Protein-Protein Binding as a Two-Step Mechanism: Preselection of Encounter Poses during the Binding of BPTI and Trypsin

Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD

The dissociation rate, or its reciprocal, the residence time (τ), is a crucial parameter for understanding the duration and biological impact of biomolecular interactions. Accurate prediction of τ is essential for understanding protein-protein interactions (PPIs) and identifying potential drug targets or modulators for tackling diseases. Conventional molecular dynamics simulation techniques are inherently constrained by their limited timescales, making it challenging to estimate residence times, which typically range from minutes to hours. Building upon its successful application in protein-small molecule systems, τ-Random Acceleration Molecular Dynamics (τRAMD) is here investigated for estimating dissociation rates of protein-protein complexes. τRAMD enables the observation of unbinding events on the nanosecond timescale, facilitating rapid and efficient computation of relative residence times. We tested this methodology for three protein-protein complexes and their extensive mutant datasets, achieving good agreement between computed and experimental data. By combining τRAMD with MD-IFP (Interaction Fingerprint) analysis, dissociation mechanisms were characterized and their sensitivity to mutations investigated, enabling the identification of molecular hotspots for selective modulation of dissociation kinetics. In conclusion, our findings underscore the versatility of τRAMD as a simple and computationally efficient approach for computing relative protein-protein dissociation rates and investigating dissociation mechanisms, thereby aiding the design of PPI modulators.

Competitive Interaction of the SGFRKMAF Peptide with 3CLpro Dimerization Intermediates: A Brownian Dynamics Investigation

The SGFRKMAF peptide is known to inhibit the dimerization of 3CLpro monomers, which is essential for SARS-CoV-2 replication. The mechanism behind this, however, is largely unknown. In this work, we used Brownian dynamics simulations to compare and contrast 3CLpro monomer-monomer interactions and 3CLpro monomer-SGFRKMAF peptide interactions. We found that formation of the 3CLpro wild-type dimer could potentially involve formation of three intermediates that are primarily stabilized by G11-G124, S1-S301, and T118-G278 interactions. Analysis of 3CLpro monomer interaction with the SGFRKMAF peptide, however, revealed the presence of eight basins of interactions where the peptide assumes the highest local densities at the 3CLPro monomer surface. The second highest-density basin was found to coincide with the interface region of the wild-type 3CLpro dimer, thereby directly blocking the 3CLpro dimer-dimer interactions. The other basins, however, were found to lie far from the interface region. Notably, we found that only 6% of the BD trajectories end up directly into the basin at the interface region and ∼39% of the trajectories end up into those basins lying away from the interface region, indicating a greater role for peptide binding at sites away from the dimer interface region. Importantly, the locations of the basins lying away from the interface were found to coincide with the 3CLpro residues involved in stabilization of the 3CLpro monomer-monomer intermediates. Given that the rate constant of the peptide reaching the monomer surface was found to be almost an order of magnitude higher than the rate constant of monomer-monomer association, the SGFRKMAF peptide has the potential to inhibit dimerization of 3CLpro monomers not only through blocking the interface region but also through blocking the formation of the intermediates involved in the dimerization process. This could potentially open new avenues for 3CLpro dimerization inhibitors that transcend traditional X-ray-based discovery approaches.

Prebound State Discovered in the Unbinding Pathway of Fluorinated Variants of the Trypsin-BPTI Complex Using Random Acceleration Molecular Dynamics Simulations

The serine protease trypsin forms a tightly bound inhibitor complex with the bovine pancreatic trypsin inhibitor (BPTI). The complex is stabilized by the P1 residue Lys15, which interacts with negatively charged amino acids at the bottom of the S1 pocket. Truncating the P1 residue of wildtype BPTI to α-aminobutyric acid (Abu) leaves a complex with moderate inhibitor strength, which is held in place by additional hydrogen bonds at the protein-protein interface. Fluorination of the Abu residue partially restores the inhibitor strength. The mechanism with which fluorination can restore the inhibitor strength is unknown, and accurate computational investigation requires knowledge of the binding and unbinding pathways. The preferred unbinding pathway is likely to be complex, as encounter states have been described before, and unrestrained umbrella sampling simulations of these complexes suggest additional energetic minima. Here, we use random acceleration molecular dynamics to find a new metastable state in the unbinding pathway of Abu-BPTI variants and wildtype BPTI from trypsin, which we call the prebound state. The prebound state and the fully bound state differ by a substantial shift in the position, a slight shift in the orientation of the BPTI variants, and changes in the interaction pattern. Particularly important is the breaking of three hydrogen bonds around Arg17. Fluorination of the P1 residue lowers the energy barrier of the transition between the fully bound state and prebound state and also lowers the energy minimum of the prebound state. While the effect of fluorination is in general difficult to quantify, here, it is in part caused by favorable stabilization of a hydrogen bond between Gln194 and Cys14. The interaction pattern of the prebound state offers insights into the inhibitory mechanism of BPTI and might add valuable information for the design of serine protease inhibitors.

