Conformational sampling of CDR-H3 in antibodies by multicanonical molecular dynamics simulation

Computational biophysics and structural biology of proteins-a Special Issue in honor of Prof. Haruki Nakamura's 70th birthday

Receiving his initial training jointly in theoretical and applied physics at the University of Tokyo, Professor Haruki Nakamura has had a long and eventful scientific career, along the way helping to shape the way that biophysics is carried out in Japan. Concentrating his research efforts on the simulation of protein structure and function, he has, over his career arc, acted as director of the Institute for Protein Research (Osaka, Japan), director of the Protein Data Bank of Japan (PDBj), president of the Biophysical Society of Japan (BSJ), president of the Protein Science Society of Japan (PSSJ), and group leader and professor of Bioinformatics and Computational Structural Biology at Osaka University. In 2022, Prof. Haruki Nakamura turned 70 years old, and to mark this occasion, his scientific colleagues from around the world have combined their efforts to produce this Festschrift Issue of the IUPAB Biophysical Reviews journal around the theme of the computational biophysics and structural biology of proteins.

Structural, functional, and physiological properties of anti-(4-hydroxy-3-nitrophenyl)acetyl antibodies during the course of affinity maturation

Structural and functional analyses of antibodies in the affinity maturation pathway can help us understand the molecular mechanisms of protein recognition. Using one of the haptens, (4-hydroxy-3-nitrophenyl)acetyl (NP), various monoclonal antibodies have been obtained, either at the early or late stage of immunization. The variable regions of monoclonal antibodies and their site-directed mutants can also be obtained as single-chain Fv (scFv) antibodies. The change in antigen-binding affinity and avidity of matured-type antibodies from germline-type antibodies could be evaluated based on binding kinetics and thermodynamics, proposing the antigen recognition mode. Crystal structures of a germline-type antibody, N1G9, and a matured-type antibody, C6, in complex with NP were determined, revealing different antigen-binding mode at atomic resolution. Notably, the Tyr to Gly mutation at the 95th residue of the heavy chain is critical for changing the configuration of complementarity determining region 3, which is involved in antigen binding. Furthermore, thermal stability analyses of scFv antibodies have revealed trade-off between antigen-binding affinity and thermal stability in the antigen-unbound state. To increase affinity, the stability of the variable region may be decreased, possibly due to protein architecture. The high stability of germline-type antibodies and the low stability of matured-type antibodies, which increase upon antigen binding, can be explained by the stability of antibodies required at the respective stages of immunization.

Enhanced sampling without borders: on global biasing functions and how to reweight them

Molecular dynamics (MD) simulations are a powerful tool to follow the time evolution of biomolecular motions in atomistic resolution. However, the high computational demand of these simulations limits the timescales of motions that can be observed. To resolve this issue, so called enhanced sampling techniques are developed, which extend conventional MD algorithms to speed up the simulation process. Here, we focus on techniques that apply global biasing functions. We provide a broad overview of established enhanced sampling methods and promising new advances. As the ultimate goal is to retrieve unbiased information from biased ensembles, we also discuss benefits and limitations of common reweighting schemes. In addition to concisely summarizing critical assumptions and implications, we highlight the general application opportunities as well as uncertainties of global enhanced sampling.

Enhanced Conformational Sampling of Nanobody CDR H3 Loop by Generalized Replica-Exchange with Solute Tempering

The variable domains of heavy-chain antibodies, known as nanobodies, are potential substitutes for IgG antibodies. They have similar affinities to antigens as antibodies, but are more heat resistant. Their small size allows us to exploit computational approaches for structural modeling or design. Here, we investigate the applicability of an enhanced sampling method, a generalized replica-exchange with solute tempering (gREST) for sampling CDR-H3 loop structures of nanobodies. In the conventional replica-exchange methods, temperatures of only a whole system or scaling parameters of a solute molecule are selected for temperature or parameter exchange. In gREST, we can flexibly select a part of a solute molecule and a part of the potential energy terms as a parameter exchange region. We selected the CDR-H3 loop and investigated which potential energy term should be selected for the efficient sampling of the loop structures. We found that the gREST with dihedral terms can explore a global conformational space, but the relaxation to the global equilibrium is slow. On the other hand, gREST with all the potential energy terms can sample the equilibrium distribution, but the structural exploration is slower than with dihedral terms. The lessons learned from this study can be applied to future studies of loop modeling.

