MHC-Fine: Fine-tuned AlphaFold for precise MHC-peptide complex prediction.

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 root-mean-square deviation (median value for Cα atoms for peptides is 0.66 Å) and also provides enhanced predicted local distance difference test 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.

Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment.

Ribonucleic acid (RNA) molecules can adopt a variety of secondary and tertiary structures in solution, with stem-loops being one of the more common motifs. Here, we present a systematic analysis of 15 RNA stem-loop sequences simulated with molecular dynamics simulations in an implicit solvent environment. Analysis of RNA cluster ensembles showed that the stem-loop structures can generally adopt the A-form RNA in the stem region. Loop structures are more sensitive, and experimental structures could only be reproduced with modification of CH···O interactions in the force field, combined with an implicit solvent nonpolar correction to better model base stacking interactions. Accurately modeling RNA with current atomistic physics-based models remains challenging, but the RNA systems studied herein may provide a useful benchmark set for testing other RNA modeling methods in the future.

SpikeScape: A Tool for Analyzing Structural Diversity in Experimental Structures of the SARS-CoV-2 Spike Glycoprotein.

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.

AmberTools.

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.

BioMThermDB 1.0: Thermophysical Database of Proteins in Solutions.

We present here a freely available web-based database, called BioMThermDB 1.0, of thermophysical and dynamic properties of various proteins and their aqueous solutions. It contains the hydrodynamic radius, electrophoretic mobility, zeta potential, self-diffusion coefficient, solution viscosity, and cloud-point temperature, as well as the conditions for those determinations and details of the experimental method. It can facilitate the meta-analysis and visualization of data, can enable comparisons, and may be useful for comparing theoretical model predictions with experiments.

The flexibility of ACE2 in the context of SARS-CoV-2 infection.

The coronavirus disease 2019 (COVID-19) pandemic has swept over the world in the past months, causing significant loss of life and consequences to human health. Although numerous drug and vaccine development efforts are underway, there are many outstanding questions on the mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral association to angiotensin-converting enzyme 2 (ACE2), its main host receptor, and host cell entry. Structural and biophysical studies indicate some degree of flexibility in the viral extracellular spike glycoprotein and at the receptor-binding domain (RBD)-receptor interface, suggesting a role in infection. Here, we perform explicitly solvated, all-atom, molecular dynamics simulations of the glycosylated, full-length, membrane-bound ACE2 receptor in both an apo and spike RBD-bound state to probe the intrinsic dynamics of the ACE2 receptor in the context of the cell surface. A large degree of fluctuation in the full-length structure is observed, indicating hinge bending motions at the linker region connecting the head to the transmembrane helix while still not disrupting the ACE2 homodimer or ACE2-RBD interfaces. This flexibility translates into an ensemble of ACE2 homodimer conformations that could sterically accommodate binding of the spike trimer to more than one ACE2 homodimer and suggests a mechanical contribution of the host receptor toward the large spike conformational changes required for cell fusion. This work presents further structural and functional insights into the role of ACE2 in viral infection that can potentially be exploited for the rational design of effective SARS-CoV-2 therapeutics.

Copper stabilizes antiparallel ß-sheet fibrils of the amyloid ß40 (Aß40)-Iowa variant.

Cerebral amyloid angiopathy (CAA) is a vascular disorder that primarily involves deposition of the 40-residue-long ß-amyloid peptide (Aß40) in and along small blood vessels of the brain. CAA is often associated with Alzheimer's disease (AD), which is characterized by amyloid plaques in the brain parenchyma enriched in the Aß42 peptide. Several recent studies have suggested a structural origin that underlies the differences between the vascular amyloid deposits in CAA and the parenchymal plaques in AD. We previously have found that amyloid fibrils in vascular amyloid contain antiparallel ß-sheet, whereas previous studies by other researchers have reported parallel ß-sheet in fibrils from parenchymal amyloid. Using X-ray fluorescence microscopy, here we found that copper strongly co-localizes with vascular amyloid in human sporadic CAA and familial Iowa-type CAA brains compared with control brain blood vessels lacking amyloid deposits. We show that binding of Cu(II) ions to antiparallel fibrils can block the conversion of these fibrils to the more stable parallel, in-register conformation and enhances their ability to serve as templates for seeded growth. These results provide an explanation for how thermodynamically less stable antiparallel fibrils may form amyloid in or on cerebral vessels by using Cu(II) as a structural cofactor.

Free Energy Landscapes from SARS-CoV-2 Spike Glycoprotein Simulations Suggest that RBD Opening Can Be Modulated via Interactions in an Allosteric Pocket.

