Use of Nonequilibrium Work Methods to Compute Free Energy Differences Between Molecular Mechanical and Quantum Mechanical Representations of Molecular Systems

Carrying out free energy simulations (FES) using quantum mechanical (QM) Hamiltonians remains an attractive, albeit elusive goal. Renewed efforts in this area have focused on using “indirect” thermodynamic cycles to connect “low level” simulation results to “high level” free energies. The main obstacle to computing converged free energy results between molecular mechanical (MM) and QM (Δ<i>A</i>^MM→QM), as recently demonstrated by us and others, is differences in the so-called “stiff” degrees of freedom (e.g., bond stretching) between the respective energy surfaces. Herein, we demonstrate that this problem can be efficiently circumvented using nonequilibrium work (NEW) techniques, i.e., Jarzynski’s and Crooks’ equations. Initial applications of computing Δ<i>A</i>_NEW^MM→QM, for blocked amino acids alanine and serine as well as to generate butane’s potentials of mean force via the indirect QM/MM FES method, showed marked improvement over traditional FES approaches

Unlocking the Binding and Reaction Mechanism of Hydroxyurea Substrates as Biological Nitric Oxide Donors

Hydroxyurea is the only FDA approved treatment of sickle cell disease. It is believed that the primary mechanism of action is associated with the pharmacological elevation of nitric oxide in the blood; however, the exact details of this are still unclear. In the current work, we investigate the atomic level details of this process using a combination of flexible-ligand/flexible-receptor virtual screening coupled with energetic analysis that decomposes interaction energies. Utilizing these methods, we were able to elucidate the previously unknown substrate binding modes of a series of hydroxyurea analogs to hemoglobin and the concomitant structural changes of the enzyme. We identify a backbone carbonyl that forms a hydrogen bond with bound substrates. Our results are consistent with kinetic and electron paramagnetic resonance (EPR) measurements of hydroxyurea–hemoglobin reactions, and a full mechanism is proposed that offers new insights into possibly improving substrate binding and/or reactivity

How Does Catalase Release Nitric Oxide? A Computational Structure–Activity Relationship Study

Hydroxyurea (HU) is the only FDA approved medication for treating sickle cell disease in adults. The primary mechanism of action is pharmacological elevation of nitric oxide (NO) levels which induces propagation of fetal hemoglobin. HU is known to undergo redox reactions with heme based enzymes like hemoglobin and catalase to produce NO. However, specific details about the HU based NO release remain unknown. Experimental studies indicate that interaction of HU with human catalase compound I produces NO. Presently, we combine flexible receptor–flexible substrate induced fit docking (IFD) with energy decomposition analyses to examine the atomic level details of a possible key step in the clinical conversion of HU to NO. Substrate binding modes of nine HU analogs with catalase compound I were investigated to determine the essential properties necessary for effective NO release. Three major binding orientations were found that provide insight into the possible reaction mechanisms for producing NO. Further results show that anion/radical intermediates produced as part of these mechanisms would be stabilized by hydrogen bonding interactions from distal residues His75, Asn148, Gln168, and oxoferryl-heme. These details will ideally contribute to both a clearer mechanistic picture and provide insights for future structure based drug design efforts

Can Molecular Dynamics and QM/MM Solve the Penicillin Binding Protein Protonation Puzzle?

Benzylpenicillin, a member of the β-lactam antibiotic class, has been widely used to combat bacterial infections since 1947. The general mechanism is well-known: a serine protease enzyme (i.e., DD-peptidase) forms a long lasting intermediate with the lactam ring of the antibiotic known as acylation, effectively preventing biosynthesis of the bacterial cell wall. Despite this overall mechanistic understanding, many details of binding and catalysis are unclear. Specifically, there is ongoing debate about active site protonation states and the role of general acids/bases in the reaction. Herein, a unique combination of MD simulations, QM/MM minimizations, and QM/MM orbital analyses is combined with systematic variation of active site residue protonation states. Critical interactions that maximize the stability of the bound inhibitor are examined and used as metrics. This approach was validated by examining cefoxitin interactions in the CTX-M β-lactamase from E. coli and compared to an ultra high-resolution (0.88 Å) crystal structure. Upon confirming the approach used, an investigation of the preacylated Streptomyces R61 active site with bound benzylpenicillin was performed, varying the protonation states of His298 and Lys65. We concluded that protonated His298 and deprotonated Lys65 are most likely to exist in the R61 active site

Identification and Characterization of Noncovalent Interactions That Drive Binding and Specificity in DD-Peptidases and β‑Lactamases

Bacterial resistance to standard (i.e., β-lactam-based) antibiotics has become a global pandemic. Simultaneously, research into the underlying causes of resistance has slowed substantially, although its importance is universally recognized. Key to unraveling critical details is characterization of the noncovalent interactions that govern binding and specificity (DD-peptidases, antibiotic targets, versus β-lactamases, the evolutionarily derived enzymes that play a major role in resistance) and ultimately resistance as a whole. Herein, we describe a detailed investigation that elicits new chemical insights into these underlying intermolecular interactions. Benzylpenicillin and a novel β-lactam peptidomimetic complexed to the Stremptomyces R61 peptidase are examined using an arsenal of computational techniques: MD simulations, QM/MM calculations, charge perturbation analysis, QM/MM orbital analysis, bioinformatics, flexible receptor/flexible ligand docking, and computational ADME predictions. Several key molecular level interactions are identified that not only shed light onto fundamental resistance mechanisms, but also offer explanations for observed specificity. Specifically, an extended π–π network is elucidated that suggests antibacterial resistance has evolved, in part, due to stabilizing aromatic interactions. Additionally, interactions between the protein and peptidomimetic substrate are identified and characterized. Of particular interest is a water-mediated salt bridge between Asp217 and the positively charged N-terminus of the peptidomimetic, revealing an interaction that may significantly contribute to β-lactam specificity. Finally, interaction information is used to suggest modifications to current β-lactam compounds that should both improve binding and specificity in DD-peptidases and their physiochemical properties

