AMBER Software Research Articles

Fast Pairwise Approximation of Solvent Accessible Surface Area for Implicit Solvent Simulations of Proteins on CPUs and GPUs.

We propose a pairwise and readily parallelizable SASA-based nonpolar solvation approach for protein simulations, inspired by our previous pairwise GB polar solvation model development. In this work, we developed a novel function to estimate the atomic and molecular SASAs of proteins, which results in comparable accuracy as the LCPO algorithm in reproducing numerical icosahedral-based SASA values. Implemented in Amber software and tested on consumer GPUs, our pwSASA method reasonably reproduces LCPO simulation results, but accelerates MD simulations up to 30 times compared to the LCPO implementation, which is greatly desirable for protein simulations facing sampling challenges. The value of incorporating the nonpolar term in implicit solvent simulations is explored on a peptide fragment containing the hydrophobic core of HP36 and evaluating thermal stability profiles of four small proteins.

Redox potential replica exchange molecular dynamics at constant pH in AMBER: Implementation and validation.

Redox processes are important in chemistry, with applications in biomedicine, chemical analysis, among others. As many redox experiments are also performed at a fixed value of pH, having an efficient computational method to support experimental measures at both constant redox potential and pH is very important. Such computational techniques have the potential to validate experimental observations performed under these conditions and to provide additional information unachievable experimentally such as an atomic level description of macroscopic measures. We present the implementation of discrete redox and protonation states methods for constant redox potential Molecular Dynamics (CEMD), for coupled constant pH and constant redox potential MD (C(pH,E)MD), and for Replica Exchange MD along the redox potential dimension (E-REMD) on the AMBER software package. Validation results are presented for a small system that contains a single heme group: N-acetylmicroperoxidase-8 (NAcMP8) axially connected to a histidine peptide. The methods implemented allow one to make standard redox potential (Eo) predictions with the same easiness and accuracy as pKa predictions using the constant pH molecular dynamics and pH-REMD methods currently available on AMBER. In our simulations, we can correctly describe, in agreement also with theoretical predictions, the following behaviors: when a redox-active group is reduced, the pKa of a near pH-active group increases because it becomes easier for a proton to be attached; equivalently, when a pH-active group is protonated, the standard redox potential (Eo) of an adjacent redox-active group rises. Furthermore, our results also show that E-REMD is able to achieve faster statistical convergence than CEMD or C(pH,E)MD. Moreover, computational benchmarks using our methodologies show high-performance of GPU (Graphics Processing Unit) accelerated calculations in comparison to conventional CPU (Central Processing Unit) calculations.

Comparing Classical Water Models Using Molecular Dynamics To Find Bulk Properties

A computational chemistry exercise for the undergraduate physical chemistry laboratory is described. In this exercise, students use the molecular dynamics package Amber to generate trajectories of bulk liquid water for 4 different water models (TIP3P, OPC, SPC/E, and TIP4Pew). Students then process the trajectory to calculate structural (radial distribution functions) and dynamic (diffusion coefficients) properties of water that they compare to experimental values and to the other models. On the basis of these comparisons, students are also able to draw conclusions regarding the relative efficacy of these water models at modeling properties of real water.

Calculation of liquid waste discharge limits for routine discharge of Tehran research reactor

Abstract One of the most important technical documents for obtaining of a reactor license (site selection, design, construction and operation license) from IINRA is public dose assessment and calculation of discharge limits into the environment. Presence of population centers and aquifers adjacent of nuclear installations is a crucial rule in public dose assessment and determination of liquid release limits into the environment. In this paper, liquid waste of TRR regards as liquid released in sewage system. The migration of radionuclides released to well through the ingestion of radionuclides via drinking water and human food-chain, inhalation of radionuclides and external irradiation from radionuclides in soil and water was modeled using the AMBER software. Then, amount of liquid released to environment with different amount of distribution coefficient, as an important effective parameter in simulation, is determined. The calculation of discharge limits shows that the liquid radioactive waste is lower than the values given into the Environmental Assessment for Tehran Research Reactor report. So the received dose doesn't exceed the dose limit of 10 μSvyr−1 for members of the public which is approved by INRA.

