The motor protein kinesin moves over the microtubule (MT) by undergoing a motility cycle involving MT-bound and -unbound states. Compared with the structurally well-defined MT-bound state, very little is known about the behaviors of kinesin in the unbound state at the atomistic level. In order to maintain motility, the unbound head hovers near the MT, where the near-range interaction remains undefined. To this end, we perform a total of over 82-μs all-atom molecular dynamics simulations of a Kinesin-1 motor head detaching and hovering over the MT lattice by using the Anton-2 supercomputer. Resistance to unbinding depended strongly on the loading direction due to the uneven response of the MT-binding elements to pulling. Such directional anisotropy is consistent with easier unbinding of the rear head and resistance to load by the front head in a kinesin dimer. The interaction between a hovering head with the MT surface was evaluated across a 102-point grid with sufficient size and overlap to cover the periodic MT lattice. Interaction with the MT C-terminal tails (CTTs) versus MT surface was strongly location dependent, which results in regions of weak repulsion, relatively free diffusion, and a landing zone formed directly behind the next binding site where attraction to the MT surface is pronounced. The hovering head tends to stay upright with a reduced footprint on the MT and interacts differently between the α-tubulin CTT (αCTT) and β-tubulin CTT (βCTT), where it can "vine-swing" between the two, or brachiate. Unexpectedly, there were a few residues forming notable contacts, including L317 on α6 of kinesin, Y451 at the C terminus of αCTT, and F446 in the middle of βCTT. These results provide a foundation for studying the stepping or diffusion of kinesins, as well as the effects of MT post-translational modifications or interaction with other MT-associated proteins.

Background: The elicitation of broadly neutralizing antibodies against conserved antigenic epitopes has been a focus of universal vaccine research. To facilitate immunofocusing on the conserved influenza hemagglutinin (HA) stalk, we designed headless trimeric antigens, initially focusing on subtypes H1, H3, and H5, and subsequently expanding to eight additional HA subtypes. Results: The designs were first evaluated in silico; they were predicted to fold correctly by AlphaFold2, and remained stable in molecular dynamics simulations in isolation, as well as bound to a broadly neutralizing antibody. The antigens expressed in HEK293-derived cells in high yields, and eluted predominantly as trimers in SEC-HPLC. Future work will explore the use of mosaic nanoparticles decorated with headless antigens of various subtypes for the optimal elicitation of broadly neutralizing anti-influenza antibodies. Overall, our study advances the use of headless HA trimers as modular antigens toward a universal influenza vaccine.

The elicitation of broadly neutralizing antibodies (bnAbs) is a major goal of vaccine design for highly mutable pathogens, such as influenza, HIV, and coronavirus. Although many rational vaccine design strategies for eliciting bnAbs have been devised, their efficacies need to be evaluated in preclinical animal models and in clinical trials. To improve outcomes for such vaccines, it would be useful to develop methods that can predict vaccine efficacies against arbitrary pathogen variants. As a step in this direction, here, we describe a simple biologically motivated model of antibody reactivity elicited by nanoparticle-based vaccines using only antigen amino acid sequences, parametrized with a small sample of experimental antibody binding data from influenza or SARS-CoV-2 nanoparticle vaccinations. Results: The model is able to recapitulate the experimental data to within experimental uncertainty, is relatively insensitive to the choice of the parametrization/training set, and provides qualitative predictions about the antigenic epitopes exploited by the vaccine, which are testable by experiment. For the mosaic nanoparticle vaccines considered here, model results suggest indirectly that the sera obtained from vaccinated mice contain bnAbs, rather than simply different strain-specific Abs. Although the present model was motivated by nanoparticle vaccines, we also apply it to a mutlivalent mRNA flu vaccination study, and demonstrate good recapitulation of experimental results. This suggests that the model formalism is, in principle, sufficiently flexible to accommodate different vaccination strategies. Finally, we show how the model could be used to rank the efficacies of vaccines with different antigen compositions. Conclusions: Overall, this study suggests that simple models of vaccine efficacy parametrized with modest amounts of experimental data could be used to compare the effectiveness of designed vaccines.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published. They include the following: new faster simulation engines, accessible user interfaces for convenient workflows, and a vast array of simulation and analysis methods that encompass quantum mechanical, atomistic, and coarse-grained levels, as well as extensive coverage of force fields. In addition to providing the current snapshot of the CHARMM development, this review may serve as a starting point for exploring relevant theories and computational methods for tackling contemporary and emerging problems in biomolecular systems. CHARMM is freely available for academic and nonprofit research at https://academiccharmm.org/program.