Disruption of an Active Site Network Leads to Activation of C2α-Lactylthiamin Diphosphate on the Antibacterial Target 1‑Deoxy‑d‑xylulose-5-phosphate Synthase

The bacterial metabolic enzyme 1-deoxy-d-xylulose-5-phosphate synthase (DXPS) catalyzes the thiamin diphosphate (ThDP)-dependent formation of DXP from pyruvate and d-glyceraldehyde-3-phosphate (d-GAP). DXP is an essential bacteria-specific metabolite that feeds into the biosynthesis of isoprenoids, pyridoxal phosphate (PLP), and ThDP. DXPS catalyzes the activation of pyruvate to give the C2α-lactylThDP (LThDP) adduct that is long-lived on DXPS in a closed state in the absence of the cosubstrate. Binding of d-GAP shifts the DXPS-LThDP complex to an open state which coincides with LThDP decarboxylation. This gated mechanism distinguishes DXPS in ThDP enzymology. How LThDP persists on DXPS in the absence of cosubstrate, while other pyruvate decarboxylases readily activate LThDP for decarboxylation, is a long-standing question in the field. We propose that an active site network functions to prevent LThDP activation on DXPS until the cosubstrate binds. Binding of d-GAP coincides with a conformational shift and disrupts the network causing changes in the active site that promote LThDP activation. Here, we show that the substitution of putative network residues, as well as nearby residues believed to contribute to network charge distribution, predictably affects LThDP reactivity. Substitutions predicted to disrupt the network have the effect to activate LThDP for decarboxylation, resulting in CO2 and acetate production. In contrast, a substitution predicted to strengthen the network fails to activate LThDP and has the effect to shift DXPS toward the closed state. Network-disrupting substitutions near the carboxylate of LThDP also have a pronounced effect to shift DXPS to an open state. These results offer initial insights to explain the long-lived LThDP intermediate and its activation through disruption of an active site network, which is unique to DXPS. These findings have important implications for DXPS function in bacteria and its development as an antibacterial target

Disruption of an Active Site Network Leads to Activation of C2α-Lactylthiamin Diphosphate on the Antibacterial Target 1‑Deoxy‑d‑xylulose-5-phosphate Synthase

The bacterial metabolic enzyme 1-deoxy-d-xylulose-5-phosphate synthase (DXPS) catalyzes the thiamin diphosphate (ThDP)-dependent formation of DXP from pyruvate and d-glyceraldehyde-3-phosphate (d-GAP). DXP is an essential bacteria-specific metabolite that feeds into the biosynthesis of isoprenoids, pyridoxal phosphate (PLP), and ThDP. DXPS catalyzes the activation of pyruvate to give the C2α-lactylThDP (LThDP) adduct that is long-lived on DXPS in a closed state in the absence of the cosubstrate. Binding of d-GAP shifts the DXPS-LThDP complex to an open state which coincides with LThDP decarboxylation. This gated mechanism distinguishes DXPS in ThDP enzymology. How LThDP persists on DXPS in the absence of cosubstrate, while other pyruvate decarboxylases readily activate LThDP for decarboxylation, is a long-standing question in the field. We propose that an active site network functions to prevent LThDP activation on DXPS until the cosubstrate binds. Binding of d-GAP coincides with a conformational shift and disrupts the network causing changes in the active site that promote LThDP activation. Here, we show that the substitution of putative network residues, as well as nearby residues believed to contribute to network charge distribution, predictably affects LThDP reactivity. Substitutions predicted to disrupt the network have the effect to activate LThDP for decarboxylation, resulting in CO2 and acetate production. In contrast, a substitution predicted to strengthen the network fails to activate LThDP and has the effect to shift DXPS toward the closed state. Network-disrupting substitutions near the carboxylate of LThDP also have a pronounced effect to shift DXPS to an open state. These results offer initial insights to explain the long-lived LThDP intermediate and its activation through disruption of an active site network, which is unique to DXPS. These findings have important implications for DXPS function in bacteria and its development as an antibacterial target

Example of Structure Editing module setup for iron-sulfur containing proteins.

<p>Example of Structure Editing module setup for iron-sulfur containing proteins.</p

Web-Based Computational Chemistry Education with CHARMMing III: Reduction Potentials of Electron Transfer Proteins

<div><p>A module for fast determination of reduction potentials, <i>E°</i>, of redox-active proteins has been implemented in the CHARMM INterface and Graphics (CHARMMing) web portal (<a href="http://www.charmming.org" target="_blank">www.charmming.org</a>). The free energy of reduction, which is proportional to <i>E°</i>, is composed of an intrinsic contribution due to the redox site and an environmental contribution due to the protein and solvent. Here, the intrinsic contribution is selected from a library of pre-calculated density functional theory values for each type of redox site and redox couple, while the environmental contribution is calculated from a crystal structure of the protein using Poisson-Boltzmann continuum electrostatics. An accompanying lesson demonstrates a calculation of <i>E°</i>. In this lesson, an ionizable residue in a [4Fe-4S]-protein that causes a pH-dependent <i>E°</i> is identified, and the <i>E°</i> of a mutant that would test the identification is predicted. This demonstration is valuable to both computational chemistry students and researchers interested in predicting sequence determinants of <i>E°</i> for mutagenesis.</p></div

Example of the graphic interface for making point mutations in CHARMMing.

<p>Example of the graphic interface for making point mutations in CHARMMing.</p