The monodomain Kunitz protein EgKU-7 from the dog tapeworm Echinococcus granulosus is a high-affinity trypsin inhibitor with two interaction sites

Typical Kunitz proteins (I2 family of the MEROPS database, Kunitz-A family) are metazoan competitive inhibitors of serine peptidases that form tight complexes of 1:1 stoichiometry, mimicking substrates. The cestode Echinococcus granulosus, the dog tapeworm causing cystic echinococcosis in humans and livestock, encodes an expanded family of monodomain Kunitz proteins, some of which are secreted to the dog host interface. The Kunitz protein EgKU-7 contains, in addition to the Kunitz domain with the anti-peptidase loop comprising a critical arginine, a C-terminal extension of ∼20 amino acids. Kinetic, electrophoretic, and mass spectrometry studies using EgKU-7, a C-terminally truncated variant, and a mutant in which the critical arginine was substituted by alanine, show that EgKU-7 is a tight inhibitor of bovine and canine trypsins with the unusual property of possessing two instead of one site of interaction with the peptidases. One site resides in the anti-peptidase loop and is partially hydrolyzed by bovine but not canine trypsins, suggesting specificity for the target enzymes. The other site is located in the C-terminal extension. This extension can be hydrolyzed in a particular arginine by cationic bovine and canine trypsins but not by anionic canine trypsin. This is the first time to our knowledge that a monodomain Kunitz-A protein is reported to have two interaction sites with its target. Considering that putative orthologs of EgKU-7 are present in other cestodes, our finding unveils a novel piece in the repertoire of peptidase-inhibitor interactions and adds new notes to the evolutionary host-parasite concerto.

Bioinformatic investigation of Nipah virus surface protein mutations: Molecular docking with Ephrin B2 receptor, molecular dynamics simulation, and structural impact analysis

The SARS-CoV-2 outbreak resulted in significant challenges and loss of life. The Nipah virus, known for its high infectivity and severity, was designated an emergency concern by the World Health Organization. To understand its mutations, the Nipah virus proteins were analyzed extensively, with a focus on the essential G and F proteins responsible for viral entry into host cells. Our bioinformatics analysis unveiled multiple mutations, including simultaneous mutations within a single sequence. Notably, the G273S mutation in the F protein was identified as a potential cause of structural damage, which carries significant implications for vaccine development. Comparing the docking scores of G and F proteins with the Ephrin B2 receptor, it was found that the Y228H mutation in the G protein and the D252G mutation in the F protein likely affect virus entry into host cells. Moreover, our investigation into stability and deformability highlighted the impact of the Y228H mutation in the G protein complex. Molecular dynamics simulations revealed increased flexibility and conformational changes in the G protein complex with the Y228H mutation compared with the known complex. Furthermore, evaluating the root mean square deviation variation demonstrated greater dynamic behavior in the G protein complex and the Ephrin B2 receptor complex. This comprehensive study provides valuable insights into Nipah virus mutations, their significance for vaccine development, and the importance of understanding protein complex behavior in drug discovery. The identified mutations, especially G273S and Y228H, hold crucial implications for future research and potential interventions against the Nipah virus.

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

Structural mechanism of Fab domain dissociation as a measure of interface stability

Therapeutic antibodies should not only recognize antigens specifically, but also need to be free from developability issues, such as poor stability. Thus, the mechanistic understanding and characterization of stability are critical determinants for rational antibody design. In this study, we use molecular dynamics simulations to investigate the melting process of 16 antigen binding fragments (Fabs). We describe the Fab dissociation mechanisms, showing a separation in the V_H-V_L and in the C_H1-C_L domains. We found that the depths of the minima in the free energy curve, corresponding to the bound states, correlate with the experimentally determined melting temperatures. Additionally, we provide a detailed structural description of the dissociation mechanism and identify key interactions in the CDR loops and in the C_H1-C_L interface that contribute to stabilization. The dissociation of the V_H-V_L or C_H1-C_L domains can be represented by conformational changes in the bend angles between the domains. Our findings elucidate the melting process of antigen binding fragments and highlight critical residues in both the variable and constant domains, which are also strongly germline dependent. Thus, our proposed mechanisms have broad implications in the development and design of new and more stable antigen binding fragments.

