Accurate Prediction of Three-Body Intermolecular Interactions via Electron Deformation Density-Based Machine Learning

This work extends the electron deformation density-based descriptor, originally developed in the electron deformation density-based interaction energy machine learning (EDDIE-ML) algorithm to predict dimer interaction energies, to the prediction of three-body interactions in trimers. Using a sequential learning process to select the training data, the resulting Gaussian process regression (GPR) model predicts the three-body interaction energy within 0.2 kcal mol^-1 of the SRS-MP2/cc-pVTZ reference values for the 3B69 and S22-3 trimer data sets. A hybrid kernel function is introduced, which combines contributions from the average and individual atomic environments, allowing the total trimer interaction energy to be predicted in addition to the three-body contribution using the same descriptor. To extend the range and diversity of trimer interaction energies available in the literature, a new data set based on a protein-ligand crystal structure is introduced, consisting of 509 structures of a central ligand with two protein fragments. Benchmark calculations are provided for the new data set, which contains significantly larger molecular interactions than current databases in the literature in addition to charged fragments. Compared to density funtional theory (DFT)- and wavefunction-based methods for calculating the three-body interaction energy, our model makes predictions in a significantly shorter time frame by reducing the number of required SCF calculations from 7 to 4 performed at the PBE0 level of theory, showcasing the utility and efficiency of our Δ-ML method particularly when applied to larger systems.

Identification of new putative inhibitors of Mycobacterium tuberculosis 3-dehydroshikimate dehydratase from a combination of ligand- and structure-based and deep learning in silico approaches

The development of new drugs against Mycobacterium tuberculosis is an essential strategy for fighting drug resistance. Although 3-dehydroquinate dehydratase (MtDHQ) is known to be a highly relevant target for M. tuberculosis, current research shows new putative inhibitors of MtDHQ selected by a large-scale ensemble-docking strategy combining ligand- and target-based chemoinformatic methods to deep learning. Initial chemical library was reduced from 216 million to approximately 460 thousand after pharmacophore, toxicity and molecular weight filters. Final library was subjected to an ensemble-docking protocol in GOLD which selected the top 300 molecules (GHITS). GHITS displayed different structures and characteristics when compared to known inhibitors (KINH). GHITS were further screened by post-docking analysis in AMMOS2 and deep learning virtual screening in DeepPurpose. DeepPurpose predicted that a number of GHITS had comparable or better affinity for the target than KINH. The best molecule was selected by consensus ranking using GOLD, AMMOS2 and DeepPurpose scores. Molecular dynamics revealed that the top hit displayed consistent and stable binding to MtDHQ, making strong interactions with active-site loop residues. Results forward new putative inhibitors of MtDHQ and reinforce the potential application of artificial intelligence methods for drug design. This work represents the first step in the validation of these molecules as inhibitors of MtDHQ.

Mycobacterium tuberculosis Shikimate Pathway Enzymes as Targets for the Rational Design of Anti-Tuberculosis Drugs

Roughly a third of the world’s population is estimated to have latent Mycobacterium tuberculosis infection, being at risk of developing active tuberculosis (TB) during their lifetime. Given the inefficacy of prophylactic measures and the increase of drug-resistant M. tuberculosis strains, there is a clear and urgent need for the development of new and more efficient chemotherapeutic agents, with selective toxicity, to be implemented on patient treatment. The component enzymes of the shikimate pathway, which is essential in mycobacteria and absent in humans, stand as attractive and potential targets for the development of new drugs to treat TB. This review gives an update on published work on the enzymes of the shikimate pathway and some insight on what can be potentially explored towards selective drug development.

QM/MM simulations identify the determinants of catalytic activity differences between type II dehydroquinase enzymes

Type II dehydroquinase enzymes (DHQ2), recognized targets for antibiotic drug discovery, show significantly different activities dependent on the species: DHQ2 from Mycobacterium tuberculosis (MtDHQ2) and Helicobacter pylori (HpDHQ2) show a 50-fold difference in catalytic efficiency. Revealing the determinants of this activity difference is important for our understanding of biological catalysis and further offers the potential to contribute to tailoring specificity in drug design. Molecular dynamics simulations using a quantum mechanics/molecular mechanics potential, with correlated ab initio single point corrections, identify and quantify the subtle determinants of the experimentally observed difference in efficiency. The rate-determining step involves the formation of an enolate intermediate: more efficient stabilization of the enolate and transition state of the key step in MtDHQ2, mainly by the essential residues Tyr24 and Arg19, makes it more efficient than HpDHQ2. Further, a water molecule, which is absent in MtDHQ2 but involved in generation of the catalytic Tyr22 tyrosinate in HpDHQ2, was found to destabilize both the transition state and the enolate intermediate. The quantification of the contribution of key residues and water molecules in the rate-determining step of the mechanism also leads to improved understanding of higher potencies and specificity of known inhibitors, which should aid ongoing inhibitor design.

