Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics

Phosphopeptide binding to the N-SH2 domain of tyrosine phosphatase SHP2 correlates with the unzipping of its central β-sheet

SHP2 is a tyrosine phosphatase that plays a regulatory role in multiple intracellular signaling cascades and is known to be oncogenic in certain contexts. In the absence of effectors, SHP2 adopts an autoinhibited conformation with its N-SH2 domain blocking the active site. Given the key role of N-SH2 in regulating SHP2, this domain has been extensively studied, often by X-ray crystallography. Using a combination of structural analyses and molecular dynamics (MD) simulations we show that the crystallographic environment can significantly influence the structure of the isolated N-SH2 domain, resulting in misleading interpretations. As an orthogonal method to X-ray crystallography, we use a combination of NMR spectroscopy and MD simulations to accurately determine the conformation of apo N-SH2 in solution. In contrast to earlier reports based on crystallographic data, our results indicate that apo N-SH2 in solution primarily adopts a conformation with a fully zipped central β-sheet, and that partial unzipping of this β-sheet is promoted by binding of either phosphopeptides or even phosphate/sulfate ions.

Computational discovery of tripeptide inhibitors targeting monkeypox virus A42R profilin-like protein

Monkeypox is an infectious disease caused by the monkeypox virus (MPXV), a member of the Orthopoxvirus genus closely related to smallpox. The structure of the A42R profilin-like protein is the first and only available structure among MPXV proteins. Biochemical studies of A42R were conducted in the 1990s and later work also analyzed the protein's function in viral replication in cells. This study aims to screen tripeptides for their potential inhibition of the A42R profilin-like protein using computational methods, with implications for MPXV therapy. A total of 8000 tripeptides underwent molecular docking simulations, resulting in the identification of 20 compounds exhibiting strong binding affinity to A42R. To validate the docking results, molecular dynamics simulations and free energy perturbation calculations were performed. These analyses revealed two tripeptides with sequences TRP-THR-TRP and TRP-TRP-TRP, which displayed robust binding affinity to A42R. Markedly, electrostatic interactions predominated over van der Waals interactions in the binding process between tripeptides and A42R. Three A42R residues, namely Glu9, Ser12, and Arg38, appear to be pivotal in mediating the interaction between A42R and the tripeptide ligands. Notably, tripeptides containing two or three tryptophan residues demonstrate a pronounced binding affinity, with the tripeptide comprising three tryptophan amino acids showing the highest level of affinity. These findings offer valuable insights for the selection of compounds sharing a similar structure and possessing a high affinity for A42R, potentially capable of inhibiting its enzyme activity. The study highlights a structural advantage and paves the way for the development of targeted therapies against MPXV infections.

The mutual and dynamic role of TSPO and ligands in their binding process: An example with PK-11195

Translocator protein (TSPO) is an 18 kDa transmembrane protein, localized primarily on the outer mitochondrial membrane. It has been found to be involved in various physiological processes and pathophysiological conditions. Though studies on its structure have been performed only recently, there is little information on the nature of dynamics and doubts about some structures referenced in the literature, especially the NMR structure of mouse TSPO. In the present work, we thoroughly study the dynamics of mouse TSPO protein by means of atomistic molecular dynamics simulations, in presence as well as in absence of the diagnostic ligand PKA. We considered two starting structures: the NMR structure and a homology model (HM) generated on the basis of X-ray structures from bacterial TSPO. We examine the conformational landscape in both the modes for both starting points, in presence and absence of the ligand, in order to measure its impact for both structures. The analysis highlights high flexibility of the protein globally, but NMR simulations show a surprisingly flexibility even in the presence of the ligand. Interestingly, this is not the case for HM calculations, to the point that the ligand seems not so stable as in the NMR system and an unbinding event process is partially sampled. All those results tend to show that the NMR structure of mTSPO seems not deficient but is just in another portion of the global conformation space of TSPO.

O-glycans Expand Lubricin and Attenuate Its Viscosity and Shear Thinning

Lubricin, an intrinsically disordered glycoprotein, plays a pivotal role in facilitating smooth movement and ensuring the enduring functionality of synovial joints. The central domain of this protein serves as a source of this excellent lubrication and is characterized by its highly glycosylated, negatively charged, and disordered structure. However, the influence of O-glycans on the viscosity of lubricin remains unclear. In this study, we employ molecular dynamics simulations in the absence and presence of shear, along with continuum simulations, to elucidate the intricate interplay between O-glycans and lubricin and the impact of O-glycans on lubricin's conformational properties and viscosity. We found the presence of O-glycans to induce a more extended conformation in fragments of the disordered region of lubricin. These O-glycans contribute to a reduction in solution viscosity but at the same time weaken shear thinning at high shear rates, compared to nonglycosylated systems with the same density. This effect is attributed to the steric and electrostatic repulsion between the fragments, which prevents their conglomeration and structuring. Our computational study yields a mechanistic mechanism underlying previous experimental observations of lubricin and paves the way to a more rational understanding of its function in the synovial fluid.

MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods

Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.

Heat-induced structural and chemical changes to a computationally designed miniprotein

The de novo design of miniprotein inhibitors has recently emerged as a new technology to create proteins that bind with high affinity to specific therapeutic targets. Their size, ease of expression, and apparent high stability makes them excellent candidates for a new class of protein drugs. However, beyond circular dichroism melts and hydrogen/deuterium exchange experiments, little is known about their dynamics, especially at the elevated temperatures they seemingly tolerate quite well. To address that and gain insight for future designs, we have focused on identifying unintended and previously overlooked heat-induced structural and chemical changes in a particularly stable model miniprotein, EHEE_rd2_0005. Nuclear magnetic resonance (NMR) studies suggest the presence of dynamics on multiple time and temperature scales. Transiently elevating the temperature results in spontaneous chemical deamidation visible in the NMR spectra, which we validate using both capillary electrophoresis and mass spectrometry (MS) experiments. High temperatures also result in greatly accelerated intrinsic rates of hydrogen exchange and signal loss in NMR heteronuclear single quantum coherence spectra from local unfolding. These losses are in excellent agreement with both room temperature hydrogen exchange experiments and hydrogen bond disruption in replica exchange molecular dynamics simulations. Our analysis reveals important principles for future miniprotein designs and the potential for high stability to result in long-lived alternate conformational states.

Effects of intrinsically disordered regions in gp120 underlying HIV neutralization phenotypes

HIV envelope protein gp120 is considered a primary molecular determinant of viral neutralization phenotype due to its critical role in viral entry and immune evasion. The intrinsically disordered regions (IDRs) in gp120 are responsible for their extensive sequence variations and significant structural rearrangements. Despite HIV neutralization phenotype and sequence/structural information of gp120 have been experimentally characterized, there remains a gap in our understanding of the correlation between the viral phenotype and IDRs in gp120. Here, we combined machine learning (ML) techniques and molecular dynamics (MD) simulations to gain data-driven and molecule-mechanism insights into relationships between viral sequence, structure, and phenotypes from the perspective of IDRs in gp120. ML models, trained only on the length and disorder score of IDRs, achieved equivalent performance to the best baseline model using amino acid sequences to discriminate HIV neutralization phenotype, indicating that the lengths or disorder of specific IDRs are strongly related to HIV neutralization phenotypes. Comparative MD analysis reveals that gp120 with extreme neutralization phenotypes in multiple conformational states, especially some IDRs, exhibit significantly distinct structural dynamics, conformational flexibility, and thermodynamic distributions. Taken together, our study provided insights into the role of IDRs in gp120 responding to HIV neutralization phenotypes, which will advance the understanding of molecular mechanisms underlying viral function associated with HIV neutralization phenotype and help develop antiviral vaccines or drugs.

