2) and nucleosome to regulate ubiquitination machinery, paving the way for the development of effective treatments for cancer and chronic pain.

MDexciteR: Enhanced Sampling Molecular Dynamics by Excited Normal Modes or Principal Components Obtained from Experiments

Molecular dynamics with excited normal modes (MDeNM) is an enhanced sampling method for exploring conformational changes in proteins with minimal biases. The excitation corresponds to injecting kinetic energy along normal modes describing intrinsic collective motions. Herein, we developed a new automated open-source implementation, MDexciteR (https://github.com/mcosta27/MDexciteR), enabling the integration of MDeNM with two commonly used simulation programs with GPU support. Second, we generalized the method to include the excitation of principal components calculated from experimental ensembles. Finally, we evaluated whether the use of coarse-grained normal modes calculated with elastic network representations preserved the performance and accuracy of the method. The advantages and limitations of these new approaches are discussed based on results obtained for three different protein test cases: two globular and a protein/membrane system.

Fragment-based inhibitor design for SARS-CoV2 main protease

COVID-19 disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV2) has resulted in tremendous loss of lives across the world and is continuing to do so. Extensive work is under progress to develop inhibitors which can prevent the disease by arresting the virus in its life cycle. One such way is by targeting the main protease of the virus which is crucial for the cleavage and conversion of polyproteins into functional units of polypeptides. In this endeavor, our effort was to identify hit molecule inhibitors for SARS-CoV2 main protease using fragment-based drug discovery (FBDD), based on the available crystal structure of chromene-based inhibitor (PDB_ID: 6M2N). The designed molecules were validated by molecular docking and molecular dynamics simulations. The stability of the complexes was further assessed by calculating their binding free energies, normal mode analysis, mechanical stiffness, and principal component analysis.

Fragment screening and structural analyses highlight the ATP-assisted ligand binding for inhibitor discovery against type 1 methionyl-tRNA synthetase

Methionyl-tRNA synthetase (MetRS) charges tRNAMet with l-methionine (L-Met) to decode the ATG codon for protein translation, making it indispensable for all cellular lives. Many gram-positive bacteria use a type 1 MetRS (MetRS1), which is considered a promising antimicrobial drug target due to its low sequence identity with human cytosolic MetRS (HcMetRS, which belongs to MetRS2). Here, we report crystal structures of a representative MetRS1 from Staphylococcus aureus (SaMetRS) in its apo and substrate-binding forms. The connecting peptide (CP) domain of SaMetRS differs from HcMetRS in structural organization and dynamic movement. We screened 1049 chemical fragments against SaMetRS preincubated with or without substrate ATP, and ten hits were identified. Four cocrystal structures revealed that the fragments bound to either the L-Met binding site or an auxiliary pocket near the tRNA CCA end binding site of SaMetRS. Interestingly, fragment binding was enhanced by ATP in most cases, suggesting a potential ATP-assisted ligand binding mechanism in MetRS1. Moreover, co-binding with ATP was also observed in our cocrystal structure of SaMetRS with a class of newly reported inhibitors that simultaneously occupied the auxiliary pocket, tRNA site and L-Met site. Our findings will inspire the development of new MetRS1 inhibitors for fighting microbial infections.

High-pressure crystallography shows noble gas intervention into protein-lipid interaction and suggests a model for anaesthetic action

In this work we examine how small hydrophobic molecules such as inert gases interact with membrane proteins (MPs) at a molecular level. High pressure atmospheres of argon and krypton were used to produce noble gas derivatives of crystals of three well studied MPs (two different proton pumps and a sodium light-driven ion pump). The structures obtained using X-ray crystallography showed that the vast majority of argon and krypton binding sites were located on the outer hydrophobic surface of the MPs – a surface usually accommodating hydrophobic chains of annular lipids (which are known structural and functional determinants for MPs). In conformity with these results, supplementary in silico molecular dynamics (MD) analysis predicted even greater numbers of argon and krypton binding positions on MP surface within the bilayer. These results indicate a potential importance of such interactions, particularly as related to the phenomenon of noble gas-induced anaesthesia.

