Minimum Free Energy Path of Ligand-Induced Transition in Adenylate Kinase

Large-scale conformational changes in proteins involve barrier-crossing transitions on the complex free energy surfaces of high-dimensional space. Such rare events cannot be efficiently captured by conventional molecular dynamics simulations. Here we show that, by combining the on-the-fly string method and the multi-state Bennett acceptance ratio (MBAR) method, the free energy profile of a conformational transition pathway in Escherichia coli adenylate kinase can be characterized in a high-dimensional space. The minimum free energy paths of the conformational transitions in adenylate kinase were explored by the on-the-fly string method in 20-dimensional space spanned by the 20 largest-amplitude principal modes, and the free energy and various kinds of average physical quantities along the pathways were successfully evaluated by the MBAR method. The influence of ligand binding on the pathways was characterized in terms of rigid-body motions of the lid-shaped ATP-binding domain (LID) and the AMP-binding (AMPbd) domains. It was found that the LID domain was able to partially close without the ligand, while the closure of the AMPbd domain required the ligand binding. The transition state ensemble of the ligand bound form was identified as those structures characterized by highly specific binding of the ligand to the AMPbd domain, and was validated by unrestrained MD simulations. It was also found that complete closure of the LID domain required the dehydration of solvents around the P-loop. These findings suggest that the interplay of the two different types of domain motion is an essential feature in the conformational transition of the enzyme

パスサンプリングを使った分子動力学とベイズ推定

要旨あり生体高分子の揺らぎとダイナミクス－シミュレーションと実験の統計解析－研究詳

Kinazy adenylanowe człowieka – klasyfikacja, budowa oraz znaczenie w fizjologii i patologii

Kinazy adenylanowe (AK, EC 2.7.4.3) to powszechnie występujące fosfotransferazy, katalizujące odwracalną reakcję przeniesienia wysokoenergetycznych grup β- i γ-fosforanowych między nukleotydami. Wszystkie sklasyfikowane AK wykazują podobny plan budowy: zawierają dużą centralną domenę CORE, domeny wiążące monofosforan i trifosforan nukleozydu (NMPbd i NTPbd) oraz domenę LID. Analizując podobieństwo sekwencji aminokwasowej u człowieka, zidentyfikowano aż dziewięć izoenzymów AK, charakteryzujących się różną lokalizacją narządowo-tkankową i subkomórkową. Spośród tych kinaz tylko dwie: AK1 i AK2, spełniają kryterium strukturalne i funkcjonalne, wykazując najwyższe powinowactwo do nukleotydów adeninowych i wykorzystując tylko AMP lub dAMP w roli akceptora reszty fosforanowej. Poszczególne izoenzymy AK biorą udział w utrzymaniu homeostazy nukleotydowej, monitorują zaburzenia ładunku energetycznego komórki, dostarczają wysokoenergetycznych substratów niezbędnych do regulowania funkcji kanałów i transporterów oraz zewnątrzkomórkowvch ligandów receptorów nukleotydowych P2 w dużych, regulacyjno-transportowych kompleksach białkowych. W stanach patologicznych organizmu mogą przejmować funkcje innych kinaz, zastępując np. kinazę kreatynową w niedotlenionym mięśniu sercowym. Ukierunkowana mutageneza oraz badania genetyczne chorób, takich jak aleukocytoza, niedokrwistość hemolityczna, pierwotna dyskineza rzęsek (PCD), pozwoliły na powiązanie obecności i aktywności AK z etiologią tych chorób. Wykazano również udział AK w regulacji różnicowania i dojrzewaniu komórek, a także w apoptozie i onkogenezie. Szeroki zakres procesów, w które są zaangażowane kinazy adenylanowe oraz skorelowanie ich z rozwojem chorób, zachęca do podjęcia dalszych badań nad AK i przemawia za medycznym aspektem wykorzystania kinazy adenylanowej w diagnostyce i terapii niektórych schorzeń. Praca systematyzuje obecny stan wiedzy dotyczący budowy, właściwości i funkcji ludzkiej kinazy adenylanowej

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. © 2014 Das et al

NMR CHARACTERIZATION OF LOCAL UNFOLDING IN E. COLI ADENYLATE KINASE.