Prediction of protein fitness from computational modeling is an area of active research in rational protein design. Here, we investigated whether protein fluctuations computed from molecular dynamics simulations can be used to predict the expression levels of SARS-CoV-2 receptor binding domain (RBD) mutants determined in the deep mutational scanning experiment of Starr et al. [Science (New York, N.Y.) 2022, 377, 420] Specifically, we performed more than 0.7 milliseconds of molecular dynamics (MD) simulations of 557 mutant RBDs in triplicate to achieve statistical significance under various simulation conditions. Our results show modest but significant anticorrelation in the range [-0.4, -0.3] between expression and RBD protein flexibility. A simple linear regression machine learning model achieved correlation coefficients in the range [0.7, 0.8], thus outperforming MD-based models, but required about 25 mutations at each residue position for training.

The local hydration around tetrameric hemoglobin (Hb) in its T0 and R4 conformational substates is analyzed based on molecular dynamics simulations. Analysis of the local hydrophobicity (LH) for all residues at the α1β2 and α2β1 interfaces, responsible for the quaternary T → R transition, which is encoded in the Monod–Wyman–Changeux model, as well as comparison with earlier computations of the solvent accessible surface area, makes clear that the two quantities measure different aspects of hydration. Local hydrophobicity quantifies the presence and structure of water molecules at the interface, whereas “buried surface” reports on the available space for solvent. For simulations with Hb frozen in its T0 and R4 states, the correlation coefficient between LH and buried surface is 0.36 and 0.44, respectively, but it increases considerably if the 95% confidence interval is used. The LH with Hb frozen and flexible changes little for most residues at the interfaces but is significantly altered for a few select ones: Thr41α, Tyr42α, Tyr140α, Trp37β, Glu101β (for T0) and Thr38α, Tyr42α, Tyr140α (for R4). The number of water molecules at the interface is found to increase by ∼25% for T0 → R4, which is consistent with earlier measurements. Since hydration is found to be essential to protein function, it is clear that hydration also plays an essential role in allostery.

Infection by sarbecoviruses begins with the attachment of the homotrimeric viral "spike" protein to the angiotensin-converting enzyme 2 receptor on the surface of mammalian cells. This requires one or more receptor-binding domains (RBDs) to be in the open (up) position. Here, we present the results of long molecular dynamics simulations with umbrella sampling (US) to compute a one-dimensional free energy profile of RBD opening/closing and the associated transition times. After ≃3.58μs of simulation time per US window (∼229 μs in total), which was required to approach trajectory decorrelation, the computed free energy profile was found to be without large barriers. This suggests that the RBD diffuses between the open and closed positions without significant energetic hindrance. This interpretation appears consistent with experiments but is at odds with some previous simulations. Modeling the RBD motion as diffusive dynamics along the computed free energy profile, we find that the overall time required for the transition is only about 2 μs, which is 5 orders of magnitude shorter than experimentally measured transition times. We speculate that the most likely reason for the transition time mismatch is our use of very short glycans, which was required to make the simulations performed here feasible. Despite the long simulation times, the final free energy profile is not fully converged with statistical errors of ≃1.16 kcal/mol, which were found to be consistent with the slow time decay in the autocorrelation of the conformational motions of the protein. The simulation lengths that would be required to obtain fully converged results remain unknown, but the present calculations would benefit from at least an order-of-magnitude extension.