Noble gases are known to interact with proteins and can be good anaesthetics in hyperbaric conditions. This study identifies argon and krypton binding sites on membrane proteins and proposes as a hypothesis that noble gases, by altering protein/lipid contacts, may affect protein function.

Optimized Elastic Network Models With Direct Characterization of Inter-Residue Cooperativity for Protein Dynamics

The elastic network models (ENMs)are known as representative coarse-grained models to capture essential dynamics of proteins. Due to simple designs of the force constants as a decay with spatial distances of residue pairs in many previous studies, there is still much room for the improvement of ENMs. In this article, we directly computed the force constants with the inverse covariance estimation using a ridge-type operater for the precision matrix estimation (ROPE)on a large-scale set of NMR ensembles. Distance-dependent statistical analyses on the force constants were further comprehensively performed in terms of several paired types of sequence and structural information, including secondary structure, relative solvent accessibility, sequence distance and terminal. Various distinguished distributions of the mean force constants highlight the structural and sequential characteristics coupled with the inter-residue cooperativity beyond the spatial distances. We finally integrated these structural and sequential characteristics to build novel ENM variations using the particle swarm optimization for the parameter estimation. The considerable improvements on the correlation coefficient of the mean-square fluctuation and the mode overlap were achieved by the proposed variations when compared with traditional ENMs. This study opens a novel way to develop more accurate elastic network models for protein dynamics.

Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods

Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.

Elucidating the molecular basis of spontaneous activation in an engineered mechanosensitive channel

Mechanosensitive channel of large conductance (MscL) detects and responds to changes in the pressure profile of cellular membranes and transduces the mechanical energy into electrical and/or chemical signals. MscL can be activated using ultrasonic or chemical activation methods to improve the absorption of medicines and bioactive compounds into cells. However, re-engineering chemical signals such as pH change can trigger channel activation in MscL. This study elucidates the activation mechanism of an engineered MscL at an atomic level through a combination of equilibrium and non-equilibrium (NE) molecular dynamics (MD) simulations. Comparing the wild-type (WT) and engineered MscL activation processes suggests that the two systems are likely associated with different active states and different transition pathways. These findings indicate that (1) periplasmic loops play a key role in the activation process of MscL, (2) the loss of various backbone-backbone hydrogen bonds and salt bridge interactions in the engineered MscL channel causes the spontaneous opening of the channel, and (3) the most significant interactions lost during the activation process are between the transmembrane helices 1 and 2 in engineered MscL channel. The orientation-based biasing approach for producing and optimizing an open MscL model used in this work is a promising way to characterize unknown protein functional states and investigate the activation processes in ion channels and transmembrane proteins in general. This work paves the way for a computational framework for engineering more efficient pH-sensing mechanosensitive channels.

Mechanisms of influence of the microtubule over-stabilizing ligands on the structure and intrinsic dynamics of α,β-Tubulin

The intervention into the cell cycle progression by administering microtubule over-stabilizing ligands that arrest the mitotic cell division by preventing spindle dissociation, is a promising strategy to fight against cancers. The building blocks of the microtubules and the spindles, i.e. the α,β-tubulin dimer, upon binding of such ligands, stay more comfortably in the microtubular multimeric form; the phenomenon of which is the key to the said over-stabilization. Using two such over-stabilizing ligands, Taxol and Taxotere, the present work reports the collective changes that these ligands induce on the structure and dynamics of the α,β-tubulin dimer which could be reconciled as the molecular basis of the over-stabilization of the microtubules; the trends have been found to be statistically significant across all independent calculations on them. The ligand binding increases the coherence between the residue communities of the two opposite faces of the β-subunit, which in a periodic arrangement in microtubule are knwon to form intermolecular contact with each other. This is likely to create an indirect cooperativity between those structural regions and this is a consequence of the reshuffling of the internal network of interactions upon ligand binding. Such reorganizations are also complemented by the increased contributions of the softer modes of the intrinsic dynamics more, which is likely to increase the plasticity of the system favourable for making structural adjustments in a multimer. Further, the ligands are able to compensate the drawback of lacking one phosphate group in protein-GDP interactions compared to the same for protein-GTP and this is in agreement with the hints form the earlier reports. The findings form a mechanistic basis of the enhanced capacity of the α,β-tubulin dimer to get more favourably accommodated into the microtubule superstructure upon binding either of Taxol and Taxotere.