Water Network in the Binding Pocket of Fluorinated BPTI-Trypsin Complexes─Insights from Simulation and Experiment

Structural waters in the S1 binding pocket of β-trypsin are critical for the stabilization of the complex of β-trypsin with its inhibitor bovine pancreatic trypsin inhibitor (BPTI). The inhibitor strength of BPTI can be modulated by replacing the critical lysine residue at the P1 position by non-natural amino acids. We study BPTI variants in which the critical Lys15 in BPTI has been replaced by α-aminobutyric acid (Abu) and its fluorinated derivatives monofluoroethylglycine (MfeGly), difluoroethylglycine (DfeGly), and trifluoroethylglycine (TfeGly). We investigate the hypothesis that additional water molecules in the binding pocket can form specific noncovalent interactions with the fluorinated side chains and thereby act as an extension of the inhibitors. We report potentials of mean force (PMF) of the unbinding process for all four complexes and enzyme activity inhibition assays. Additionally, we report the protein crystal structure of the Lys15MfeGly-BPTI-β-trypsin complex (pdb: 7PH1). Both experimental and computational data show a stepwise increase in inhibitor strength with increasing fluorination of the Abu side chain. The PMF additionally shows a minimum for the encounter complex and an intermediate state just before the bound state. In the bound state, the computational analysis of the structure and dynamics of the water molecules in the S1 pocket shows a highly dynamic network of water molecules that does not indicate a rigidification or stabilizing trend in regard to energetic properties that could explain the increase in inhibitor strength. The analysis of the energy and the entropy of the water molecules in the S1 binding pocket using grid inhomogeneous solvation theory confirms this result. Overall, fluorination systematically changes the binding affinity, but the effect cannot be explained by a persistent water network in the binding pocket. Other effects, such as the hydrophobicity of fluorinated amino acids and the stability of the encounter complex as well as the additional minimum in the potential of mean force in the bound state, likely influence the affinity more directly.

Fluorine-induced polarity increases inhibitory activity of BPTI towards chymotrypsin

Substituting the P1 position in bovine pancreatic trypsin inhibitor (BPTI) is known to heavily influence its inhibitory activity towards serine proteases. Side-chain fluorinated aliphatic amino acids have been shown to alter numerous properties of peptides and proteins and thus are of interest in the context of BPTI. In our study, we systematically investigated the site-specific incorporation of non-canonical amino acids into BPTI by microwave-assisted solid-phase peptide synthesis (SPPS). Inhibitor activity of the variants was tested towards the serine protease α-chymotrypsin. We observed enhanced inhibition of two fluorinated BPTIs compared to wild type and hydrocarbon variants. To further investigate the complexes, we performed X-ray structure analysis. Our findings underline the power fluorine offers as a tool in protein engineering to beneficially alter the effects on phenomena as protein-protein interactions.

Identifying the leading dynamics of ubiquitin: A comparison between the tICA and the LE4PD slow fluctuations in amino acids' position

Molecular Dynamics (MD) simulations of proteins implicitly contain the information connecting the atomistic molecular structure and proteins' biologically relevant motion, where large-scale fluctuations are deemed to guide folding and function. In the complex multiscale processes described by MD trajectories, it is difficult to identify, separate, and study those large-scale fluctuations. This problem can be formulated as the need to identify a small number of collective variables that guide the slow kinetic processes. The most promising method among the ones used to study the slow leading processes in proteins' dynamics is the time-structure based on time-lagged independent component analysis (tICA), which identifies the dominant components in a noisy signal. Recently, we developed an anisotropic Langevin approach for the dynamics of proteins, called the anisotropic Langevin Equation for Protein Dynamics or LE4PD-XYZ. This approach partitions the protein's MD dynamics into mostly uncorrelated, wavelength-dependent, diffusive modes. It associates with each mode a free-energy map, where one measures the spatial extension and the time evolution of the mode-dependent, slow dynamical fluctuations. Here, we compare the tICA modes' predictions with the collective LE4PD-XYZ modes. We observe that the two methods consistently identify the nature and extension of the slowest fluctuation processes. The tICA separates the leading processes in a smaller number of slow modes than the LE4PD does. The LE4PD provides time-dependent information at short times and a formal connection to the physics of the kinetic processes that are missing in the pure statistical analysis of tICA.