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.

AI-driven multiscale simulations illuminate mechanisms of SARS-CoV-2 spike dynamics.

We develop a generalizable AI-driven workflow that leverages heterogeneous HPC resources to explore the time-dependent dynamics of molecular systems. We use this workflow to investigate the mechanisms of infectivity of the SARS-CoV-2 spike protein, the main viral infection machinery. Our workflow enables more efficient investigation of spike dynamics in a variety of complex environments, including within a complete SARS-CoV-2 viral envelope simulation, which contains 305 million atoms and shows strong scaling on ORNL Summit using NAMD. We present several novel scientific discoveries, including the elucidation of the spike's full glycan shield, the role of spike glycans in modulating the infectivity of the virus, and the characterization of the flexible interactions between the spike and the human ACE2 receptor. We also demonstrate how AI can accelerate conformational sampling across different systems and pave the way for the future application of such methods to additional studies in SARS-CoV-2 and other molecular systems.

Blinded prediction of protein-ligand binding affinity using Amber thermodynamic integration for the 2018 D3R grand challenge 4.

In the framework of the 2018 Drug Design Data Resource grand challenge 4, blinded predictions on relative binding free energy were performed for a set of 39 ligands of the Cathepsin S protein. We leveraged the GPU-accelerated thermodynamic integration of Amber 18 to advance our computational prediction. When our entry was compared to experimental results, a good correlation was observed (Kendall's τ: 0.62, Spearman's ρ: 0.80 and Pearson's R: 0.82). We designed a parallelized transformation map that placed ligands into several groups based on common alchemical substructures; TI transformations were carried out for each ligand to the relevant substructure, and between substructures. Our calculations were all conducted using the linear potential scaling scheme in Amber TI because we believe the softcore potential/dual-topology approach as implemented in current Amber TI is highly fault-prone for some transformations. The issue is illustrated by using two examples in which typical preparation for the dual-topology approach of Amber TI fails. Overall, the high accuracy of our prediction is a result of recent advances in force fields (ff14SB and GAFF), as well as rapid calculation of ensemble averages enabled by the GPU implementation of Amber. The success shown here in a blinded prediction strongly suggests that alchemical free energy calculation in Amber is a promising tool for future commercial drug design.

A human transcription factor in search mode.

Transcription factors (TF) can change shape to bind and recognize DNA, shifting the energy landscape from a weak binding, rapid search mode to a higher affinity recognition mode. However, the mechanism(s) driving this conformational change remains unresolved and in most cases high-resolution structures of the non-specific complexes are unavailable. Here, we investigate the conformational switch of the human mitochondrial transcription termination factor MTERF1, which has a modular, superhelical topology complementary to DNA. Our goal was to characterize the details of the non-specific search mode to complement the crystal structure of the specific binding complex, providing a basis for understanding the recognition mechanism. In the specific complex, MTERF1 binds a significantly distorted and unwound DNA structure, exhibiting a protein conformation incompatible with binding to B-form DNA. In contrast, our simulations of apo MTERF1 revealed significant flexibility, sampling structures with superhelical pitch and radius complementary to the major groove of B-DNA. Docking these structures to B-DNA followed by unrestrained MD simulations led to a stable complex in which MTERF1 was observed to undergo spontaneous diffusion on the DNA. Overall, the data support an MTERF1-DNA binding and recognition mechanism driven by intrinsic dynamics of the MTERF1 superhelical topology.

A dynamic checkpoint in oxidative lesion discrimination by formamidopyrimidine-DNA glycosylase.

In contrast to proteins recognizing small-molecule ligands, DNA-dependent enzymes cannot rely solely on interactions in the substrate-binding centre to achieve their exquisite specificity. It is widely believed that substrate recognition by such enzymes involves a series of conformational changes in the enzyme-DNA complex with sequential gates favoring cognate DNA and rejecting nonsubstrates. However, direct evidence for such mechanism is limited to a few systems. We report that discrimination between the oxidative DNA lesion, 8-oxoguanine (oxoG) and its normal counterpart, guanine, by the repair enzyme, formamidopyrimidine-DNA glycosylase (Fpg), likely involves multiple gates. Fpg uses an aromatic wedge to open the Watson-Crick base pair and everts the lesion into its active site. We used molecular dynamics simulations to explore the eversion free energy landscapes of oxoG and G by Fpg, focusing on structural and energetic details of oxoG recognition. The resulting energy profiles, supported by biochemical analysis of site-directed mutants disturbing the interactions along the proposed path, show that Fpg selectively facilitates eversion of oxoG by stabilizing several intermediate states, helping the rapidly sliding enzyme avoid full extrusion of every encountered base for interrogation. Lesion recognition through multiple gating intermediates may be a common theme in DNA repair enzymes.

