Physical Chemistry Chemical Physics
Abstract: The extracellular environment but also cellular metabolism can generate oxidative stress that can chemically modify and damage protein molecules. The sulfur containing amino acid cysteine (CYS) is particularly vulnerable to oxidation. The molecular details of how CYS oxidation can modulate stability and binding of proteins is still not well understood. Using alchemical free energy simulations, we calculate the change in protein stability and association upon CYS oxidation to different oxidation states for two example proteins. In the case of the URN1 splicing factor FF domain (URN1-FF) the simulations predict a significant decrease in stability upon oxidation in agreement with experiment and the effect also depends on the final oxidation state. In addition, the oxidation leads to conformational changes and partial unfolding at the protein C-terminus. In contrast, for the second system, Parkinson disease protein 7 (DJ-1), CYS oxidation enhances significantly the protein monomer stability again in agreement with the experimental observation and slightly destabilizes homo dimerization. Analysis of the molecular details associated with CYS oxidation in the folded proteins allows us to gain insights into why both stabilizing as well as destabilizing effects can be observed. The CYS oxidation simulation methodology could also serve as a general protocol to analyze single and multiple CYS oxidations in other protein systems and its influence on protein binding and stability.
Computational and Structural Biotechnology Journal, Vol. 31, pp. 61-73
Abstract: Cathepsins are papain-like proteolytic enzymes localized in lysosomes and the extracellular matrix, where they participate in diverse physiological and pathological processes. They are synthesized as inactive precursors—procathepsins—containing a propeptide domain that blocks access to the active site. The activity of (pro)cathepsins can be modulated by glycosaminoglycans (GAGs), which are negatively charged, sulfated polysaccharides. This study aimed to develop machine learning (ML) models to predict MM-GBSA binding free energies in (pro)cathepsin–GAG complexes. Molecular dynamics simulations were performed using the ff14SB/GLYCAM06j force field for six (pro)cathepsins and six GAGs, representing four periodic states and six binding poses. Structural and energetic descriptors derived from these simulations were used as input features for eight ML algorithms: ElasticNet, Linear Regression, LinearSVR (with RBFSampler), LightGBM, Histogram Gradient Boosting, Fully Connected Neural Network (FCNN), and Random Forest. The FCNN yielded the most accurate predictions (R2 = 0.7124 ± 0.0089; MAE = 5.2033 ± 0.0876 kcal/mol), with GradientBoost-based models performing comparably. Optimal FCNN performance was achieved with a minimal architecture (no hidden layers, dropout rate 0.01, ReLU activation). Incorporating Linear Interaction Energy (LIE) components significantly improved prediction accuracy, and approximately 17,000 data points were sufficient for stable model performance. Overall, this study provides a proof of concept for using ML to estimate binding free energies in protein–GAG systems and establishes a foundation for generalizable, structure-based predictors applicable to a broad range of biomolecular complexes. Beyond predictive accuracy, this approach enables rapid screening of MMGBSA interactions, facilitating the identification of favorable binding regions and accelerating structure-guided design efforts.
Chemical Science, Vol. 17, pp. 3198-3211
Abstract: DNA mimic foldamers are helically folded aromatic oligoamides bearing negatively charged side chains that mimic the shape and charge distribution of double-stranded B-DNA. They have been shown to bind to some DNA-binding proteins better than DNA itself and thus have potential to interfere with DNA-protein interactions. Their structure has been previously characterized in detail by X-ray crystallography. We have now investigated their structural dynamics both computationally and experimentally. The force field parameters of the building blocks required for DNA mimicry were optimized and implemented in AMBER to perform molecular dynamics simulations of the foldamer helices. The position of the negatively charged side chains on the helix, the charge state of the side chains, and the presence of salt were systematically varied. The simulations revealed that the global flexibility parameters for twisting and bending of the foldamer helices are of similar magnitude to those of B-DNA, though distinct kinking events and motions are involved. A range of sequences were then prepared for experimental investigations using 1H NMR, UV-vis absorption and circular dichroism spectroscopies. Measurements revealed that the foldamer helices are stable over a broad range of temperature, pH and salt conditions in aqueous solutions, but that they nevertheless undergo structural changes when conditions are modified. An assay was developed to quantitatively assess foldamer helix stability through the measurement of the rate of interconversion between right-handed and left-handed diastereomeric conformers. Unexpectedly, suppressing some negatively charged side chains had a destabilizing effect on the helix, suggesting a more complex role of the side chains than electrostatic repulsions.