Structural insights and molecular dynamics into the inhibitory mechanism of a Kunitz-type trypsin inhibitor from Tamarindus indica L

Trypsin inhibitors from tamarind seed have been studied in vitro and in preclinical studies for the treatment of obesity, its complications and associated comorbidities. It is still necessary to fully understand the structure and behaviour of these molecules. We purifed this inhibitor, sequenced de novo by MALDI-TOF/TOF, performed its homology modelling, and assessed the interaction with the trypsin enzyme through molecular dynamics (MD) simulation under physiological conditions. We identified additional 75 amino acid residues, reaching approximately 72% of total coverage. The four best conformations of the best homology modelling were submitted to the MD. The conformation n°287 was selected considering the RMSD analysis and interaction energy (-301.0128 kcal.mol-1). Residues Ile (54), Pro (57), Arg (59), Arg (63), and Glu (78) of pTTI presented the highest interactions with trypsin, and arginine residues were mainly involved in its binding mechanism. The results favour bioprospecting of this protein for pharmaceutical health applications.

Computational investigation of the binding of a designed peptide to λ light chain amyloid fibril

Systemic light chain amyloidosis (AL) causes a malignant pathology associated with the formation of amyloid fibrils that deposit in human organs and tissues, leading to dysfunction and severe morbidity. Amyloid fibril-reactive antibodies have been used to remove amyloid from organs and are effective in restoring organ function in patients with AL amyloidosis. Unfortunately, antibodies do not bind amyloid in all AL patients, nor do they efficiently bind many other forms of amyloid. Recently, a synthetic peptide P62 was developed, which binds many forms of systemic amyloidosis and can be further modified and fused to a high-affinity peptide epitope to expand its utility as a novel amyloid immunotherapeutic. However, the molecular-level details of P62-fibril binding mechanisms, critical for future peptide design, are unclear. Here, we combine protein docking, all-atom molecular dynamics simulation and umbrella sampling to study the dynamical interactions between peptide P62 and a structural model of the λ light chain in systemic amyloidosis. We found that P62 only binds to the canonical interface of the fibril where the peptide inserts into the fibril groove and its two termini are more mobile than the helix core. Our results also revealed an important role of the lysine residues of P62 in the binding process by forming initial contacts with aspartic acids on the fibril surface. Collectively, our computational study provided molecular-level insights into the binding mechanism between an amyloid fibril model and peptide P62, which could lay a foundation for rational design of peptides for improved amyloid diagnosis and immunotherapy.

Energy penalties enhance flexible receptor docking in a model cavity

Protein flexibility remains a major challenge in library docking because of difficulties in sampling conformational ensembles with accurate probabilities. Here, we use the model cavity site of T4 lysozyme L99A to test flexible receptor docking with energy penalties from molecular dynamics (MD) simulations. Crystallography with larger and smaller ligands indicates that this cavity can adopt three major conformations: open, intermediate, and closed. Since smaller ligands typically bind better to the cavity site, we anticipate an energy penalty for the cavity opening. To estimate its magnitude, we calculate conformational preferences from MD simulations. We find that including a penalty term is essential for retrospective ligand enrichment; otherwise, high-energy states dominate the docking. We then prospectively docked a library of over 900,000 compounds for new molecules binding to each conformational state. Absent a penalty term, the open conformation dominated the docking results; inclusion of this term led to a balanced sampling of ligands against each state. High ranked molecules were experimentally tested by Tm upshift and X-ray crystallography. From 33 selected molecules, we identified 18 ligands and determined 13 crystal structures. Most interesting were those bound to the open cavity, where the buried site opens to bulk solvent. Here, highly unusual ligands for this cavity had been predicted, including large ligands with polar tails; these were confirmed both by binding and by crystallography. In docking, incorporating protein flexibility with thermodynamic weightings may thus access new ligand chemotypes. The MD approach to accessing and, crucially, weighting such alternative states may find general applicability.

