Elucidation of the protonation states of the catalytic residues in mtKasA: implications for inhibitor design

Mechanistic Insight into how β-Ketoacyl ACP Synthase I (KasA) Recognizes the Fatty Acid Chain Length of its Substrate

β-ketoacyl ACP synthase I (KasA) has been considered as a promising drug target against Tuberculosis because it is known to play a pivotal role in the survival of Mycobacterium Tuberculosis, a causative agent of Tuberculosis. KasA catalyzes the reaction elongating only the acyl chain that is 16 carbon atoms in length or longer, but the molecular details of how KasA selectively recognizes only the substrate longer than a certain length still remain unknown. In the present study, this challenging subject is addressed, and to this end, molecular dynamics (MD) simulations and free energy calculations for actual substrate binding process are carried out. The results illustrate that the substrate specificity of KasA is highly linked to its cooperativity and this cooperativity is realized through the activation of catalytic residues. Through these results, the mechanistic details of how KasA can be selectively activated only by the substrate with a proper length are suggested.

Mycobacterium tuberculosis KasA as a drug target: Structure-based inhibitor design

Recent studies have reported the β-ketoacyl-acyl carrier protein KasA as a druggable target for Mycobacterium tuberculosis. This review summarizes the current status of major classes of KasA inhibitors with an emphasis on significant contributions from structure-based design methods leveraging X-ray crystal structures of KasA alone and in complex with inhibitors. The issues addressed within each inhibitor class are discussed while detailing the characterized interactions with KasA and structure-activity relationships. A critical analysis of these findings should lay the foundation for new KasA inhibitors to study the basic biology of M. tuberculosis and to form the basis of new antitubercular molecules of clinical significance with activity against drug-sensitive and drug-resistant infections.

User-Friendly Quantum Mechanics: Applications for Drug Discovery

Quantum mechanics (QM) methods provide a fine description of receptor-ligand interactions and of chemical reactions. Their use in drug design and drug discovery is increasing, especially for complex systems including metal ions in the binding sites, for the design of highly selective inhibitors, for the optimization of bi-specific compounds, to understand enzymatic reactions, and for the study of covalent ligands and prodrugs. They are also used for generating molecular descriptors for predictive QSAR/QSPR models and for the parameterization of force fields. Thanks to the continuous increase of computational power offered by GPUs and to the development of sophisticated algorithms, QM methods are becoming part of the standard tools used in computer-aided drug design (CADD). We present the most used QM methods and software packages, and we discuss recent representative applications in drug design and drug discovery.

Synergistic Lethality of a Binary Inhibitor of Mycobacterium tuberculosis KasA

We report GSK3011724A (DG167) as a binary inhibitor of β-ketoacyl-ACP synthase (KasA) in Mycobacterium tuberculosis Genetic and biochemical studies established KasA as the primary target. The X-ray crystal structure of the KasA-DG167 complex refined to 2.0-Å resolution revealed two interacting DG167 molecules occupying nonidentical sites in the substrate-binding channel of KasA. The binding affinities of KasA to DG167 and its analog, 5g, which binds only once in the substrate-binding channel, were determined, along with the KasA-5g X-ray crystal structure. DG167 strongly augmented the in vitro activity of isoniazid (INH), leading to synergistic lethality, and also synergized in an acute mouse model of M. tuberculosis infection. Synergistic lethality correlated with a unique transcriptional signature, including upregulation of oxidoreductases and downregulation of molecular chaperones. The lead structure-activity relationships (SAR), pharmacokinetic profile, and detailed interactions with the KasA protein that we describe may be applied to evolve a next-generation therapeutic strategy for tuberculosis (TB).IMPORTANCE Cell wall biosynthesis inhibitors have proven highly effective for treating tuberculosis (TB). We discovered and validated members of the indazole sulfonamide class of small molecules as inhibitors of Mycobacterium tuberculosis KasA-a key component for biosynthesis of the mycolic acid layer of the bacterium's cell wall and the same pathway as that inhibited by the first-line antitubercular drug isoniazid (INH). One lead compound, DG167, demonstrated synergistic lethality in combination with INH and a transcriptional pattern consistent with bactericidality and loss of persisters. Our results also detail a novel dual-binding mechanism for this compound as well as substantial structure-activity relationships (SAR) that may help in lead optimization activities. Together, these results suggest that KasA inhibition, specifically, that shown by the DG167 series, may be developed into a potent therapy that can synergize with existing antituberculars.