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds

To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.

Molecular Insights into the Impact of Mutations on the Binding Affinity of Targeted Covalent Inhibitors of BTK

Targeted covalent inhibitors (TCIs) have witnessed a significant resurgence in recent years, particularly in the kinase drug discovery field for treating diverse clinical indications. The inhibition of Bruton's tyrosine kinase (BTK) for treating B-cell cancers is a classic example where TCIs such as ibrutinib have had breakthroughs in targeted therapy. However, selectivity remains challenging, and the emergence of resistance mutations is a critical concern for clinical efficacy. Computational methods that can accurately predict the impact of mutations on inhibitor binding affinity could prove helpful in informing targeted approaches─providing insights into drug resistance mechanisms. In addition, such systems could help guide the systematic evaluation and impact of mutations in disease models for optimal experimental design. Here, we have employed in silico physics-based methods to understand the effects of mutations on the binding affinity and conformational dynamics of select TCIs of BTK. The TCIs studied include ibrutinib, acalabrutinib, and zanubrutinib─all of which are FDA-approved drugs for treating multiple forms of leukemia and lymphoma. Our results offer useful molecular insights into the structural determinants, thermodynamics, and conformational energies that impact ligand binding for this biological target of clinical relevance.

Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin

Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.

Structural insights into the octamerization of glycerol dehydrogenase

Glycerol dehydrogenase (GDH) catalyzes glycerol oxidation to dihydroxyacetone in a NAD+-dependent manner. As an initiator of the oxidative pathway of glycerol metabolism, a variety of functional and structural studies of GDH have been conducted previously. Structural studies revealed intriguing features of GDH, like the flexible β-hairpin and its significance. Another commonly reported structural feature is the enzyme's octameric oligomerization, though its structural details and functional significance remained unclear. Here, with a newly reported GDH structure, complexed with both NAD+ and glycerol, we analyzed the octamerization of GDH. Structural analyses revealed that octamerization reduces the structural dynamics of the N-domain, which contributes to more consistently maintaining a distance required for catalysis between the cofactor and substrate. This suggests that octamerization may play a key role in increasing the likelihood of the enzyme reaction by maintaining the ligands in an appropriate configuration for catalysis. These findings expand our understanding of the structure of GDH and its relation to the enzyme's activity.

Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies

VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.

Elucidating the reversible and irreversible self-assembly mechanisms of low-complexity aromatic-rich kinked peptides and steric zipper peptides

Many RNA-binding proteins such as fused-in sarcoma (FUS) can self-assemble into reversible liquid droplets and fibrils through the self-association of their low-complexity (LC) domains. Recent experiments have revealed that SYG-rich segments in the FUS LC domains play critical roles in the reversible self-assembly behaviors of FUS. These FUS LC segments alone can self-assemble into reversible kinked fibrils, which are markedly different from the canonical irreversible steric zipper β-sheet fibrils. However, the molecular determinants underlying the reversible and irreversible self-assembly are poorly understood. Herein we conducted extensive all-atom and coarse-grained molecular dynamics simulations of four representative hexapeptides: two low-complexity aromatic-rich kinked peptides from the amyotrophic lateral sclerosis-related FUS protein, FUS37-42 (SYSGYS) and FUS54-59 (SYSSYG); and two steric zipper peptides from Alzheimer's-associated Aβ and Tau proteins, Aβ16-21 (KLVFFA) and Tau306-311 (VQIVYK). We dissected their reversible and irreversible self-assembly dynamics, predicted their phase separation behaviors, and elucidated the underpinning molecular interactions. Our simulations showed that alternating stickers (Tyr) and spacers (Gly and Ser) in FUS37-42 and FUS54-59 facilitate the formation of highly dynamic coil-rich oligomers and lead to reversible self-assembly, while consecutive hydrophobic residues of LVFF in Aβ16-21 and IVY in Tau306-311 act as hydrophobic patches, favoring the formation of stable β-sheet-rich oligomers and driving the irreversible self-assembly. Intriguingly, we found that FUS37-42 and FUS54-59 peptides, possessing the same amino acid composition and the same number of sticker and spacer residues, display differential self-assembly propensities. This finding suggests that the self-assembly behaviors of FUS peptides are fine-tuned by the site-specific patterning of spacer residues (Ser and Gly). This study provides significant mechanistic insights into reversible and irreversible peptide self-assembly, which would be helpful for understanding the molecular mechanisms underlying the formation of biological liquid condensates and pathological solid amyloid fibrils.

Integrative modeling of guanylate binding protein dimers

Guanylate-binding proteins (GBPs) are essential interferon-γ-activated large GTPases that play a crucial role in host defense against intracellular bacteria and parasites. While their protective functions rely on protein polymerization, our understanding of the structural intricacies of these multimerized states remains limited. To bridge this knowledge gap, we present dimer models for human GBP1 (hGBP1) and murine GBP2 and 7 (mGBP2 and mGBP7) using an integrative approach, incorporating the crystal structure of hGBP1's GTPase domain dimer, crosslinking mass spectrometry, small-angle X-ray scattering, protein-protein docking, and molecular dynamics simulations. Our investigation begins by comparing the protein dynamics of hGBP1, mGBP2, and mGBP7. We observe that the M/E domain in all three proteins exhibits significant mobility and hinge motion, with mGBP7 displaying a slightly less pronounced motion but greater flexibility in its GTPase domain. These dynamic distinctions can be attributed to variations in the sequences of mGBP7 and hGBP1/mGBP2, resulting in different dimerization modes. Unlike hGBP1 and its close ortholog mGBP2, which exclusively dimerize through their GTPase domains, we find that mGBP7 exhibits three equally probable alternative dimer structures. The GTPase domain of mGBP7 is only partially involved in its dimerization, primarily due to an accumulation of negative charge, allowing mGBP7 to dimerize independently of GTP. Instead, mGBP7 exhibits a strong tendency to dimerize in an antiparallel arrangement across its stalks. The results of this work go beyond the sequence-structure-function relationship, as the sequence differences in mGBP7 and mGBP2/hGBP1 do not lead to different structures, but to different protein dynamics and dimerization. The distinct GBP dimer structures are expected to encode specific functions crucial for disrupting pathogen membranes.