PIGSPro: prediction of immunoGlobulin structures v2

PIGSpro is a significant upgrade of the popular PIGS server for the prediction of the structure of immunoglobulins. The software has been completely rewritten in python following a similar pipeline as in the original method, but including, at various steps, relevant modifications found to improve its prediction accuracy, as demonstrated here. The steps of the pipeline include the selection of the appropriate framework for predicting the conserved regions of the molecule by homology; the target template alignment for this portion of the molecule; the selection of the main chain conformation of the hypervariable loops according to the canonical structure model, the prediction of the third loop of the heavy chain (H3) for which complete canonical structures are not available and the packing of the light and heavy chain if derived from different templates. Each of these steps has been improved including updated methods developed along the years. Last but not least, the user interface has been completely redesigned and an automatic monthly update of the underlying database has been implemented. The method is available as a web server at http://biocomputing.it/pigspro.

Computer-Aided Antibody Design: An Overview

The use of monoclonal antibody as the next generation protein therapeutics with remarkable success has surged the development of antibody engineering to design molecules for optimizing affinity, better efficacy, greater safety and therapeutic function. Therefore, computational methods have become increasingly important to generate hypotheses, interpret and guide experimental works. In this chapter, we discussed the overall antibody design by computational approches.

Promiscuous antibodies characterised by their physico-chemical properties: From sequence to structure and back

Human B cells produce antibodies, which bind to their cognate antigen based on distinct molecular properties of the antibody CDR loop. We have analysed a set of 10 antibodies showing a clear difference in their binding properties to a panel of antigens, resulting in two subsets of antibodies with a distinct binding phenotype. We call the observed binding multiplicity ‘promiscuous’ and selected physico-chemical CDRH3 characteristics and conformational preferences may characterise these promiscuous antibodies. To classify CDRH3 physico-chemical properties playing a role in their binding properties, we used statistical analyses of the sequences annotated by Kidera factors. To characterise structure-function requirements for antigen binding multiplicity we employed Molecular Modelling and Monte Carlo based coarse-grained simulations. The ability to predict the molecular causes of promiscuous, multi-binding behaviour would greatly improve the efficiency of the therapeutic antibody discovery process.

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected]

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Blind prediction performance of RosettaAntibody 3.0: grafting, relaxation, kinematic loop modeling, and full CDR optimization

Antibody Modeling Assessment II (AMA-II) provided an opportunity to benchmark RosettaAntibody on a set of 11 unpublished antibody structures. RosettaAntibody produced accurate, physically realistic models, with all framework regions and 42 of the 55 non-H3 CDR loops predicted to under an Ångström. The performance is notable when modeling H3 on a homology framework, where RosettaAntibody produced the best model among all participants for four of the 11 targets, two of which were predicted with sub-Ångström accuracy. To improve RosettaAntibody, we pursued the causes of model errors. The most common limitation was template unavailability, underscoring the need for more antibody structures and/or better de novo loop methods. In some cases, better templates could have been found by considering residues outside of the CDRs. De novo CDR H3 modeling remains challenging at long loop lengths, but constraining the C-terminal end of H3 to a kinked conformation allows near-native conformations to be sampled more frequently. We also found that incorrect VL -VH orientations caused models with low H3 RMSDs to score poorly, suggesting that correct VL -VH orientations will improve discrimination between near-native and incorrect conformations. These observations will guide the future development of RosettaAntibody.

Replica exchange molecular dynamics simulations of an α/β-type small acid soluble protein (SASP)

Small acid soluble proteins (SASPs) of α/β-type play a major role in the resistance of spore DNAs to external assaults. It has been found that α/β-type SASP exhibits intrinsic disorder on isolation, but it acquires a defined native state upon binding to DNA. This disorder to order transition is not yet understood. Other questions related to the role of the thermodynamics and structure of the individual protein in the complex formation remain elusive. Characterization of the unbound state of α/β-type SASP in experiments could be a challenging problem because of the heterogeneous nature of the ensemble. Here, computer simulations can help gain more insights into the unbound state of α/β-type SASP. In the present work, by using replica exchange molecular dynamics (REMD), we simulated an α/β-type SASP on isolation with an implicit solvent. We found that α/β-type SASP undergoes a continuous phase transition with a small free energy barrier, a common feature of intrinsically disordered proteins (IDPs). Additionally, we detected the presence of residual α-helical structures at local level and a high degree of plasticity in the chain which can contribute to the fast disorder to order transition by reducing the fly-casting mechanism.

