Molecular Modeling Reveals the Mechanism of Ran-RanGAP-Catalyzed Guanosine Triphosphate Hydrolysis without an Arginine Finger

Luminescent Metal-Organic Framework with Negative Electrostatic Pores for Highly Selective GDP Sensing

Electrostatic potential (ESP) plays an essential role in studying interactions among molecules. Developing probe materials capable of selectively detecting analytes by aligning their molecular ESP with the electrostatic interaction of the host probe material is critically important for identifying analogous analytes; however, relevant research is extremely lacking. In this work, we synthesized a luminescent metal-organic framework (LMOF, Cd-DBDP) featuring negative electrostatic pore environments achieved by incorporating numerous electronegative oxygen atoms and N-containing aromatic rings from organic linkers. The molecular ESP distributions of Cd-DBDP and RNA-related nucleotides were calculated and employed to predict the sensing results. Fluorescence tests demonstrated that Cd-DBDP represents the first example of an MOF-based sensor for guanosine diphosphate (GDP) sensing, and the experimental observations were highly consistent with the theoretical prediction. The sensing mechanism for GDP was thoroughly studied through Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy/energy-dispersive spectroscopy (SEM/EDS), X-ray photoelectron spectroscopy (XPS), and theoretical calculations. These findings provide valuable insights into understanding the interplay between the molecular ESP distribution condition and the sensing results. This study offers a theoretical guide for future sensory research and provides effective means for the design and synthesis of highly efficient sensing MOFs, lending a solid groundwork for further exploration in this field.

Molecular dynamics simulations for the structure-based drug design: targeting small-GTPases proteins

INTRODUCTION

Molecular Dynamics (MD) simulations can support mechanism-based drug design. Indeed, MD simulations by capturing biomolecule motions at finite temperatures can reveal hidden binding sites, accurately predict drug-binding poses, and estimate the thermodynamics and kinetics, crucial information for drug discovery campaigns. Small-Guanosine Triphosphate Phosphohydrolases (GTPases) regulate a cascade of signaling events, that affect most cellular processes. Their deregulation is linked to several diseases, making them appealing drug targets. The broad roles of small-GTPases in cellular processes and the recent approval of a covalent KRas inhibitor as an anticancer agent renewed the interest in targeting small-GTPase with small molecules.

AREA COVERED

This review emphasizes the role of MD simulations in elucidating small-GTPase mechanisms, assessing the impact of cancer-related variants, and discovering novel inhibitors.

EXPERT OPINION

The application of MD simulations to small-GTPases exemplifies the role of MD simulations in the structure-based drug design process for challenging biomolecular targets. Furthermore, AI and machine learning-enhanced MD simulations, coupled with the upcoming power of quantum computing, are promising instruments to target elusive small-GTPases mutations and splice variants. This powerful synergy will aid in developing innovative therapeutic strategies associated to small-GTPases deregulation, which could potentially be used for personalized therapies and in a tissue-agnostic manner to treat tumors with mutations in small-GTPases.

Molecular Basis of the Substrate Specificity of Phosphotriesterase from Pseudomonas diminuta: A Combined QM/MM MD and Electron Density Study

The occurrence of organophosphorus compounds, pesticides, and flame-retardants in wastes is an emerging ecological problem. Bacterial phosphotriesterases are capable of hydrolyzing some of them. We utilize modern molecular modeling tools to study the hydrolysis mechanism of organophosphorus compounds with good and poor leaving groups by phosphotriesterase from Pseudomonas diminuta (Pd-PTE). We compute Gibbs energy profiles for enzymes with different cations in the active site: native Zn2+cations and Co2+cations, which increase the steady-state rate constant. Hydrolysis occurs in two elementary steps via an associative mechanism and formation of the pentacoordinated intermediate. The first step, a nucleophilic attack, occurs with a low energy barrier independently of the substrate. The second step has a low energy barrier and considerable stabilization of products for substrates with good leaving groups. For substrates with poor leaving groups, the reaction products are destabilized relative to the ES complex that suppresses the reaction. The reaction proceeds with low energy barriers for substrates with good leaving groups with both Zn2+and Co2+cations in the active site; thus, the product release is likely to be a limiting step. Electron density and geometry analysis of the QM/MM MD trajectories of the intermediate states with all considered compounds allow us to discriminate substrates by their ability to be hydrolyzed by the Pd-PTE. For hydrolyzable substrates, the cleaving bond between a phosphorus atom and a leaving group is elongated, and electron density depletion is observed on the Laplacian of electron density maps.

Mechanism-Based Redesign of GAP to Activate Oncogenic Ras

Ras GTPases play a crucial role in cell signaling pathways. Mutations of the Ras gene occur in about one third of cancerous cell lines and are often associated with detrimental clinical prognosis. Hot spot residues Gly12, Gly13, and Gln61 cover 97% of oncogenic mutations, which impair the enzymatic activity in Ras. Using QM/MM free energy calculations, we present a two-step mechanism for the GTP hydrolysis catalyzed by the wild-type Ras.GAP complex. We found that the deprotonation of the catalytic water takes place via the Gln61 as a transient Brønsted base. We also determined the reaction profiles for key oncogenic Ras mutants G12D and G12C using QM/MM minimizations, matching the experimentally observed loss of catalytic activity, thereby validating our reaction mechanism. Using the optimized reaction paths, we devised a fast and accurate procedure to design GAP mutants that activate G12D Ras. We replaced GAP residues near the active site and determined the activation barrier for 190 single mutants. We furthermore built a machine learning for ultrafast screening, by fast prediction of the barrier heights, tested both on the single and double mutations. This work demonstrates that fast and accurate screening can be accomplished via QM/MM reaction path optimizations to design protein sequences with increased catalytic activity. Several GAP mutations are predicted to re-enable catalysis in oncogenic G12D, offering a promising avenue to overcome aberrant Ras-driven signal transduction by activating enzymatic activity instead of inhibition. The outlined computational screening protocol is readily applicable for designing ligands and cofactors analogously.