Exploring the conformational dynamics and thermodynamics of EGFR S768I and G719X + S768I mutations in non-small cell lung cancer: An in silico approaches

Non-small cell lung cancer (NSCLC) is often driven by mutations in the epidermal growth factor receptor (EGFR) gene. However, rare mutations such as G719X and S768I lack standard anti-EGFR targeted therapies. Understanding the structural differences between wild-type EGFR and these rare mutants is crucial for developing EGFR-targeted drugs. We performed a systematic analysis using molecular dynamics simulations, essential dynamics (ED), molecular mechanics Poisson-Boltzmann surface area, and free energy calculation methods to compare the kinetic properties, molecular motion, and free energy distribution between wild-type EGFR and the rare mutants' structures G719X-EGFR, S768I-EGFR, and G719X + S768I-EGFR. Our results showed that S768I-EGFR and G719X + S768I-EGFR have higher global and local conformational flexibility and lower thermal and global structural stability than WT-EGFR. ED analysis revealed different molecular motion patterns between S768I-EGFR, G719X + S768I-EGFR, and WT-EGFR. The A-loop and αC-helix, crucial structural elements related to the active state, showed a tendency toward active state development, providing a molecular mechanism explanation for NSCLC caused by EGFR S768I and EGFR G719C + S768I mutations. The present study may be helpful in the development of new EGFR-targeted drugs based on the structure of rare mutations. Our findings may aid in developing new targeted treatments for patients with EGFR S768I and EGFR G719X + S768I mutations.

Combined NMR and molecular dynamics conformational filter identifies unambiguously dynamic ensembles of Dengue protease NS2B/NS3pro

The dengue protease NS2B/NS3pro has been reported to adopt either an 'open' or a 'closed' conformation. We have developed a conformational filter that combines NMR with MD simulations to identify conformational ensembles that dominate in solution. Experimental values derived from relaxation parameters for the backbone and methyl side chains were compared with the corresponding back-calculated relaxation parameters of different conformational ensembles obtained from free MD simulations. Our results demonstrate a high prevalence for the 'closed' conformational ensemble while the 'open' conformation is absent, indicating that the latter conformation is most probably due to crystal contacts. Conversely, conformational ensembles in which the positioning of the co-factor NS2B results in a 'partially' open conformation, previously described in both MD simulations and X-ray studies, were identified by our conformational filter. Altogether, we believe that our approach allows for unambiguous identification of true conformational ensembles, an essential step for reliable drug discovery.

Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

Structural and functional insights into the flexible β-hairpin of glycerol dehydrogenase

During glycerol metabolism, the initial step of glycerol oxidation is catalysed by glycerol dehydrogenase (GDH), which converts glycerol to dihydroxyacetone in a NAD+ -dependent manner via an ordered Bi-Bi kinetic mechanism. Structural studies conducted with GDH from various species have mainly elucidated structural details of the active site and ligand binding. However, the structure of the full GDH complex with both cofactor and substrate bound is not determined, and thus, the structural basis of the kinetic mechanism of GDH remains unclear. Here, we report the crystal structures of Escherichia coli GDH with a substrate analogue bound in the absence or presence of NAD+ . Structural analyses including molecular dynamics simulations revealed that GDH possesses a flexible β-hairpin, and that during the ordered progression of the kinetic mechanism, the flexibility of the β-hairpin is reduced after NAD+ binding. It was also observed that this alterable flexibility of the β-hairpin contributes to the cofactor binding and possibly to the catalytic efficiency of GDH. These findings suggest the importance of the flexible β-hairpin to GDH enzymatic activity and shed new light on the kinetic mechanism of GDH.

Cross-Linked α-Synuclein as Inhibitor of Amyloid Formation

The aggregation and amyloid formation of α-synuclein is associated with Parkinson's disease and other synucleinopathies. In its native, monomeric form α-synuclein is an intrinsically disordered protein represented by highly dynamic conformational ensembles. Inhibition of α-synuclein aggregation using small molecules, peptides, or proteins has been at the center of interest in recent years. Our aim was to explore the effects of cross-linking on the structure and aggregation/amyloid formation properties of α-synuclein. Comparative analysis of available high-resolution amyloid structures and representative structural models and MD trajectory of monomeric α-synuclein revealed that potential cross-links in the monomeric protein are mostly incompatible with the amyloid forms and thus might inhibit fibrillation. Monomeric α-synuclein has been intramolecularly chemically cross-linked under various conditions using different cross-linkers. We determined the location of cross-links and their frequency using mass spectrometry and found that most of them cannot be realized in the amyloid structures. The inhibitory potential of cross-linked proteins has been experimentally investigated using various methods, including thioflavin-T fluorescence and transmission electron microscopy. We found that conformational constraints applied by cross-linking fully blocked α-synuclein amyloid formation. Moreover, DTSSP-cross-linked molecules exhibited an inhibitory effect on the aggregation of unmodified α-synuclein as well.

Impact of Structure, Coupling Scheme, and State of Interest on the Energy Transfer in CP29

The Qy and Bx excitation energy transfer (EET) in the minor light-harvesting complex CP29 (LHCII B4.1) antenna complex of Pisum sativum was characterized using a computational approach. We applied Förster resonance energy transfer (FRET) and the transition density cube (TDC) method to estimate the Coulombic coupling, based on a combination of classical molecular dynamics and quantum mechanics/molecular mechanics calculations. Employing TDC instead of FRET mostly affects the EET between chlorophylls (Chls) and carotenoids (Crts), as expected due to the Crts being spatially more challenging for FRET. Only between Chls, effects are found to be small (about only 0.1 EET efficiency change when introducing TDC instead of FRET). Effects of structural sampling were found to be small, illustrated by a small average standard deviation for the Qy state coupling elements (FRET/TDC: 0.97/0.94 cm-1). Due to the higher flexibility of the Bx state, the corresponding deviations are larger (FRET/TDC between Chl-Chl pairs: 17.58/22.67 cm-1, between Crt-Chl pairs: 62.58/31.63 cm-1). In summary, it was found for the Q band that the coupling between Chls varies only slightly depending on FRET or TDC, resulting in a minute effect on EET acceptor preference. In contrast, the coupling in the B band spectral region is found to be more affected. Here, the S2 (1Bu) states of the spatially challenging Crts may act as acceptors in addition to the B states of the Chls. Depending on FRET or TDC, several Chls show different Chl-to-Crt couplings. Interestingly, the EET between Chls or Crts in the B band is found to often outcompete the corresponding decay processes. The individual efficiencies for B band EET to Crts vary however strongly with the chosen coupling scheme (e.g., up to 0.29/0.99 FRET/TDC efficiency for the Chl a604/neoxanthin pair). Thus, the choice of the coupling scheme must involve a consideration of the state of interest.

NMR-Chemical-Shift-Driven Protocol Reveals the Cofactor-Bound, Complete Structure of Dynamic Intermediates of the Catalytic Cycle of Oncogenic KRAS G12C Protein and the Significance of the Mg2+ Ion

In this work, catalytically significant states of the oncogenic G12C variant of KRAS, those of Mg2+-free and Mg2+-bound GDP-loaded forms, have been determined using CS-Rosetta software and NMR-data-driven molecular dynamics simulations. There are several Mg2+-bound G12C KRAS/GDP structures deposited in the Protein Data Bank (PDB), so this system was used as a reference, while the structure of the Mg2+-free but GDP-bound state of the RAS cycle has not been determined previously. Due to the high flexibility of the Switch-I and Switch-II regions, which also happen to be the catalytically most significant segments, only chemical shift information could be collected for the most important regions of both systems. CS-Rosetta was used to derive an "NMR ensemble" based on the measured chemical shifts, which, however, did not contain the nonprotein components of the complex. We developed a torsional restraint set for backbone torsions based on the CS-Rosetta ensembles for MD simulations, overriding the force-field-based parametrization in the presence of the reinserted cofactors. This protocol (csdMD) resulted in complete models for both systems that also retained the structural features and heterogeneity defined by the measured chemical shifts and allowed a detailed comparison of the Mg2+-bound and Mg2+-free states of G12C KRAS/GDP.