Peptide free energy landscapes calibrated by molecular orbital calculations

Free energy landscapes of peptide conformations werecalibrated by ab initiomolecular orbital calculations, after enhancedconformational sampling using the multicanonical molecular dynamicssimulations. Three different potentials of mean force for an isolateddipeptide were individually obtained using the conventional force fields,AMBER parm94, AMBER parm96, and CHARMm22. Each potential ofmean force was calibrated based on the umbrella sampling algorithm fromthe adiabatic energy map that was calculated separately by the abinitiomolecular orbital method. All the calibrated potentials of mean forcecoincided well. The calibration was applied to a peptide in explicit water,and the calibrated free energy landscapes did not depend on the force fieldused in conformational sampling, as far as the conformational space waswell sampled.

Homology modeling a fast tool for drug discovery: current perspectives

Major goal of structural biology involve formation of protein-ligand complexes; in which the protein molecules act energetically in the course of binding. Therefore, perceptive of protein-ligand interaction will be very important for structure based drug design. Lack of knowledge of 3D structures has hindered efforts to understand the binding specificities of ligands with protein. With increasing in modeling software and the growing number of known protein structures, homology modeling is rapidly becoming the method of choice for obtaining 3D coordinates of proteins. Homology modeling is a representation of the similarity of environmental residues at topologically corresponding positions in the reference proteins. In the absence of experimental data, model building on the basis of a known 3D structure of a homologous protein is at present the only reliable method to obtain the structural information. Knowledge of the 3D structures of proteins provides invaluable insights into the molecular basis of their functions. The recent advances in homology modeling, particularly in detecting and aligning sequences with template structures, distant homologues, modeling of loops and side chains as well as detecting errors in a model contributed to consistent prediction of protein structure, which was not possible even several years ago. This review focused on the features and a role of homology modeling in predicting protein structure and described current developments in this field with victorious applications at the different stages of the drug design and discovery.

Computer-aided antibody design

Recent clinical trials using antibodies with low toxicity and high efficiency have raised expectations for the development of next-generation protein therapeutics. However, the process of obtaining therapeutic antibodies remains time consuming and empirical. This review summarizes recent progresses in the field of computer-aided antibody development mainly focusing on antibody modeling, which is divided essentially into two parts: (i) modeling the antigen-binding site, also called the complementarity determining regions (CDRs), and (ii) predicting the relative orientations of the variable heavy (V(H)) and light (V(L)) chains. Among the six CDR loops, the greatest challenge is predicting the conformation of CDR-H3, which is the most important in antigen recognition. Further computational methods could be used in drug development based on crystal structures or homology models, including antibody-antigen dockings and energy calculations with approximate potential functions. These methods should guide experimental studies to improve the affinities and physicochemical properties of antibodies. Finally, several successful examples of in silico structure-based antibody designs are reviewed. We also briefly review structure-based antigen or immunogen design, with application to rational vaccine development.

Experimental identification and theoretical analysis of a thermally stabilized green fluorescent protein variant

In this study, we aim to relate experimentally measured macroscopic properties to dynamic and structural changes as calculated by molecular dynamics (MD) simulations. We performed the analysis on four GFP (green fluorescent protein) variants, which have amino acid replacements or insertion in a flexible region on the protein surface and which resulted from a previous protein splicing reaction optimization experiment. The variants are a reference GFP (CEGFP), GFP-N144C, GFP-N144C/Y145F, and a GFP with five residues inserted between Y145 and N146 (GFP-5ins). As a result, we identified a single Y145F mutation that increased the thermal stability of GFP-N144C/Y145F by 3-4 °C. Because circular dichroism measurements indicated that the overall GFP β-barrel fold was maintained in all variants, we presumed that the fluorescence activity and thermal stability related to local changes that could be detected by standard MD simulations. The 60 ns MD simulations indicated that the Y145's hydroxyl group, which is straight and buried in the crystal structure, was bent avoiding the hydrophobic core during the simulation in both CEGFP and GFP-N144C. This local strain was relieved in GFP-N144C/Y145F, where the tyrosine's hydroxyl group was replaced with the F145 hydrophobic aliphatic carbon. F145 remained indeed buried during the simulation maintaining local compactness, which presumably reflected the improved thermal stability of GFP-N144C/Y145F. Furthermore, the analysis of internal water molecules localized within the GFP's β-barrel suggested that a change in the local hydrogen bonding pattern around the chromophore correlated with a strong fluorescence activity decrease in GFP-5ins. Although relating experimental observation with calculated molecular features proved to be delicate, this study suggested that some microscopic features could be useful reporters for redesigning GFPs and other proteins. The newly identified GFP-N144C/Y145F was among the most stable GFP variant and demonstrates the potential of such computer-aided design.