Dynamics of Post-Translational Modification Inspires Drug Design in the Kinase Family

Post-translational modification (PTM) on protein plays important roles in the regulation of cellular function and disease pathogenesis. The systematic analysis of PTM dynamics presents great opportunities to enlarge the target space by PTM allosteric regulation. Here, we presented a framework by integrating the sequence, structural topology, and particular dynamics features to characterize the functional context and druggabilities of PTMs in the well-known kinase family. The machine learning models with these biophysical features could successfully predict PTMs. On the other hand, PTMs were identified to be significantly enriched in the reported allosteric pockets and the allosteric potential of PTM pockets were thus proposed through these biophysical features. In the end, the covalent inhibitor DC-Srci-6668 targeting the PTM pocket in c-Src kinase was identified, which inhibited the phosphorylation and locked c-Src in the inactive state. Our findings represent a crucial step toward PTM-inspired drug design in the kinase family.

Mechanistic Picture for Chemomechanical Coupling in a Bacterial Proton-Coupled Oligopeptide Transporter from Streptococcus Thermophilus

Proton-coupled oligopeptide transporters (POTs) use the proton electrochemical gradient to transport peptides across the cell membrane. Despite the significant biological and biomedical relevance of these proteins, a detailed mechanistic picture for chemomechanical couplings involved in substrate/proton transport and protein structural changes is missing. Therefore, we performed microsecond-level molecular dynamics simulations of bacterial POT PepT_St, which shares ∼80% sequence identity with the human POT, PepT1, in the substrate-binding region. Three different conformational states of PepT_St were simulated, including (i) occluded, apo, (ii) inward-facing, apo, and (iii) inward-facing_occluded, Leu-Ala bound. We propose that the interaction of R33 with E299 and E300 acts as a conformational switch (i.e., to trigger the conformational change from an inward- to outward-facing state) in the substrate transport. Additionally, we propose that E299 and E400 disengage from interacting with the substrate either through protonation or through coordination with a cation for the substrate to get transported. This study provides clues to understand the chemomechanical couplings in POTs and paves the way to decipher the molecular-level underpinnings of the structure-function relationship in this important family of transporters.

ClustENMD: Efficient sampling of biomolecular conformational space at atomic resolution

Summary

Efficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace.

Availability and implementation

ClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy.

Supplementary information

Supplementary data are available at Bioinformatics online.

Data-Driven Ensemble Docking to Map Molecular Interactions of Steroid Analogs with Hepatic Organic Anion Transporting Polypeptides

Hepatic organic anion transporting polypeptides—OATP1B1, OATP1B3, and OATP2B1—are expressed at the basolateral membrane of hepatocytes, being responsible for the uptake of a wide range of natural substrates and structurally unrelated pharmaceuticals. Impaired function of hepatic OATPs has been linked to clinically relevant drug–drug interactions leading to altered pharmacokinetics of administered drugs. Therefore, understanding the commonalities and differences across the three transporters represents useful knowledge to guide the drug discovery process at an early stage. Unfortunately, such efforts remain challenging because of the lack of experimentally resolved protein structures for any member of the OATP family. In this study, we established a rigorous computational protocol to generate and validate structural models for hepatic OATPs. The multistep procedure is based on the systematic exploration of available protein structures with shared protein folding using normal-mode analysis, the calculation of multiple template backbones from elastic network models, the utilization of multiple template conformations to generate OATP structural models with various degrees of conformational flexibility, and the prioritization of models on the basis of enrichment docking. We employed the resulting OATP models of OATP1B1, OATP1B3, and OATP2B1 to elucidate binding modes of steroid analogs in the three transporters. Steroid conjugates have been recognized as endogenous substrates of these transporters. Thus, investigating this data set delivers insights into mechanisms of substrate recognition. In silico predictions were complemented with in vitro studies measuring the bioactivity of a compound set on OATP expressing cell lines. Important structural determinants conferring shared and distinct binding patterns of steroid analogs in the three transporters have been identified. Overall, this comparative study provides novel insights into hepatic OATP-ligand interactions and selectivity. Furthermore, the integrative computational workflow for structure-based modeling can be leveraged for other pharmaceutical targets of interest.

