Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb), which remains a significant global health challenge. The emergence of multidrug-resistant (MDR) Mtb strains imposes the development of new therapeutic strategies. This study focuses on the identification and evaluation of potential inhibitors against Mtb H37Ra through a comprehensive screening of an in-house chemolibrary. Subsequently, a promising pyrimidine derivative (LQM495) was identified as promising and then further investigated by experimental and in silico approaches. In this context, computational techniques were used to elucidate the potential molecular target underlying the inhibitory action of LQM495. Then, a consensus reverse docking (CRD) protocol was used to investigate the interactions between this compound and several Mtb targets. Out of 98 Mtb targets investigated, the enhanced intracellular survival (Eis) protein emerged as a target for LQM495. To gain insights into the stability of the LQM495-Eis complex, molecular dynamics (MD) simulations were conducted over a 400 ns trajectory. Further insights into its binding modes within the Eis binding site were obtained through a Quantum mechanics (QM) approach, using density functional theory (DFT), with B3LYP/D3 basis set. These calculations shed light on the electronic properties and reactivity of LQM495. Subsequently, inhibition assays and kinetic studies of the Eis activity were used to investigate the activity of LQM495. Then, an IC50 value of 11.0 ± 1.4 µM was found for LQM495 upon Eis protein. Additionally, its Vmax, Km, and Ki parameters indicated that it is a competitive inhibitor. Lastly, this study presents LQM495 as a promising inhibitor of Mtb Eis protein, which could be further explored for developing novel anti-TB drugs in the future.

Trafficking receptors control protein localization through the recognition of specific signal sequences that specify unique cellular locations. Differences in luminal pH are important for the vectorial trafficking of cargo receptors. The KDEL receptor is responsible for maintaining the integrity of the ER by retrieving luminally localized folding chaperones in a pH-dependent mechanism. Structural studies have revealed the end states of KDEL receptor activation and the mechanism of selective cargo binding. However, precisely how the KDEL receptor responds to changes in luminal pH remains unclear. To explain the mechanism of pH sensing, we combine analysis of X-ray crystal structures of the KDEL receptor at neutral and acidic pH with advanced computational methods and cell-based assays. We show a critical role for ordered water molecules that allows us to infer a direct connection between protonation in different cellular compartments and the consequent changes in the affinity of the receptor for cargo.

Metal-organic framework (MOF) in biomass valorization is a promising technology developed in recent decades. By tailoring both the metal nodes and organic ligands, MOFs exhibit multiple functionalities, which not only extend their applicability in biomass conversion but also increase the complexity of material designs. To address this issue, quantum mechanical simulations have been used to provide mechanistic insights into the catalysis of biomass-derived molecules, which could potentially facilitate the development of novel MOF-based materials for biomass valorization. The aim of this review is to survey recent quantum mechanical simulations on biomass reactions occurring in MOF catalysts, with the emphasis on the studies of the catalytic activity of active sites and the effects of organic ligand and porous structures on the kinetics. Moreover, different model systems and computational methods used for MOF simulations are also surveyed and discussed in this review.

Lysyl oxidase-like 2 (LOXL2) is a copper-dependent amine oxidase that catalyzes the oxidative deamination of the ε-amino group of lysines/hydroxylysines on substrate proteins (collagen and elastin) to form aldehyde groups. The generated aldehyde groups are of significance in crosslinking with the adjacent aldehyde or ε-amino group on proteins in extracellular matrix. In this paper, we have studied the reaction mechanism of LOXL2 by means of quantum mechanics (QM) and combined QM and molecular mechanics (QM/MM) methods. This study is divided into two parts, i.e. the biosynthesis of lysine tyrosylquinone (LTQ) cofactor and oxidative deamination of ε-amino group of lysine by LTQ. For the former part, the reaction is driven by a large exothermicity of about 284 kJ/mol. Dopaquinone radical (DPQr) is suggested to be an intermediate state in this reaction. In addition, His652 residue is predicted to serve as proton acceptor. The rate-determining step for the biosynthesis of LTQ is found to be hydrogen-atom abstraction from the benzene ring on substrate by Cu2+-hydroxide, which is a proton-coupled electron transfer (PCET) process with an energy barrier of 84 kJ/mol. For the latter part, the reaction is exothermic by about 145 kJ/mol, and the copper ion is proposed to play a role of redox catalyst in the last step to generate the product of aldehyde. However, the copper ion might not be indispensable for the latter part, which is consistent with the previous study.

