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The SARS-CoV-2 coronavirus is an enveloped, positive-sense single-stranded RNA virus that is responsible for the COVID-19 pandemic. The spike is a class I viral fusion glycoprotein that extends from the viral surface and is responsible for viral entry into the host cell and is the primary target of neutralizing antibodies. The receptor binding domain (RBD) of the spike samples multiple conformations in a compromise between evading immune recognition and searching for the host-cell surface receptor. Using atomistic simulations of the glycosylated wild-type spike in the closed and 1-up RBD conformations, we map the free energy landscape for RBD opening and identify interactions in an allosteric pocket that influence RBD dynamics. The results provide an explanation for experimental observation of increased antibody binding for a clinical variant with a substitution in this pocket. Our results also suggest the possibility of allosteric targeting of the RBD equilibrium to favor open states via binding of small molecules to the hinge pocket. In addition to potential value as experimental probes to quantify RBD conformational heterogeneity, small molecules that modulate the RBD equilibrium could help explore the relationship between RBD opening and S1 shedding.

Molecular dynamics (MD) simulations have become increasingly popular in studying the motions and functions of biomolecules. The accuracy of the simulation, however, is highly determined by the molecular mechanics (MM) force field (FF), a set of functions with adjustable parameters to compute the potential energies from atomic positions. However, the overall quality of the FF, such as our previously published ff99SB and ff14SB, can be limited by assumptions that were made years ago. In the updated model presented here (ff19SB), we have significantly improved the backbone profiles for all 20 amino acids. We fit coupled φ/ψ parameters using 2D φ/ψ conformational scans for multiple amino acids, using as reference data the entire 2D quantum mechanics (QM) energy surface. We address the polarization inconsistency during dihedral parameter fitting by using both QM and MM in aqueous solution. Finally, we examine possible dependency of the backbone fitting on side chain rotamer. To extensively validate ff19SB parameters, and to compare to results using other Amber models, we have performed a total of ∼5 ms MD simulations in explicit solvent. Our results show that after amino-acid-specific training against QM data with solvent polarization, ff19SB not only reproduces the differences in amino-acid-specific Protein Data Bank (PDB) Ramachandran maps better but also shows significantly improved capability to differentiate amino-acid-dependent properties such as helical propensities. We also conclude that an inherent underestimation of helicity is present in ff14SB, which is (inexactly) compensated for by an increase in helical content driven by the TIP3P bias toward overly compact structures. In summary, ff19SB, when combined with a more accurate water model such as OPC, should have better predictive power for modeling sequence-specific behavior, protein mutations, and also rational protein design. Of the explicit water models tested here, we recommend use of OPC with ff19SB.

The precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold’s capabilities by fine-tuning it with a specialized dataset consisting of exclusively high-resolution Class I MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold’s original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of Class I MHC-peptide interaction prediction. A comparative analysis was conducted against the homology-modeling-based method Pandora, as well as the AlphaFold multimer model. Our results demonstrate that our fine-tuned model outperforms others in terms of RMSD (median value for C-alpha atoms for peptides is 0.66 Å) and also provides enhanced predicted lDDT scores, offering a more reliable assessment of the predicted structures. These advances have substantial implications for computational immunology, potentially accelerating the development of novel therapeutics and vaccines by providing a more precise computational lens through which to view MHC-peptide interactions.