Different Single-Enzyme Conformational Dynamics upon Binding Hydrolyzable or Nonhydrolyzable Ligands

Single-molecule measurements of protein dynamics help unveil the complex conformational changes and transitions that occur during ligand binding and catalytic processes. Using high-resolution single-molecule nanocircuit techniques, we have investigated differences in the conformational dynamics and transitions of lysozyme interacting with three ligands: peptidoglycan substrate, substrate-based chitin analogue, and indole derivative inhibitors. While processing peptidoglycan, lysozyme followed one of the two mechanistic pathways for the hydrolysis of the glycosidic bonds: a concerted mechanism inducing direct conformational changes from open to fully closed conformations or a nonconcerted mechanism involving transient pauses in intermediate conformations between the open and closed conformations. In the presence of either chitin or an indole inhibitor, lysozyme was unable to access the fully closed conformation where catalysis occurs. Instead, lysozymes' conformational closures terminated at slightly closed, "excited" conformations that were approximately one-quarter of the full hinge-bending range. With the indole inhibitor, lysozyme reached this excited conformation in a single step without any evidence of rate-liming intermediates, but the same conformational motions with chitin involved three hidden, intermediate processes and features similar to the nonconcerted peptidoglycan mechanism. The similarities suggest that these hidden processes involve attempts to accommodate imperfectly aligned polysaccharides in the active site. The results provide a detailed glimpse of the enzyme-ligand interplay at the crux of molecular recognition, enzyme specificity, and catalysis.

Physical Constraints on Epistasis

Living systems evolve one mutation at a time, but a single mutation can alter the effect of subsequent mutations. The underlying mechanistic determinants of such epistasis are unclear. Here, we demonstrate that the physical dynamics of a biological system can generically constrain epistasis. We analyze models and experimental data on proteins and regulatory networks. In each, we find that if the long-time physical dynamics is dominated by a slow, collective mode, then the dimensionality of mutational effects is reduced. Consequently, epistatic coefficients for different combinations of mutations are no longer independent, even if individually strong. Such epistasis can be summarized as resulting from a global nonlinearity applied to an underlying linear trait, that is, as global epistasis. This constraint, in turn, reduces the ruggedness of the sequence-to-function map. By providing a generic mechanistic origin for experimentally observed global epistasis, our work suggests that slow collective physical modes can make biological systems evolvable.

Identification of potential allosteric binding sites in cathepsin K based on intramolecular communication

Network theory methods and molecular dynamics (MD) simulations are accepted tools to study allosteric regulation. Indeed, dynamic networks built upon correlation analysis of MD trajectories provide detailed information about communication paths between distant sites. In this context, we aimed to understand whether the efficiency of intramolecular communication could be used to predict the allosteric potential of a given site. To this end, we performed MD simulations and network theory analyses in cathepsin K (catK), whose allosteric sites are well defined. To obtain a quantitative measure of the efficiency of communication, we designed a new protocol that enables the comparison between properties related to ensembles of communication paths obtained from different sites. Further, we applied our strategy to evaluate the allosteric potential of different catK cavities not yet considered for drug design. Our predictions of the allosteric potential based on intramolecular communication correlate well with previous catK experimental and theoretical data. We also discuss the possibility of applying our approach to other proteins from the same family.

Towards gaining sight of multiscale events: utilizing network models and normal modes in hybrid methods

With the explosion of normal mode analyses (NMAs) based on elastic network models (ENMs) in the last decade, and the proven precision of MD simulations for visualizing interactions at atomic scale, many hybrid methods have been proposed in recent years. These aim at exploiting the best of both worlds: the atomic precision of MD that often fall short of exploring time and length scales of biological interest, and the capability of ENM-NMA to predict the cooperative and often functional rearrangements of large structures and assemblies, albeit at low resolution. We present an overview of recent progress in the field with examples of successful applications highlighting the utility of such hybrid methods and pointing to emerging future directions guided by advances in experimental characterization of biomolecular systems structure and dynamics.

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation

Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.