Grid-Based Surface Generalized Born Model for Calculation of Electrostatic Binding Free Energies

Fast and accurate calculation of solvation free energies is central to many applications, such as rational drug design. In this study, we present a grid-based molecular surface implementation of "R6" flavor of the generalized Born (GB) implicit solvent model, named GBNSR6. The speed, accuracy relative to numerical Poisson-Boltzmann treatment, and sensitivity to grid surface parameters are tested on a set of 15 small protein-ligand complexes and a set of biomolecules in the range of 268 to 25099 atoms. Our results demonstrate that the proposed model provides a relatively successful compromise between the speed and accuracy of computing polar components of the solvation free energies (ΔGpol) and binding free energies (ΔΔGpol). The model tolerates a relatively coarse grid size h = 0.5 Å, where the grid artifact error in computing ΔΔGpol remains in the range of kBT ∼ 0.6 kcal/mol. The estimated ΔΔGpols are well correlated (r2 = 0.97) with the numerical Poisson-Boltzmann reference, while showing virtually no systematic bias and RMSE = 1.43 kcal/mol. The grid-based GBNSR6 model is available in Amber (AmberTools) package of molecular simulation programs.

Improved Accuracy for Constant pH-REMD Simulations through Modification of Carboxylate Effective Radii.

The accuracy of computational models for simulating biomolecules under specific solution pH conditions is critical for properly representing the effect of pH in biological processes. Constant pH (CpH) simulations involving implicit solvent using the AMBER software often incorrectly estimate pKa values of aspartate and glutamate residues due to large effective radii stemming from the presence of dummy protons. These inaccuracies stem from problems in the sampled ensembles of titratable residues that can influence other observable pH-dependent behavior, such as conformational change. We investigate new radii assignments for atoms in titratable residues with carboxylate groups to mitigate the systematic overestimation in the current method. We find that decreased carboxylate radii correspond with increased agreement with experimentally derived pKa values for residues in hen egg-white lysozyme and Δ+PHS variants of staphylococcal nuclease (SNase) and improved conformation state sampling compared to experimentally described expectations of native-like structure. Our CpH simulations suggest that decreasing the effective radii of these carboxylate groups is essential for eliminating a significant source of systematic error that hurts the accuracy of both conformational and protonation state sampling with implicit solvent.

Structural studies of the ArsD arsenic metallochaperone using molecular dynamics

Over the past three decades the occurrence of high environmental concentrations of arsenic has been recognized as a major public health concern. Arsenic is a carcinogen and causative agent for number of diseases. The toxic and carcinogenic effects of arsenic are the result of inactivation of specific enzymes of metabolism, induction of oxidative stress, inhibition of DNA repair mechanisms and deregulation of cell proliferation. Despite its toxicity, arsenic has a long history of usage as chemotherapeutic agent. Today, drugs containing arsenic (and the related metalloid antimony) are used for treating acute promyelocytic leukemia and diseases caused by protozoan parasites. In response to its toxicity, many microorganisms have developed arsenic resistance mechanism. In bacteria, arsenic resistance genes are organized in ars operons. The best characterized, the ars operon from Escherichia coli plasmid R773, has five genes, arsRDABC. ArsC is a reductase that reduces inorganic As(V) to As(III). ArsR is a 117-residue homodimeric As(III)-responsive transcriptional repressor with high affinity for the ars promoter. ArsA is an ATPase, which is the catalytic subunit of the ArsAB efflux pump, and ArsD is an As(III) chaperone to the ArsAB pump. ArsD is a homodimer of two 120-residue subunits with three vicinal cysteine pairs, Cys12-Cys13, Cys112-Cys113 and Cys119-Cys120. A fully-active truncated version of ArsD protein with 109 residues (ArsD109) has been crystallized, and the structure has been solved using X-ray crystallography. Biochemical studies suggested that wild-type ArsD binds three As(III) per monomer, while the derivative with a truncation at residue 109 binds only a single As(III). To understand the secondary structure and folding of the C-terminus of ArsD, which includes two cysteine pairs Cys112-Cys113 and Cys119-Cys120, Molecular Dynamics (MD) simulations were employed using AMBER software in presence or absence of arsenite [As(III)] ligand.