Inhibitor Design Strategy for Myostatin: Dynamics and Interaction Networks Define the Affinity and Release Mechanisms of the Inhibited Complexes

Myostatin, an important negative regulator of muscle mass, is a therapeutic target for muscle atrophic disorders such as muscular dystrophy. Thus, the inhibition of myostatin presents a strategy to treat these disorders. It has long been established that the myostatin prodomain is a strong inhibitor of the mature myostatin, and the minimum peptide of the prodomain-corresponding to the α1-helix of its lasso-region-responsible for the inhibitory efficiency was defined and characterized as well. Here we show that the minimum peptide segment based on the growth differentiation factor 11 (GDF11), which we found to be more helical in its stand-alone solvated stfate than the similar segment of myostatin, is a promising new base scaffold for inhibitor design. The proposed inhibitory peptides in their solvated state and in complex with the mature myostatin were analyzed by in silico molecule modeling supplemented with the electronic circular dichroism spectroscopy measurements. We defined the Gaussian-Mahalanobis mean score to measure the fraction of dihedral angle-pairs close to the desired helical region of the Ramachandran-plot, carried out RING analysis of the peptide-protein interaction networks and characterized the internal motions of the complexes using our rigid-body segmentation protocol. We identified a variant-11m2-that is sufficiently ordered both in solvent and within the inhibitory complex, forms a high number of contacts with the binding-pocket and induces such changes in its internal dynamics that lead to a rigidified, permanently locked conformation that traps this peptide in the binding site. We also showed that the naturally evolved α1-helix has been optimized to simultaneously fulfill two very different roles: to function as a strong binder as well as a good leaving group. It forms an outstanding number of non-covalent interactions with the mature core of myostatin and maintains the most ordered conformation within the complex, while it induces independent movement of the gate-keeper β-hairpin segment assisting the dissociation and also results in the least-ordered solvated form which provides extra stability for the dissociated state and discourages rebinding.

Structural determinants underlying high-temperature adaptation of thermophilic xylanase from hot-spring microorganisms

Thermophilic xylanases from hot-spring microorganisms play potential biological and industrial applications for renewable and sustainable social development. However, high-temperature adaptation mechanisms of these thermophilic xylanases remain elusive at the molecular and evolutionary levels. Here, two recently reported xylanases, named XynDRTY1 and XynM1, from hot springs were subjected to molecular dynamics (MD) simulations at a series of temperature gradients and comparatively analyzed in comparison with the evolutionary background of the xylanase family. Comparative analysis of MD trajectories revealed that the XynM1 exhibits smaller structural dynamics and greater thermal stability than the XynDRTY1, although both share a similar fold architecture with structural differences in the βα_loops. Local regions whose conformational flexibility and regular secondary structure exhibited differences as temperature increases were closely related to the high-temperature adaptation of xylanase, implying that stabilization of these regions is a feasible strategy to improve the thermal stability of xylanases. Furthermore, coevolutionary information from the xylanase family further specified the structural basis of xylanases. Thanks to these results about the sequence, structure, and dynamics of thermophilic xylanases from hot springs, a series of high-temperature-related structural determinants were resolved to promote understanding of the molecular mechanism of xylanase high-temperature adaptation and to provide direct assistance in the improvement of xylanase thermal stability.

Fitting Force Field Parameters to NMR Relaxation Data

We present an approach to optimize force field parameters using time-dependent data from NMR relaxation experiments. To do so, we scan parameters in the dihedral angle potential energy terms describing the rotation of the methyl groups in proteins and compare NMR relaxation rates calculated from molecular dynamics simulations with the modified force fields to deuterium relaxation measurements of T4 lysozyme. We find that a small modification of C^γ methyl groups improves the agreement with experiments both for the protein used to optimize the force field and when validating using simulations of CI2 and ubiquitin. We also show that these improvements enable a more effective a posteriori reweighting of the MD trajectories. The resulting force field thus enables more direct comparison between simulations and side-chain NMR relaxation data and makes it possible to construct ensembles that better represent the dynamics of proteins in solution.

Molecular Insights into the Binding Behavior of Imidazolium Ionic Liquids to the Receptor Binding Domain of the SARS-CoV-2 Spike Protein

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein is considered as a key target for the design and development of COVID-19 drugs and inhibitors. Due to their unique structure and properties, ionic liquids (ILs) have many special interactions with proteins, showing great potential in biomedicine. Nevertheless, few research studies have been carried out on ILs and the spike RBD protein. Here, we explore the interaction of ILs and the RBD protein through large-scale molecular dynamics simulations (4 μs in total). It was found that IL cations with long alkyl chain lengths (nchain) could spontaneously bind to the cavity region of the RBD protein. The longer the alkyl chain is, the stabler the cations bind to the protein. The binding free energy (ΔG) had the same trend, peaking at nchain = 12 with -101.19 kJ/mol. The cationic chain lengths and their fit to the pocket are decisive factors that influence the binding strength of cations and proteins. The cationic imidazole ring has a high contact frequency with phenylalanine and tryptophan, and the hydrophobic residues phenylalanine, valine, leucine, and isoleucine are the most interacting residues with side chains of cations. Meanwhile, through analysis of the interaction energy, the hydrophobic and π-π interactions are the main contributors to the high affinity between cations and the RBD protein. In addition, the long-chain ILs would also act on the protein through clustering. These studies not only provide insights into the molecular interaction between ILs and the RBD of SARS-CoV-2 but also contribute to the rational design of IL-based drugs, drug carriers, and selective inhibitors as a therapeutic for SARS-CoV-2.

Identification of Catechins' Binding Sites in Monomeric Aβ42 through Ensemble Docking and MD Simulations

The assembly of the amyloid-β peptide (Aβ) into toxic oligomers and fibrils is associated with Alzheimer's disease and dementia. Therefore, disrupting amyloid assembly by direct targeting of the Aβ monomeric form with small molecules or antibodies is a promising therapeutic strategy. However, given the dynamic nature of Aβ, standard computational tools cannot be easily applied for high-throughput structure-based virtual screening in drug discovery projects. In the current study, we propose a computational pipeline-in the framework of the ensemble docking strategy-to identify catechins' binding sites in monomeric Aβ₄₂. It is shown that both hydrophobic aromatic interactions and hydrogen bonding are crucial for the binding of catechins to Aβ₄₂. Additionally, it has been found that all the studied ligands, especially EGCG, can act as potent inhibitors against amyloid aggregation by blocking the central hydrophobic region of Aβ. Our findings are evaluated and confirmed with multi-microsecond MD simulations. Finally, it is suggested that our proposed pipeline, with low computational cost in comparison with MD simulations, is a suitable approach for the virtual screening of ligand libraries against Aβ.