The local hydration around tetrameric hemoglobin (Hb) in its T0 and R4 conformational substates is analyzed based on molecular dynamics simulations. Analysis of the local hydrophobicity (LH) for all residues at the α1β2 and α2β1 interfaces, responsible for the quaternary T → R transition, which is encoded in the Monod-Wyman-Changeux model, as well as comparison with earlier computations of the solvent accessible surface area, makes clear that the two quantities measure different aspects of hydration. Local hydrophobicity quantifies the presence and structure of water molecules at the interface, whereas "buried surface" reports on the available space for solvent. For simulations with Hb frozen in its T0 and R4 states, the correlation coefficient between LH and buried surface is 0.36 and 0.44, respectively, but it increases considerably if the 95% confidence interval is used. The LH with Hb frozen and flexible changes little for most residues at the interfaces but is significantly altered for a few select ones: Thr41α, Tyr42α, Tyr140α, Trp37β, Glu101β (for T0) and Thr38α, Tyr42α, Tyr140α (for R4). The number of water molecules at the interface is found to increase by ∼25% for T0 → R4, which is consistent with earlier measurements. Since hydration is found to be essential to protein function, it is clear that hydration also plays an essential role in allostery.

The elicitation of broadly neutralizing antibodies (bnAbs) is a major goal in the design of vaccines against rapidly-mutating viruses. In the case of influenza, many bnAbs that target conserved epitopes on the stem of the hemagglutinin protein (HA) have been discovered. However, these antibodies are rare, are not boosted well upon reinfection, and often have low neutralization potency, compared to strain-specific antibodies directed to the HA head. Different hypotheses have been proposed to explain this phenomenon. We use a coarse-grained computational model of the germinal center reaction to investigate how B-cell receptor binding valency affects the growth and affinity maturation of competing B-cells. We find that receptors that are unable to bind antigen bivalently, and also those that do not bind antigen cooperatively, have significantly slower rates of growth, memory B-cell production, and, under certain conditions, rates of affinity maturation. The corresponding B-cells are predicted to be outcompeted by B-cells that bind bivalently and cooperatively. We use the model to explore strategies for a universal influenza vaccine,e.g., how to boost the concentrations of the slower growing cross-reactive antibodies directed to the stem. The results suggest that, upon natural reinfections subsequent to vaccination, the protectiveness of such vaccines would erode, possibly requiring regular boosts. Collectively, our results strongly support the importance of bivalent antibody binding in immunodominance, and suggest guidelines for developing a universal influenza vaccine.

This paper describes ppdx, a python workflow tool that combines protein sequence alignment, homology modeling, and structural refinement, to compute a broad array of descriptors for characterizing protein-protein interactions. The descriptors can be used to predict various properties of interest, such as protein-protein binding affinities, or inhibitory concentrations (IC50), using approaches that range from simple regression to more complex machine learning models. The software is highly modular. It supports different protocols for generating structures, and 95 descriptors can be currently computed. More protocols and descriptors can be easily added. The implementation is highly parallel and can fully exploit the available cores in a single workstation, or multiple nodes on a supercomputer, allowing many systems to be analyzed simultaneously. As an illustrative application, ppdx is used to parametrize a model that predicts the IC50 of a set of antigens and a class of antibodies directed to the influenza hemagglutinin stalk.

Constrained peptides represent a relatively new class of biologic therapeutics, which have the potential to overcome several limitations of small-molecule drugs, and of designed antibodies. Because of their modest size, the rational design of such peptides is becoming increasingly amenable to computer simulation; multi-microsecond molecular dynamic (MD) simulations are now routinely possible on consumer-grade graphical processors (GPUs). Here, we describe the procedures for performing and analyzing MD simulations of hydrocarbon-stapled peptides using the CHARMM energy function, in isolation and in complex with a binding partner, to investigate their conformational properties and to compute changes in their binding affinity upon mutation.