LAGUERRE-INTERSECTION METHOD FOR IMPLICIT SOLVATION.

Explicit solvent molecular dynamics simulations of a macromolecule are slow as the number of solvent atoms considered typically increases by order of magnitude. Implicit methods introduce surface-dependent corrections to the force field, gaining speed at the expense of accuracy. Properties such as molecular interface surfaces, volumes and cavities are captured by Laguerre tessellations of macromolecules. However, Laguerre cells of exterior atoms tend to be overly large or unbounded. Our method, the inclusion-exclusion based Laguerre-Intersection method, caps cells in a physically accurate manner by considering the intersection of the space-filling diagram with the Laguerre tessellation. We optimize an adjustable parameter, the weight, to ensure the areas and volumes of capped cells exposed to solvent are as close as possible, on average, to those computed from equilibrated explicit solvent simulations. The contact planes are radical planes, meaning that as the solvent weight is varied, interior cells remain constant. We test the consistency of our model using a high-quality trajectory of HIV-protease, a dimer with flexible loops and open-close transitions. We also compare our results with interval-arithmetic Gauss-Bonnet based method. Optimal solvent parameters quickly converge, which we use to illustrate the increased fidelity of the Laguerre-Intersection method over two recently proposed methods as compared to the explicit model.

DNA Deformation-Coupled Recognition of 8-Oxoguanine: Conformational Kinetic Gating in Human DNA Glycosylase.

8-Oxoguanine (8-oxoG), a mutagenic DNA lesion generated under oxidative stress, differs from its precursor guanine by only two substitutions (O8 and H7). Human 8-oxoguanine glycosylase 1 (OGG1) can locate and remove 8-oxoG through extrusion and excision. To date, it remains unclear how OGG1 efficiently distinguishes 8-oxoG from a large excess of undamaged DNA bases. We recently showed that formamidopyrimidine-DNA glycosylase (Fpg), a bacterial functional analog of OGG1, can selectively facilitate eversion of oxoG by stabilizing several intermediate states, and it is intriguing whether OGG1 also employs a similar mechanism in lesion recognition. Here, we use molecular dynamics simulations to explore the mechanism by which OGG1 discriminates between 8-oxoG and guanine along the base-eversion pathway. The MD results suggest an important role for kinking of the DNA by the glycosylase, which positions DNA phosphates in a way that assists lesion recognition during base eversion. The computational predictions were validated through experimental enzyme assays on phosphorothioate substrate analogs. Our simulations suggest that OGG1 distinguishes between 8-oxoG and G using their chemical dissimilarities not only at the active site but also at earlier stages during base eversion, and this mechanism is at least partially conserved in Fpg despite a lack of structural homology. The similarity also suggests that lesion recognition through multiple gating steps may be a common theme in DNA repair. Our results provide new insight into how enzymes can exploit kinetics and DNA conformational changes to probe the chemical modifications present in DNA lesions.

Characterization of Biomolecular Helices and Their Complementarity Using Geometric Analysis.

A general method is presented to characterize the helical properties of potentially irregular helices, such as those found in protein secondary and tertiary structures and nucleic acids. The method was validated using artificial helices with varying numbers of points, points per helical turn, pitch, and radius. The sensitivity of the method was validated by applying increasing amounts of random perturbation to the coordinates of these helices; 399 360 helices in total were evaluated. In addition, the helical parameters of protein secondary structure elements and nucleic acid helices were analyzed. Generally, at least seven points were required to recapitulate the parameters of a helix using our method. The method can also be used to calculate the helical parameters of nucleic acid-binding proteins, like TALE, enabling direct analysis of their helix complementarity to sequence-dependent DNA distortions.

Active destabilization of base pairs by a DNA glycosylase wedge initiates damage recognition.

Formamidopyrimidine-DNA glycosylase (Fpg) excises 8-oxoguanine (oxoG) from DNA but ignores normal guanine. We combined molecular dynamics simulation and stopped-flow kinetics with fluorescence detection to track the events in the recognition of oxoG by Fpg and its mutants with a key phenylalanine residue, which intercalates next to the damaged base, changed to either alanine (F110A) or fluorescent reporter tryptophan (F110W). Guanine was sampled by Fpg, as evident from the F110W stopped-flow traces, but less extensively than oxoG. The wedgeless F110A enzyme could bend DNA but failed to proceed further in oxoG recognition. Modeling of the base eversion with energy decomposition suggested that the wedge destabilizes the intrahelical base primarily through buckling both surrounding base pairs. Replacement of oxoG with abasic (AP) site rescued the activity, and calculations suggested that wedge insertion is not required for AP site destabilization and eversion. Our results suggest that Fpg, and possibly other DNA glycosylases, convert part of the binding energy into active destabilization of their substrates, using the energy differences between normal and damaged bases for fast substrate discrimination.