Life depends on proper function of biological macromolecules such as proteins. However, the application of knowledge about proteins and other macromolecules suffers from a lack of understanding of basic properties. This is further evident in the study of enzymes that catalyze chemical reactions. Conformational fluctuations between the ground state and one or more intermediate states have emerged as a strong candidate for the missing link in the canonical structure-function paradigm. Such states have shown to be important in enzyme function, allosteric signaling, and ligand binding. These processes are difficult to study due to low populations of one or more conformations and their transient nature. In this study, we investigated a locally unfolded (LU), intermediate state in E. coli adenylate kinase (AK). The LU state was stabilized using entropy-enhancing mutations that increase the degeneracy of unfolded conformations while maintaining the original ground-state structure. The population of the LU state was tuned to varying degrees, giving access to different equilibrium populations. Nuclear magnetic resonance was used to probe the structural characteristics of the LU state and measure conformational dynamics between the ground and LU states. Chemical shift differences observed directly and inferred from dynamics matched one another and are consistent with an LU intermediate conformation for all variants studied. This study directly characterizes a functionally important locally-unfolded, intermediate conformation in AK and exemplifies the ability of entropy-enhancing mutations to study unfolded conformations in proteins

Searching for the origin of protein conformational changes: Protein responses to specific forces in simulations

It is widely accepted that the structure of a protein and its motions are critical for a protein’s function, and that protein functions are usually accompanied by highly specific conformational changes. However, in many cases it is still unclear how the details of motion relate to a protein’s functionality and especially what causes conformational changes, despite having a significant number of proteins with multiple experimentally determined conformations. Here we investigate the conformational changes in proteins by collecting ensembles of different conformations of the same protein structure and simulate the application of external forces originating from exothermic chemical reactions such as ATP hydrolysis or the forces arising upon physical impact of ligands when they bind. External forces are applied to a structure in a novel approach of introducing directed forces at single residues as well as the Metropolis Monte Carlo simulation where more randomness is introduced. Both of these types of simulations are conducted within the framework of elastic network models. By applying single iterative forces to single residues, our approach shows that the forces able to drive the conformation to the known final structure are usually highly directional in nature. Our simulations also reveal that external forces can push a conformation to the known target form by pushing on only a few residues, and that such residues are sequentially conserved, indicating their functional importance. During the Metropolis Monte Carlo simulations, we observe the that forces enable a protein structure to overcome energy barriers in moving towards the known final form, and for all structures studied, the final state reached is within less than 3.8Å from the known final conformation, in terms of root-mean-square-deviation, and usually substantially closer. We also generate energy landscapes to investigate conformational transition pathways. The landscapes are generated by computing the free energies interpolated from known experimental structures and extracting the dominant motions in terms of their principal component. The generated energy landscapes agree with the concept that native structures usually fall within low energy basins. We project the conformational transition pathways generated by Metropolis Monte Carlo simulations and observe that the pathways generally follow low energy pathways and are overall energetically favorable

Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins

abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible. Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code.Dissertation/ThesisDoctoral Dissertation Physics 201

Application of Computational Methods for the Design of New Potential Therapeutic Agents