Proteins are vital components of living systems, serving as building blocks, molecular machines, enzymes, receptors, ion channels, sensors, and transporters. Protein-protein interactions (PPIs) are a key part of their function. There are more than 645,000 reported disease-relevant PPIs in the human interactome, but drugs have been developed for only 2% of these targets. The advances in PPI-focused drug discovery are highly dependent on the availability of structural data and accurate computational tools for analysis of this data. Quantum mechanical approaches are often too expensive computationally, but the fragment molecular orbital (FMO) method offers an excellent solution that combines accuracy, speed and the ability to reveal key interactions that would otherwise be hard to detect. FMO provides essential information for PPI drug discovery, namely, identification of key interactions formed between residues of two proteins, including their strength (in kcal/mol) and their chemical nature (electrostatic or hydrophobic). In this chapter, we have demonstrated how three different FMO-based approaches (pair interaction energy analysis (PIE analysis), subsystem analysis (SA) and analysis of protein residue networks (PRNs)) have been applied to study PPI in three protein-protein complexes.

Acyl migration (AM) is the main side reaction in the large-scale, regio-specific lipase catalyzed production of structural triglycerides (STs). A detailed understanding of the mechanism of AM was obtained during the process of lipase-catalyzed schemes (LCSs), which play a vital role in improving the quality and total yield of STs. However, currently, the mechanism of AM remains controversial. Herein, the two mechanisms (non-catalyzed (NCM) and lipase-catalyzed (LCM)) of AM have been analyzed in detail by the density functional theory (DFT) at the molecular level. Based on the computational results, we concluded that the energy barrier of the rate-limiting step in the LCM was 18.8 kcal/mol, which is more in agreement with the available experimental value (17.8 kcal/mol), indicating that LCM could significantly accelerate the rate of AM, because it has an energy barrier ~2 times lower than that of the NCM. Interestingly, we also found that the catalytic triad (Asp-His-Ser) of the lipase and water could effectively drop the reaction barrier, which served as the general acid or base, or shuttle of the proton.

Metalloenzymes catalyze many different types of biological reactions with high efficiency and remarkable selectivity. The quantum chemical cluster approach and the combined quantum mechanics/molecular mechanics methods have proven very successful in the elucidation of the reaction mechanism and rationalization of selectivities in enzymes. In this review, recent progress in the computational understanding of various selectivities including chemoselectivity, regioselectivity, and stereoselectivity, in metalloenzymes, is discussed.

Piperlongumine (PL) is an anticancer compound whose activity is related to the inhibition of human glutathione transferase of pi class (GSTP1) overexpressed in cancerous tumors and implicated in the metabolism of electrophilic compounds. In the present work, the inhibition mechanism of hydrolyzed piperlongumine (hPL) has been investigated employing QM and QM/MM levels of theory. The potential energy surfaces (PESs) underline the contributions of Tyr residue close to G site in the catalytic pocket of the enzyme. The proposed mechanism occurs through a one-step process represented by the nucleophilic addition of the glutathione thiol to electrophilic species giving rise to the simultaneous C-S and H-C bonds formation. Both the used methods give barrier heights (19.8 and 21.5 kcal mol-1 at QM/MM and QM, respectively) close to that experimentally measured for the C-S bond formations (23.8 kcal mol-1).

We present a new version of the simulation software COBRAMM, a program package interfacing widely known commercial and academic software for molecular modeling. It allows a problem-driven tailoring of computational chemistry simulations with effortless ground and excited-state electronic structure computations. Calculations can be executed within a pure QM or combined quantum mechanical/molecular mechanical (QM/MM) framework, bridging from the atomistic to the nanoscale. The user can perform all necessary steps to simulate ground state and photoreactions in vacuum, complex biopolymer, or solvent environments. Starting from ground-state optimization, reaction path computations, initial conditions sampling, spectroscopy simulation, and photodynamics with deactivation events, COBRAMM is designed to assist in characterization and analysis of complex molecular materials and their properties. Interpretation of recorded spectra range from steady-state to time-resolved measurements. Various tools help the user to set up the system of interest and analyze the results.

Terpene synthases comprise a family of enzymes that convert acyclic oligo-isoprenyl diphosphates to terpene natural products with complex, polycyclic carbon backbones via the generation and protection of carbocation intermediates. To accommodate this chemistry, terpene synthase active sites generally are lined with alkyl and aromatic, i.e., nonpolar, sidechains. Predicting the correct, mechanistically relevant binding modes for entire terpene synthase reaction pathways remains an unsolved challenge. Here we describe a method for identifying such modes: TerDockin, a series of protocols to predict the orientation of carbon skeletons of substrates and derived carbocations relative to the bound diphosphate group in terpene synthase active sites. Using this recipe for bornyl diphosphate synthase, we have predicted binding modes that are consistent with all current experimental observations, including the results of isotope labeling experiments and known stereoselectivity. In addition, the predicted binding modes recapitulate key findings of a seminal study involving more computationally demanding QM/MM molecular dynamics methods on part of this pathway. This work illustrates the value of the TerDockin approach as a starting point for more involved calculations and sets the stage for the rational engineering of this family of enzymes.