Water stabilizes an alternate turn conformation in horse heart myoglobin

Comparison of myoglobin structures reveals that protein isolated from horse heart consistently adopts an alternate turn conformation in comparison to its homologues. Analysis of hundreds of high-resolution structures discounts crystallization conditions or the surrounding amino acid protein environment as explaining this difference, that is also not captured by the AlphaFold prediction. Rather, a water molecule is identified as stabilizing the conformation in the horse heart structure, which immediately reverts to the whale conformation in molecular dynamics simulations excluding that structural water.

Mitochondrial Haemoglobin Is Upregulated with Hypoxia in Skeletal Muscle and Has a Conserved Interaction with ATP Synthase and Inhibitory Factor 1

The globin protein superfamily has diverse functions. Haemoglobin has been found in non-erythroid locations, including within the mitochondria. Using co-immunoprecipitation and in silico methods, we investigated the interaction of mitochondrial haemoglobin with ATP synthase and its associated proteins, including inhibitory factor 1 (IF1). We measured the expression of mitochondrial haemoglobin in response to hypoxia. In vitro and in silico evidence of interactions between mitochondrial haemoglobin and ATP synthase were found, and we report upregulated mitochondrial haemoglobin expression in response to hypoxia within skeletal muscle tissue. Our observations indicate that mitochondrial pH and ATP synthase activity are implicated in the mitochondrial haemoglobin response to hypoxia.

Structures of calmodulin-melittin complexes show multiple binding modes lacking classical anchoring interactions

Calmodulin (CaM) is a Ca²⁺ sensor protein found in all eukaryotic cells that regulates a large number of target proteins in a Ca²⁺ concentration-dependent manner. As a transient type hub protein, it recognizes linear motifs of its targets, though for the Ca²⁺-dependent binding no consensus sequence was identified. Its complex with melittin, a major component of bee venom, is often used as a model system of protein - protein complexes. Yet, the structural aspects of the binding are not well understood, as only diverse, low-resolution data are available concerning the association. We present the crystal structure of melittin in complex with Ca²⁺-saturated calmodulins from two, evolutionarily distant species, Homo sapiens and Plasmodium falciparum representing three binding modes of the peptide. Results - augmented by molecular dynamics simulations - indicate that multiple binding modes can exist for CaM-melittin complexes, as an intrinsic characteristic of the binding. While the helical structure of melittin remains, swapping of its salt bridges and partial unfolding of its C-terminal segment can occur. In contrast to the classical way of target recognition by CaM, we found that different sets of residues can anchor at the hydrophobic pockets of CaM, which were considered as main recognition sites. Finally, the nanomolar binding affinity of the CaM-melittin complex is created by an ensemble of arrangements of similar stability - tight binding is achieved not by optimized specific interactions but by simultaneously satisfying less optimal interaction patterns in co-existing different conformers.

Study on molecular mechanisms of CD4 dependency and independency of HIV-1 gp120

Different HIV-1 strains have different antibody neutralization phenotypes (or CD4-dependencies). However, the molecular mechanisms underlying these differences remain to be elucidated. In this study, we constructed gp120 structural models from the CD4-dependent, neutralization-resistant JR-FL strain and the CD4-independent, neutralization-sensitive R2 strain and carried out several conventional molecular dynamics (MD) simulations and free energy landscape (FEL) constructions. Comparative analyses of the MD simulations and FELs indicated that R2 gp120 had higher global structural flexibility and greater conformational diversity than JR-FL gp120. This provides the preconditions for R2 gp120 to adopt a more open conformation than JR-FL gp120. Essential dynamics (ED) analysis showed that the collective motions of R2 gp120 tend towards an open state while those of JR-FL gp120 tend to retain a closed state. Based on conformational selection theory, R2 gp120's more readily sampled open state makes it more sensitive to neutralizing antibodies (or more CD4-independent) than JR-FL gp120, which may explain why the HIV-1 R2 and JR-FL strains show CD4-independent and -dependent phenotypes, respectively. Our study provides thermodynamic and kinetic insights into the CD4-dependent and -independent molecular mechanisms of HIV-1 gp120 and helps shed light on HIV-1 immune evasion.

Inviting C5-Trifluoromethylated Pseudoprolines into Collagen Mimetic Peptides

Numerous collagen mimetic peptides (CMPs) have been engineered using proline derivatives substituted at their C(3) and/or C(4) position in order to stabilize or functionalize collagen triple-helix mimics. However, no example has been reported so far with C(5) substitutions. Here, we introduce a fluorinated CMP incorporating trifluoromethyl groups at the C(5) position of pseudoproline residues. In tripeptide models, our CD, NMR, and molecular dynamics (MD) studies have shown that, when properly arranged, these residues meet the structural requirements for a triple-helix assembly. Two host-guest CMPs were synthesized and analyzed by CD spectroscopy. The NMR analysis in solution of the most stable confirmed the presence of structured homotrimers that we interpret as triple helices. MD calculations showed that the triple-helix model remained stable throughout the simulation with all six trifluoromethyl groups pointing outward from the triple helix. Pseudoprolines substituted at the C(5) positions appeared as valuable tools for the design of new fluorinated collagen mimetic peptides.

Predicting binding affinity changes from long-distance mutations using molecular dynamics simulations and Rosetta

Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions.

Domain motions, dimerization, and membrane interactions of the murine guanylate binding protein 2

Guanylate-binding proteins (GBPs) are a group of GTPases that are induced by interferon-[Formula: see text] and are crucial components of cell-autonomous immunity against intracellular pathogens. Here, we examine murine GBP2 (mGBP2), which we have previously shown to be an essential effector protein for the control of Toxoplasma gondii replication, with its recruitment through the membrane of the parasitophorous vacuole and its involvement in the destruction of this membrane likely playing a role. The overall aim of our work is to provide a molecular-level understanding of the mutual influences of mGBP2 and the parasitophorous vacuole membrane. To this end, we performed lipid-binding assays which revealed that mGBP2 has a particular affinity for cardiolipin. This observation was confirmed by fluorescence microscopy using giant unilamellar vesicles of different lipid compositions. To obtain an understanding of the protein dynamics and how this is affected by GTP binding, mGBP2 dimerization, and membrane binding, assuming that each of these steps are relevant for the function of the protein, we carried out standard as well as replica exchange molecular dynamics simulations with an accumulated simulation time of more than 30 μs. The main findings from these simulations are that mGBP2 features a large-scale hinge motion in its M/E domain, which is present in each of the studied protein states. When bound to a cardiolipin-containing membrane, this hinge motion is particularly pronounced, leading to an up and down motion of the M/E domain on the membrane, which did not occur on a membrane without cardiolipin. Our prognosis is that this up and down motion has the potential to destroy the membrane following the formation of supramolecular mGBP2 complexes on the membrane surface.

