First-in-class MKK4 inhibitors enhance liver regeneration and prevent liver failure.

Diminished hepatocyte regeneration is a key feature of acute and chronic liver diseases and after extended liver resections, resulting in the inability to maintain or restore a sufficient functional liver mass. Therapies to restore hepatocyte regeneration are lacking, making liver transplantation the only curative option for end-stage liver disease. Here, we report on the structure-based development and characterization (nuclear magnetic resonance [NMR] spectroscopy) of first-in-class small molecule inhibitors of the dual-specificity kinase MKK4 (MKK4i). MKK4i increased liver regeneration upon hepatectomy in murine and porcine models, allowed for survival of pigs in a lethal 85% hepatectomy model, and showed antisteatotic and antifibrotic effects in liver disease mouse models. A first-in-human phase I trial (European Union Drug Regulating Authorities Clinical Trials [EudraCT] 2021-000193-28) with the clinical candidate HRX215 was conducted and revealed excellent safety and pharmacokinetics. Clinical trials to probe HRX215 for prevention/treatment of liver failure after extensive oncological liver resections or after transplantation of small grafts are warranted.

HilE represses the activity of the Salmonella virulence regulator HilD via a mechanism distinct from that of intestinal long-chain fatty acids.

The expression of virulence factors essential for the invasion of host cells by Salmonella enterica is tightly controlled by a network of transcription regulators. The AraC/XylS transcription factor HilD is the main integration point of environmental signals into this regulatory network, with many factors affecting HilD activity. Long-chain fatty acids, which are highly abundant throughout the host intestine, directly bind to and repress HilD, acting as environmental cues to coordinate virulence gene expression. The regulatory protein HilE also negatively regulates HilD activity, through a protein-protein interaction. Both of these regulators inhibit HilD dimerization, preventing HilD from binding to target DNA. We investigated the structural basis of these mechanisms of HilD repression. Long-chain fatty acids bind to a conserved pocket in HilD, in a comparable manner to that reported for other AraC/XylS regulators, whereas HilE forms a stable heterodimer with HilD by binding to the HilD dimerization interface. Our results highlight two distinct, mutually exclusive mechanisms by which HilD activity is repressed, which could be exploited for the development of new antivirulence leads.

Virtual Screening Assisted Search for Inhibitors of the Translocated Intimin Receptor of Enteropathogenic Escherichia Coli.

This study aimed to identify inhibitors of the translocated intimin receptor (Tir) of enteropathogenic Escherichia coli (EPEC). EPEC is an intestinal pathogen that causes diarrhea and is a major health concern worldwide. Because Tir is a key virulence factor involved in EPEC pathogenesis, inhibiting its function is a potential strategy for controlling EPEC infections. Virtual screening was applied to chemical libraries to search for compounds that inhibit Tir-mediated bacterial adherence to host cells. Three sites were targeted using the cocrystal structure published earlier. A selection of compounds was then assessed in a cell-based infection model and fluorescence microscopy assay. The results of this study provide a basis for further optimization and testing of Tir inhibitors as potential therapeutic agents for EPEC infections.

Aminopyrimidine Derivatives as Multiflavivirus Antiviral Compounds Identified from a Consensus Virtual Screening Approach.

Around three billion people are at risk of infection by the dengue virus (DENV) and potentially other flaviviruses. Worldwide outbreaks of DENV, Zika virus (ZIKV), and yellow fever virus (YFV), the lack of antiviral drugs, and limitations on vaccine usage emphasize the need for novel antiviral research. Here, we propose a consensus virtual screening approach to discover potential protease inhibitors (NS3pro) against different flavivirus. We employed an in silico combination of a hologram quantitative structure-activity relationship (HQSAR) model and molecular docking on characterized binding sites followed by molecular dynamics (MD) simulations, which filtered a data set of 7.6 million compounds to 2,775 hits. Lastly, docking and MD simulations selected six final potential NS3pro inhibitors with stable interactions along the simulations. Five compounds had their antiviral activity confirmed against ZIKV, YFV, DENV-2, and DENV-3 (ranging from 4.21 ± 0.14 to 37.51 ± 0.8 µM), displaying aggregator characteristics for enzymatic inhibition against ZIKV NS3pro (ranging from 28 ± 7 to 70 ± 7 µM). Taken together, the compounds identified in this approach may contribute to the design of promising candidates to treat different flavivirus infections.