Modeling the archetype cysteine protease reaction using dispersion corrected density functional methods in ONIOM-type hybrid QM/MM calculations; the proteolytic reaction of papain

A proteolytic reaction of papain with a simple peptide model substrate N-methylacetamide has been studied. Our aim was twofold: (i) we proposed a plausible reaction mechanism with the aid of potential energy surface scans and second geometrical derivatives calculated at the stationary points, and (ii) we investigated the applicability of the dispersion corrected density functional methods in comparison with the popular hybrid generalized gradient approximations (GGA) method (B3LYP) without such a correction in the QM/MM calculations for this particular problem. In the resting state of papain the ion pair and neutral forms of the Cys-His catalytic dyad have approximately the same energy and they are separated by only a small barrier. Zero point vibrational energy correction shifted this equilibrium slightly to the neutral form. On the other hand, the electrostatic solvation free energy corrections, calculated using the Poisson-Boltzmann method for the structures sampled from molecular dynamics simulation trajectories, resulted in a more stable ion-pair form. All methods we applied predicted at least a two elementary step acylation process via a zwitterionic tetrahedral intermediate. Using dispersion corrected DFT methods the thioester S-C bond formation and the proton transfer from histidine occur in the same elementary step, although not synchronously. The proton transfer lags behind (or at least does not precede) the S-C bond formation. The predicted transition state corresponds mainly to the S-C bond formation while the proton is still on the histidine Nδ atom. In contrast, the B3LYP method using larger basis sets predicts a transition state in which the S-C bond is almost fully formed and the transition state can be mainly featured by the Nδ(histidine) to N(amid) proton transfer. Considerably lower activation energy was predicted (especially by the B3LYP method) for the next amide bond breaking elementary step of acyl-enzyme formation. Deacylation appeared to be a single elementary step process in all the methods we applied.

New Algorithms for Global Optimization and Reaction Path Determination

We present new schemes to improve the convergence of an important global optimization problem and to determine reaction pathways (RPs) between identified minima. Those methods have been implemented into the CAST program (Conformational Analysis and Search Tool). The first part of this chapter shows how to improve convergence of the Monte Carlo with minimization (MCM, also known as Basin Hopping) method when applied to optimize water clusters or aqueous solvation shells using a simple model. Since the random movement on the potential energy surface (PES) is an integral part of MCM, we propose to employ a hydrogen bonding-based algorithm for its improvement. We show comparisons of the results obtained for random dihedral and for the proposed random, rigid-body water molecule movement, giving evidence that a specific adaption of the distortion process greatly improves the convergence of the method. The second part is about the determination of RPs in clusters between conformational arrangements and for reactions. Besides standard approaches like the nudged elastic band method, we want to focus on a new algorithm developed especially for global reaction path search called Pathopt. We started with argon clusters, a typical benchmark system, which possess a flat PES, then stepwise increase the magnitude and directionality of interactions. Therefore, we calculated pathways for a water cluster and characterize them by frequency calculations. Within our calculations, we were able to show that beneath local pathways also additional pathways can be found which possess additional features.

Investigation of Structural Dynamics of Enzymes and Protonation States of Substrates Using Computational Tools

This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations.

Evidence for substrate binding-induced zwitterion formation in the catalytic Cys-His dyad of the SARS-CoV main protease

The coronavirus main protease (M(pro)) represents an attractive drug target for antiviral therapy of coronavirus (CoV) infections, including severe acute respiratory syndrome (SARS). The SARS-CoV M(pro) and related CoV proteases have several distinct features, such as an uncharged Cys-His catalytic dyad embedded in a chymotrypsin-like protease fold, that clearly separate these enzymes from archetypical cysteine proteases. To further characterize the catalytic system of CoV main proteases and to obtain information about improved inhibitors, we performed comprehensive simulations of the proton-transfer reactions in the SARS-CoV M(pro) active site that lead to the Cys(-)/His(+) zwitterionic state required for efficient proteolytic activity. Our simulations, comprising the free enzyme as well as substrate-enzyme and inhibitor-enzyme complexes, lead us to predict that zwitterion formation is fostered by substrate binding but not inhibitor binding. This indicates that M(pro) employs a substrate-induced catalytic mechanism that further enhances its substrate specificity. Our computational data are in line with available experimental results, such as X-ray geometries, measured pKa values, mutagenesis experiments, and the measured differences between the kinetic parameters of substrates and inhibitors. The data also provide an atomistic picture of the formerly postulated electrostatic trigger involved in SARS-CoV M(pro) activity. Finally, they provide information on how a specific microenvironment may finely tune the activity of M(pro) toward specific viral protein substrates, which is known to be required for efficient viral replication. Our simulations also indicate that the low inhibition potencies of known covalently interacting inhibitors may, at least in part, be attributed to insufficient fostering of the proton-transfer reaction. These findings suggest ways to achieve improved inhibitors.