Searching for potential inhibitors of SARS-COV-2 main protease using supervised learning and perturbation calculations

Inhibiting the biological activity of SARS-CoV-2 Mpro can prevent viral replication. In this context, a hybrid approach using knowledge- and physics-based methods was proposed to characterize potential inhibitors for SARS-CoV-2 Mpro. Initially, supervised machine learning (ML) models were trained to predict a ligand-binding affinity of ca. 2 million compounds with the correlation on a test set of R = 0.748 ± 0.044 . Atomistic simulations were then used to refine the outcome of the ML model. Using LIE/FEP calculations, nine compounds from the top 100 ML inhibitors were suggested to bind well to the protease with the domination of van der Waals interactions. Furthermore, the binding affinity of these compounds is also higher than that of nirmatrelvir, which was recently approved by the US FDA to treat COVID-19. In addition, the ligands altered the catalytic triad Cys145 - His41 - Asp187, possibly disturbing the biological activity of SARS-CoV-2.

Target Recognition in Tandem WW Domains: Complex Structures for Parallel and Antiparallel Ligand Orientation in h-FBP21 Tandem WW

Protein-protein interactions often rely on specialized recognition domains, such as WW domains, which bind to specific proline-rich sequences. The specificity of these protein-protein interactions can be increased by tandem repeats, i.e., two WW domains connected by a linker. With a flexible linker, the WW domains can move freely with respect to each other. Additionally, the tandem WW domains can bind in two different orientations to their target sequences. This makes the elucidation of complex structures of tandem WW domains extremely challenging. Here, we identify and characterize two complex structures of the tandem WW domain of human formin-binding protein 21 and a peptide sequence from its natural binding partner, the core-splicing protein SmB/B'. The two structures differ in the ligand orientation and, consequently, also in the relative orientation of the two WW domains. We analyze and probe the interactions in the complexes by molecular simulations and NMR experiments. The workflow to identify the complex structures uses molecular simulations, density-based clustering, and peptide docking. It is designed to systematically generate possible complex structures for repeats of recognition domains. These structures will help us to understand the synergistic and multivalency effects that generate the astonishing versatility and specificity of protein-protein interactions.

The Importance of Mg2+ -Free State in Nucleotide Exchange of Oncogenic K-Ras Mutants

For efficient targeting of oncogenic K-Ras interaction sites, a mechanistic picture of the Ras-cycle is necessary. Herein, we used NMR relaxation techniques and molecular dynamics simulations to decipher the role of slow dynamics in wild-type and three oncogenic P-loop mutants of K-Ras. Our measurements reveal a dominant two-state conformational exchange on the ms timescale in both GDP- and GTP-bound K-Ras. The identified low-populated higher energy state in GDP-loaded K-Ras has a conformation reminiscent of a nucleotide-bound/Mg²⁺ -free state characterized by shortened β2/β3-strands and a partially released switch-I region preparing K-Ras for the interaction with the incoming nucleotide exchange factor and subsequent reactivation. By providing insight into mutation-specific differences in K-Ras structural dynamics, our systematic analysis improves our understanding of prolonged K-Ras signaling and may aid the development of allosteric inhibitors targeting nucleotide exchange in K-Ras.

Contribution of the 12–17 hydrophobic region of islet amyloid polypeptide in self-assembly and cytotoxicity

The islet amyloid polypeptide (IAPP) is a 37-residue aggregation-prone peptide hormone whose deposition as insoluble fibrils in the islets of Langerhans is associated with type II diabetes. Therapeutic interventions targeting IAPP amyloidogenesis, which contributes to pancreatic β-cell degeneration, remain elusive owing to the lack of understanding of the self-assembly mechanisms and of the quaternary proteospecies mediating toxicity. While countless studies have investigated the contributions of the 20–29 amyloidogenic core in self-assembly, IAPP central region, i.e. positions 11 to 19, has been less studied, notwithstanding its potential key role in oligomerization. In this context, the present study aimed at investigating the physicochemical and conformational properties driving IAPP self-assembly and associated cytotoxicity. Computational tools and all-atom molecular dynamics simulation suggested that the hydrophobic 12–17 segment promotes IAPP self-recognition and aggregation. Alanine scanning revealed that the hydrophobic side chains of Leu12, Phe15 and Val17 are critical for amyloid fibril formation. Destabilization of the α-helical folding by Pro substitution enhanced self-assembly when the pyrrolidine ring was successively introduced at positions Ala13, Asn14 and Phe15, in comparison to respective Ala-substituted counterparts. Modulating the peptide backbone flexibility at position Leu16 through successive incorporation of Pro, Gly and α-methylalanine, inhibited amyloid formation and reduced cytotoxicity, while the isobutyl side chain of Leu16 was not critical for self-assembly and IAPP-mediated toxicity. These results highlight the importance of the 12–17 hydrophobic region of IAPP for self-recognition, ultimately supporting the development of therapeutic approaches to prevent oligomerization and/or fibrillization.

Characterization of the Conformations of Amyloid Beta 42 in Solution That May Mediate Its Initial Hydrophobic Aggregation

Intrinsically disordered peptides, such as amyloid β42 (Aβ42), lack a well-defined structure in solution. Aβ42 can undergo abnormal aggregation and amyloidogenesis in the brain, forming fibrillar plaques, a hallmark of Alzheimer's disease. The insoluble fibrillar forms of Aβ42 exhibit well-defined, cross β-sheet structures at the molecular level and are less toxic than the soluble, intermediate disordered oligomeric forms. However, the mechanism of initial interaction of monomers and subsequent oligomerization is not well understood. The structural disorder of Aβ42 adds to the challenges of determining the structural properties of its monomers, making it difficult to understand the underlying molecular mechanism of pathogenic aggregation. Certain regions of Aβ42 are known to exhibit helical propensity in different physiological conditions. NMR spectroscopy has shown that the Aβ42 monomer at lower pH can adopt an α-helical conformation and as the pH is increased, the peptide switches to β-sheet conformation and aggregation occurs. CD spectroscopy studies of aggregation have shown the presence of an initial spike in the amount of α-helical content at the start of aggregation. Such an increase in α-helical content suggests a mechanism wherein the peptide can expose critical non-polar residues for interaction, leading to hydrophobic aggregation with other interacting peptides. We have used molecular dynamics simulations to characterize in detail the conformational landscape of monomeric Aβ42 in solution to identify molecular properties that may mediate the early stages of oligomerization. We hypothesized that conformations with α-helical structure have a higher probability of initiating aggregation because they increase the hydrophobicity of the peptide. Although random coil conformations were found to be the most dominant, as expected, α-helical conformations are thermodynamically accessible, more so than β-sheet conformations. Importantly, for the first time α-helical conformations are observed to increase the exposure of aromatic and hydrophobic residues to the aqueous solvent, favoring their hydrophobically driven interaction with other monomers to initiate aggregation. These findings constitute a first step toward characterizing the mechanism of formation of disordered, low-order oligomers of Aβ42.