Filling the Blank Space: Branched 4-Nonylphenol Isomers Are Responsible for Robust Constitutive Androstane Receptor (CAR) Activation by Nonylphenol.

4-Nonylphenol (4-NP), a para-substituted phenolic compound with a straight or branched carbon chain, is a ubiquitous environmental pollutant and food contaminant. 4-NP, particularly the branched form, has been identified as an endocrine disruptor (ED) with potent activities on estrogen receptors. Constitutive Androstane Receptor (CAR) is another crucial nuclear receptor that regulates hepatic lipid, glucose, and steroid metabolism and is involved in the ED mechanism of action. An NP mixture has been described as an extremely potent activator of both human and rodent CAR. However, detailed mechanistic aspects of CAR activation by 4-NP are enigmatic, and it is not known if 4-NP can directly interact with the CAR ligand binding domain (LBD). Here, we examined interactions of individual branched (22NP, 33NP, and 353NP) and linear 4-NPs with CAR variants using molecular dynamics (MD) simulations, cellular experiments with various CAR expression constructs, recombinant CAR LBD in a TR-FRET assay, or a differentiated HepaRG hepatocyte cellular model. Our results demonstrate that branched 4-NPs display more stable poses to activate both wild-type CAR1 and CAR3 variant LBDs in MD simulations. Consistently, branched 4-NPs activated CAR3 and CAR1 LBD more efficiently than linear 4-NP. Furthermore, in HepaRG cells, we observed that all 4-NPs upregulated CYP2B6 mRNA, a relevant hallmark for CAR activation. This is the first study to provide detailed insights into the direct interaction between individual 4-NPs and human CAR-LBD, as well as its dominant variant CAR3. The work could contribute to the safer use of individual 4-NPs in many areas of industry.

Sodium-Dependent Neutral Amino Acid Transporter 2 Can Serve as a Tertiary Carrier for l-Type Amino Acid Transporter 1-Utilizing Prodrugs.

Membrane transporters are the key determinants of the homeostasis of endogenous compounds in the cells and their exposure to drugs. However, the substrate specificities of distinct transporters can overlap. In the present study, the interactions of l-type amino acid transporter 1 (LAT1)-utilizing prodrugs with sodium-coupled neutral amino acid transporter 2 (SNAT2) were explored. The results showed that the cellular uptake of LAT1-utilizing prodrugs into a human breast cancer cell line, MCF-7 cells, was mediated via SNATs as the uptake was increased at higher pH (8.5), decreased in the absence of sodium, and inhibited in the presence of unselective SNAT-inhibitor, (α-(methylamino)isobutyric acid, MeAIB). Moreover, docking the compounds to a SNAT2 homology model (inward-open conformation) and further molecular dynamics simulations and the subsequent trajectory and principal component analyses confirmed the chemical features supporting the interactions of the studied compounds with SNAT2, which was found to be the main SNAT expressed in MCF-7 cells.

Structural Features Affecting the Interactions and Transportability of LAT1-Targeted Phenylalanine Drug Conjugates.

L-type amino acid transporter 1 (LAT1) transfers essential amino acids across cell membranes. Owing to its predominant expression in the blood-brain barrier and tumor cells, LAT1 has been exploited for drug delivery and targeting to the central nervous system (CNS) and various cancers. Although the interactions of amino acids and their mimicking compounds with LAT1 have been extensively investigated, the specific structural features for an optimal drug scaffold have not yet been determined. Here, we evaluated a series of LAT1-targeted drug-phenylalanine conjugates (ligands) by determining their uptake rates by in vitro studies and investigating their interaction with LAT1 via induced-fit docking. Combining the experimental and computational data, we concluded that although LAT1 can accommodate various types of structures, smaller compounds are preferred. As the ligand size increased, its flexibility became more crucial in determining the compound's transportability and interactions. Compounds with linear or planar structures exhibited reduced uptake; those with rigid lipophilic structures lacked interactions and likely utilized other transport mechanisms for cellular entry. Introducing polar groups between aromatic structures enhanced interactions. Interestingly, compounds with a carbamate bond in the aromatic ring's para-position displayed very good transport efficiencies for the larger compounds. Compared to the ester bond, the corresponding amide bond had superior hydrogen bond acceptor properties and increased interactions. A reverse amide bond was less favorable than a direct amide bond for interactions with LAT1. The present information can be applied broadly to design appropriate CNS or antineoplastic drug candidates with a prodrug strategy and to discover novel LAT1 inhibitors used either as direct or adjuvant cancer therapy.