Ab initio simulation of a 57-residue protein in explicit solvent reproduces the native conformation in the lowest free-energy cluster

An enhanced conformational sampling method, multicanonical molecular dynamics (McMD), was applied to the ab intio folding of the 57-residue first repeat of human glutamyl- prolyl-tRNA synthetase (EPRS-R1) in explicit solvent. The simulation started from a fully extended structure of EPRS-R1 and did not utilize prior structural knowledge. A canonical ensemble, which is a conformational ensemble thermodynamically probable at an arbitrary temperature, was constructed by reweighting the sampled structures. Conformational clusters were obtained from the canonical ensemble at 300 K, and the largest cluster (i.e., the lowest free-energy cluster), which contained 34% of the structures in the ensemble, was characterized by the highest similarity to the NMR structure relative to all alternative clusters. This lowest free-energy cluster included native-like structures composed of two anti-parallel α-helices. The canonical ensemble at 300 K also showed that a short Gly-containing segment, which adopts an α-helix in the native structure, has a tendency to be structurally disordered. Atomic-level analyses demonstrated clearly that inter-residue hydrophobic interactions drive the helix formation of the Gly-containing segment, and that increasing the hydrophobic contacts accompanies exclusion of water molecules from the vicinity of this segment. This study has shown, for the first time, that the free-energy landscape of a structurally well-ordered protein of about 60 residues is obtainable with an all atom model in explicit water without prior structural knowledge.

Theory for trivial trajectory parallelization of multicanonical molecular dynamics and application to a polypeptide in water

Trivial trajectory parallelization of multicanonical molecular dynamics (TTP-McMD) explores the conformational space of a biological system with multiple short runs of McMD starting from various initial structures. This method simply connects (i.e., trivially parallelizes) the short trajectories and generates a long trajectory. First, we theoretically prove that the simple trajectory connection satisfies a detailed balance automatically. Thus, the resultant long trajectory is regarded as a single multicanonical trajectory. Second, we applied TTP-McMD to an alanine decapeptide with an all-atom model in explicit water to compute a free-energy landscape. The theory imposes two requirements on the multiple trajectories. We have demonstrated that TTP-McMD naturally satisfies the requirements. The TTP-McMD produces the free-energy landscape considerably faster than a single-run McMD does. We quantitatively showed that the accuracy of the computed landscape increases with increasing the number of multiple runs. Generally, the free-energy landscape of a large biological system is unknown a priori. The current method is suitable for conformational sampling of such a large system to reduce the waiting time to obtain a canonical ensemble statistically reliable.

Affinity maturation of a humanized rat antibody for anti-RAGE therapy: comprehensive mutagenesis reveals a high level of mutational plasticity both inside and outside the complementarity-determining regions

Antibodies that neutralize RAGE (receptor for advanced glycation end products)-ligand interactions have potential therapeutic applications in both acute and chronic diseases. We generated XT-M4, a rat anti-RAGE monoclonal antibody that has in vivo efficacy in an acute sepsis model. This antibody was subsequently humanized. To improve the affinity of this antibody for the treatment of chronic indications, we used random and targeted mutagenesis strategies in combination with ribosome and phage-display technologies, respectively, to generate libraries of XT-M4 variants. We identified a panel of single-chain Fv antibody fragments (scFv's) that was improved up to 110-fold in a homogeneous time-resolved fluorescence competition assay against parental XT-M4 immunoglobulin G (IgG). After reformatting to bivalent scFv-Fc fusions and IgGs, we observed similar gains in potency in the same assay. Further analysis of binding kinetics as IgG revealed multiple variants with subnanomolar apparent affinity that was dictated primarily by improvements in the off-rate. All variants also had improved binding to cell surface-expressed human RAGE, and all retained, or had improved, apparent affinity for mouse RAGE. F100bL in V(H) (variable region of the heavy chain) complementarity-determining region 3 (CDR3) was one of a number of key mutations that correlated with affinity improvements and was independently identified by both mutagenesis strategies. Random mutagenesis coupled with ribosome display and high-throughput screening revealed an unexpectedly high level of mutational plasticity across the whole length of the humanized scFv, suggesting greater scope for structural optimization outside of the primary antigen-combining site defined by V(H) CDR3 and V(kappa) CDR3. In summary, our comprehensive mutagenesis approach not only achieved the desired affinity maturation of XT-M4 but also defined multiple mutational hotspots across the antibody sequence, provided an insight into the specificity-determining residues of the antibody paratope, and identified additional sites within the CDR loops where human germ-line amino acids may be introduced without affecting function.