Favored and less favored codon–anticodon duplexes arising from the GC codon family box encoding for alanine: some computational perspectives

Alanine is encoded by the four codons of the GC box (GCA, GCG, GCU, and GCC). Known alanine anticodons include the UGC, IGC, and VGC triplets (I = inosine; V = uridine-5-oxyacetic acid). The energy-minimized structures of all possible codon–anticodon combinations involving all the alanine codons GCA, GCG, GCU, and GCC with the alanine anticodons UGC, IGC, and VGC are studied using the AMBER software. Fifteen H-bonded duplex structures arising out of these combinations are studied here, all having Watson–Crick-type base pairs at the first and second codon positions, and a variety of base pairing possibilities at the third (or wobble) position. Structural and stability considerations suggest that some codon–anticodon duplexes would be more favored than others for accommodation during the translation process. The UGC anticodon is predicted to favor the GCA codon for reading, while the GCC codon is least favored. The IGC anticodon would prefer to read the GCC codon, the GCG codon being least favored, while a syn conformer for A in the GCA codon could allow for it to be read. For the VGC anticodon, the GCA codon is predicted to be read most favorably, and the GCC codon least favorably, while a syn conformer for V in the anticodon would allow for the codon GCU to be read through a wobble pair which involves the exocyclic 5-oxyacetate group of V in H-bonding.

Protocols for Molecular Dynamics Simulations of RNA Nanostructures.

Molecular dynamics (MD) simulations have been used as one of the main research tools to study a wide range of biological systems and bridge the gap between X-ray crystallography or NMR structures and biological mechanism. In the field of RNA nanostructures, MD simulations have been used to fix steric clashes in computationally designed RNA nanostructures, characterize the dynamics, and investigate the interaction between RNA and other biomolecules such as delivery agents and membranes.In this chapter we present examples of computational protocols for molecular dynamics simulations in explicit and implicit solvent using the Amber Molecular Dynamics Package. We also show examples of post-simulation analysis steps and briefly mention selected tools beyond the Amber package. Limitations of the methods, tools, and protocols are also discussed. Most of the examples are illustrated for a small RNA duplex (helix), but the protocols are applicable to any nucleic acid structure, subject only to the computational speed and memory limitations of the hardware available to the user.

Solvated and generalised Born calculations differences using GPU CUDA and multi-CPU simulations of an antifreeze protein with AMBER

While there has been an increase in the number of biomolecular computational studies employing graphics processing units (GPU), results describing their use with the molecular dynamics package AMBER with the CUDA implementation are scarce. No information is available comparing MD methodologies pmemd.cuda, pmemd.mpi or sander.mpi, available in AMBER, for generalised Born (GB) simulations or with solvated systems. As part of our current studies with antifreeze proteins (AFP), and for the previous reasons, we present details of our experience comparing performance of MD simulations at varied temperatures between multi-CPU runs using sander.mpi, pmemd.mpi and pmemd.cuda with the AFP from the fish ocean pout (1KDF). We found extremely small differences in total energies between multi-CPU and GPU CUDA implementations of AMBER12 in 1ns production simulations of the solvated system using the TIP3P water model. Additionally, GPU computations achieved typical one order of magnitude speedups when using mixed precision but were similar to CPU speeds when computing with double precision. However, we found that GB calculations were highly sensitive to the choice of initial GB parametrisation regardless of the type of methodology, with substantial differences in total energies.

Docking, QM/MM, and molecular dynamics simulations of the hexose transporter from Plasmodium falciparum (PfHT)

Malaria is the most prevalent parasitic disease in the world. Currently, an effective vaccine for malaria does not exist, and chemotherapy must be used to treat the disease. Because of increasing resistance to current antimalarial drugs, new treatments must be developed. Among the many potential molecular targets, the hexose transporter of Plasmodium falciparum (PfHT) is particularly promising because it plays a vital role in glucose transport for the parasite. Thus, this study aims to determine the three-dimensional structure of PfHT and to describe the intermolecular interactions between active glycoside derivatives and PfHT. Such information should aid in the development of new antimalarial drugs. The receptor PfHT was constructed from primary sequences deposited in the SWISS MODEL database. Next, molecular docking simulations between O-(undec-10-en)-l-D-glucose and the constructed active site models were performed using Autodock Vina. The glycoside derivative-PfHT complexes were then refined using the hybrid QM/MM (PM3/ff03) method within the AMBER package. The models were then evaluated using Ramachandran plots, which indicated that 93.2% of the residues in the refined PfHT models (P5) were present in favorable regions. Furthermore, graphical plots using ANOLEA showed that the potential energies of interaction for atoms unbonded to P5 were negative. Finally, the O-(undec-10-en)-l-D-glucose-PfHT complex was evaluated using 20-ns Molecular Dynamics simulations with an ff03 force field. Docking and QM/MM studies revealed the amino acids essential for molecular recognition of and activity on glycosides. Inhibition of glucose transporters may prevent the development and metabolism of P. falciparum, so a description of the receptor’s structure is a critical step towards rational drug design.