The design of vaccines against highly mutable pathogens, such as HIV and influenza, requires a detailed understanding of how the adaptive immune system responds to encountering multiple variant antigens (Ags). Here, we describe a multiscale model of B cell receptor (BCR) affinity maturation that employs actual BCR nucleotide sequences and treats BCR/Ag interactions in atomistic detail. We apply the model to simulate the maturation of a broadly neutralizing Ab (bnAb) against HIV. Starting from a germline precursor sequence of the VRC01 anti-HIV Ab, we simulate BCR evolution in response to different vaccination protocols and different Ags, which were previously designed by us. The simulation results provide qualitative guidelines for future vaccine design and reveal unique insights into bnAb evolution against the CD4 binding site of HIV. Our model makes possible direct comparisons of simulated BCR populations with results of deep sequencing data, which will be explored in future applications.

Highly mutable pathogens pose daunting challenges for antibody design. The usual criteria of high potency and specificity are often insufficient to design antibodies that provide long-lasting protection. This is due, in part, to the ability of the pathogen to rapidly acquire mutations that permit them to evade the designed antibodies. To overcome these limitations, design of antibodies with a larger neutralizing breadth can be pursued. Such broadly neutralizing antibodies (bnAbs) should remain targeted to a specific epitope, yet show robustness against pathogen mutability, thereby neutralizing a higher number of antigens. This is particularly important for highly mutable pathogens, like the influenza virus and the human immunodeficiency virus (HIV). The protocol describes a method for computing the "breadth" of a given antibody, an essential aspect of antibody design.

„Ein Buch voller Inspiration. Martin Karplus erzählt meisterhaft eine Geschichte über Spitzenwissenschaft und stellt gleichzeitig Aussagen über die Zukunft infrage.“ (Dudley Herschbach, Chemie-Nobelpreisträger 1986) „Der ergreifende Lebensbericht eines versierten Ornithologen, Fotografen, Kochs, politischen „Umstürzlers“, Chemie-Nobelpreisträgers und Menschenfreundes ist reich an Worten und Bildern. Martin lässt uns die Welt durch seine Augen sehen und lenkt den Blick mit außergewöhnlicher gedanklicher Klarheit und Kompetenz auf das Wesentliche. Seine Berichte über Menschen, Orte und Leistungen, aber auch seine Visionen für die Zukunft vermitteln einen optimistischen, einfühlsamen Blick auf unsere Welt.“ (John Straub, Boston University, USA) „In diesem Buch erzählt Martin Karplus sehr lebendig sein Leben. Aufgewachsen in einer jüdischen Großfamilie in Wien, vertrieben 1938 durch die Nationalsozialisten, machte er in den USA eine beeindruckende Karriere zum weltberühmten Wissenschaftler. Die Beschreibungen von Martin Karplus, sei es über seine Neugier in Bezug auf die Wissenschaft, seine Passion zur Fotografie oder seine Erlebnisse mit berühmten Köchen, machen dieses Buch, besonders auch für die junge Generation, absolut lesenswert.“ (Anton Zeilinger, Präsident der Österreichischen Akademie der Wissenschaften)

A vaccine which is effective against the HIV virus is considered to be the best solution to the ongoing global HIV/AIDS epidemic. In the past thirty years, numerous attempts to develop an effective vaccine have been made with little or no success, due, in large part, to the high mutability of the virus. More recent studies showed that a vaccine able to elicit broadly neutralizing antibodies (bnAbs), that is, antibodies that can neutralize a high fraction of global virus variants, has promise to protect against HIV. Such a vaccine has been proposed to involve at least three separate stages: First, activate the appropriate precursor B cells; second, shepherd affinity maturation along pathways toward bnAbs; and, third, polish the Ab response to bind with high affinity to diverse HIV envelopes (Env). This final stage may require immunization with a mixture of Envs. In this paper, we set up a framework based on theory and modeling to design optimal panels of antigens to use in such a mixture. The designed antigens are characterized experimentally and are shown to be stable and to be recognized by known HIV antibodies.