Enhanced metastable state models of TAM kinase binding to cabozantinib explains the dynamic nature of receptor tyrosine kinases

Receptor tyrosine kinases (RTKs) are essential proteins in the regulation of cell signaling. Tyro3, Axl and Mer are members of TAM RTKs and are overexpressed in several cancer forms. Kinase inhibitors such as cabozantinib, foretinib are reported to inhibit TAM kinases at nanomolar concentrations. The atomistic details of structure and mechanism of functional regulation is required to understand their normal physiological process and when bound to an inhibitor. The docking of cabozantinib into the active state conformations of TAM kinases (crystal structure and computational models) revealed the best binding pose and the complex formation that is mediated through non-bonding interactions involving the hinge region residues. The alterations in the conformations and the regions of flexibility in apo and complexed TAM kinases as a course of time are studied using 250 ns molecular dynamics (MD) simulations. The post-MD trajectory analysis using Python libraries like ProDy, MDTraj and PyEMMA revealed encrypted protein dynamic motions in active kinetic metastable states. Comparison between Principal component analysis and Anisotropic mode analysis deciphered structural residue interactions and salt bridge contacts between apo and inhibitor bound TAM kinases. Various structural changes occurred in αC-helix and activation loop involving hydrogen bonding between residues from Lys-(β3 sheet), Glu-(αC-helix) and Asp-(DFG-motif) resulting in higher RMSD. Mechanical stiffness plots revealed that similar regions in apo and cabozantinib bound Axl fluctuated during MD simulations whereas different regions in Tyro3 and Mer kinases. The residue interaction network plots revealed important salt bridges that lead to constrained domain motions in the TAM kinases.Communicated by Ramaswamy H. Sarma.

Modulation of Toroidal Proteins Dynamics in Favor of Functional Mechanisms upon Ligand Binding

Toroidal proteins serve as molecular machines and play crucial roles in biological processes such as DNA replication and RNA transcription. Despite progress in the structural characterization of several toroidal proteins, we still lack a mechanistic understanding of the significance of their architecture, oligomerization states, and intermolecular interactions in defining their biological function. In this work, we analyze the collective dynamics of toroidal proteins with different oligomerization states, namely, dimeric and trimeric DNA sliding clamps, nucleocapsid proteins (4-, 5-, and 6-mers) and Trp RNA-binding attenuation proteins (11- and 12-mers). We observe common global modes, among which cooperative rolling stands out as a mechanism enabling DNA processivity, and clamshell motions as those underlying the opening/closure of the sliding clamps. Alterations in global dynamics due to complexation with DNA or the clamp loader are shown to assist in enhancing motions to enable robust function. The analysis provides new insights into the differentiation and enhancement of functional motions upon intersubunit and intermolecular interactions.

Opposites Attract: Escherichia coli Heptosyltransferase I Conformational Changes Induced by Interactions between the Substrate and Positively Charged Residues

Gram-negative bacterial viability is greatly reduced by the disruption of heptose sugar addition during the biosynthesis of lipopolysaccharide (LPS), an important bacterial outer membrane component. Heptosyltransferase I (HepI), a member of the GT-B structural subclass of glycosyltransferases, is therefore an essential enzyme for the biosynthesis of the LPS. The disruption of HepI also increases the susceptibility of bacteria to hydrophobic antibiotics, making HepI a potential target for drug development. In this work, the structural and dynamic properties of the catalytic cycle of HepI are explored. Previously, substrate-induced stabilization of HepI was observed and hypothesized to be assisted by interactions between the substrate and residues located on dynamic loops. Herein, positively charged amino acids were probed to identify binding partners of the negatively charged phosphates and carboxylates of Kdo₂-lipid A and its analogues. Mutant enzymes were characterized to explore changes in enzymatic activities and protein stability. Molecular modeling of HepI in the presence and absence of ligands was then performed with the wild type and mutant enzyme to allow determination of the relative change in substrate binding affinity resulting from each mutation. Together, these studies suggest that multiple residues are involved in mediating substrate binding, and a lack of additivity of these effects illustrates the functional redundancy of these binding interactions. The redundancy of residues mediating conformational transitions in HepI illustrates the evolutionary importance of these structural rearrangements for catalysis. This work enhances the understanding of HepI's protein dynamics and mechanism and is a model for improving our understanding of glycosyltransferase enzymes.

