Molecular dynamics analysis of antibody recognition and escape by human H1N1 influenza hemagglutinin

Unraveling Bacterial Single-Stranded Sequence Specificities: Insights from Molecular Dynamics and MMPBSA Analysis of Oligonucleotide Probes

We utilized molecular dynamics (MD) simulations and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) free energy calculations to investigate the specificity of two oligonucleotide probes, namely probe B and probe D, in detecting single-stranded DNA (ssDNA) within three bacteria families: Enterobacteriaceae, Pasteurellaceae, and Vibrionaceae. Due to the limited understanding of molecular mechanisms in the previous research, we have extended the discussion to focus specifically on investigating the binding process of bacteria-probe DNA duplexes, with an emphasis on analyzing the binding free energy. The role of electrostatic contributions in the specificity between the oligonucleotide probes and the bacterial ssDNAs was investigated and found to be crucial. Our calculations yielded results that were highly consistent with the experimental data. Through our study, we have successfully exhibited the benefits of utilizing in-silico approaches as a powerful virtual-screening tool, particularly in research areas that demand a thorough comprehension of molecular interactions.

Computer-aided Affinity Enhancement of a Cross-reactive Antibody against Dengue Virus Envelope Domain III

The dengue virus (DENV), composed of four distinct but serologically related Flaviviruses, causes the most important emerging viral disease, with nearly 400 million infections yearly. Currently, there are no approved therapies. Although DENV infection induces lifelong immunity against the same serotype, the antibodies raised contribute to severe disease in heterotypic infections. Therefore, understanding the mechanism of DENV neutralization by antibodies is crucial in the design of vaccines against all serotypes. This study reports a comparative structural and energetic analysis of the monoclonal antibody (mAb) 4E11 in complex with its target domain III of the envelope protein for all four DENV serotypes. We use extensive replica molecular dynamics simulations in conjunction with the binding free energy calculations. Further single point and double mutations were designed through computational site-directed mutagenesis and observed that the re-engineered antibody exhibits high affinity to binding and broadly neutralizing activity against serotypes. Our results showed improved binding affinity by the gain of enthalpy, which could be attributed to the stabilization of salt-bridge and hydrogen bond interactions at the antigen-antibody interface. The findings provide valuable results in understanding the structural dynamics and energetic contributions that will be helpful to the design of high-affinity antibodies against dengue infections.

Interfacial water molecules contribute to antibody binding to the receptor-binding domain of SARS-CoV-2 spike protein

Antibodies that recognize the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), especially the neutralizing antibodies, carry great hope in the treatment and final elimination of COVID-19. Driven by a synchronized global effort, thousands of antibodies against the spike protein have been identified during the past two years, with the structural information available at atomistic detail for hundreds of these antibodies. We developed an improved molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) method including explicitly treated interfacial water to calculate the binding free energy between representative antibodies and the receptor binding domain (RBD) domain of SARS-COV-2 spike proteins. We discovered that explicit treatment of water molecules located at the interface between RBD and antibody effectively improves the results for the WT and variants of concern (VOC) systems. Interfacial water molecules, together with surface and internal water molecules, behave drastically from bulk water and exert peculiar impacts on protein dynamics and energy, and thus warrant explicit treatment to complement implicit solvent models. Our results illustrate the importance of including interfacial water molecules to approach efficient and reliable prediction of binding free energy.Communicated by Ramaswamy H. Sarma.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Unraveling the Tomaralimab Epitope on the Toll-like Receptor 2 via Molecular Dynamics and Deep Learning

Tomaralimab (OPN-305) is the first humanized immunoglobulin G4 monoclonal antibody against TLR2 and is designed to prevent inflammation that is driven by inappropriate or excessive activation of innate immune pathways. Here, we constructed a homology model of Tomaralimab and its complex with TLR2 at different mapped epitopes and unraveled their behavior at the atomistic level. Furthermore, we predicted a novel epitope (leucine-rich region 9-12) near the lipopeptide-binding site that can be targeted and studied for the utility of therapeutic antibodies. A geometric deep learning algorithm was used to envisage Tomaralimab binding affinity changes upon mutation. There was a significant difference in binding affinity for Tomaralimab following epitope-mutated alanine substitutions of Val266, Pro294, Arg295, Asn319, Pro326, and His372. Using deep learning-based ΔΔG prediction, we computationally contrasted human TLR2-TLR2, TLR2-TLR1, and TLR2-TLR6 dimerization. These results reveal the mechanism that underlies Tomaralimab binding to TLR2 and should help to design structure-based mimics or bispecific antibodies that can be used to inhibit both lipopeptide-binding and TLR2 dimerization.