Computer-aided drug discovery (CADD) represents a very useful tool to search for potential drug candidates and plays a strategic role in the discovery of new potential therapeutic agents for both pharmaceutical companies and academic research groups. Nevertheless, the modelling of biological systems still represents a challenge for computational chemists, and, at present, a single computational method able to face such challenge is not available. Computational tools are therefore evolving in the direction of combining molecular-mechanic (MM), molecular dynamics (MD), and quantum-mechanical (QM) approaches in order to achieve an overall better simulation of the actual molecular behaviour. In addition, many sampling methods have been developed and applied for the characterisation and comparison of the collective motions of protein structures related to the dynamics of proteins, protein folding and ligand-protein docking simulations. This prompted us, as computational medicinal chemists, to develop various CADD approaches, depending on the specific case under study, integrating theoretical and experimental data. In particular, the research activity carried out during the three years of my PhD led to: i) the development of three-dimensional (3-D) pharmacophore models for the analysis of 3-D structure-activity relationships (SARs) of bioactive compounds, ii) the identification of new molecular targets, iii) the simulation of large-scale protein conformational changes, iv) the simulation of protein/protein and ligand/protein interactions, and v) the design of new bioactive compounds. Computational studies were always performed in the frame of multi-disciplinary projects guided by a unique research strategy, which involved several international and national research groups, and were carried out by integrating and validating our computational studies with the experimental data coming from the other researchers involved in the various projects. The results obtained enabled to: i) identify a new class of anticancer agents against paclitaxel resistant cancer cells, ii) provide important information on the mechanism of action of cationic porphyrins, a novel class of proteasome conformational regulators with great potentiality as “lead” pharmacophores, and iii) optimise the cellular pharmacokinetic and pharmacodynamic properties of a new series of antimalarial agents. In addition, I spent a training period abroad of eight-months at the Institute of Research in Biomedicine (IRB) in Barcelona, under the supervision of prof. Modesto Orozco, during which I have had the opportunity to extend my computational background by learning and, then, performing metadynamic and MD simulations, investigating the open/close conformational transition of 20S human proteasome by molecular dynamics simulations

Application of Computational Methods for the Design of New Potential Therapeutic Agents

Computer-aided drug discovery (CADD) represents a very useful tool to search for potential drug candidates and plays a strategic role in the discovery of new potential therapeutic agents for both pharmaceutical companies and academic research groups. Nevertheless, the modelling of biological systems still represents a challenge for computational chemists, and, at present, a single computational method able to face such challenge is not available. Computational tools are therefore evolving in the direction of combining molecular-mechanic (MM), molecular dynamics (MD), and quantum-mechanical (QM) approaches in order to achieve an overall better simulation of the actual molecular behaviour. In addition, many sampling methods have been developed and applied for the characterisation and comparison of the collective motions of protein structures related to the dynamics of proteins, protein folding and ligand-protein docking simulations. This prompted us, as computational medicinal chemists, to develop various CADD approaches, depending on the specific case under study, integrating theoretical and experimental data. In particular, the research activity carried out during the three years of my PhD led to: i) the development of three-dimensional (3-D) pharmacophore models for the analysis of 3-D structure-activity relationships (SARs) of bioactive compounds, ii) the identification of new molecular targets, iii) the simulation of large-scale protein conformational changes, iv) the simulation of protein/protein and ligand/protein interactions, and v) the design of new bioactive compounds. Computational studies were always performed in the frame of multi-disciplinary projects guided by a unique research strategy, which involved several international and national research groups, and were carried out by integrating and validating our computational studies with the experimental data coming from the other researchers involved in the various projects. The results obtained enabled to: i) identify a new class of anticancer agents against paclitaxel resistant cancer cells, ii) provide important information on the mechanism of action of cationic porphyrins, a novel class of proteasome conformational regulators with great potentiality as “lead” pharmacophores, and iii) optimise the cellular pharmacokinetic and pharmacodynamic properties of a new series of antimalarial agents. In addition, I spent a training period abroad of eight-months at the Institute of Research in Biomedicine (IRB) in Barcelona, under the supervision of prof. Modesto Orozco, during which I have had the opportunity to extend my computational background by learning and, then, performing metadynamic and MD simulations, investigating the open/close conformational transition of 20S human proteasome by molecular dynamics simulations