Modeling loop backbone flexibility in receptor‐ligand docking simulations

The relevance of receptor conformational change during ligand binding is well documented for many pharmaceutically relevant receptors, but is still not fully accounted for in in silico docking methods. While there has been significant progress in treatment of receptor side chain flexibility sampling of backbone flexibility remains challenging because the conformational space expands dramatically and the scoring function must balance protein–protein and protein–ligand contributions. Here, we investigate an efficient multistage backbone reconstruction algorithm for large loop regions in the receptor and demonstrate that treatment of backbone receptor flexibility significantly improves binding mode prediction starting from apo structures and in cross docking simulations. For three different kinase receptors in which large flexible loops reconstruct upon ligand binding, we demonstrate that treatment of backbone flexibility results in accurate models of the complexes in simulations starting from the apo structure. At the example of the DFG‐motif in the p38 kinase, we also show how loop reconstruction can be used to model allosteric binding. Our approach thus paves the way to treat the complex process of receptor reconstruction upon ligand binding in docking simulations and may help to design new ligands with high specificity by exploitation of allosteric mechanisms. © 2012 Wiley Periodicals, Inc.     

Molecular simulation studies to reveal the binding mechanisms of shikonin derivatives inhibiting VEGFR-2 kinase

Traditional vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors can manage angiogenesis; however, severe toxicity and resistance limit their long-term applications in clinical therapy. Shikonin (SHK) and its derivatives could be promising to inhibit the VEGFR-2 mediated angiogenesis, as they are reported to bind in the catalytic kinase domain with low affinity. However, the detailed molecular insights and binding dynamics of these natural inhibitors are unknown, which is crucial for potential SHK based lead design. Therefore, the present study employed molecular modeling and simulations techniques to get insight into the binding behaviors of SHK and its two derivates, β-hydroxyisovalerylshikonin (β-HIVS) and acetylshikonin (ACS). Here the intermolecular interactions between protein and ligands were studied by induced fit docking approach, which were further evaluated by treating QM/MM (quantum mechanics/molecular mechanics) and molecular dynamics (MD) simulation. The result showed that the naphthazarin ring of the SHK derivates is vital for strong binding to the catalytic domain; however, the binding stability can be modulated by the side chain modification. Because of having electrostatic potential, this ring makes essential interactions with the DFG (Asp1046 and Phe1047) motif and also allows interacting with the allosteric binding site. Taken together, the studies will advance our knowledge and scope for the development of new selective VEGFR-2 inhibitors based on SHK and its analogs.     

Efficient inclusion of receptor flexibility in grid-based protein-ligand docking

Accounting for receptor flexibility is an essential component of successful protein-ligand docking but still marks a major computational challenge. For many target molecules of pharmaceutical relevance, global backbone conformational changes are relevant during the ligand binding process. However, popular methods that represent the protein receptor molecule as a potential grid typically assume a rigid receptor structure during ligand-receptor docking. A new approach has been developed that combines inclusion of global receptor flexibility with the efficient potential grid representation of the receptor molecule. This is achieved using interpolation between grid representations of the receptor protein deformed in selected collective degrees of freedom. The method was tested on the docking of three ligands to apo protein kinase A (PKA), an enzyme that undergoes global structural changes upon inhibitor binding. Structural variants of PKA were generated along the softest normal mode of an elastic network representation of apo PKA. Inclusion of receptor deformability during docking resulted in a significantly improved docking performance compared with rigid PKA docking, thus allowing for systematic virtual screening applications at small additional computational cost.     

Monitoring allostery in D2O: a necessary control in studies using hydrogen/deuterium exchange to characterize allosteric regulation

There is currently a renewed focus aimed at understanding allosteric mechanisms at atomic resolution. This current interest seeks to understand how both changes in protein conformations and changes in protein dynamics contribute to relaying an allosteric signal between two ligand binding sites on a protein (e.g., active and allosteric sites). Both nuclear magnetic resonance (NMR), by monitoring protein dynamics directly, and hydrogen/deuterium exchange, by monitoring solvent accessibility of backbone amides, offer insights into protein dynamics. Unfortunately, many allosteric proteins exceed the size limitations of standard NMR techniques. Although hydrogen/deuterium exchange as detected by mass spectrometry (H/DX-MS) offers an alternative evaluation method, any application of hydrogen/deuterium exchange requires that the property being measured functions in both H₂O and D₂O. Due to the promising future H/DX-MS has in the evaluation of allosteric mechanisms in large proteins, we demonstrate an evaluation of allosteric regulation in D₂O. Exemplified using phenylalanine inhibition of rabbit muscle pyruvate kinase, we find that binding of the inhibitor is greatly reduced in D₂O, but the effector continues to elicit an allosteric response.     