Unraveling the kinetic diversity of microbial 3-dehydroquinate dehydratases of shikimate pathway

3-Dehydroquinate dehydratase (DHQase) catalyzes the conversion of 3-dehydroquinic acid to 3-dehydroshikimic acid of the shikimate pathway. In this study, 3180 prokaryotic genomes were examined and 459 DHQase sequences were retrieved. Based on sequence analysis and their original hosts, 38 DHQase genes were selected for chemical synthesis. The selected DHQases were translated into new DNA sequences according to the genetic codon usage bias by both Escherichia coli and Corynebacterium glutamicum. The new DNA sequences were customized for synthetic biological applications by adding Biobrick adapters at both ends and by removal of any related restriction endonuclease sites. The customized DHQase genes were successfully expressed in E. coli, and functional DHQases were obtained. Kinetic parameters of Km, kcat, and Vmax of DHQases were determined with a newly established high-throughput method for DHQase activity assay. Results showed that DHQases possessed broad strength of substrate affinities and catalytic capacities. In addition to the DHQase kinetic diversities, this study generated a DHQase library with known catalytic constants that could be applied to design artificial modules of shikimate pathway for metabolic engineering and synthetic biology.

Mechanistic insight into the reaction catalysed by bacterial type II dehydroquinases1

The present study identified the residue that deprotonates the essential tyrosine that triggers the catalytic process and provides details of the required motions for the catalytic turnover. A previously unknown key role for the essential arginine and two conserved arginines is also reported.

Mechanistic basis of the inhibition of type II dehydroquinase by (2S)- and (2R)-2-benzyl-3-dehydroquinic acids

The structural changes caused by the substitution of the aromatic moiety in (2S)-2-benzyl-3-dehydroquinic acids and its epimers in C2 by electron-withdrawing or electron-donating groups in type II dehydroquinase enzyme from M. tuberculosis and H. pylori has been investigated by structural and computational studies. Both compounds are reversible competitive inhibitors of this enzyme, which is essential in these pathogenic bacteria. The crystal structures of M. tuberculosis and H. pylori in complex with (2S)-2-(4-methoxy)benzyl- and (2S)-2-perfluorobenzyl-3-dehydroquinic acids have been solved at 2.0, 2.3, 2.0, and 1.9 Å, respectively. The crystal structure of M. tuberculosis in complex with (2R)-2-(benzothiophen-5-yl)methyl-3-dehydroquinic acid is also reported at 1.55 Å. These crystal structures reveal key differences in the conformation of the flexible loop of the two enzymes, a difference that depends on the presence of electron-withdrawing or electron-donating groups in the aromatic moiety of the inhibitors. This loop closes over the active site after substrate binding, and its flexibility is essential for the function of the enzyme. These differences have also been investigated by molecular dynamics simulations in an effort to understand the significant inhibition potency differences observed between some of these compounds and also to obtain more information about the possible movements of the loop. These computational studies have also allowed us to identify key structural factors of the H. pylori loop that could explain its reduced flexibility in comparison to the M. tuberculosis loop, specifically by the formation of a key salt bridge between the side chains of residues Asp18 and Arg20.

Comparative binding energy COMBINE analysis for understanding the binding determinants of type II dehydroquinase inhibitors

Herein we report comparative binding energy (COMBINE) analyses to derive quantitative structure-activity relationship (QSAR) models that help rationalize the determinants of binding affinity for inhibitors of type II dehydroquinase (DHQ2), the third enzyme of the shikimic acid pathway. Independent COMBINE models were derived for Helicobacter pylori and Mycobacterium tuberculosis DHQ2, which is an essential enzyme in both these pathogenic bacteria that has no counterpart in human cells. These studies quantify the importance of the hydrogen bonding interactions between the ligands and the water molecule involved in the DHQ2 reaction mechanism. They also highlight important differences in the ligand interactions with the interface pocket close to the active site that could provide guides for future inhibitor design.

Structural investigation of inhibitor designs targeting 3-dehydroquinate dehydratase from the shikimate pathway of Mycobacterium tuberculosis

The shikimate pathway is essential in Mycobacterium tuberculosis and its absence from humans makes the enzymes of this pathway potential drug targets. In the present paper, we provide structural insights into ligand and inhibitor binding to 3-dehydroquinate dehydratase (dehydroquinase) from M. tuberculosis (MtDHQase), the third enzyme of the shikimate pathway. The enzyme has been crystallized in complex with its reaction product, 3-dehydroshikimate, and with six different competitive inhibitors. The inhibitor 2,3-anhydroquinate mimics the flattened enol/enolate reaction intermediate and serves as an anchor molecule for four of the inhibitors investigated. MtDHQase also forms a complex with citrazinic acid, a planar analogue of the reaction product. The structure of MtDHQase in complex with a 2,3-anhydroquinate moiety attached to a biaryl group shows that this group extends to an active-site subpocket inducing significant structural rearrangement. The flexible extensions of inhibitors designed to form π-stacking interactions with the catalytic Tyr24 have been investigated. The high-resolution crystal structures of the MtDHQase complexes provide structural evidence for the role of the loop residues 19-24 in MtDHQase ligand binding and catalytic mechanism and provide a rationale for the design and efficacy of inhibitors.