Structural basis for the recognition of mycolic acid precursors by KasA, a condensing enzyme and drug target from Mycobacterium tuberculosis

The survival of Mycobacterium tuberculosis depends on mycolic acids, very long α-alkyl-β-hydroxy fatty acids comprising 60-90 carbon atoms. However, despite considerable efforts, little is known about how enzymes involved in mycolic acid biosynthesis recognize and bind their hydrophobic fatty acyl substrates. The condensing enzyme KasA is pivotal for the synthesis of very long (C38-42) fatty acids, the precursors of mycolic acids. To probe the mechanism of substrate and inhibitor recognition by KasA, we determined the structure of this protein in complex with a mycobacterial phospholipid and with several thiolactomycin derivatives that were designed as substrate analogs. Our structures provide consecutive snapshots along the reaction coordinate for the enzyme-catalyzed reaction and support an induced fit mechanism in which a wide cavity is established through the concerted opening of three gatekeeping residues and several α-helices. The stepwise characterization of the binding process provides mechanistic insights into the induced fit recognition in this system and serves as an excellent foundation for the development of high affinity KasA inhibitors.

Benchmark Study for the Cysteine-Histidine Proton Transfer Reaction in a Protein Environment: Gas Phase, COSMO, QM/MM Approaches

Proton transfer reactions are of crucial interest for the investigation of proteins. We have investigated the accuracy of commonly used quantum chemical methods for the description of proton transfer reactions in different environments (gas phase, COSMO, QM/MM) using the proton transfer between the catalytic dyad residues cysteine 145 and histidine 41 of SARS coronavirus main protease as a case study. The test includes thermodynamic, kinetic, and structural properties. The study comprises computationally demanding ab initio approaches (HF, CC2, MP2, SCS-CC2, SCS-MP2, CCSD(T)), popular density functional theories (BLYP, B3LYP, M06-2X), and semiempirical methods (MNDO/d, AM1, RM1, PM3, PM6). The approximated coupled cluster approach LCCSD(T) is taken as a reference method. We find that the robustness of the tested methods with respect to the environment correlates well with the level of theory. As an example HF, CC2, MP2, and their SCS variants show similar errors for gas phase, COSMO, or QM/MM computations. In contrast for semiempirical methods, the errors strongly diversify if one goes from gas phase to COSMO or QM/MM. Particular problems are observed for the recent semiempirical methods PM6 and RM1, which show the best performance for gas phase calculations but possess larger errors in conjunction with COSMO. Finally, a combination of SCS-MP2 and B3LYP or M06-2X allows reliable estimates about remaining errors.

Molecular dynamics of Mycobacterium tuberculosis KasA: implications for inhibitor and substrate binding and consequences for drug design

Inhibition of the production of fatty acids as essential components of the mycobacterial cell wall has been an established way of fighting tuberculosis for decades. However, increasing resistances and an outdated medical treatment call for the validation of new targets involved in this crucial pathway. In this regard, the β-ketoacyl ACP synthase KasA is a promising enzyme. In this study, three molecular dynamics simulations based on the wildtype crystal structures of inhibitor bound and unbound KasA were performed in order to investigate the flexibility and conformational space of this target. We present an exhaustive analysis of the binding-site flexibility and representative pocket conformations that may serve as new starting points for structure-based drug design. We also revealed a mechanism which may account for the comparatively low binding affinity of thiolactomycin. Furthermore, we examined the behavior of water molecules within the binding pocket and provide recommendations how to handle them in the drug design process. Finally, we analyzed the dynamics of a channel that accommodates the long-chain fatty acid substrates and, thereby, propose a mechanism of substrate access to this channel and how products are most likely released.