Molecular Determinants for the Activation/Inhibition of Bak Protein by BH3 Peptides

Apoptosis is a key cell death pathway in mammalian cells. Understanding this process and its regulation has been a subject of study in the last three decades. Members of the Bcl-2 family of proteins are involved in the regulation of apoptosis through mitochondrial poration with the subsequent initiation of apoptosis. Deregulation of proapoptotic proteins contributes to the progression of many tumor processes. Understanding how these pore-forming Bcl-2 proteins Bak and Bax are activated is key to find new anticancer treatments. As no drug capable of activating Bak has been disclosed yet, the study of the structural features of BH3 peptides-known as Bak activators-relevant for binding along with its binding energy decomposition analysis, becomes essential for designing novel small-molecule mimics of BH3. Interestingly, a BH3 Bim analogue-inactivating Bak has recently been discovered, opening a question on the molecular features that determine the functions of BH3 peptides. Therefore, the present work is aimed at understanding the way BH3 peptides activate or inactivate Bak in order to identify differential structural features that can be used in drug design. For this purpose, complexes of Bak with an activator and an inhibitor have been subjected to a molecular dynamics study. Structural differences were assessed by means of the fluctuations of the corresponding principal components. Moreover, the MMPB/GBSA approach was used to compute the binding free energy of the diverse complexes to identify those residues of the BH3 peptide that exhibit the larger contributions to complex formation. The results obtained in this work show differences between activators and inhibitors, both in structural and energetic terms, which can be used in the design of new molecules that can activate or inactivate proapoptotic Bak.

Exploring Conformational Change of Adenylate Kinase by Replica Exchange Molecular Dynamic Simulation

Replica exchange molecular dynamics (REMD) simulation is a popular enhanced sampling method that is widely used for exploring the atomic mechanism of protein conformational change. However, the requirement of huge computational resources for REMD, especially with the explicit solvent model, largely limits its application. In this study, the availability and efficiency of a variant of velocity-scaling REMD (vsREMD) was assessed with adenylate kinase as an example. Although vsREMD achieved results consistent with those from conventional REMD and experimental studies, the number of replicas required for vsREMD (30) was much less than that for conventional REMD (80) to achieve a similar acceptance rate (∼0.2), demonstrating high efficiency of vsREMD to characterize the protein conformational change and associated free-energy profile. Thus, vsREMD is a highly efficient approach for studying the large-scale conformational change of protein systems.

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.

An Efficient Timer and Sizer of Biomacromolecular Motions

Life ticks as fast as how proteins move. Computationally expensive molecular dynamics simulation has been the only theoretical tool to gauge the time and sizes of these motions, though barely to their slowest ends. Here, we convert a computationally cheap elastic network model (ENM) into a molecular timer and sizer to gauge the slowest functional motions of structured biomolecules. Quasi-harmonic analysis, fluctuation profile matching, and the Wiener-Khintchine theorem are used to define the "time periods," t, for anharmonic principal components (PCs), which are validated by nuclear magnetic resonance (NMR) order parameters. The PCs with their respective "time periods" are mapped to the eigenvalues (λ_ENM) of the corresponding ENM modes. Thus, the power laws t(ns) = 56.1λ_ENM^-1.6 and σ²(Ų) = 32.7λ_ENM^-3.0 can be established allowing the characterization of the timescales of NMR-resolved conformers, crystallographic anisotropic displacement parameters, and important ribosomal motions, as well as motional sizes of the latter.

Mechanical properties of tubulin intra- and inter-dimer interfaces and their implications for microtubule dynamic instability

Thirteen tubulin protofilaments, made of αβ-tubulin heterodimers, interact laterally to produce cytoskeletal microtubules. Microtubules exhibit the striking property of dynamic instability, manifested in their intermittent growth and shrinkage at both ends. This behavior is key to many cellular processes, such as cell division, migration, maintenance of cell shape, etc. Although assembly and disassembly of microtubules is known to be linked to hydrolysis of a guanosine triphosphate molecule in the pocket of β-tubulin, detailed mechanistic understanding of corresponding conformational changes is still lacking. Here we take advantage of the recent generation of in-microtubule structures of tubulin to examine the properties of protofilaments, which serve as important microtubule assembly and disassembly intermediates. We find that initially straight tubulin protofilaments, relax to similar non-radially curved and slightly twisted conformations. Our analysis further suggests that guanosine triphosphate hydrolysis primarily affects the flexibility and conformation of the inter-dimer interface, without a strong impact on the shape or flexibility of αβ-heterodimer. Inter-dimer interfaces are significantly more flexible compared to intra-dimer interfaces. We argue that such a difference in flexibility could be key for distinct stability of the plus and minus microtubule ends. The higher flexibility of the inter-dimer interface may have implications for development of pulling force by curving tubulin protofilaments during microtubule disassembly, a process of major importance for chromosome motions in mitosis.