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

The enoyl-ACP reductase (ENR) catalyzes the last reaction in the elongation cycle of the bacterial type II fatty acid biosynthesis (FAS-II) pathway. While the FabI ENR is a well-validated drug target in organisms such as Mycobacterium tuberculosisand Staphylococcus aureus, alternate ENR isoforms have been discovered in other pathogens, including the FabV enzyme that is the sole ENR in Yersinia pestis(ypFabV). Previously, we showed that the prototypical ENR inhibitor triclosan was a poor inhibitor of ypFabV and that inhibitors based on the 2-pyridone scaffold were more potent [Hirschbeck, M. (2012) Structure20(1), 89–100]. These studies were performed with the T276S FabV variant. In the work presented here, we describe a detailed examination of the mechanism and inhibition of wild-type ypFabV and the T276S variant. The T276S mutation significantly reduces the affinity of diphenyl ether inhibitors for ypFabV (20-fold → 100-fold). In addition, while T276S ypFabV generally displays an affinity for 2-pyridone inhibitors higher than that of the wild-type enzyme, the 4-pyridone scaffold yields compounds with similar affinity for both wild-type and T276S ypFabV. T276 is located at the N-terminus of the helical substrate-binding loop, and structural studies coupled with site-directed mutagenesis reveal that alterations in this residue modulate the size of the active site portal. Subsequently, we were able to probe the mechanism of time-dependent inhibition in this enzyme family by extending the inhibition studies to include P142W ypFabV, a mutation that results in a gain of slow-onset inhibition for the 4-pyridone PT156.

AmberTools is a free and open-source collection of programs used to set up, run, and analyze molecular simulations. The newer features contained within AmberTools23 are briefly described in this Application note.

In this application note, we describe a tool which we developed to help structural biologists who study the SARS-CoV-2 spike glycoprotein. There are more than 500 structures of this protein available in the Protein Data Bank. These structures are available in different flavors: wild type spike, different variants, 2P substitutions, structures with bound antibodies, structures with Receptor Binding Domains (RBD) in closed or open conformation, etc. Understanding differences between these structures could provide insight into how the spike structure changes in different variants or upon interaction with different molecules such as receptors or antibodies. However, inconsistencies among deposited structures, such as different chain or sequence numbering, hamper a straightforward comparison of all structures. The tool described in this note fixes those chain inconsistencies and calculates the distribution of the requested distance between any two atoms across all SARS-CoV-2 spike structures available in the Protein Data Bank (excluding PDB files with only spike fragments such as the RBD), with the option to filter by various selections. The tool provides a histogram and cumulative frequency of the calculated distribution, as the ability to download the results and corresponding PDB IDs.

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

Molecular mechanics is powerful for its speed in atomistic simulations, but an accurate force field is required. The Amber ff99SB force field improved protein secondary structure balance and dynamics from earlier force fields like ff99, but weaknesses in side chain rotamer and backbone secondary structure preferences have been identified. Here, we performed a complete refit of all amino acid side chain dihedral parameters, which had been carried over from ff94. The training set of conformations included multidimensional dihedral scans designed to improve transferability of the parameters. Improvement in all amino acids was obtained as compared to ff99SB. Parameters were also generated for alternate protonation states of ionizable side chains. Average errors in relative energies of pairs of conformations were under 1.0 kcal/mol as compared to QM, reduced 35% from ff99SB. We also took the opportunity to make empirical adjustments to the protein backbone dihedral parameters as compared to ff99SB. Multiple small adjustments of φ and ψ parameters were tested against NMR scalar coupling data and secondary structure content for short peptides. The best results were obtained from a physically motivated adjustment to the φ rotational profile that compensates for lack of ff99SB QM training data in the β-ppII transition region. Together, these backbone and side chain modifications (hereafter called ff14SB) not only better reproduced their benchmarks, but also improved secondary structure content in small peptides and reproduction of NMR χ1 scalar coupling measurements for proteins in solution. We also discuss the Amber ff12SB parameter set, a preliminary version of ff14SB that includes most of its improvements.