Direct pathway cloning and expression of the radiosumin biosynthetic gene cluster.

Radiosumins are a structurally diverse family of low molecular weight natural products that are produced by cyanobacteria and exhibit potent serine protease inhibition. Members of this family are dipeptides characterized by the presence of two similar non-proteinogenic amino acids. Here we used a comparative bioinformatic analysis to identify radiosumin biosynthetic gene clusters from the genomes of 13 filamentous cyanobacteria. We used direct pathway cloning to capture and express the entire 16.8 kb radiosumin biosynthetic gene cluster from Dolichospermum planctonicum UHCC 0167 in Escherichia coli. Bioinformatic analysis demonstrates that radiosumins represent a new group of chorismate-derived non-aromatic secondary metabolites. High-resolution liquid chromatography-mass spectrometry, nuclear magnetic resonance spectroscopy and chemical degradation analysis revealed that cyanobacteria produce a cocktail of novel radiosumins. We report the chemical structure of radiosumin D, an N-methyl dipeptide, containing a special Aayp (2-amino-3-(4-amino-2-cyclohexen-1-ylidene) propionic acid) with R configuration that differs from radiosumin A-C, an N-Me derivative of Aayp (Amyp) and two acetyl groups. Radiosumin C inhibits all three human trypsin isoforms at micromolar concentrations with preference for trypsin-1 and -3 (IC50 values from 1.7 µM to >7.2 µM). These results provide a biosynthetic logic to explore the genetic and chemical diversity of the radiosumin family and suggest that these natural products may be a source of drug leads for selective human serine proteases inhibitors.

Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries.

The emergence of ultra-large screening libraries, filled to the brim with billions of readily available compounds, poses a growing challenge for docking-based virtual screening. Machine learning (ML)-boosted strategies like the tool HASTEN combine rapid ML prediction with the brute-force docking of small fractions of such libraries to increase screening throughput and take on giga-scale libraries. In our case study of an anti-bacterial chaperone and an anti-viral kinase, we first generated a brute-force docking baseline for 1.56 billion compounds in the Enamine REAL lead-like library with the fast Glide high-throughput virtual screening protocol. With HASTEN, we observed robust recall of 90% of the true 1000 top-scoring virtual hits in both targets when docking only 1% of the entire library. This reduction of the required docking experiments by 99% significantly shortens the screening time. In the kinase target, the employment of a hydrogen bonding constraint resulted in a major proportion of unsuccessful docking attempts and hampered ML predictions. We demonstrate the optimization potential in the treatment of failed compounds when performing ML-boosted screening and benchmark and showcase HASTEN as a fast and robust tool in a growing arsenal of approaches to unlock the chemical space covered by giga-scale screening libraries for everyday drug discovery campaigns.

In Vitro Identification and In Vivo Confirmation of Inhibitors for Sweet Potato Chlorotic Stunt Virus RNA Silencing Suppressor, a Viral RNase III.

Sweet potato virus disease (SPVD), caused by synergistic infection of Sweet potato chlorotic stunt virus (SPCSV) and Sweet potato feathery mottle virus (SPFMV), is responsible for substantial yield losses all over the world. However, there are currently no approved treatments for this severe disease. The crucial role played by RNase III of SPCSV (CSR3) as an RNA silencing suppressor during the viruses' synergistic interaction in sweetpotato makes it an ideal drug target for developing antiviral treatment. In this study, high-throughput screening (HTS) of small molecular libraries targeting CSR3 was initiated by a virtual screen using Glide docking, allowing the selection of 6,400 compounds out of 136,353. We subsequently developed and carried out kinetic-based HTS using fluorescence resonance energy transfer technology, which isolated 112 compounds. These compounds were validated with dose-response assays including kinetic-based HTS and binding affinity assays using surface plasmon resonance and microscale thermophoresis. Finally, the interference of the selected compounds with viral accumulation was verified in planta In summary, we identified five compounds belonging to two structural classes that inhibited CSR3 activity and reduced viral accumulation in plants. These results provide the foundation for developing antiviral agents targeting CSR3 to provide new strategies for controlling sweetpotato virus diseases.IMPORTANCE We report here a high-throughput inhibitor identification method that targets a severe sweetpotato virus disease caused by coinfection with two viruses (SPCSV and SPFMV). The disease is responsible for up to 90% yield losses. Specifically, we targeted the RNase III enzyme encoded by SPCSV, which plays an important role in suppressing the RNA silencing defense system of sweetpotato plants. Based on virtual screening, laboratory assays, and confirmation in planta, we identified five compounds that could be used to develop antiviral drugs to combat the most severe sweetpotato virus disease.