Multiple Timescale Dynamic Analysis of Functionally-Impairing Mutations in Human Ileal Bile Acid-Binding Protein

Human ileal bile acid-binding protein (hI-BABP) has a key role in the enterohepatic circulation of bile salts. Its two internal binding sites exhibit positive cooperativity accompanied by a site-selectivity of glycocholate (GCA) and glycochenodeoxycholate (GCDA), the two most abundant bile salts in humans. To improve our understanding of the role of dynamics in ligand binding, we introduced functionally impairing single-residue mutations at two key regions of the protein and subjected the mutants to NMR relaxation analysis and MD simulations. According to our results, mutation in both the vicinity of the C/D (Q51A) and the G/H (Q99A) turns results in a redistribution of motional freedom in apo hI-BABP. Mutation Q51A, deteriorating the site-selectivity of GCA and GCDA, results in the channeling of ms fluctuations into faster motions in the binding pocket hampering the realization of key side chain interactions. Mutation Q99A, abolishing positive binding cooperativity for GCDA, leaves ms motions in the C-terminal half unchanged but by decoupling βD from a dynamic cluster of the N-terminal half displays an increased flexibility in the vicinity of site 1. MD simulations of the variants indicate structural differences in the portal region and mutation-induced changes in dynamics, which depend on the protonation state of histidines. A dynamic coupling between the EFGH portal, the C/D-region, and the helical cap is evidenced highlighting the interplay of structural and dynamic effects in bile salt recognition in hI-BABP.

Estimating the binding energetics of reversible covalent inhibitors of the SARS-CoV-2 main protease: an in silico study

The main protease (M^pro) of the SARS-CoV-2 virus is an attractive therapeutic target for developing antivirals to combat COVID-19. M^pro is essential for the replication cycle of the SARS-CoV-2 virus, so inhibiting M^pro blocks a vital piece of the cell replication machinery of the virus. A promising strategy to disrupt the viral replication cycle is to design inhibitors that bind to the active site cysteine (Cys145) of the M^pro. Cysteine targeted covalent inhibitors are gaining traction in drug discovery owing to the benefits of improved potency and extended drug-target engagement. An interesting aspect of these inhibitors is that they can be chemically tuned to form a covalent, but reversible bond, with their targets of interest. Several small-molecule cysteine-targeting covalent inhibitors of the M^pro have been discovered-some of which are currently undergoing evaluation in early phase human clinical trials. Understanding the binding energetics of these inhibitors could provide new insights to facilitate the design of potential drug candidates against COVID-19. Motivated by this, we employed rigorous absolute binding free energy calculations and hybrid quantum mechanical/molecular mechanical (QM/MM) calculations to estimate the energetics of binding of some promising reversible covalent inhibitors of the M^pro. We find that the inclusion of enhanced sampling techniques such as replica-exchange algorithm in binding free energy calculations can improve the convergence of predicted non-covalent binding free energy estimates of inhibitors binding to the M^pro target. In addition, our results indicate that binding free energy calculations coupled with multiscale simulations can be a useful approach to employ in ranking covalent inhibitors to their targets. This approach may be valuable in prioritizing and refining covalent inhibitor compounds for lead discovery efforts against COVID-19 and other coronavirus infections.

Arg236 in human chymotrypsin B2 (CTRB2) is a key determinant of high enzyme activity, trypsinogen degradation capacity, and protection against pancreatitis

Pancreatic chymotrypsins (CTRs) are digestive proteases that in humans include CTRB1, CTRB2, CTRC, and CTRL. The highly similar CTRB1 and CTRB2 are the products of gene duplication. A common inversion at the CTRB1-CTRB2 locus reverses the expression ratio of these isoforms in favor of CTRB2. Carriers of the inversion allele are protected against the inflammatory disorder pancreatitis presumably via their increased capacity for CTRB2-mediated degradation of harmful trypsinogen. To reveal the protective molecular determinants of CTRB2, we compared enzymatic properties of CTRB1, CTRB2, and bovine CTRA (bCTRA). By evolving substrate-like Schistocerca gregaria proteinase inhibitor 2 (SGPI-2) inhibitory loop variants against the chymotrypsins, we found that the substrate binding groove of the three enzymes had overlapping specificities. Based on the selected sequences, we produced eight SGPI-2 variants. Remarkably, CTRB2 and bCTRA bound these inhibitors with significantly higher affinity than CTRB1. Moreover, digestion of peptide substrates, beta casein, and human anionic trypsinogen unequivocally confirmed that CTRB2 is a generally better enzyme than CTRB1 while the potency of bCTRA lies between those of the human isoforms. Unexpectedly, mutation D236R alone converted CTRB1 to a CTRB2-like high activity protease. Modeling indicated that in CTRB1 Met210 partially obstructed the substrate binding groove, which was relieved by the D236R mutation. Taken together, we identify CTRB2 Arg236 as a key positive determinant, while CTRB1 Asp236 as a negative determinant for chymotrypsin activity. These findings strongly support the concept that in carriers of the CTRB1-CTRB2 inversion allele, the superior trypsinogen degradation capacity of CTRB2 protects against pancreatitis.

Omicron Binding Mode: Contact Analysis and Dynamics of the Omicron Receptor-Binding Domain in Complex with ACE2

On 26 November 2021, the WHO classified the Omicron variant of the SARS-CoV-2 virus (B.1.1.529 lineage) as a variant of concern (VOC) (COVID-19 Variant Data, Department of Health, 2022). The Omicron variant contains as many as 26 unique mutations of effects not yet determined (Venkatakrishnan, A., Open Science Framework, 2021). Out of its total of 34 Spike protein mutations, 15 are located on the receptor-binding domain (S-RBD) (Stanford Coronavirus Antiviral & Resistance Database, 2022) that directly contacts the angiotensin-converting enzyme 2 (ACE2) host receptor and is also a primary target for antibodies. Here, we studied the binding mode of the S-RBD domain of the Spike protein carrying the Omicron mutations and the globular domain of human ACE2 using molecular dynamics (MD) simulations. We identified new and key Omicron-specific interactions such as R493 (of mutation Q493R), which forms salt bridges both with E35 and D38 of ACE2, Y501 (N501Y), which forms an edge-to-face aromatic interaction with Y41, and Y505 (Y505H), which makes an H-bond with E37 and K353. The glycan chains of ACE2 also bind differently in the WT and Omicron variants in response to different charge distributions on the surface of Spike proteins. However, while the Omicron mutations considerably improve the overall electrostatic fit of the two interfaces, the total number of specific and favorable interactions between the two does not increase. The dynamics of the complexes are highly affected too, making the Omicron S-RBD:ACE2 complex more rigid; the two main interaction sites, Patches I and II, isolated in the WT complex, become connected in the Omicron complex through the alternating interaction of R493 and R498 with E35 and D38.

Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics

Purpose

The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease.

Methods

We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and Disgenet databases, and the Venny was used for intersection processing. We observed the gene expression differences in the GEO database. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration, and the solvent accessible surface area.

Results

Aspirin had 294 gene targets, Kawasaki disease had 416 gene targets, 42 intersecting targets were obtained, we screened 13 core targets by PPI; In the GO analysis, we learned that the biological process of Kawasaki disease involved the positive regulation of chemokine biosynthesis and inflammatory response; pathway enrichment involved PI3K-AKT signaling pathway, tumor necrosis factor signaling pathway, etc. After molecular docking, the data showed that CTSG, ELANE, and FGF1 had the best binding degree to aspirin. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, and Aspirin/ELANE combination has the strongest binding energy.