Slow-onset enzyme inhibitors are of great interest for drug discovery programs since the slow dissociation of the inhibitor from the drug–target complex results in sustained target occupancy leading to improved pharmacodynamics. However, the structural basis for slow-onset inhibition is often not fully understood, hindering the development of structure-kinetic relationships and the rational optimization of drug-target residence time. Previously we demonstrated that slow-onset inhibition of the Mycobacterium tuberculosisenoyl-ACP reductase InhA correlated with motions of a substrate-binding loop (SBL) near the active site. In the present work, X-ray crystallography and molecular dynamics simulations have been used to map the structural and energetic changes of the SBL that occur upon enzyme inhibition. Helix-6 within the SBL adopts an open conformation when the inhibitor structure or binding kinetics is substrate-like. In contrast, slow-onset inhibition results in large-scale local refolding in which helix-6 adopts a closed conformation not normally populated during substrate turnover. The open and closed conformations of helix-6 are hypothesized to represent the EI and EI* states on the two-step induced-fit reaction coordinate for enzyme inhibition. These two states were used as the end points for nudged elastic band molecular dynamics simulations resulting in two-dimensional potential energy profiles that reveal the barrier between EI and EI*, thus rationalizing the binding kinetics observed with different inhibitors. Our findings indicate that the structural basis for slow-onset kinetics can be understood once the structures of both EI and EI* have been identified, thus providing a starting point for the rational control of enzyme–inhibitor binding kinetics.

The generalized Born (GB) model is one of the fastest implicit solvent models, and it has become widely adopted for Molecular Dynamics (MD) simulations. This speed comes with trade-offs, and many reports in the literature have pointed out weaknesses with GB models. Because the quality of a GB model is heavily affected by empirical parameters used in calculating solvation energy, in this work we have refit these parameters for GB-Neck, a recently developed GB model, in order to improve the accuracy of both the solvation energy and effective radii calculations. The data sets used for fitting are significantly larger than those used in the past. Comparing to other pairwise GB models like GB-OBC and the original GB-Neck, the new GB model (GB-Neck2) has better agreement with Poisson–Boltzmann (PB) in terms of reproducing solvation energies for a variety of systems ranging from peptides to proteins. Secondary structure preferences are also in much better agreement with those obtained from explicit solvent MD simulations. We also obtain near-quantitative reproduction of experimental structure and thermal stability profiles for several model peptides with varying secondary structure motifs. Extension to nonprotein systems will be explored in the future.

The commitment of transplant physicians to protect the physical and psychological health of potential donors is fundamental to the process of living donor organ transplantation. It is appropriate that strict regulations to govern an individual’s decision to donate have been developed. Some may argue that adherence to such regulations creates a doctor-patient relationship that is rooted in paternalism, which is in drastic contrast with a doctor-patient relationship that is rooted in patients’ autonomy, characteristic of most other operative interventions.In this article we analyze the similarities between cosmetic plastic surgery and living donor surgery as examples of surgeries governed by different ethical principles. It is interesting that, while the prevailing ethical approach in living donor surgery is based on paternalism, the ethical principle guiding cosmetic surgery is respect for patients’ autonomy. The purpose of this article is not to criticize either practice, but to suggest that, given the similarities between the two procedures, both operative interventions should be guided by the same ethical principle: a respect for patients’ autonomy. We further suggest that if living organ donation valued donors’ autonomy as much as cosmetic plastic surgery does, we might witness a wider acceptance of and increase in living organ donation.

Nitrogen mustard reloaded: Over 60 years after nitrogen mustards (NMs) were the first agents used to treat tumors by chemotherapy, we provide a method to generate the main DNA adduct formed by NMs and validate them by using molecular dynamics simulations (see graphic). We are able to provide amounts that permit extensive structural and biological studies.

We present the three-dimensional molecular theory of solvation (also known as 3D-RISM) coupled with molecular dynamics (MD) simulation by contracting solvent degrees of freedom, accelerated by extrapolating solvent-induced forces and applying them in large multiple time steps (up to 20 fs) to enable simulation of large biomolecules. The method has been implemented in the Amber molecular modeling package and is illustrated here on alanine-dipeptide and protein-G.