Structural classification of CDR-H3 revisited: a lesson in antibody modeling

Among the six complementarity-determining regions (CDRs) in the variable domains of an antibody, the third CDR of the heavy chain (CDR-H3), which lies in the center of the antigen-binding site, plays a particularly important role in antigen recognition. CDR-H3 shows significant variability in its length, sequence, and structure. Although difficult, model building of this segment is the most critical step in antibody modeling. Since our first proposal of the "H3-rules," which classify CDR-H3 structure based on amino acid sequence, the number of experimentally determined antibody structures has increased. Here, we revise these H3-rules and propose an improved classification scheme for CDR-H3 structure modeling. In addition, we determine the common features of CDR-H3 in antibody drugs as well as discuss the concept of "antibody druggability," which can be applied as an indicator of antibody evaluation during drug discovery.

Generation of a flexible loop structural ensemble and its application to induced-fit structural changes following ligand binding

Molecular recognition is often mediated by flexible loops that have widely fluctuating structures and are sometimes disordered, but that form particular complex structures following ligand binding. In fact, many loop structures found in the PDB database are too flexible to be determined precisely. A new loop modeling method was therefore developed using force-biased multicanonical molecular dynamics with the implicit solvent model to generate an ensemble of putative loop structures with low free energy values. The method was then used to create ensembles for several flexible loops that were compared with the corresponding NMR and X-ray structures. The induced-fit structural change of dihydrofolate reductase (DHFR) was also predicted from a structural ensemble of ligand-free M20 loop conformations and successive docking simulations.

Modelling of third cytoplasmic loop of bovine rhodopsin by multicanonical molecular dynamics

The third cytoplasmic loop (C3) of bovine rhodopsin (Rh) is an important site for its interaction with G-protein transducin. The tertiary structure of Rh was determined by X-ray crystallography, although the local conformation around the C3 loop (residues: 236-240) was not visible in electron density maps. We constructed a canonical conformation ensemble at 310 K for the C3 loop (residues: 227-244) using a multicanonical molecular dynamics simulation, and predicted several putative conformations. The conformation ensemble was classified by principal component analysis into several distinct structural clusters, some of which could provide the putative structural models of Rh and the activated state of Rh.

Germline antibody recognition of distinct carbohydrate epitopes

High-resolution structures reveal how a germline antibody can recognize a range of clinically relevant carbohydrate epitopes. The germline response to a carbohydrate immunogen can be critical to survivability, with selection for antibody gene segments that both confer protection against common pathogens and retain the flexibility to adapt to new disease organisms. We show here that antibody S25-2 binds several distinct inner-core epitopes of bacterial lipopolysaccharides (LPSs) by linking an inherited monosaccharide residue binding site with a subset of complementarity-determining regions (CDRs) of limited flexibility positioned to recognize the remainder of an array of different epitopes. This strategy allows germline antibodies to adapt to different epitopes while minimizing entropic penalties associated with the immobilization of labile CDRs upon binding of antigen, and provides insight into the link between the genetic origin of individual CDRs and their respective roles in antigen recognition.

Identification of protein functions from a molecular surface database, eF-site

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson-Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.

Determination of multicanonical weight based on a stochastic model of sampling dynamics

Based on the stochastic interpretation of the sampling process modeled by a Langevin equation, we present an effective iteration scheme to determine the weight in multicanonical molecular dynamics. Our method enables an automatic determination of the weight producing a uniform energy sampling via an iterative cancellation of the deterministic force in a Langevin equation. The deterministic force has been calculated from the energy trajectory by identifying the moments of the transition probability of a Fokker-Planck equation associated with a Langevin equation. The intimate relationship between the sampling process and the stochastic dynamics has been verified by applying the iteration scheme to a helix-coil transition of the 8-polyalanine system in a gas phase.