SARS-CoV-2-host proteome interactions for antiviral drug discovery.

Treatment options for COVID-19, caused by SARS-CoV-2, remain limited. Understanding viral pathogenesis at the molecular level is critical to develop effective therapy. Some recent studies have explored SARS-CoV-2-host interactomes and provided great resources for understanding viral replication. However, host proteins that functionally associate with SARS-CoV-2 are localized in the corresponding subnetwork within the comprehensive human interactome. Therefore, constructing a downstream network including all potential viral receptors, host cell proteases, and cofactors is necessary and should be used as an additional criterion for the validation of critical host machineries used for viral processing. This study applied both affinity purification mass spectrometry (AP-MS) and the complementary proximity-based labeling MS method (BioID-MS) on 29 viral ORFs and 18 host proteins with potential roles in viral replication to map the interactions relevant to viral processing. The analysis yields a list of 693 hub proteins sharing interactions with both viral baits and host baits and revealed their biological significance for SARS-CoV-2. Those hub proteins then served as a rational resource for drug repurposing via a virtual screening approach. The overall process resulted in the suggested repurposing of 59 compounds for 15 protein targets. Furthermore, antiviral effects of some candidate drugs were observed in vitro validation using image-based drug screen with infectious SARS-CoV-2. In addition, our results suggest that the antiviral activity of methotrexate could be associated with its inhibitory effect on specific protein-protein interactions.

Structure of POPC Lipid Bilayers in OPLS3e Force Field.

It is crucial for molecular dynamics simulations of biomembranes that the force field parameters give a realistic model of the membrane behavior. In this study, we examined the OPLS3e force field for the carbon-hydrogen order parameters SCH of POPC (1-palmitoyl-2-oleoylphosphatidylcholine) lipid bilayers at varying hydration conditions and ion concentrations. The results show that OPLS3e behaves similarly to the CHARMM36 force field and relatively accurately follows the experimentally measured SCH for the lipid headgroup, the glycerol backbone, and the acyl tails. Thus, OPLS3e is a good choice for POPC bilayer simulations under many biologically relevant conditions. The exception are systems with an abundancy of ions, as similarly to most other force fields OPLS3e strongly overestimates the membrane-binding of cations, especially Ca2+. This leads to undesirable positive charge of the membrane surface and drastically lowers the concentration of Ca2+ in the surrounding solvent, which might cause issues in systems sensitive to correct charge distribution profiles across the membrane.

Do Go Chasing Waterfalls: Enoyl Reductase (FabI) in Complex with Inhibitors Stabilizes the Tetrameric Structure and Opens Water Channels.

The enzyme enoyl-ACP reductase (FabI) is the limiting step of the membrane's fatty acid biosynthesis in bacteria and a druggable target for novel antibacterial agents. The FabI active form is a homotetramer, which displays the highest affinity to inhibitors. Herein, molecular dynamics studies were carried out using the structure of FabI in complex with known inhibitors to investigate their effects on tetramerization. Our results suggest that multimerization is essential for the integrity of the catalytic site and that inhibitor binding enables the multimerization by stabilizing the substrate binding loop (SBL, L:195-200) coupled with changes in the H4/5 (QR interface). We also observed that AFN-1252 (naphtpyridinone derivative) promotes unique conformational changes affecting monomer-monomer interfaces. These changes are induced by AFN-1252 interaction with key residues in the binding sites (Ala95, Tyr146, and Tyr156). In addition, the analysis of water trajectories indicated that AFN-1252 complexes allow more water molecules to enter the binding site than triclosan and MUT056399 complexes. FabI-AFN-1252 simulations show accumulation of water molecules near the Tyr146/147 pocket, which can become a hotspot to the design of novel FabI inhibitors.

Structure-Based Identification of Naphthoquinones and Derivatives as Novel Inhibitors of Main Protease Mpro and Papain-like Protease PLpro of SARS-CoV-2.