Selectivity of Pyridone- and Diphenyl Ether-Based Inhibitors for the Yersinia pestis FabV Enoyl-ACP Reductase.

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 tuberculosis and 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) Structure 20 (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.

Experimental and Computational Analysis of Protein Stabilization by Gly-to-d-Ala Substitution: A Convolution of Native State and Unfolded State Effects.

The rational and predictable enhancement of protein stability is an important goal in protein design. Most efforts target the folded state, however stability is the free energy difference between the folded and unfolded states thus both are suitable targets. Strategies directed at the unfolded state usually seek to decrease chain entropy by introducing cross-links or by replacing glycines. Cross-linking has led to mixed results. Replacement of glycine with an l-amino acid, while reducing the entropy of the unfolded state, can introduce unfavorable steric interactions in the folded state, since glycine is often found in conformations that require a positive φ angle such as helical C-capping motifs or type I' and II″ ß-turns. l-Amino acids are strongly disfavored in these conformations, but d-amino acids are not. However, there are few reported examples and conflicting results have been obtained when glycines are replaced with d-Ala. We critically examine the effect of Gly-to-d-Ala substitutions on protein stability using experimental approaches together with molecular dynamics simulations and free energy calculations. The data, together with a survey of high resolution structures, show that the vast majority of proteins can be stabilized by substitution of C-capping glycines with d-Ala. Sites suitable for substitutions can be identified via sequence alignment with a high degree of success. Steric clashes in the native state due to the new side chain are rarely observed, but are likely responsible for the destabilizing or null effect observed for the small subset of Gly-to-d-Ala substitutions which are not stabilizing. Changes in backbone solvation play less of a role. Favorable candidates for d-Ala substitution can be identified using a rapid algorithm based on molecular mechanics.

Rational Modulation of the Induced-Fit Conformational Change for Slow-Onset Inhibition in Mycobacterium tuberculosis InhA.

Slow-onset enzyme inhibitors are the subject of considerable interest as an approach to increasing the potency of pharmaceutical compounds by extending the residence time of the inhibitor on the target (the lifetime of the drug-receptor complex). However, rational modulation of residence time presents significant challenges because it requires additional mechanistic insight, such as the nature of the transition state for postbinding isomerization. Our previous work, based on X-ray crystallography, enzyme kinetics, and molecular dynamics simulation, suggested that the slow step in inhibition of the Mycobacterium tuberculosis enoyl-ACP reductase InhA involves a change in the conformation of the substrate binding loop from an open state in the initial enzyme-inhibitor complex to a closed state in the final enzyme-inhibitor complex. Here, we use multidimensional free energy landscapes for loop isomerization to obtain a computational model for the transition state. The results suggest that slow-onset inhibitors crowd key side chains on helices that slide past each other during isomerization, resulting in a steric clash. The landscapes become significantly flatter when residues involved in the steric clash are replaced with alanine. Importantly, this lower barrier can be increased by rational inhibitor redesign to restore the steric clash. Crystallographic studies and enzyme kinetics confirm the predicted effects on loop structure and flexibility, as well as inhibitor residence time. These loss and regain of function studies validate our mechanistic hypothesis for interactions controlling substrate binding loop isomerization, providing a platform for the future design of inhibitors with longer residence times and better in vivo potency. Similar opportunities for slow-onset inhibition via the same mechanism are identified in other pathogens.

The role of select subtype polymorphisms on HIV-1 protease conformational sampling and dynamics.

HIV-1 protease is an essential enzyme for viral particle maturation and is a target in the fight against HIV-1 infection worldwide. Several natural polymorphisms are also associated with drug resistance. Here, we utilized both pulsed electron double resonance, also called double electron-electron resonance, and NMR (15)N relaxation measurements to characterize equilibrium conformational sampling and backbone dynamics of an HIV-1 protease construct containing four specific natural polymorphisms commonly found in subtypes A, F, and CRF_01 A/E. Results show enhanced backbone dynamics, particularly in the flap region, and the persistence of a novel conformational ensemble that we hypothesize is an alternative flap orientation of a curled open state or an asymmetric configuration when interacting with inhibitors.