Higher Affinity Antibodies Bind With Lower Hydration and Flexibility in Large Scale Simulations

We have carried out a long-timescale simulation study on crystal structures of nine antibody-antigen pairs, in antigen-bound and antibody-only forms, using molecular dynamics with enhanced sampling and an explicit water model to explore interface conformation and hydration. By combining atomic level simulation and replica exchange to enable full protein flexibility, we find significant numbers of bridging water molecules at the antibody-antigen interface. Additionally, a higher proportion of interactions excluding bulk waters and a lower degree of antigen bound CDR conformational sampling are correlated with higher antibody affinity. The CDR sampling supports enthalpically driven antibody binding, as opposed to entropically driven, in that the difference between antigen bound and unbound conformations do not correlate with affinity. We thus propose that interactions with waters and CDR sampling are aspects of the interface that may moderate antibody-antigen binding, and that explicit hydration and CDR flexibility should be considered to improve antibody affinity prediction and computational design workflows.

Computational Analysis of Binding Interactions between the Ryanodine Receptor Type 2 and Calmodulin

Mutations in the cardiac ryanodine receptor type 2 (RyR2) have been linked to a variety of cardiac arrhythmias, such as catecholaminergic polymorphic ventricular tachycardia (CPVT). RyR2 is regulated by calmodulin (CaM), and mutations that disrupt their interaction can cause aberrant calcium release, leading to an arrhythmia. It was recently shown that increasing the RyR2-CaM binding affinity could rescue a defective CPVT-related RyR2 channel to near wild-type behavior. However, the interactions that determine the binding affinity at the RyR2-CaM binding interface are not well understood. In this study, we identify the key domains and interactions, including several new interactions, involved in the binding of CaM to RyR2. Also, our comparison between the wild-type and V3599K mutant suggests how the RyR2-CaM binding affinity can be increased via a change in the central and N-terminal lobe binding contacts for CaM. This computational approach provides new insights into the effect of a mutation at the RyR2-CaM binding interface, and it may find utility in drug design for the future treatment of cardiac arrhythmias.

Protein-Protein Interactions: Insight from Molecular Dynamics Simulations and Nanoparticle Tracking Analysis

Protein-protein interaction plays an essential role in almost all cellular processes and biological functions. Coupling molecular dynamics (MD) simulations and nanoparticle tracking analysis (NTA) assay offered a simple, rapid, and direct approach in monitoring the protein-protein binding process and predicting the binding affinity. Our case study of designed ankyrin repeats proteins (DARPins)—AnkGAG1D4 and the single point mutated AnkGAG1D4-Y56A for HIV-1 capsid protein (CA) were investigated. As reported, AnkGAG1D4 bound with CA for inhibitory activity; however, it lost its inhibitory strength when tyrosine at residue 56 AnkGAG1D4, the most key residue was replaced by alanine (AnkGAG1D4-Y56A). Through NTA, the binding of DARPins and CA was measured by monitoring the increment of the hydrodynamic radius of the AnkGAG1D4-gold conjugated nanoparticles (AnkGAG1D4-GNP) and AnkGAG1D4-Y56A-GNP upon interaction with CA in buffer solution. The size of the AnkGAG1D4-GNP increased when it interacted with CA but not AnkGAG1D4-Y56A-GNP. In addition, a much higher binding free energy (∆GB) of AnkGAG1D4-Y56A (−31 kcal/mol) obtained from MD further suggested affinity for CA completely reduced compared to AnkGAG1D4 (−60 kcal/mol). The possible mechanism of the protein-protein binding was explored in detail by decomposing the binding free energy for crucial residues identification and hydrogen bond analysis.