The worldwide COVID-19 pandemic caused by the coronavirus SARS-CoV-2 urgently demands novel direct antiviral treatments. The main protease (Mpro) and papain-like protease (PLpro) are attractive drug targets among coronaviruses due to their essential role in processing the polyproteins translated from the viral RNA. In this study, we virtually screened 688 naphthoquinoidal compounds and derivatives against Mpro of SARS-CoV-2. Twenty-four derivatives were selected and evaluated in biochemical assays against Mpro using a novel fluorogenic substrate. In parallel, these compounds were also assayed with SARS-CoV-2 PLpro. Four compounds inhibited Mpro with half-maximal inhibitory concentration (IC50) values between 0.41 µM and 9.0 µM. In addition, three compounds inhibited PLpro with IC50 ranging from 1.9 µM to 3.3 µM. To verify the specificity of Mpro and PLpro inhibitors, our experiments included an assessment of common causes of false positives such as aggregation, high compound fluorescence, and inhibition by enzyme oxidation. Altogether, we confirmed novel classes of specific Mpro and PLpro inhibitors. Molecular dynamics simulations suggest stable binding modes for Mpro inhibitors with frequent interactions with residues in the S1 and S2 pockets of the active site. For two PLpro inhibitors, interactions occur in the S3 and S4 pockets. In summary, our structure-based computational and biochemical approach identified novel naphthoquinonal scaffolds that can be further explored as SARS-CoV-2 antivirals.

Synthesis and evaluation of 1,2,3-dithiazole inhibitors of the nucleocapsid protein of feline immunodeficiency virus (FIV) as a model for HIV infection.

We disclose a series of potent anti-viral 1,2,3-dithiazoles, accessed through a succinct synthetic approach from 4,5-dichloro-1,2,3-dithiazolium chloride (Appel's salt). A series of small libraries of compounds were screened against feline immunodeficiency virus (FIV) infected cells as a model for HIV. This approach highlighted new structure activity relationship understanding and led to the development of sub-micro molar anti-viral compounds with reduced toxicity. In addition, insight into the mechanistic progress of this system is provided via advanced QM-MM modelling. The 1,2,3-dithiazole represents a versatile scaffold with potential for further development to treat both FIV and HIV.

Comparative Modelling of Organic Anion Transporting Polypeptides: Structural Insights and Comparison of Binding Modes.

To better understand the functionality of organic anion transporting polypeptides (OATPs) and to design new ligands, reliable structural data of each OATP is needed. In this work, we used a combination of homology model with molecular dynamics simulations to generate a comprehensive structural dataset, that encompasses a diverse set of OATPs but also their relevant conformations. Our OATP models share a conserved transmembrane helix folding harbouring a druggable binding pocket in the shape of an inner pore. Our simulations suggest that the conserved salt bridges at the extracellular region between residues on TM1 and TM7 might influence the entrance of substrates. Interactions between residues on TM1 and TM4 within OATP1 family shown their importance in transport of substrates. Additionally, in transmembrane (TM) 1/2, a known conserved element, interact with two identified motifs in the TM7 and TM11. Our simulations suggest that TM1/2-TM7 interaction influence the inner pocket accessibility, while TM1/2-TM11 salt bridges control the substrate binding stability.

DeepCDA: deep cross-domain compound-protein affinity prediction through LSTM and convolutional neural networks.

MOTIVATION: An essential part of drug discovery is the accurate prediction of the binding affinity of new compound-protein pairs. Most of the standard computational methods assume that compounds or proteins of the test data are observed during the training phase. However, in real-world situations, the test and training data are sampled from different domains with different distributions. To cope with this challenge, we propose a deep learning-based approach that consists of three steps. In the first step, the training encoder network learns a novel representation of compounds and proteins. To this end, we combine convolutional layers and long-short-term memory layers so that the occurrence patterns of local substructures through a protein and a compound sequence are learned. Also, to encode the interaction strength of the protein and compound substructures, we propose a two-sided attention mechanism. In the second phase, to deal with the different distributions of the training and test domains, a feature encoder network is learned for the test domain by utilizing an adversarial domain adaptation approach. In the third phase, the learned test encoder network is applied to new compound-protein pairs to predict their binding affinity. RESULTS: To evaluate the proposed approach, we applied it to KIBA, Davis and BindingDB datasets. The results show that the proposed method learns a more reliable model for the test domain in more challenging situations. AVAILABILITY AND IMPLEMENTATION: https://github.com/LBBSoft/DeepCDA.

Structural Characterization of LsrK as a Quorum Sensing Target and a Comparison between X-ray and Homology Models.