A Simple Molecular Dynamics Lab To Calculate Viscosity as a Function of Temperature

A simple molecular dynamics experiment is described to demonstrate transport properties for the undergraduate physical chemistry laboratory. The AMBER package is used to monitor self-diffusion in n-hexane. Scripts (available in the Supporting Information) make the process considerably easier for students, allowing them to focus on the simulations and their meaning. Mean-squared displacements are determined as a function of simulation time for 250 ps in a small simulation box at a variety of temperatures. From these, the Einstein–Smoluchowski and Stokes–Einstein relationships are used to determine the viscosity, which can be directly compared to literature values. The needed trajectories can be calculated in less than 1 h and analyzed in a second hour, leaving a third hour for further explorations as appropriate.

Molecular dynamics simulation of the interactions between EHD1 EH domain and multiple peptides.

To provide essential information for peptide inhibitor design, the interactions of Eps15 homology domain of Eps15 homology domain-containing protein 1 (EHD1 EH domain) with three peptides containing NPF (asparagine-proline-phenylalanine), DPF (aspartic acid-proline-phenylalanine), and GPF (glycine-proline-phenylalanine) motifs were deciphered at the atomic level. The binding affinities and the underlying structure basis were investigated. Molecular dynamics (MD) simulations were performed on EHD1 EH domain/peptide complexes for 60 ns using the GROMACS package. The binding free energies were calculated and decomposed by molecular mechanics/generalized Born surface area (MM/GBSA) method using the AMBER package. The alanine scanning was performed to evaluate the binding hot spot residues using FoldX software. The different binding affinities for the three peptides were affected dominantly by van der Waals interactions. Intermolecular hydrogen bonds provide the structural basis of contributions of van der Waals interactions of the flanking residues to the binding. van der Waals interactions should be the main consideration when we design peptide inhibitors of EHD1 EH domain with high affinities. The ability to form intermolecular hydrogen bonds with protein residues can be used as the factor for choosing the flanking residues.

Grid-based backbone correction to the ff12SB protein force field for implicit-solvent simulations.

Force fields, such as Amber's ff12SB, can be fairly accurate models of the physical forces in proteins and other biomolecules. When coupled with accurate solvation models, force fields are able to bring insight into the conformational preferences, transitions, pathways, and free energies for these biomolecules. When computational speed/cost matters, implicit solvent is often used but at the cost of accuracy. We present an empirical grid-like correction term, in the spirit of cMAPs, to the combination of the ff12SB protein force field and the GBneck2 implicit-solvent model. Ff12SB-cMAP is parametrized on experimental helicity data. We provide validation on a set of peptides and proteins. Ff12SB-cMAP successfully improves the secondary structure biases observed in ff12SB + Gbneck2. Ff12SB-cMAP can be downloaded ( https://github.com/laufercenter/Amap.git ) and used within the Amber package. It can improve the agreement of force fields + implicit solvent with experiments.

The Adaptively Biased Molecular Dynamics method revisited: New capabilities and an application

The free energy is perhaps one of the most important quantity required for describing biomolecular systems at equilibrium. Unfortunately, accurate and reliable free energies are notoriously difficult to calculate. To address this issue, we previously developed the Adaptively Biased Molecular Dynamics (ABMD) method for accurate calculation of rugged free energy surfaces (FES). Here, we briefly review the workings of the ABMD method with an emphasis on recent software additions, along with a short summary of a selected ABMD application based on the B-to-Z DNA transition. The ABMD method, along with current extensions, is currently implemented in the AMBER (ver.10-14) software package.

Refinement of Generalized Born Implicit Solvation Parameters for Nucleic Acids and Their Complexes with Proteins.