Monoamine transporters: structure, intrinsic dynamics and allosteric regulation

Monoamine transporters (MATs) regulate neurotransmission via the reuptake of dopamine, serotonin and norepinephrine from extra-neuronal regions and thus maintain neurotransmitter homeostasis. As targets of a wide range of compounds, including antidepressants, substances of abuse and drugs for neuropsychiatric and neurodegenerative disorders, their mechanism of action and their modulation by small molecules have long been of broad interest. Recent advances in the structural characterization of dopamine and serotonin transporters have opened the way for structure-based modeling and simulations, which, together with experimental data, now provide mechanistic understanding of their transport function and interactions. Here we review recent progress in the elucidation of the structural dynamics of MATs and their conformational landscape and transitions, as well as allosteric regulation mechanisms.

Toward understanding calmodulin plasticity by molecular dynamics

Aim: Calmodulin interacts in many different ways with its ligands. We aim to shed light on its plasticity analyzing the changes followed by the linker region and the relative position of the lobes using conventional molecular dynamics, accelerated MD and scaled MD (sMD). Materials & methods: Three different structures of calmodulin are compared, obtaining a total of 2.5 μs of molecular dynamics, which have been analyzed using the principal component analysis and clustering methodologies. Results: sMD simulations reach conformations that conventional molecular dynamics is not able to, without compromising the stability of the protein. On the other hand, accelerated MD requires optimization of the setup parameters to be useful. Conclusion: sMD is useful to study flexible proteins, highlighting those factors that justify its promiscuity.

Characterization of Differential Dynamics, Specificity, and Allostery of Lipoxygenase Family Members

Accurate modeling of structural dynamics of proteins and their differentiation across different species can help us understand generic mechanisms of function shared by family members and the molecular basis of the specificity of individual members. We focused here on the family of lipoxygenases, enzymes that catalyze lipid oxidation, the mammalian and bacterial structures of which have been elucidated. We present a systematic method of approach for characterizing the sequence, structure, dynamics, and allosteric signaling properties of these enzymes using a combination of structure-based models and methods and bioinformatics tools applied to a data set of 88 structures. The analysis elucidates the signature dynamics of the lipoxygenase family and its differentiation among members, as well as key sites that enable its adaptation to specific substrate binding and allosteric activity.

Coarse-Grained Simulation of Full-Length Integrin Activation

Integrin conformational dynamics are critical to their receptor and signaling functions in many cellular processes, including spreading, adhesion, and migration. However, assessing integrin conformations is both experimentally and computationally challenging because of limitations in resolution and dynamic sampling. Thus, structural changes that underlie transitions between conformations are largely unknown. Here, focusing on integrin αvβ₃, we developed a modified form of the coarse-grained heterogeneous elastic network model (hENM), which allows sampling conformations at the onset of activation by formally separating local fluctuations from global motions. Both local fluctuations and global motions are extracted from all-atom molecular dynamics simulations of the full-length αvβ₃ bent integrin conformer, but whereas the former are incorporated in the hENM as effective harmonic interactions between groups of residues, the latter emerge by systematically identifying and treating weak interactions between long-distance domains with flexible and anharmonic connections. The new hENM model allows integrins and single-point mutant integrins to explore various conformational states, including the initiation of separation between α- and β-subunit cytoplasmic regions, headpiece extension, and legs opening.