A molecular docking study of potential inhibitors and repurposed drugs against SARS-CoV-2 main protease enzyme

COVID-19 has affected millions of people. Although many drugs are in use to combat disease, there is not any sufficient treatment yet. Having critical role in propagation of the novel coronavirus (SARS-CoV-2) works Main Protease up into a significant drug target. We have performed a molecular docking study to define possible inhibitor candidates against SARS-CoV-2 Main Protease enzyme. Besides docking Remdesivir, Ribavirin, Chloroquine and 28 other antiviral inhibitors (totally 31 inhibitors) to Main Protease enzyme, we have also performed a molecular docking study of 2177 ligands, which are used against Main Protease for the first time by using molecular docking program Autodock4. All ligands were successfully docked into Main Protease enzyme binding site. Among all ligands, EY16 coded ligand which previously used as EBNA1-DNA binding blocker candidate showed the best score for Main Protease with a binding free energy of −10.83 ​kcal/mol which was also lower than re-docking score of N3 ligand (−10.72 ​kcal/mol) contained in crystal structure of Main Protease. After analyzing the docking modes and docking scores we have found that our ligands have better binding free energy values than the inhibitors in use of treatment. We believe that further studies such as molecular dynamics or Molecular Mechanic Poisson Boltzmann Surface Area studies can make contribution that is more exhaustive to the docking results.     

One site fits both: A model for the ternary complex of folate + NADPH in R67 dihydrofolate reductase, a D2 symmetric enzyme

R67 dihydrofolate reductase (DHFR) is a novel enzyme that confers resistance to the antibiotic trimethoprim. The crystal structure of R67 DHFR displays a toroidal structure with a central active-site pore. This homotetrameric protein exhibits 222 symmetry, with only a few residues from each chain contributing to the active site, so related sites must be used to bind both substrate (dihydrofolate) and cofactor (NADPH) in the productive R67 DHFR?NADPH?dihydrofolate complex. Whereas the site of folate binding has been partially resolved crystallographically, an interesting question remains: how can the highly symmetrical active site also bind and orient NADPH for catalysis? To model this ternary complex, we employed DOCK and SLIDE, two methods for docking flexible ligands into proteins using quite different algorithms. The bound pteridine ring of folate (Fol I) from the crystal structure of R67 DHFR was used as the basis for docking the nicotinamide-ribose-P_i (NMN) moiety of NADPH. NMN was positioned by both DOCK and SLIDE on the opposite side of the pore from Fol I, where it interacts with Fol I at the pore's center. Numerous residues serve dual roles in binding. For example, Gln 67 from both the B and D subunits has several contacts with the pteridine ring, while the same residue from the A and C subunits has several contacts with the nicotinamide ring. The residues involved in dual roles are generally amphipathic, allowing them to make both hydrophobic and hydrophilic contacts with the ligands. The result is a `hot spot' binding surface allowing the same residues to co-optimize the binding of two ligands, and orient them for catalysis.     

Virtual screening using docking and molecular dynamics of cannabinoid analogs against CB1 and CB2 receptors

BackgroundCannabis sativa has been attributed to different pharmacological properties. A number of secondary metabolites such as tetrahydrocannabinol (THC), cannabinol (CBD), and different analogs, with highly promising biological activity on CB₁ and CB₂ receptors, have been identified.MethodsThus, this study aimed was to evaluate the activity of THC, CBD, and their analogs using molecular docking and molecular dynamics simulations (MD) methods. Initially, the molecules (ligands) were selected by bioinformatics searches in databases. Subsequently, CB₁ and CB₂ receptors were retrieved from the protein data bank database. Afterward, each receptor and its ligands were optimized to perform molecular docking. Then, MD Simulation was performed with the most stable ligand-receptor complexes. Finally, the Molecular Mechanics-Generalized Born Surface Area (MM-PBSA) method was applied to analyze the binding free energy between ligands and cannabinoid receptors.ResultsThe results obtained showed that ligand LS-61176 presented the best affinity in the molecular docking analysis. Also, this analog could be a CB₁ negative allosteric modulator like CBD and probably an agonist in CB₂ like THC and CBD according to their dynamic behavior in silico. The possibility of having a THC and a CBD analog (LS-61176) as a promising molecule for experimental evaluation since it could have no central side-effects on CB₁ and have effects of CB₂ useful in pain, inflammation, and some immunological disorders. Docking results were validate using ROC curve for both cannabinoids receptor where AUC for CB1 receptor was 0.894±0.024, and for CB2 receptor AUC was 0.832±0032, indicating good affinity prediction.     

Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes

Many molecular docking programs are available nowadays, and thus it is of great practical value to evaluate and compare their performance. We have conducted an extensive evaluation of four popular commercial molecular docking programs, including Glide, GOLD, LigandFit, and Surflex. Our test set consists of 195 protein‐ligand complexes with high‐resolution crystal structures (resolution ≤2.5 Å) and reliable binding data [dissociation constant (K_d) or inhibition constant (K_i)], which are selected from the PDBbind database with an emphasis on diversity. The top‐ranked solutions produced by these programs are compared to the native ligand binding poses observed in crystal structures. Glide and GOLD demonstrate better accuracy than the other two on the entire test set. Their results are also less sensitive to the starting structures for docking. Comparison of the results produced by these programs at three different computation levels reveal that their accuracy are not always proportional to CPU cost as one may expect. The binding scores of the top‐ranked solutions produced by these programs are in low to moderate correlations with experimentally measured binding data. Further analyses on the outcomes of these programs on three suites of subsets of protein‐ligand complexes indicate that these programs are less capable to handle really flexible ligands and relatively flat binding sites, and they have different preferences to hydrophilic/hydrophobic binding sites. Our evaluation can help other researchers to make reasonable choices among available molecular docking programs. It is also valuable for program developers to improve their methods further. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Multiple ligand simultaneous docking: Orchestrated dancing of ligands in binding sites of protein

Present docking methodologies simulate only one single ligand at a time during docking process. In reality, the molecular recognition process always involves multiple molecular species. Typical protein–ligand interactions are, for example, substrate and cofactor in catalytic cycle; metal ion coordination together with ligand(s); and ligand binding with water molecules. To simulate the real molecular binding processes, we propose a novel multiple ligand simultaneous docking (MLSD) strategy, which can deal with all the above processes, vastly improving docking sampling and binding free energy scoring. The work also compares two search strategies: Lamarckian genetic algorithm and particle swarm optimization, which have respective advantages depending on the specific systems. The methodology proves robust through systematic testing against several diverse model systems: E. coli purine nucleoside phosphorylase (PNP) complex with two substrates, SHP2NSH2 complex with two peptides and Bcl‐xL complex with ABT‐737 fragments. In all cases, the final correct docking poses and relative binding free energies were obtained. In PNP case, the simulations also capture the binding intermediates and reveal the binding dynamics during the recognition processes, which are consistent with the proposed enzymatic mechanism. In the other two cases, conventional single‐ligand docking fails due to energetic and dynamic coupling among ligands, whereas MLSD results in the correct binding modes. These three cases also represent potential applications in the areas of exploring enzymatic mechanism, interpreting noisy X‐ray crystallographic maps, and aiding fragment‐based drug design, respectively. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Allosteric Modulation of the CB1 Cannabinoid Receptor by Cannabidiol—A Molecular Modeling Study of the N-Terminal Domain and the Allosteric-Orthosteric Coupling