The interface between hemoglobin (Hb) and its environment, in particular water, is of great physiological relevance. Here, results from in vitro, in vivo, and computational experiments (molecular dynamics simulations) are summarized and put into perspective. One of the main findings from the computations is that the stability of the deoxy, ligand-free T-state (T-0) can be stabilized relative to the deoxy R-state (R-0) only in sufficiently large simulation boxes for the hydrophobic effect to manifest itself. This effect directly influences protein stability and is operative also under physiological conditions. Furthermore, molecular simulations provide a dynamical interpretation of the Perutz model for Hb function. Results from experiments using higher protein concentrations and realistic cellular environments are also discussed. One of the next great challenges for computational studies, which as we show is likely to be taken up in the near future, is to provide a molecular-level understanding of the dynamics of proteins in such crowded environments.

A reaction path is presented by which the ef- fects of oxygen binding in hemoglobin are transmitted from a heme group to the surface of its subunit. Starting from the known deoxy geometry, it is shown by calculations with em- pirical energy functions and comparisons with available data how the change in heme geometry on ligation introduces a perturbation that leads to the tertiary structural alterations es- sential for cooperativity. It is found that there is little strain on the unliganded heme; instead, the reduced oxygen affinity of hemoglobin results from the strain on the liganded subunit in a tetramer with the deoxy quaternary structure.

Efficient search for DNA damage embedded in vast expanses of the DNA genome presents one of the greatest challenges to DNA repair enzymes. We report here crystal structures of human 8-oxoguanine (oxoG) DNA glycosylase, hOGG1, that interact with the DNA containing the damaged base oxoG and the normal base G while they are nested in the DNA helical stack. The structures reveal that hOGG1 engages the DNA using different protein-DNA contacts from those observed in the previously determined lesion recognition complex and other hOGG1-DNA complexes. By applying molecular dynamics simulations, we have determined the pathways taken by the lesion and normal bases when extruded from the DNA helix and their associated free energy profiles. These results reveal how the human oxoG DNA glycosylase hOGG1 locates the lesions inside the DNA helix and facilitates their extrusion for repair.

The water dynamics, as characterized by the local hydrophobicity (LH), is investigated for tetrameric hemoglobin and dimeric melittin. For the T0 to R0 transition in Hb it is found that LH provides additional molecular-level insight into the Perutz mechanism, i.e., the breaking and formation of salt bridges at the alpha1 / beta2 and alpha2 / beta1 interface is accompanied by changes in LH. For Hb in cubic water boxes with 90 Aengstroem and 120 Aengstroem edge length it is observed that following a decrease in LH as a consequence of reduced water density or change of water orientation at the protein/water interface the alpha / beta interfaces are destabilized; this is a hallmark of the Perutz stereochemical model for the T to R transition in Hb. The present work thus provides a dynamical view of the classical structural model relevant to the molecular foundations of Hb function. For dimeric melittin, earlier results by Cheng and Rossky (Nature, 1998, 392, 696-699) are confirmed and interpreted on the basis of LH from simulations in which the protein structure is frozen. For the flexible melittin dimer the changes in the local hydration can be as much as 30 % than for the rigid dimer, reflecting the fact that protein and water dynamics are coupled.

We present an extension of the locally enhanced sampling method. A restraint potential is introduced to drive the many-replica system to the canonical ensemble corresponding to the physical, single-replica system. Convergence properties are demonstrated using a model rugged two-dimensional potential, for which sampling by conventional equilibrium molecular dynamics is inefficient. Restrained locally enhanced sampling (RLES) is found to explore the space of configurations with an efficiency comparable to that of temperature replica exchange. To demonstrate the potential of RLES for realistic applications, the method is used to fold the 12-residue tryptophan zipper miniprotein in explicit solvent. The RLES algorithm can be incorporated into existing LES implementations with minor code modifications.