The Generalized Born (GB) implicit solvent model has undergone significant improvements in accuracy for modeling of proteins and small molecules. However, GB still remains a less widely explored option for nucleic acid simulations, in part because fast GB models are often unable to maintain stable nucleic acid structures or they introduce structural bias in proteins, leading to difficulty in application of GB models in simulations of protein-nucleic acid complexes. Recently, GB-neck2 was developed to improve the behavior of protein simulations. In an effort to create a more accurate model for nucleic acids, a similar procedure to the development of GB-neck2 is described here for nucleic acids. The resulting parameter set significantly reduces absolute and relative energy error relative to Poisson-Boltzmann for both nucleic acids and nucleic acid-protein complexes, when compared to its predecessor GB-neck model. This improvement in solvation energy calculation translates to increased structural stability for simulations of DNA and RNA duplexes, quadruplexes, and protein-nucleic acid complexes. The GB-neck2 model also enables successful folding of small DNA and RNA hairpins to near native structures as determined from comparison with experiment. The functional form and all required parameters are provided here and also implemented in the AMBER software.

Speed of Conformational Change: Comparing Explicit and Implicit Solvent Molecular Dynamics Simulations

Adequate sampling of conformation space remains challenging in atomistic simulations, especially if the solvent is treated explicitly. Implicit-solvent simulations can speed up conformational sampling significantly. We compare the speed of conformational sampling between two commonly used methods of each class: the explicit-solvent particle mesh Ewald (PME) with TIP3P water model and a popular generalized Born (GB) implicit-solvent model, as implemented in the AMBER package. We systematically investigate small (dihedral angle flips in a protein), large (nucleosome tail collapse and DNA unwrapping), and mixed (folding of a miniprotein) conformational changes, with nominal simulation times ranging from nanoseconds to microseconds depending on system size. The speedups in conformational sampling for GB relative to PME simulations, are highly system- and problem-dependent. Where the simulation temperatures for PME and GB are the same, the corresponding speedups are approximately onefold (small conformational changes), between ∼1- and ∼100-fold (large changes), and approximately sevenfold (mixed case). The effects of temperature on speedup and free-energy landscapes, which may differ substantially between the solvent models, are discussed in detail for the case of miniprotein folding. In addition to speeding up conformational sampling, due to algorithmic differences, the implicit solvent model can be computationally faster for small systems or slower for large systems, depending on the number of solute and solvent atoms. For the conformational changes considered here, the combined speedups are approximately twofold, ∼1- to 60-fold, and ∼50-fold, respectively, in the low solvent viscosity regime afforded by the implicit solvent. For all the systems studied, 1) conformational sampling speedup increases as Langevin collision frequency (effective viscosity) decreases; and 2) conformational sampling speedup is mainly due to reduction in solvent viscosity rather than possible differences in free-energy landscapes between the solvent models.

Abstract 5370: Use of molecular dynamics simulations to rationalise the DNA sequence-selectivity of pyrrolobenzodiazepine-MPB conjugates

Abstract We have previously reported the identification of a GC-interactive non-covalent-binding moiety, a biaryl 4-(1-methyl-1H-pyrrol-3-yl)benzenamine (MPB) motif, through a combined approach involving rational library design and a Fluorescent Intercalation Displacement (FID) assay. This MPB motif, when tethered to a covalently-binding pyrrolobenzodiazepine (PBD) moiety via either an imidazole or pyrrole linkage to form PBD-Imidazole-MPB or PBD-Pyrrole-MPB structures, results in cytotoxicity in the low picomolar range in some tumour cell lines. To assess the DNA-binding affinity and sequence selectivity of PBD-Imidazole-MPB (TSG-1301) and PBD-Pyrrole-MPB (TSG-1302), we have previously reported the use of a FRET-based DNA melting assay based on a duel-labelled hairpin-forming oligonucleotide containing only one PBD binding site. Although having similar cytotoxicities, the sequence selectivity of TSG-1301 and TSG-1302 differ markedly. Melting temperatures (ΔTm) showed that TSG-1301 stabilised both AT- and GC-rich sequences of DNA to an equal extent (i.e., ΔTm of 6°C for each), with TSG-1302 selectively stabilising AT-rich sequences with an approximately 3.5-fold selectivity (i.e., ΔTm of 5°C for AT-rich sequences and 1.4°C for GC-rich). Therefore, Molecular Dynamics (MD) simulations were undertaken to try to understand these differences in sequence selectivity. Simulations were first conducted in implicit solvent for 25ns, and confirmed using extensive explicit solvent simulations using the AMBER software. The results clearly demonstrate the importance of the imidazole ring nitrogen of TSG-1301 in inducing GC-selective interactions through hydrogen bonding. Both the distance between the imidazole ring nitrogen and the terminal ester (an average of 12Å over the duration of simulation), and the shape of the molecule, were found to be crucial for the production of GC interactions, with the Im-MPB moiety ideally spanning side-by-side guanine residues. The AT-selectivity of TSG-1302 could be rationalised using similar techniques, with the Py-MPB moiety contributing to van der Waals interactions between the ligand and AT-rich DNA, due to the MPB moiety presenting a strongly van der Waals-interactive face to the minor-groove. These results were further exemplified using free energy of binding calculations from implicit solvent simulations which provided a difference of -2kcal/mol in favour of the interaction of TSG-1302 with AT-rich compared to GC-rich sequences. The results of this MD study are consistent with observations from our previously reported FRET studies, and the simulations have provided valuable insights into the mode of DNA-interaction of minor groove-binding ligands of this type. This information can be used for the rational design of further generations of agents with improved DNA sequence-selectivity. Citation Format: Paul JM Jackson, Khondaker M. Rahman, David E. Thurston. Use of molecular dynamics simulations to rationalise the DNA sequence-selectivity of pyrrolobenzodiazepine-MPB conjugates. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5370. doi:10.1158/1538-7445.AM2014-5370