The CB₁ cannabinoid receptor (CB₁R) contains one of the longest N termini among class A G protein-coupled receptors. Mutagenesis studies suggest that the allosteric binding site of cannabidiol (CBD) involves residues from the N terminal domain. In order to study the allosteric binding of CBD to CB₁R we modeled the whole N-terminus of this receptor using the replica exchange molecular dynamics with solute tempering (REST2) approach. Then, the obtained structures of CB₁R with the N terminus were used for ligand docking. A natural cannabinoid receptor agonist, Δ⁹-THC, was docked to the orthosteric site and a negative allosteric modulator, CBD, to the allosteric site positioned between extracellular ends of helices TM1 and TM2. The molecular dynamics simulations were then performed for CB₁R with ligands: (i) CBD together with THC, and (ii) THC-only. Analyses of the differences in the residue-residue interaction patterns between those two cases allowed us to elucidate the allosteric network responsible for the modulation of the CB₁R by CBD. In addition, we identified the changes in the orthosteric binding mode of Δ⁹-THC, as well as the changes in its binding energy, caused by the CBD allosteric binding. We have also found that the presence of a complete N-terminal domain is essential for a stable binding of CBD in the allosteric site of CB₁R as well as for the allosteric-orthosteric coupling mechanism.     

The sensitivity of the results of molecular docking to induced fit effects: Application to thrombin, thermolysin and neuraminidase

This paper describes the application of PRO_–LEADS to the flexible docking of ligands into crystallographically derived enzyme structures that are assumed to be rigid. PRO_–LEADS uses a Tabu search methodology to perform the flexible search and an empirically derived estimate of the binding affinity to drive the docking process. The paper tests the extent to which the assumption of a rigid enzyme compromises the accuracy of the results. All-pairs docking experiments are performed for three enzymes (thrombin, thermolysin and influenza virus neuraminidase) based on six or more ligand-enzyme crystal structures for each enzyme. In 76% of the cases, PRO_–LEADS can successfully identify the correct ligand conformation as the lowest energy configuration when the enzyme structure is derived from that ligand's crystal structure, but the methodology only docks 49% of the cases successfully when the ligand is docked against enzyme crystal structures derived from other ligands. Small movements in the enzyme structure lead to an under-prediction in the energy of the correct binding mode by up to 14 kJ/mol and in some cases this under-prediction can lead to the native mode not being recognised as the lowest energy solution. The type of movements responsible for mis-docking are: the movement of sidechains as a result of changes in C position; the movement of sidechains without changes in C position; the movement of flexible portions of main chains to facilitate the formation of hydrogen bonds; and the movement of metal atoms bound to the enzyme active site. The work illustrates that the assumption of a rigid active site can lead to errors in identification of the correct binding mode and the assessment of binding affinity, even for enzymes which show relatively small shift in atomic positions from one ligand to the next. A good docking code, such as PRO_–LEADS, can usually dock successfully if there is induced fit in relatively rigid enzymes but there remains the need to develop improved strategies for dealing with enzyme flexibility. The work implies that treatments of enzyme flexibility which focus only on sidechain rotations will not deal with the critical shifts responsible for mis-docking of ligands in thrombin, thermolysin and neuraminidase. The paper demonstrates the utility of all pairs docking experiments as a method of assessing the effectiveness of docking methodologies in dealing with enzyme flexibility.     

Extended-ensemble docking to probe dynamic variation of ligand binding sites during large-scale structural changes of proteins

Proteins can sample a broad landscape as they undergo conformational transition between different functional states. At the same time, as key players in almost all cellular processes, proteins are important drug targets. Considering the different conformational states of a protein is therefore central for a successful drug-design strategy. Here we introduce a novel docking protocol, termed extended-ensemble docking, pertaining to proteins that undergo large-scale (global) conformational changes during their function. In its application to multidrug ABC-transporter P-glycoprotein (Pgp), extensive non-equilibrium molecular dynamics simulations employing system-specific collective variables are first used to describe the transition cycle of the transporter. An extended set of conformations (extended ensemble) representing the full transition cycle between the inward- and the outward-facing states is then used to seed high-throughput docking calculations of known substrates, non-substrates, and modulators of the transporter. Large differences are predicted in the binding affinities to different conformations, with compounds showing stronger binding affinities to intermediate conformations compared to the starting crystal structure. Hierarchical clustering of the binding modes shows all ligands preferably bind to the large central cavity of the protein, formed at the apex of the transmembrane domain (TMD), whereas only small binding populations are observed in the previously described R and H sites present within the individual TMD leaflets. Based on the results, the central cavity is further divided into two major subsites, first preferably binding smaller substrates and high-affinity inhibitors, whereas the second one shows preference for larger substrates and low-affinity modulators. These central subsites along with the low-affinity interaction sites present within the individual TMD leaflets may respectively correspond to the proposed high- and low-affinity binding sites in Pgp. We propose further an optimization strategy for developing more potent inhibitors of Pgp, based on increasing its specificity to the extended ensemble of the protein, instead of using a single protein structure, as well as its selectivity for the high-affinity binding site. In contrast to earlier in silico studies using single static structures of Pgp, our results show better agreement with experimental studies, pointing to the importance of incorporating the global conformational flexibility of proteins in future drug-discovery endeavors.