Structural and molecular analyses of functional epitopes and escape mutants in Japanese encephalitis virus envelope protein domain III

The Japanese encephalitis virus (JEV) is one of the vector borne causes of encephalitis found in southeastern Asia. This positive single-stranded RNA virus is a member of the Flaviviridae family, which notably includes dengue, tick-borne, West Nile, Zika as well as yellow fever, and transmits to humans by infected mosquitos. The main site of interactions for antibodies against this virus is the envelope protein domain III (ED3). The present report investigates the time-dependent structural and conformational changes of JEV ED3 functional epitopes and escape mutants by computer simulations. The results indicate the presence of significant structural differences between the functional epitopes and the escape mutants. Mutation-induced structural/conformational instabilities of this type can decrease the antibody neutralization activity. Among the different escape mutants studied here, Ser40Lys/Asp41Arg appear to be most unstable, while Ser40Glu/Asp41Leu exhibit the lowest structural variations. The highest level of escape mutation observed in Ser40Lys is linked to the relatively higher values of root mean square deviation/fluctuation found in the molecular dynamics simulation of this protein. Secondary-structure deviations and depletion of H bonding are other contributing factors to the protein’s increased instability. Overall, the proteins with residue 41 mutations are found to be structurally more ordered than those with residue 40 mutations. The detailed time-based structural assessment of the mutant epitopes described here may contribute to the development of novel vaccines and antiviral drugs necessary to defend against future outbreaks of JEV escape mutants.

Toward rational antibody design: recent advancements in molecular dynamics simulations

Because antibodies have become an important therapeutic tool, rational antibody design is a challenging issue involving various science and technology fields. From the computational aspect, many types of design-assist methods have been developed, but their accuracy is not fully satisfactory. Because of recent advancements in computational power, molecular dynamics (MD) simulation has become a helpful tool to trace the motion of proteins and to characterize their properties. Thus, MD simulation has been applied to various systems involving antigen-antibody complexes and has been shown to provide accurate insight into antigen-antibody interactions and dynamics at an atomic resolution. Therefore, it is highly possible that MD simulation will play several roles complementing the conventional antibody design. In this review, we address several important features of MD simulation in the context of rational antibody design.

Optimisation of human VH domain antibodies specific to Mycobacterium tuberculosis heat shock protein (HSP16.3)

Mycobacterium tuberculosis (Mtb) 16.3 kDa heat shock protein 16.3 (HSP16.3) is a latency-associated antigen that can be targeted for latent tuberculosis (TB) diagnostic and therapeutic development. We have previously developed human V_H domain antibodies (dAbs; clone E3 and F1) specific against HSP16.3. In this work, we applied computational methods to optimise and design the antibodies in order to improve the binding affinity with HSP16.3. The V_H domain antibodies were first docked to the dimer form of HSP16.3 and further sampled using molecular dynamics simulation. The calculated binding free energy of the HSP16.3-dAb complexes showed non-polar interactions were responsible for the antigen-antibody association. Per-residue free energy decomposition and computational alanine scanning have identified one hotspot residue for E3 (Y391) and 4 hotspot residues for F1 (M394, Y396, R397 and M398). These hotspot residues were then mutated and evaluated by binding free energy calculations. Phage ELISA assay was carried out on the potential mutants (E3_Y391W, F1_M394E, F1_R397N and F1_M398Y). The experimental assay showed improved binding affinities of E3_Y391W and F1_M394E against HSP16.3 compared with the wild type E3 and F1. This case study has thus showed in silico methods are able to assist in optimisation or improvement of antibody-antigen binding.

Deciphering evolution of immune recognition in antibodies

Background

Antibody, the primary effector molecule of the immune system, evolves after initial encounter with the antigen from a precursor form to a mature one to effectively deal with the antigen. Antibodies of a lineage diverge through antigen-directed isolated pathways of maturation to exhibit distinct recognition potential. In the context of evolution in immune recognition, diversity of antigen cannot be ignored. While there are reports on antibody lineage, structural perspective with respect to diverse recognition potential in a lineage has never been studied. Hence, it is crucial to evaluate how maturation leads to topological tailoring within a lineage enabling them to interact with significantly distinct antigens.

Results

A data-driven approach was undertaken for the study. Global experimental mouse and human antibody-antigen complex structures from PDB were compiled into a coherent database of germline-linked antibodies bound with distinct antigens. Structural analysis of all lineages showed variations in CDRs of both H and L chains. Observations of conformational adaptation made from analysis of static structures were further evaluated by characterizing dynamics of interaction in two lineages, mouse V_H1–84 and human V_H5–51. Sequence and structure analysis of the lineages explained that somatic mutations altered the geometries of individual antibodies with common structural constraints in some CDRs. Additionally, conformational landscape obtained from molecular dynamics simulations revealed that incoming pathogen led to further conformational divergence in the paratope (as observed across datasets) even while maintaining similar overall backbone topology. MM-GB/SA analysis showed binding energies to be in physiological range. Results of the study are coherent with experimental observations.