Base flipping is a common strategy utilized by many enzymes to gain access to the functional groups of nucleic acid bases in duplex DNA which are otherwise protected by the DNA backbone and hydrogen bonding with their partner bases. Several X-ray crystallography studies have revealed flipped conformations of nucleotides bound to enzymes. However, little is known about the base-flipping process itself, even less about the role of the enzymes. Computational studies have used umbrella sampling to elicit the free energy profile of the base-flipping process using a pseudodihedral angle to represent the reaction coordinate. In this study, we have used an unrestrained trajectory in which a flipped base spontaneously reinserted into the helix in order to evaluate and improve the previously defined pseudodihedral angle. Our modified pseudodihedral angles use a new atom selection to improve the numerical stability of the restraints and also provide better correlation to the extent of flipping observed in simulations. Furthermore, on the basis of the comparison of potential of mean force (PMF) generated using different reaction coordinates, we observed that the shape of a flipping PMF profile is strongly dependent on the definition of the reaction coordinate, even for the same data set.

Force-field validation is essential for the identification of weaknesses in current models and the development of more accurate models of biomolecules. NMR coupling and relaxation methods have been used to effectively diagnose the strengths and weaknesses of many existing force fields. Studies using the ff99SB force field have shown excellent agreement between experimental and calculated order parameters and residual dipolar calculations. However, recent studies have suggested that ff99SB demonstrates poor agreement with J-coupling constants for short polyalanines. We performed extensive replica-exchange molecular-dynamics simulations on Ala3and Ala5in TIP3P and TIP4P-Ew solvent models. Our results suggest that the performance of ff99SB is among the best of currently available models. In addition, scalar coupling constants derived from simulations in the TIP4P-Ew model show a slight improvement over those obtained using the TIP3P model. Despite the overall excellent agreement, the data suggest areas for possible improvement.

Replica exchange or parallel tempering molecular dynamics (REMD) is widely used to enhance the exploration of free energy landscapes for complex molecular systems. However its application to large systems is hampered by the scaling of the number of required replicas with an increasing system size. We recently proposed an improved REMD method where the exchange probabilities were calculated using a hybrid explicit/implicit solvent model. We previously tested this hybrid solvent REMD approach on alanine polypeptides of 1, 3, and 10 residues and obtained very good agreement with fully solvated REMD simulations while significantly reducing the number of replicas required. In this study we continue evaluating the applicability of the hybrid solvent REMD method through comparing the free energy of formation of ion pairs using model peptides. In accord with other studies, pure GB simulations resulted in overstabilized salt bridges, whereas the hybrid models produced free energy profiles in close agreement with fully solvated simulations, including solvent separated minima. Furthermore, the structure of the salt bridge in explicit solvent is reproduced by the hybrid solvent REMD method, while the GB simulations favor a different geometry.

In kidney paired donation (KPD), incompatible pairs exchange kidneys so that each recipient receives a compatible organ. This modality is underutilized partly because of the difficulty of finding a suitable match among incompatible pairs. Alternatively, recipients with compatible donors might enter KPD arrangements in order to be matched with a donor predicted to give greater allograft durability or for other altruistic reasons. Using simulated donors and recipients, we investigated the impact of allowing recipients and their compatible donors to participate in KPD. For KPD programs of any size, the participation of compatible donorrecipient pairs nearly doubled the match rate for incompatible pairs (28.2 to 64.5 for single-center program, 37.4 to 75.4 for national program). Legal, logistical, and governmental controversies have hampered the expansion of KPD in the United States by delaying the creation of a national program. The inclusion of compatible pairs into small single-center pools could achieve match rates that would surpass that which could be realized by a national list made up of only incompatible pairs. This new paradigm of KPD can immediately be instituted at the single-center level, while the greatest gains will be achieved by incorporating compatible pairs into a national program.

Although the medical excuse is routinely used by many transplant programs, ethical issues arising from its use have received little critical attention. The present review will define the medical excuse and briefly discuss its history, purposes, and use in the context of evaluating donor candidates, and will provide a framework for evaluating some of the ethical issues related to its use through consideration of, and comparison with, ethical issues arising from the use of deception in medical practice.