Druggability Simulations and X-Ray Crystallography Reveal a Ligand-Binding Site in the GluA3 AMPA Receptor N-Terminal Domain

Ionotropic glutamate receptors (iGluRs) mediate the majority of excitatory neurotransmission in the brain. Their dysfunction is implicated in many neurological disorders, rendering iGluRs potential drug targets. Here, we performed a systematic analysis of the druggability of two major iGluR subfamilies, using molecular dynamics simulations in the presence of drug-like molecules. We demonstrate the applicability of druggability simulations by faithfully identifying known agonist and modulator sites on AMPA receptors (AMPARs) and NMDA receptors. Simulations produced the expected allosteric changes of the AMPAR ligand-binding domain in response to agonist. We also identified a novel ligand-binding site specific to the GluA3 AMPAR N-terminal domain (NTD), resulting from its unique conformational flexibility that we explored further with crystal structures trapped in vastly different states. In addition to providing an in-depth analysis into iGluR NTD dynamics, our approach identifies druggable sites and permits the determination of pharmacophoric features toward novel iGluR modulators.

Sensory Rhodopsin I and Sensory Rhodopsin II Form Trimers of Dimers in Complex with their Cognate Transducers

Archaeal photoreceptors consist of sensory rhodopsins in complex with their cognate transducers. After light excitation, a two-component signaling chain is activated, which is homologous to the chemotactic signaling cascades in enterobacteria. The latter system has been studied in detail. From structural and functional studies, a picture emerges which includes stable signaling complexes, which assemble to receptor arrays displaying hexagonal structural elements. At this higher order structural level, signal amplification and sensory adaptation occur. Here, we describe electron microscopy data, which show that also the archaeal phototaxis receptors sensory rhodopsin I and II in complex with their cognate transducers can form hexagonal lattices even in the presence of a detergent. This result could be confirmed by molecular dynamics calculations, which revealed similar structural elements. Calculations of the global modes of motion displayed one mode, which resembles the "U"-"V" transition of the NpSRII:NpHtrII complex, which was previously argued to represent a functionally relevant global conformational change accompanying the activation process [Ishchenko et al. (2013) J. Photochem. Photobiol. B 123, 55-58]. A model of cooperativity at the transmembrane level is discussed.

Flexibility enables to discriminate between ligands: Lessons from structural ensembles of Bcl-xl and Mcl-1

The proteins of Bcl-2 family, which are promising anti-cancer-drug targets, have substantial similarity in primary sequence and share homologous domains as well as similar structural folds. In spite of similarities in sequence and structures, the members of its pro- and anti- apoptotic subgroups form complexes with different type of partners with discriminating binding affinities. Understanding the origin of this discrimination is very important for designing ligands that can either selectively target a protein or could be made broad ranged as necessary. Using principal component analysis (PCA) of the available structures and from the analysis of the evolution of the binding pocket residues, the correlation has been investigated considering two important anti-apoptotic protein Bcl-xl and Mcl-1, which serve as two ideal representatives of this family. The flexibility of the receptor enables them to discriminate between the ligands or the binding partners. It has been observed that although Bcl-xl and Mcl-1 are classified as homologous proteins, through the course of evolution the binding pocket residues are highly conserved for Bcl-xl; whereas they have been substituted frequently in Mcl-1. The investigation has revealed that the Bcl-xl can adjust the backbone conformation of the binding pocket residues to a larger extent to complement with the shape of different binding partners whereas the Mcl-1 shows more variation in the side chain conformation of binding pocket residues for the same purpose.

Free-energy simulations reveal molecular mechanism for functional switch of a DNA helicase

Helicases play key roles in genome maintenance, yet it remains elusive how these enzymes change conformations and how transitions between different conformational states regulate nucleic acid reshaping. Here, we developed a computational technique combining structural bioinformatics approaches and atomic-level free-energy simulations to characterize how the Escherichia coli DNA repair enzyme UvrD changes its conformation at the fork junction to switch its function from unwinding to rezipping DNA. The lowest free-energy path shows that UvrD opens the interface between two domains, allowing the bound ssDNA to escape. The simulation results predict a key metastable 'tilted' state during ssDNA strand switching. By simulating FRET distributions with fluorophores attached to UvrD, we show that the new state is supported quantitatively by single-molecule measurements. The present study deciphers key elements for the 'hyper-helicase' behavior of a mutant and provides an effective framework to characterize directly structure-function relationships in molecular machines.