Journal of Molecular Biology, Vol. 438
Abstract: Cellular metabolic systems but also the extracellular environment can generate reactive oxygen species that lead to oxidation of methionine (MET) and interfere with protein folding and protein–protein association. The molecular mechanism of how MET oxidation (MEO) influences conformational stability and binding is not well understood. We employ alchemical free energy simulations to systematically study the influence of MET oxidation on protein–protein binding using the tetramerization domain of the tumor suppression protein p53 as a model system. A single MEO in one tetramerisation domain destabilizes the tetramer by ≈1.1–1.8 kcal/mol depending slightly on the MEO diastereomer. The simulations on double and triple oxidations reveal increased destabilization (≈3–7 kcal/mol) and significant cooperative effects depending on the relative position of the oxidized residues. The MET oxidation effects are of similar magnitude for the change in stability of the human prion protein (HPP) that served as a second model system and also agreed with available experimental data. The calculations predict a significant dependence of stability changes on the position of the MEO and also indicate non-additive effects of multiple oxidations which may play a role to protect proteins from oxidative damage and stress. Analysis of the Molecular Dynamics trajectories allowed us to interpret the oxidation effects in molecular detail. The simulation methodology could also serve as a general protocol to analyze single and multiple MET oxidations in other systems and its influence on protein binding and stability.
Biophysical Journal, Vol. 125, pp. 950-961
Abstract: Numerous proteins are associated with cellular membranes and often contain single or multiple membrane-spanning helices. These helices can mediate membrane protein interactions to form functional complexes involved in enzymatic or signaling processes. A detailed understanding of interactions and driving forces is essential for the understanding of membrane protein association and for membrane protein complex design. The glycophorin-A transmembrane helical dimer has been studied extensively by biochemical and structural methods, including mutagenesis of dimer interface residues. We use alchemical free energy simulations to investigate the effect of amino acid substitutions on the binding free energy and the change in membrane insertion free energy. Simulations on more than 30 substitutions were performed in different lipid environments and resulted in overall good agreement with experimental data, both for the change in membrane insertion and dimerization free energies. For the membrane insertion, the simulations slightly underestimated the stabilization due to larger nonpolar residues and overestimated the destabilization by substitution with polar residues. Interestingly, very little influence of the lipid type on changes in membrane insertion free energy was observed. The influence of lipid environment on the calculated binding free energy changes was also modest for most substitutions but significant for mutations that affect the glycine residues in the central GxxxG interaction motif. Enhanced lipid dynamics of unsaturated lipids may compensate for conformational changes in the case of mutations of interface glycine to larger residues. Mutations, especially of residues V84 and T87 to other polar and nonpolar residues, allowed us to estimate the contribution of additional hydrogen bonds (∼-1.0 kcal/mol) and removal of methyl groups (∼0.5 kcal/mol) to dimerization. Our study also demonstrates the usefulness of alchemical free energy simulations to quantify the influence of amino acid substitutions on membrane helix association and could be valuable for the design of new membrane protein interactions.
Proteins: Structure, Function and Bioinformatics
Abstract: The control and modulation of protein–protein interactions (PPIs) is of central importance for the majority of biological processes and most biomedical applications. Stabilization of PPIs, besides inhibition, is of growing pharmaceutical interest. Due to their small size, drug-like organic molecules may not provide sufficient interaction surfaces to allow for high-affinity dual binding to both partners of a protein–protein complex. Cyclic peptides offer larger interaction surfaces, making them a promising class of stabilizers of PPIs. We have developed a computational protocol to rapidly and systematically design cyclic peptides that optimize not only the interaction with one target protein but simultaneously optimize the dual binding to two protein partners. The cyclic peptide generation is based on a modified AlphaFold2-based peptide design approach and combines confidence scoring with force field-based scoring using Molecular Dynamics simulations. The performance of the method is tested on protein–protein complexes with known cyclic peptide binders and stabilizers. In addition, the approach is used to design cyclic peptides that can act as bifunctional molecules, recruiting the cellular protein degradation system to a target protein. The designed cyclic peptides achieve similar or better calculated interaction scores than known binders and exhibit well-balanced interactions with both protein partners. The design protocol is generally applicable to cyclic peptide design for modulating or inducing protein–protein association and could be useful for many biomedical design efforts.