A peptide mimetic of an anti-CD4 monoclonal antibody by rational design

The development of rational methods to design 'continuous' sequence mimetics of discontinuous regions of protein sequence has, to now, been only marginally successful. This has been largely due to the difficulty of constraining the recognition elements of a mimetic structure to the relative conformational and spatial orientations present in the parent molecule. Using peptide mapping to determine 'active' antigen recognition residues, molecular modeling, and a molecular dynamics trajectory analysis, we have developed a peptide mimic of an anti-CD4 antibody, containing antigen contact residues from multiple CDRs. The design described is a 27-residue peptide formed by juxtaposition of residues from 5 CDR regions. It displays an affinity for the antigen (CD4) of 0.9nM, compared to 2nM for the parent antibody ST40. Nevertheless, the mimetic shows low biological activity in an anti-retroviral assay.

Structural consequences of target epitope-directed functional alteration of an antibody. The case of anti-hen lysozyme antibody, HyHEL-10

Decreased affinity of an antibody for a mutated epitope in an antigen can be enhanced and reversed by mutations in certain antibody residues. Here we describe the crystal structures of (a) the complex between a naturally mutated proteinaceous antigen and an antibody that was mutated and selected in vitro, and (b) the complex between the normal antigen and the mutated antibody. The mutated and selected antibody recognizes essentially the same epitope as in the wild-type antibody, indicating successful target site-directed functional alteration of the antibody. In comparing the structure of the mutated antigen-mutant antibody complex with the previously established structure of the wild-type antigen-wild-type antibody complex, we found that the enhanced affinity of the mutated antibody for the mutant antigen originated not from improvements in local complementarity around the mutated sites but from subtle and critical structural changes in nonmutated sites, including an increase in variable domain interactions. Our findings indicate that only a few mutations in the antigen-binding region of an antibody can lead to some structural changes in its paratopes, emphasizing the critical roles of the plasticity of loops in the complementarity-determining region and also the importance of the plasticity of the interaction between the variable regions of immunoglobulin heavy and light chains in determining the specificity of an antibody.

Structural genomics of membrane proteins

A program on the structural genomics of membrane proteins has started at the BIRC, AIST, involving other academic institutions and industrial companies. Emphasis is being put on the development of techniques for the structural determination of membrane proteins of biological importance and ligand-receptor interactions by means of electron microscopy, X-ray diffraction, NMR, and computer simulation. Most efforts at the present stage, however, are being directed to finding suitable expression and purification systems and crystallization conditions for such proteins. The program is expected to be linked with the human full-length cDNA project and should lead to medical and industrial uses.

beta-Hairpins, alpha-helices, and the intermediates among the secondary structures in the energy landscape of a peptide from a distal beta-hairpin of SH3 domain

Energy landscape of a peptide, extracted from a distal beta-hairpin of src SH3 domain, in explicit water was obtained with the multicanonical molecular dynamics. A variety of beta-hairpins with various strand-strand hydrogen bonds were found in the energy landscape at 300 K. There was no energy barrier between random-coil and hairpins. Thus, the peptide conformation can easily change from the random-coil to the hairpins in the thermal fluctuations at 300 K. The landscape also included two clusters of alpha-helices, among which an energy barrier existed, and besides, these helix clusters were separated from the other conformations. Thus, the free-energy barrier exists among the helices and the other conformations. Intermediate clusters were found between the helix and the hairpin clusters. The current study showed that the isolated state of this peptide in water fluctuates among random-coil, beta-hairpin, and alpha-helix. In SH3 domain, which has a topology of mainly beta-protein, the whole-protein folding may proceed when the segment is folded in the beta-hairpin and the other parts of the protein are coupled with the beta-hairpin in an energetically or kinetically favorite way.

Hybrid Monte Carlo with multidimensional replica exchanges: conformational equilibria of the hypervariable regions of a llama VHH antibody domain

Since the structural repertoire of the hypervariable regions of human antibodies is known to be more restricted than what is implied by sequence variability, a common approach to structural prediction is to use a knowledge-based (KB) method, such as the canonical structure model (C. Chothia and A. M. Lesk, Journal of Molecular Biology, 1987, Vol. 196, pp. 901-917). However, this model is less successful when applied to camelid heavy chain antibodies. In this study, molecular simulations were used to examine the conformational equilibria of the hypervariable regions (H1, H2, and H3) of a llama heavy chain variable domain, for which KB predictions are poor. Simulations were carried out using both conventional molecular dynamics (MD) and hybrid Monte Carlo with multidimensional replica exchanges (HYMREX). The advantage of the latter method is its ability to selectively target parts of the Hamiltonian that can most readily improve sampling. A novel variant of HYMREX was implemented in which, besides the temperature, torsional interactions and the range of nonbonded interactions were varied. To compare the sampling abilities of MD and this HYMREX scheme, simulations were started from a misfolded conformational state. Overall, MD yielded final conformations more similar to the initial state, implying quasi-ergodic sampling. In contrast, HYMREX achieved more ergodic sampling, and the majority of conformations that it sampled agreed well with the known crystal structure. The HYMREX simulation results were used to help identify the chief interactions governing the conformational equilibria and to reexamine the key assumptions underlying the KB predictions. The data show that the H1 region exhibited significant conformational freedom, in support of the hypothesis that main-chain structural variability in this region could play a greater role in antigen binding in camelid antibodies than it does in normal antibodies. Key H1 residues and associated inter-loop interactions are conjectured to account for the poor KB predictions.