Functional states of P-glycoprotein formed during its full transition cycle (red to blue), captured by molecular dynamics simulations, form a structural framework for extended-ensemble docking of small-molecule ligands of diverse activities.     

The Mitochondrial Protein MitoNEET as a Probe for the Allostery of Glutamate Dehydrogenase

The proteins glutamate dehydrogenase (GDH) and mitoNEET are both targets of drug development efforts to treat metabolic disorders, cancer, and neurodegenerative diseases. However, these two proteins differ starkly in the current knowledge about ligand binding sites. MitoNEET is a [2Fe-2S]-containing protein with no obvious binding site for small ligands observed in its crystal structures. In contrast, GDH is known to have a variety of ligands at multiple allosteric sites thereby leading to complex regulation in activity. In fact, while GDH can utilize either NAD(H) or NADP(H) for catalysis at the active site, only NAD(H) binds at a regulatory site to inhibit GDH activity. Previously, we found that mitoNEET forms a covalent bond with GDH in vitro and increases the catalytic activity of the enzyme. In this study we evaluated the effects of mitoNEET binding on the allosteric control of GDH conferred by inhibitors. We examined all effectors using NAD or NADP as the coenzyme to determine allosteric linkage by the NAD-binding regulatory site. We found that GDH activity, in the presence of the inhibitory palmitoyl-CoA and EGCG, can be rescued by mitoNEET, regardless of the coenzyme used. This suggests that mitoNEET rescues GDH by stabilizing the open conformation.     

Molecular activities and ligand-binding specificities of StAR-related lipid transfer domains: exploring integrated in silico methods and ensemble-docking approaches

In this study, cholesterol biotransformation gene-set of human steroidogenic acute regulatory protein-related lipid transfer (START) domains were evaluated from high-throughput gene screening approaches. It was shown that STARD1, STARD3 and STARD4 proteins are better effective transporters of cholesterol than STARD5 and STARD6 domains. Docking studies show a strong agreement with gene ontology enrichment data. According to both complementary strategies, it was found that only STARD1, STARD3 and STARD4 are potentially involved in cholesterol biotransformation in mitochondria through Ω1-loop of C-terminal α4-helical domain. Ensemble docking assessment for a set of selected chemicals of protein–chemical networks has shown possible binding probabilities with START domains. Among those, reproductive toxicity evoked drugs (mifepristone), insecticides (rotenone), tobacco pulmonary carcinogens (benzo(a)pyrene) and endocrine disruptor chemicals (EDCs) including perfluorooctanesulfonic acid (PFOS) and aflatoxin B₁ (AFB₁) potentially bound with novel hotspot residues of the α4-helical domain. Compound representation space and clustering approaches reveal that the START proteins show more sensitivity with these lead scaffolds, so they could provide probable barrier assets in cholesterol and steroidogenic acute regulatory (StAR) binding and leads adverse consequences in steroidogenesis. These findings indicate potential START domains and their binding levels with toxic chemicals; sorted viewpoints could be useful as a promising way to identify chemicals with related steroidogenisis impacts on human health.     

Identifying the binding mode of a molecular scaffold

We describe a method for docking of a scaffold-based series and present its advantages over docking of individual ligands, for determining the binding mode of a molecular scaffold in a binding site. The method has been applied to eight different scaffolds of protein kinase inhibitors (PKI). A single analog of each of these eight scaffolds was previously crystallized with different protein kinases. We have used FlexX to dock a set of molecules that share the same scaffold, rather than docking a single molecule. The main mode of binding is determined by the mode of binding of the largest cluster among the docked molecules that share a scaffold. Clustering is based on our 'nearest single neighbor' method [J. Chem. Inf. Comput. Sci., 43 (2003) 208-217]. Additional criteria are applied in those cases in which more than one significant binding mode is found. Using the proposed method, most of the crystallographic binding modes of these scaffolds were reconstructed. Alternative modes, that have not been detected yet by experiments, could also be identified. The method was applied to predict the binding mode of an additional molecular scaffold that was not yet reported and the predicted binding mode has been found to be very similar to experimental results for a closely related scaffold. We suggest that this approach be used as a virtual screening tool for scaffold-based design processes.     