Quorum sensing is being investigated as an alternative therapeutic strategy in antibacterial drug discovery programs aimed at combatting bacterial resistance. LsrK is an autoinducer-2 kinase (belongs to the sugar kinase family), playing a key role in the phosphorylation of the autoinducer-2 (AI-2) signaling molecules involved in quorum sensing. Inhibiting LsrK could result in reduced pathogenicity by interfering with quorum sensing signaling. Previously, we have generated homology models to employ in structure-based virtual screening and successfully identified the first class of LsrK inhibitors. While conducting these studies, the crystal structure of LsrK was released, providing us with an opportunity to evaluate the reliability and quality of our models. A comparative structural analysis of the crystal structure and homology models revealed consistencies among them in the overall structural fold and binding site. Furthermore, the binding characteristics and conformational changes of LsrK have been investigated using molecular dynamics to inspect whether LsrK undergoes similar conformational changes as that of sugar kinases. These studies revealed the flexibility of the LsrK C-terminal domain (Domain II) attributing to the conformational changes in LsrK resulting in open and closed states during the phosphorylation. Further, simulations provided us with insights into the flexibility of a loop in Domain I that can influence the ligand accessibility to the LsrK binding site.

Molecular characteristics supporting l-Type amino acid transporter 1 (LAT1)-mediated translocation.

l-Type amino acid transporter 1 (LAT1) is an interesting protein due to its peculiar expression profile. It can be utilized not only as a carrier for improved or targeted drug delivery, e.g., into the brain but also as a target protein by which amino acid supply can be restricted, e.g., from the cancer cells. The recognition and binding processes of LAT1-ligands, such as amino acids and clinically used small molecules, including l-dopa, gabapentin, and melphalan, are today well-known. Binding to LAT1 is crucial, particularly when designing the LAT1-inhibitors. However, it will not guarantee effective translocation across the cell membrane via LAT1, which is a definite requirement for LAT1-substrates, such as drugs that elicit their pharmacological effects inside the cells. Therefore, in the present study, the accumulation of known LAT1-utilizing compounds into the selected LAT1-expressing cancer cells (MCF-7) was explored experimentally over a time period. The differences found among the transport efficiency and affinity of the studied compounds for LAT1 were subsequently explained by docking the ligands into the human LAT1 model (based on the recent cryo-electron microscopy structure). Thus, the findings of this study clarify the favorable structural requirements of the size, shape, and polarity of the ligands that support the translocation and effective transport across the cell membrane via LAT1. This knowledge can be applied in future drug design to attain improved or targeted drug delivery and hence, successful LAT1-utilizing drugs with increased therapeutic effects.

Docking-Based 3D-QSAR Studies for 1,3,4-oxadiazol-2-one Derivatives as FAAH Inhibitors.

This work aimed to construct 3D-QSAR CoMFA and CoMSIA models for a series of 31 FAAH inhibitors, containing the 1,3,4-oxadiazol-2-one moiety. The obtained models were characterized by good statistical parameters: CoMFA Q2 = 0.61, R2 = 0.98; CoMSIA Q2 = 0.64, R2 = 0.93. The CoMFA model field contributions were 54.1% and 45.9% for steric and electrostatic fields, respectively. In the CoMSIA model, electrostatic, steric, hydrogen bond donor, and hydrogen acceptor properties were equal to 34.6%, 23.9%, 23.4%, and 18.0%, respectively. These models were validated by applying the leave-one-out technique, the seven-element test set (CoMFA r2test-set = 0.91; CoMSIA r2test-set = 0.91), a progressive scrambling test, and external validation criteria developed by Golbraikh and Tropsha (CoMFA r20 = 0.98, k = 0.95; CoMSIA r20 = 0.98, k = 0.89). As the statistical significance of the obtained model was confirmed, the results of the CoMFA and CoMSIA field calculation were mapped onto the enzyme binding site. It gave us the opportunity to discuss the structure-activity relationship based on the ligand-enzyme interactions. In particular, examination of the electrostatic properties of the established CoMFA model revealed fields that correspond to the regions where electropositive substituents are not desired, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one moiety. This highlights the importance of heterocycle, a highly electronegative moiety in this area of each ligand. Examination of hydrogen bond donor and acceptor properties contour maps revealed several spots where the implementation of another hydrogen-bond-donating moiety will positively impact molecules' binding affinity, e.g., in the neighborhood of the 1,3,4-oxadiazol-2-one ring. On the other hand, there is a large isopleth that refers to the favorable H-bond properties close to the terminal phenoxy group of a ligand, which means that, generally speaking, H-bond acceptors are desired in this area.