X-Entropy: A Parallelized Kernel Density Estimator with Automated Bandwidth Selection to Calculate Entropy

X-Entropy is a Python package used to calculate the entropy of a given distribution, in this case, based on the distribution of dihedral angles. The dihedral entropy facilitates an alignment-independent measure of local protein flexibility. The key feature of our approach is a Gaussian kernel density estimation (KDE) using a plug-in bandwidth selection, which is fully implemented in a C++ backend and parallelized with OpenMP. We further provide a Python frontend, with predefined wrapper functions for classical coordinate-based dihedral entropy calculations, using a 1D approximation. This makes the package very straightforward to include in any Python-based analysis workflow. Furthermore, the frontend allows full access to the C++ backend, so that the KDE can be used on any binnable one-dimensional input data. In this application note, we discuss implementation and usage details and illustrate potential applications. In particular, we benchmark the performance of our module in calculating the entropy of samples drawn from a Gaussian distribution and the analytical solution thereof. Further, we analyze the computational performance of this module compared to well-established python libraries that perform KDE analyses. X-Entropy is available free of charge on GitHub (https://github.com/liedllab/X-Entropy).

Shark Antibody Variable Domains Rigidify Upon Affinity Maturation-Understanding the Potential of Shark Immunoglobulins as Therapeutics

Sharks and other cartilaginous fish are the phylogenetically oldest living organisms that have antibodies as part of their adaptive immune system. As part of their humoral adaptive immune response, they produce an immunoglobulin, the so-called immunoglobulin new antigen receptor (IgNAR), a heavy-chain only antibody. The variable domain of an IgNAR, also known as V NAR , binds the antigen as an independent soluble domain. In this study, we structurally and dynamically characterized the affinity maturation mechanism of the germline and somatically matured (PBLA8) V NAR to better understand their function and their applicability as therapeutics. We observed a substantial rigidification upon affinity maturation, which is accompanied by a higher number of contacts, thereby contributing to the decrease in flexibility. Considering the static x-ray structures, the observed rigidification is not obvious, as especially the mutated residues undergo conformational changes during the simulation, resulting in an even stronger network of stabilizing interactions. Additionally, the simulations of the V NAR in complex with the hen egg-white lysozyme show that the V NAR antibodies evidently follow the concept of conformational selection, as the binding-competent state already preexisted even without the presence of the antigen. To have a more detailed description of antibody-antigen recognition, we also present here the binding/unbinding mechanism between the hen egg-white lysozyme and both the germline and matured V NAR s. Upon maturation, we observed a substantial increase in the resulting dissociation-free energy barrier. Furthermore, we were able to kinetically and thermodynamically describe the binding process and did not only identify a two-step binding mechanism, but we also found a strong population shift upon affinity maturation toward the native binding pose.

Detection of Sub-Nanomolar Concentration of Trypsin by Thickness-Shear Mode Acoustic Biosensor and Spectrophotometry

The determination of protease activity is very important for disease diagnosis, drug development, and quality and safety assurance for dairy products. Therefore, the development of low-cost and sensitive methods for assessing protease activity is crucial. We report two approaches for monitoring protease activity: in a volume and at surface, via colorimetric and acoustic wave-based biosensors operated in the thickness-shear mode (TSM), respectively. The TSM sensor was based on a β-casein substrate immobilized on a piezoelectric quartz crystal transducer. After an enzymatic reaction with trypsin, it cleaved the surface-bound β-casein, which increased the resonant frequency of the crystal. The limit of detection (LOD) was 0.48 ± 0.08 nM. A label-free colorimetric assay for trypsin detection has also been performed using β-casein and 6-mercaptohexanol (MCH) functionalized gold nanoparticles (AuNPs/MCH-β-casein). Due to the trypsin cleavage of β-casein, the gold nanoparticles lost shelter, and MCH increased the attractive force between the modified AuNPs. Consequently, AuNPs aggregated, and the red shift of the absorption spectra was observed. Spectrophotometric assay enabled an LOD of 0.42 ± 0.03 nM. The Michaelis-Menten constant, KM, for reverse enzyme reaction has also been estimated by both methods. This value for the colorimetric assay (0.56 ± 0.10 nM) is lower in comparison with those for the TSM sensor (0.92 ± 0.44 nM). This is likely due to the better access of the trypsin to the β-casein substrate at the surface of AuNPs in comparison with those at the TSM transducer.