A novel scoring function for molecular docking

We present a novel scoring function for docking of small molecules to protein binding sites. The scoring function is based on a combination of two main approaches used in the field, the empirical and knowledge-based approaches. To calibrate the scoring function we used an iterative procedure in which a ligand's position and its score were determined self-consistently at each iteration. The scoring function demonstrated superiority in prediction of ligand positions in docking tests against the commonly used Dock, FlexX and Gold docking programs. It also demonstrated good accuracy of binding affinity prediction for the docked ligands.     

Site mapping and small molecule blind docking reveal a possible target site on the SARS-CoV-2 main protease dimer interface

The SARS-CoV-2 virus is causing COVID-19 resulting in an ongoing pandemic with serious health, social, and economic implications. Much research is focused in repurposing or identifying new small molecules which may interact with viral or host-cell molecular targets. An important SARS-CoV-2 target is the main protease (M^pro), and the peptidomimetic α-ketoamides represent prototypical experimental inhibitors. The protease is characterised by the dimerization of two monomers each which contains the catalytic dyad defined by Cys¹⁴⁵ and His⁴¹ residues (active site). Dimerization yields the functional homodimer. Here, our aim was to investigate small molecules, including lopinavir and ritonavir, α-ketoamide 13b, and ebselen, for their ability to interact with the M^pro. The sirtuin 1 agonist SRT1720 was also used in our analyses. Blind docking to each monomer individually indicated preferential binding of the ligands in the active site. Site-mapping of the dimeric protease indicated a highly reactive pocket in the dimerization region at the domain III apex. Blind docking consistently indicated a strong preference of ligand binding in domain III, away from the active site. Molecular dynamics simulations indicated that ligands docked both to the active site and in the dimerization region at the apex, formed relatively stable interactions. Overall, our findings do not obviate the superior potency with respect to inhibition of protease activity of covalently-linked inhibitors such as α-ketoamide 13b in the M^pro active site. Nevertheless, along with those from others, our findings highlight the importance of further characterisation of the M^pro active site and any potential allosteric sites.     

Computational Design and Study of Artificial Selenoenzyme with Controllable Activity Based on an Allosteric Protein Scaffold

The establishment of new enzymatic function in an existing scaffold is a great challenge for protein engineers. In previous work, a highly efficient artificial selenoenzyme with controllable activity was constructed, based on a Ca²⁺-responsive recoverin (Rn) protein. In this study, a design strategy combining docking, molecular dynamics, and MM-PBSA is presented, to predict the catalytically active site of glutathione peroxidase (GPx) on the allosteric domain of Rn. The energy contributions of the binding hot spot residues are evaluated further by energy decomposition analysis to determine the detailed substrate recognition mechanism of Rn, which provides clear guidance for artificial enzyme design for improved substrate binding (Michaelis–Menten constant, K_m).     

Novel Inhibitors of 2′-O-Methyltransferase of the SARS-CoV-2 Coronavirus

The COVID-19 pandemic is still affecting many people worldwide and causing a heavy burden to global health. To eliminate the disease, SARS-CoV-2, the virus responsible for the pandemic, can be targeted in several ways. One of them is to inhibit the 2′-O-methyltransferase (nsp16) enzyme that is crucial for effective translation of viral RNA and virus replication. For methylation of substrates, nsp16 utilizes S-adenosyl methionine (SAM). Binding of a small molecule in the protein site where SAM binds can disrupt the synthesis of viral proteins and, as a result, the replication of the virus. Here, we performed high-throughput docking into the SAM-binding site of nsp16 for almost 40 thousand structures, prepared for compounds from three libraries: Enamine Coronavirus Library, Enamine Nucleoside Mimetics Library, and Chemdiv Nucleoside Analogue Library. For the top scoring ligands, semi-empirical quantum-chemical calculations were performed, to better estimate protein–ligand binding enthalpy. Relying upon the calculated binding energies and predicted docking poses, we selected 21 compounds for experimental testing.