Folding simulations for proteins with diverse topologies are accessible in days with a physics-based force field and implicit solvent.

The millisecond time scale needed for molecular dynamics simulations to approach the quantitative study of protein folding is not yet routine. One approach to extend the simulation time scale is to perform long simulations on specialized and expensive supercomputers such as Anton. Ideally, however, folding simulations would be more economical while retaining reasonable accuracy, and provide feedback on structure, stability and function rapidly enough if partnered directly with experiment. Approaches to this problem typically involve varied compromises between accuracy, precision, and cost; the goal here is to address whether simple implicit solvent models have become sufficiently accurate for their weaknesses to be offset by their ability to rapidly provide much more precise conformational data as compared to explicit solvent. We demonstrate that our recently developed physics-based model performs well on this challenge, enabling accurate all-atom simulated folding for 16 of 17 proteins with a variety of sizes, secondary structure, and topologies. The simulations were carried out using the Amber software on inexpensive GPUs, providing ∼1 μs/day per GPU, and >2.5 ms data presented here. We also show that native conformations are preferred over misfolded structures for 14 of the 17 proteins. For the other 3, misfolded structures are thermodynamically preferred, suggesting opportunities for further improvement.

Systematic Assessment of the Effects of an All-Atom Force Field and the Implicit Solvent Model on the Refinement of NMR Structures with Subsets of Distance Restraints

Jun-Goo JeeResearch Institute of Pharmaceutical Sciences, College of Pharmacy, Kyungpook National University, Daegu 702-701, Korea. E-mail: jjee@knu.ac.krReceived February 22, 2014, Accepted March 5, 2014Employment of a time consuming, sophisticated calculation using the all-atom force field and generalized-Born implicit solvent model (GBIS) for refinement of NMR structures has become practical through advancesin computational methods and capacities. GBIS refinement improves the qualities of the resulting NMRstructures with reduced computational times. However, the contribution of GBIS to NMR structures has notbeen sufficiently studied in a quantitative way. In this paper, we report the effects of GBIS on the refined NMRstructures of ubiquitin (UBQ) and GB1 with subsets of distance restraints derived from experimental data.Random omission prepared a series of distance restraints 0.05, 0.1, 0.3, 0.5, and 0.7 times smaller. For eachnumber, we produced five different restraints for statistical analysis. We then recalculated the NMR structuresusing CYANA software, followed by GBIS refinements using the AMBER package. GBIS improved both theprecision and accuracy of all the structures, but to varied levels. The degrees of improvement were significantwhen the input restraints were insufficient. In particular, GBIS enabled GB1 to form an accurate structure evenwith distance restraints of 5%, revealing that the root-mean-square deviation was less than 1 A from the X-raybackbone structure. We also showed that the efficiency of searching the conformational space was moreimportant for finding accurate structures with the calculation of UBQ with 5% distance restraints than thenumber of conformations generated. Our data will provide a meaningful guideline to judge and compare thestructural improvements by GBIS. Key Words : NMR, Generalized-Born implicit solvent model, Ubiquitin, GB1IntroductionSteady advances in algorithms for both NOE assignmentsand structure calculations have made automatic calculationsof protein 3D structures with raw NOE data, provided thechemical shifts are assigned for most atoms and sufficientpeaks exist.