Multiscale Simulations of the Covalent Inhibition of the SARS-CoV-2 Main Protease: Four Compounds and Three Reaction Mechanisms

We report the results of computational modeling of the reactions of the SARS-CoV-2 main protease (MPro) with four potential covalent inhibitors. Two of them, carmofur and nirmatrelvir, have shown experimentally the ability to inhibit MPro. Two other compounds, X77A and X77C, were designed computationally in this work. They were derived from the structure of X77, a non-covalent inhibitor forming a tight surface complex with MPro. We modified the X77 structure by introducing warheads capable of reacting with the catalytic cysteine residue in the MPro active site. The reaction mechanisms of the four molecules with MPro were investigated by quantum mechanics/molecular mechanics (QM/MM) simulations. The results show that all four compounds form covalent adducts with the catalytic cysteine Cys 145 of MPro. From the chemical perspective, the reactions of these four molecules with MPro follow three distinct mechanisms. The reactions are initiated by a nucleophilic attack of the thiolate group of the deprotonated cysteine residue from the catalytic dyad Cys145-His41 of MPro. In the case of carmofur and X77A, the covalent binding of the thiolate to the ligand is accompanied by the formation of the fluoro-uracil leaving group. The reaction with X77C follows the nucleophilic aromatic substitution SNAr mechanism. The reaction of MPro with nirmatrelvir (which has a reactive nitrile group) leads to the formation of a covalent thioimidate adduct with the thiolate of the Cys145 residue in the enzyme active site. Our results contribute to the ongoing search for efficient inhibitors of the SARS-CoV-2 enzymes.

Dynamic regulation of RAS and RAS signaling

RAS proteins regulate most aspects of cellular physiology. They are mutated in 30% of human cancers and 4% of developmental disorders termed Rasopathies. They cycle between active GTP-bound and inactive GDP-bound states. When active, they can interact with a wide range of effectors that control fundamental biochemical and biological processes. Emerging evidence suggests that RAS proteins are not simple on/off switches but sophisticated information processing devices that compute cell fate decisions by integrating external and internal cues. A critical component of this compute function is the dynamic regulation of RAS activation and downstream signaling that allows RAS to produce a rich and nuanced spectrum of biological outputs. We discuss recent findings how the dynamics of RAS and its downstream signaling is regulated. Starting from the structural and biochemical properties of wild-type and mutant RAS proteins and their activation cycle, we examine higher molecular assemblies, effector interactions and downstream signaling outputs, all under the aspect of dynamic regulation. We also consider how computational and mathematical modeling approaches contribute to analyze and understand the pleiotropic functions of RAS in health and disease.

How Reproducible Are QM/MM Simulations? Lessons from Computational Studies of the Covalent Inhibition of the SARS-CoV-2 Main Protease by Carmofur

This work explores the level of transparency in reporting the details of computational protocols that is required for practical reproducibility of quantum mechanics/molecular mechanics (QM/MM) simulations. Using the reaction of an essential SARS-CoV-2 enzyme (the main protease) with a covalent inhibitor (carmofur) as a test case of chemical reactions in biomolecules, we carried out QM/MM calculations to determine the structures and energies of the reactants, the product, and the transition state/intermediate using analogous QM/MM models implemented in two software packages, NWChem and Q-Chem. Our main benchmarking goal was to reproduce the key energetics computed with the two packages. Our results indicate that quantitative agreement (within the numerical thresholds used in calculations) is difficult to achieve. We show that rather minor details of QM/MM simulations must be reported in order to ensure the reproducibility of the results and offer suggestions toward developing practical guidelines for reporting the results of biosimulations.

Two Sides of Quantum-Based Modeling of Enzyme-Catalyzed Reactions: Mechanistic and Electronic Structure Aspects of the Hydrolysis by Glutamate Carboxypeptidase

We report the results of a computational study of the hydrolysis reaction mechanism of N-acetyl-l-aspartyl-l-glutamate (NAAG) catalyzed by glutamate carboxypeptidase II. Analysis of both mechanistic and electronic structure aspects of this multistep reaction is in the focus of this work. In these simulations, model systems are constructed using the relevant crystal structure of the mutated inactive enzyme. After selection of reaction coordinates, the Gibbs energy profiles of elementary steps of the reaction are computed using molecular dynamics simulations with ab initio type QM/MM potentials (QM/MM MD). Energies and forces in the large QM subsystem are estimated in the DFT(PBE0-D3/6-31G**) approximation. The established mechanism includes four elementary steps with the activation energy barriers not exceeding 7 kcal/mol. The models explain the role of point mutations in the enzyme observed in the experimental kinetic studies; namely, the Tyr552Ile substitution disturbs the "oxyanion hole", and the Glu424Gln replacement increases the distance of the nucleophilic attack. Both issues diminish the substrate activation in the enzyme active site. To quantify the substrate activation, we apply the QTAIM-based approaches and the NBO analysis of dynamic features of the corresponding enzyme-substrate complexes. Analysis of the 2D Laplacian of electron density maps allows one to define structures with the electron density deconcentration on the substrate carbon atom, i.e., at the electrophilic site of reactants. The similar electronic structure element in the NBO approach is a lone vacancy on the carbonyl carbon atom in the reactive species. The electronic structure patterns revealed in the NBO and QTAIM-based analyses consistently clarify the reactivity issues in this system.