Bioinformatics, Vol. 42
Abstract: Motivation The rational design of chemical compounds that bind to a desired protein target molecule is a major goal of drug discovery. Most current molecular docking but also fragment-based buildup or machine learning-based generative drug design approaches employ a rigid protein target structure. Results Based on recent progress in predicting protein structures and complexes with chemical compounds, we have designed an approach, AI-MCLig, to optimize a chemical compound bound to a fully flexible and conformationally adaptable protein binding region. During a Monte Carlo (MC)-type simulation to randomly change a chemical compound, the target protein–compound complex is completely rebuilt at every MC step using the Chai-1 protein structure prediction program. Besides compound flexibility it allows the protein to adapt to the chemically changing compound. MC protocols based on atom-/bond-type changes or based on combining larger chemical fragments have been tested. Simulations on four test targets resulted in potential ligands that show very good binding scores comparable to experimentally known binders using several different scoring schemes. The MC-based compound design approach is complementary to existing approaches and could help for the rapid design of putative binders including induced fit of the protein target. Availability and implementation Datasets, examples, and source code are available on our public GitHub repository https://github.com/JakobAgamia/AI-MCLig and on Zenodo at https://doi.org/10.5281/zenodo.17800140.
Virchows Archiv
Abstract: Small cell lung carcinoma (SCLC) is classically defined by biallelic inactivation of RB1 and TP53. However, a small subset of tumors retains Rb expression and exhibits distinct molecular features. Here, we report two Rb-retained SCLC cases that expand the biological and therapeutic spectrum of this subgroup. Both tumors occurred in middle-aged women, showed small cell morphology with some variant features, and displayed complex copy number alterations. Case 1 harbored a truncal KRAS p.G12C mutation with high-level amplification of chromosome 11q13-q14, including CCND1, and demonstrated a clinical response to sotorasib. Case 2 harbored a TP53 mutation, CDKN2A loss, STK11 inactivation, and a novel IKZF2::ERBB4 fusion. These findings highlight the molecular heterogeneity of Rb-retained SCLC and demonstrate that this subgroup can harbor clinically actionable oncogenic drivers. Accordingly, routine assessment of Rb expression in SCLC, followed by comprehensive molecular profiling of Rb-retained tumors, is warranted to uncover therapeutically relevant targets.
Langmuir, Vol. 42, pp. 8443-8452
Abstract: Interactions between RNA and lipids are fundamental to biological processes and are increasingly exploited for RNA delivery by lipid nanoparticles. However, RNA-lipid interactions remain challenging to characterize at the molecular level. Here, we address the modeling of RNA at lipid/water interfaces using coarse-grained (CG) simulations, experimental validation using scattering data, and prediction of neutron (NR) and X-ray reflectivity (XRR) profiles from the simulations. Using neutral DOPC and cationic DOTAP bilayers, we show that lipid-RNA interactions depend strongly on RNA secondary structure, with single-stranded regions exhibiting interfacial affinity higher than that of double-stranded segments. We validate the CG lipid simulations, showing that while they reproduce experimental X-ray scattering data only qualitatively, the agreement improves markedly after back-mapping to atomistic resolution followed by energy minimization and short all-atom molecular dynamics simulations. We further simulated distinct tRNA conformations and analyzed the influence of RNA secondary structure, concentration, solvent contrast, and lipid deuteration on NR and XRR signals, identifying the conditions under which such experiments probe RNA adsorption and discriminate between different RNA conformations. Together, these results demonstrate that CG simulations combined with reflectivity data provide a powerful approach to probe RNA adsorption and structure at lipid-water interfaces and support the design and interpretation of scattering experiments.
Chemical Science, Vol. 16, pp. 9472-9483
Abstract: Treatment of Mycobacterium tuberculosis infections is a challenging task due to long treatment regiments and a growing number of resistant clinical isolates. To identify new antibiotic hits, we screened a focused library of 400 synthetic compounds derived from a recently discovered molecule with promising anti-mycobacterial activity. A suite of more potent hit molecules was deciphered with sub-micromolar activity. Utilising tailored affinity-based probes for chemical proteomic investigations, we successfully pinpointed the mycolic acid transporter MmpL3 and two epoxide hydrolases, EphD and EphF, also linked to mycolic acid biosynthesis, as specific targets of the compounds. These targets were thoroughly and independently validated by activity assays, under- and overexpression, resistance generation, and proteomic studies. Structural refinement of the most potent hit molecules led to the development of a new lead compound that demonstrates enhanced biological activity in M. tuberculosis, low human cytotoxicity, and improved solubility and oral bioavailability - traits that are often challenging to achieve with anti-mycobacterial drugs. Overall, drug-likeness, as well as the dual mode of action, addressing the mycolic acid cell wall assembly at two distinct steps, holds significant potential for further in vivo applications.