Dynamical origin of uniform sampling in multicanonical ensemble

The stochastic model describing the sampling process in multicanonical ensemble has been derived by considering the sampling process as an overdamped Brownian motion on the free energy surface. The essential dynamics of the multicanonical sampling has been characterized by a Langevin equation in a piecewise multivalleyed free energy landscape, modulated by a temperature-dependent curvature. Based on the stochastic model we showed that the multicanonical weight can be determined by interpolating maximum probability energy points of the canonical samplings at different temperatures.

Conformational transition states of a beta-hairpin peptide between the ordered and disordered conformations in explicit water

The conformational transition states of a beta-hairpin peptide in explicit water were identified from the free energy landscapes obtained from the multicanonical ensemble, using an enhanced conformational sampling calculation. The beta-hairpin conformations were significant at 300 K in the landscape, and the typical nuclear Overhauser effect signals were reproduced, consistent with the previously reported experiment. In contrast, the disordered conformations were predominant at higher temperatures. Among the stable conformations at 300 K, there were several free energy barriers, which were not visible in the landscapes formed with the conventional parameters. We identified the transition states around the saddle points along the putative folding and unfolding paths between the beta-hairpin and the disordered conformations in the landscape. The characteristic features of these transition states are the predominant hydrophobic contacts and the several hydrogen bonds among the side-chains, as well as some of the backbone hydrogen bonds. The unfolding simulations at high temperatures, 400 K and 500 K, and their principal component analyses also provided estimates for the transition state conformations, which agreed well with those at 400 K and 500 K deduced from the current free energy landscapes at 400 K and 500 K, respectively. However, the transition states at high temperatures were much more widely distributed on the landscape than those at 300 K, and their conformations were different.

Calibration of force-field dependency in free energy landscapes of peptide conformations by quantum chemical calculations

The free energy landscapes of peptide conformations were calibrated by ab initio quantum chemical calculations, after the enhanced conformational diversity search using the multicanonical molecular dynamics simulations. Three different potentials of mean force for an isolated dipeptide were individually obtained by the multicanonical molecular dynamics simulations using the conventional force fields, AMBER parm94, AMBER parm96, and CHARMm22. Each potential of mean force was then calibrated based upon the umbrella sampling algorithm from the adiabatic energy map that was calculated separately by the ab initio molecular orbital method, and all of the calibrated potentials of mean force coincided well. The calibration method was also applied to the simulations of a peptide dimer in explicit water models, and it was shown that the calibrated free energy landscapes did not depend on the force field used in the classical simulations, as far as the conformational space was sampled well. The current calibration method fuses the classical free energy calculation with the quantum chemical calculation, and it should generally make simulations for biomolecular systems much more reliable when combining with enhanced conformational sampling.

Energy landscape of a peptide consisting of alpha-helix, 3(10)-helix, beta-turn, beta-hairpin, and other disordered conformations

The energy landscape of a peptide [Ace-Lys-Gln-Cys-Arg-Glu-Arg-Ala-Nme] in explicit water was studied with a multicanonical molecular dynamics simulation, and the AMBER parm96 force field was used for the energy calculation. The peptide was taken from the recognition helix of the DNA-binding protein, c-MYB: A rugged energy landscape was obtained, in which the random-coil conformations were dominant at room temperature. The CD spectra of the synthesized peptide revealed that it is in the random state at room temperature. However, the 300 K canonical ensemble, Q(300K), contained alpha-helix, 3(10)-helix, beta-turn, and beta-hairpin structures with small but notable probabilities of existence. The complete alpha-helix, imperfect alpha-helix, and random-coil conformations were separated from one another in the conformational space. This means that the peptide must overcome energy barriers to form the alpha-helix. The overcoming process may correspond to the hydrogen-bond rearrangements from peptide-water to peptide-peptide interactions. The beta-turn, imperfect 3(10)-helix, and beta-hairpin structures, among which there are no energy barriers at 300 K, were embedded in the ensemble of the random-coil conformations. Two types of beta-hairpin with different beta-turn regions were observed in Q(300K). The two beta-hairpin structures may have different mechanisms for the beta-hairpin formation. The current study proposes a scheme that the random state of this peptide consists of both ordered and disordered conformations. In contrast, the energy landscape obtained from the parm94 force field was funnel like, in which the peptide formed the helical conformation at room temperature and random coil at high temperature.