Conclusions

The findings of this study highlight basic structural principles shaping the molecular evolution of a lineage for significantly diverse antigens. Antibodies of a lineage follow different developmental pathways while preserving the imprint of the germline. From the study, it can be generalized that structural diversification of the paratope is an outcome of natural selection of a conformation from an available ensemble, which is further optimized for antigen interaction. The study establishes that starting from a common lineage, antibodies can mature to recognize a wide range of antigens. This hypothesis can be further tested and validated experimentally.

Electronic supplementary material

The online version of this article (10.1186/s12900-018-0096-1) contains supplementary material, which is available to authorized users.

All-atom virus simulations

The constant threat of viral disease can be combated by the development of novel vaccines and therapeutics designed to disrupt key features of virus structure or infection cycle processes. Such development relies on high-resolution characterization of viruses and their dynamical behaviors, which are often challenging to obtain solely by experiment. In response, all-atom molecular dynamics simulations are widely leveraged to study the structural components of viruses, leading to some of the largest simulation endeavors undertaken to date. The present work reviews exemplary all-atom simulation work on viruses, as well as progress toward simulating entire virions.

Recent Developments and Applications of the MMPBSA Method

The Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) approach has been widely applied as an efficient and reliable free energy simulation method to model molecular recognition, such as for protein-ligand binding interactions. In this review, we focus on recent developments and applications of the MMPBSA method. The methodology review covers solvation terms, the entropy term, extensions to membrane proteins and high-speed screening, and new automation toolkits. Recent applications in various important biomedical and chemical fields are also reviewed. We conclude with a few future directions aimed at making MMPBSA a more robust and efficient method.

A Kepler Workflow Tool for Reproducible AMBER GPU Molecular Dynamics

With the drive toward high throughput molecular dynamics (MD) simulations involving ever-greater numbers of simulation replicates run for longer, biologically relevant timescales (microseconds), the need for improved computational methods that facilitate fully automated MD workflows gains more importance. Here we report the development of an automated workflow tool to perform AMBER GPU MD simulations. Our workflow tool capitalizes on the capabilities of the Kepler platform to deliver a flexible, intuitive, and user-friendly environment and the AMBER GPU code for a robust and high-performance simulation engine. Additionally, the workflow tool reduces user input time by automating repetitive processes and facilitates access to GPU clusters, whose high-performance processing power makes simulations of large numerical scale possible. The presented workflow tool facilitates the management and deployment of large sets of MD simulations on heterogeneous computing resources. The workflow tool also performs systematic analysis on the simulation outputs and enhances simulation reproducibility, execution scalability, and MD method development including benchmarking and validation.

Investigating Substitutions in Antibody-Antigen Complexes Using Molecular Dynamics: A Case Study with Broad-spectrum, Influenza A Antibodies

In studying the binding of host antibodies to the surface antigens of pathogens, the structural and functional characterization of antibody–antigen complexes by X-ray crystallography and binding assay is important. However, the characterization requires experiments that are typically time consuming and expensive: thus, many antibody–antigen complexes are under-characterized. For vaccine development and disease surveillance, it is often vital to assess the impact of amino acid substitutions on antibody binding. For example, are there antibody substitutions capable of improving binding without a loss of breadth, or antigen substitutions that lead to antigenic escape? The questions cannot be answered reliably from sequence variation alone, exhaustive substitution assays are usually impractical, and alanine scans provide at best an incomplete identification of the critical residue–residue interactions. Here, we show that, given an initial structure of an antibody bound to an antigen, molecular dynamics simulations using the energy method molecular mechanics with Generalized Born surface area (MM/GBSA) can model the impact of single amino acid substitutions on antibody–antigen binding energy. We apply the technique to three broad-spectrum antibodies to influenza A hemagglutinin and examine both previously characterized and novel variant strains observed in the human population that may give rise to antigenic escape. We find that in some cases the impact of a substitution is local, while in others it causes a reorientation of the antibody with wide-ranging impact on residue–residue interactions: this explains, in part, why the change in chemical properties of a residue can be, on its own, a poor predictor of overall change in binding energy. Our estimates are in good agreement with experimental results—indeed, they approximate the degree of agreement between different experimental techniques. Simulations were performed on commodity computer hardware; hence, this approach has the potential to be widely adopted by those undertaking infectious disease research. Novel aspects of this research include the application of MM/GBSA to investigate binding between broadly binding antibodies and a viral glycoprotein; the development of an approach for visualizing substrate–ligand interactions; and the use of experimental assay data to rescale our predictions, allowing us to make inferences about absolute, as well as relative, changes in binding energy.