Conclusion

In the treatment of Kawasaki disease, aspirin may regulate inflammatory response and vascular remodeling through CTSG, ELANE, and FGF1.

Neuronal-specific septin-3 binds Atg8/LC3B, accumulates and localizes to autophagosomes during induced autophagy

In synapses that show signs of local apoptosis and mitochondrial stress and undergo neuro-immunological synapse pruning, an increase in the levels of the presynaptic protein, neuronal-specific septin-3 can be observed. Septin-3 is a member of the septin GTPase family with the ability to form multimers and contribute to the cytoskeleton. However, the function of septin-3 remains elusive. Here, we provide evidence that septin-3 is capable of binding the most-studied autophagy protein Atg8 homolog microtubule-associated protein 1 light chain 3B (LC3B), besides another homolog, GABA receptor-associated protein-like 2 (GABARAPL2). Moreover, we demonstrate that colocalization of septin-3 and LC3B increases upon chemical autophagy induction in primary neuronal cells. Septin-3 is accumulated in primary neurons upon autophagy enhancement or blockade, similar to autophagy proteins. Using electron microscopy, we also show that septin-3 localizes to LC3B positive membranes and can be found at mitochondria. However, colocalization results of septin-3 and the early mitophagy marker PTEN-induced kinase 1 (PINK1) do not support that binding of septin-3 to mitochondria is mitophagy related. We conclude that septin-3 correlates with synaptic/neuronal autophagy, binds Atg8 and localizes to autophagic membranes that can be enhanced with chemical autophagy induction. Based on our results, elevated septin-3 levels might indicate enhanced or impeded autophagy in neurons.

Distal mutation V486M disrupts the catalytic activity of DPP4 by affecting the flap of the propeller domain

Dipeptidyl peptidase-4 (DPP4) plays a crucial role in regulating the bioactivity of glucagon-like peptide-1 (GLP-1) that enhances insulin secretion and pancreatic β-cell proliferation, making it a therapeutic target for type 2 diabetes. Although the crystal structure of DPP4 has been determined, its structure-function mechanism is largely unknown. Here, we examined the biochemical properties of sporadic human DPP4 mutations distal from its catalytic site, among which V486M ablates DPP4 dimerization and causes loss of enzymatic activity. Unbiased molecular dynamics simulations revealed that the distal V486M mutation induces a local conformational collapse in a β-propeller loop (residues 234-260, defined as the flap) and disrupts the dimerization of DPP4. The "open/closed" conformational transitions of the flap whereby capping the active site, are involved in the enzymatic activity of DPP4. Further site-directed mutagenesis guided by theoretical predictions verified the importance of the conformational dynamics of the flap for the enzymatic activity of DPP4. Therefore, the current studies that combined theoretical modeling and experimental identification, provide important insights into the biological function of DPP4 and allow for the evaluation of directed DPP4 genetic mutations before initiating clinical applications and drug development.

Molecular Modeling Predicts Novel Antibody Escape Mutations in the Respiratory Syncytial Virus Fusion Glycoprotein

Monoclonal antibodies are increasingly used for the prevention and/or treatment of viral infections. One caveat of their use is the ability of viruses to evolve resistance to antibody binding and neutralization. Computational strategies to identify viral mutations that may disrupt antibody binding would leverage the wealth of viral genomic sequence data to monitor for potential antibody-resistant mutations. The respiratory syncytial virus is an important pathogen for which monoclonal antibodies against the fusion (F) protein are used to prevent severe disease in high-risk infants. In this study, we used an approach that combines molecular dynamics simulations with FoldX to estimate changes in free energy in F protein folding and binding to the motavizumab antibody upon each possible amino acid change. We systematically selected 8 predicted escape mutations and tested them in an infectious clone. Consistent with our F protein stability predictions, replication-effective viruses were observed for each selected mutation. Six of the eight variants showed increased resistance to neutralization by motavizumab. Flow cytometry was used to validate the estimated (model-predicted) effects on antibody binding to F. Using surface plasmon resonance, we determined that changes in the on-rate of motavizumab binding were associated with the reduced affinity for two novel escape mutations. Our study empirically validated the accuracy of our molecular modeling approach and emphasized the role of biophysical protein modeling in predicting viral resistance to antibody-based therapeutics that can be used to monitor the emergence of resistant viruses and to design improved therapeutic antibodies. IMPORTANCE Respiratory syncytial virus (RSV) causes severe disease in young infants, particularly those with heart or lung diseases or born prematurely. Because no vaccine is currently available, monoclonal antibodies are used to prevent severe RSV disease in high-risk infants. While it is known that RSV evolves to avoid recognition by antibodies, screening tools that can predict which changes to the virus may lead to antibody resistance are greatly needed.

Identifying Possible AChE Inhibitors from Drug-like Molecules via Machine Learning and Experimental Studies

Acetylcholinesterase (AChE) is one of the most important drug targets for Alzheimer's disease (AD) treatment. In this work, a machine learning model was trained to rapidly and accurately screen large chemical databases for the potential inhibitors of AChE. The obtained results were then validated via in vitro enzyme assay. Moreover, atomistic simulations including molecular docking and molecular dynamics simulations were then used to understand molecular insights into the binding process of ligands to AChE. In particular, two compounds including benzyl trifluoromethyl ketone and trifluoromethylstyryl ketone were indicated as highly potent inhibitors of AChE because they established IC₅₀ values of 0.51 and 0.33 μM, respectively. The obtained IC₅₀ of two compounds is significantly lower than that of galantamine (2.10 μM). The predicted log(BB) suggests that the compounds may be able to traverse the blood-brain barrier. A good agreement between computational and experimental studies was observed, indicating that the hybrid approach can enhance AD therapy.

Competitive inhibition of the classical complement pathway using exogenous single-chain C1q recognition proteins

Complement component 1q (C1q) is a protein complex of the innate immune system with well-characterized binding partners that constitutes part of the classical complement pathway (CP). In addition, C1q was recently described in the central nervous system as having a role in synapse elimination both in the healthy brain and in neurodegenerative diseases. However, the molecular mechanism of C1q-associated synapse phagocytosis is still unclear. Here, we designed monomer and multimer protein constructs which comprised the globular interaction recognition parts of mouse C1q (gC1q) as single-chain molecules (sc-gC1q proteins) lacking the collagen-like effector region. These molecules, which can competitively inhibit the function of C1q, were expressed in an E. coli expression system, and their structure and capabilities to bind known CP activators were validated by mass spectrometry, analytical size exclusion chromatography, analytical ultracentrifugation, circular dichroism spectroscopy, and ELISA. We further characterized the interactions between these molecules and immunoglobulins and neuronal pentraxins using surface plasmon resonance spectroscopy. We demonstrated that sc-gC1qs potently inhibited the function of C1q. Furthermore, these sc-gC1qs competed with C1q in binding to the embryonal neuronal cell membrane. We conclude that the application of sc-gC1qs can reveal neuronal localization and functions of C1q in assays in vivo and might serve as a basis for engineering inhibitors for therapeutic purposes.