Generalized-ensemble algorithms for molecular simulations of biopolymers

In complex systems with many degrees of freedom such as peptides and proteins, there exists a huge number of local-minimum-energy states. Conventional simulations in the canonical ensemble are of little use, because they tend to get trapped in states of these energy local minima. A simulation in generalized ensemble performs a random walk in potential energy space and can overcome this difficulty. From only one simulation run, one can obtain canonical-ensemble averages of physical quantities as functions of temperature by the single-histogram and/or multiple-histogram reweighting techniques. In this article we review uses of the generalized-ensemble algorithms in biomolecular systems. Three well-known methods, namely, multicanonical algorithm, simulated tempering, and replica-exchange method, are described first. Both Monte Carlo and molecular dynamics versions of the algorithms are given. We then present three new generalized-ensemble algorithms that combine the merits of the above methods. The effectiveness of the methods for molecular simulations in the protein folding problem is tested with short peptide systems.

Canonical antigen-binding loop structures in immunoglobulins: more structures, more canonical classes?

Grafting the antigen-binding loops onto a human antibody scaffold is a widely used technique to humanise murine antibodies. The success of this approach depends largely on the observation that the antigen-binding loops adopt only a limited number of canonical structures. Identification of the correct canonical structure is therefore essential. Algorithms that predict the main-chain conformation of the hypervariable loops using only the amino acid sequence often provide this information. Here, we describe new canonical loop conformations for the hypervariable regions H1 and H2 as found in single-domain antibody fragments of dromedaries or llama. Although the occurrence of these new loop conformations was not predicted by the algorithms used, it seems that they could occur in human or mouse antigen-binding loops. Their discovery indicates that the currently used set of canonical structures is incomplete and that the prediction algorithms should be extended to include these new structures.

Free energy landscapes of peptides by enhanced conformational sampling

The free energy landscapes of peptide conformations in water have been observed by the enhanced conformational sampling method, applying the selectively enhanced multicanonical molecular dynamics simulations. The conformations of the peptide dimers, -Gly-Gly-, -Gly-Ala-, -Gly-Ser-, -Ala-Gly-, -Asn-Gly-, -Pro-Gly-, -Pro-Ala-, and -Ala-Ala-, which were all blocked with N-terminal acetyl and C-terminal N-methyl groups, were individually sampled with the explicit TIP3P water molecules. From each simulation trajectory, we obtained the canonical ensemble at 300 K, from which the individual three-dimensional landscape was drawn by the potential of mean force using the three reaction coordinates: the backbone dihedral angle, psi, of the first amino acid, the backbone dihedral angle, phi, of the second amino acid, and the distance between the carbonyl oxygen of the N-terminal acetyl group and the C-terminal amide proton. The most stable state and several meta-stable states correspond to extended conformations and typical beta-turn conformations, and their free energy values were accounted for from the potentials of mean force at the states. In addition, the contributions from the intra-molecular energies of peptides and those from the hydration effects were analyzed. Consequently, the stable beta-turn conformations in the free energy landscape were consistent with the empirically preferred beta-turn types for each amino acid sequence. The thermodynamic values for the hydration effect were decomposed and they correlated well with the empirical values estimated from the solvent accessible surface area of each molecular conformation during the trajectories. The origin of the architecture of protein local fragments was analyzed from the viewpoint of the free energy and its decomposed factors.

H3-rules: identification of CDR-H3 structures in antibodies

For the third complementarity determining region of the antibody heavy chain (CDR-H3), we propose the 'H3-rules', which should identify the tertiary structure from the amino acid sequence of the CDR-H3 segment. A total of 100 CDR-H3 segments from well-determined crystal structures were analyzed. Distinctive relationships between the structures and the sequences were revealed from 55 segments, and the rules were examined for the other 45 segments and were verified. In some antibodies, basic residues at specific positions were revealed to be notable signals, with their ability to form salt bridges and to assume conformations inconsistent with the rules.