Pose prediction accuracy in docking studies and enrichment of actives in the active site of GSK-3beta

We present molecular docking studies on the inhibitors of GSK-3beta kinase in the enzyme binding sites of the X-ray complexes (1H8F, 1PYX, 1O9U, 1Q4L, 1Q5K, and 1UV5) using the Schr?dinger docking tool Glide. Cognate and cross-docking studies using standard precision (SP) and extraprecision (XP) algorithms have been carried out. Cognate docking studies demonstrate that docked poses similar to X-ray poses (root-mean-square deviations of less than 2 A) are found within the top four ranks of the GlideScore and E-model scores. However, cross-docking studies typically produce poses that are significantly deviated from X-ray poses in all but a couple of cases, implying potential for induced fit effects in ligand binding. In this light, we have also carried out induced fit docking studies in the active sites of 1O9U, 1Q4L, and 1Q5K. Specifically, conformational changes have been effected in the active sites of these three protein structures to dock noncognate ligands. Thus, for example, the active site of 1O9U has been induced to fit the ligands of 1Q4L, 1Q5K, and 1UV5. These studies produce ligand docked poses which have significantly lower root-mean-square deviations relative to their X-ray crystallographic poses, when compared to the corresponding values from the cross-docking studies. Furthermore, we have used an ensemble of the induced fit models and X-ray structures to enhance the retrieval of active GSK-3beta inhibitors seeded in a decoy database, normally used in Glide validation studies. Thus, our studies provide valuable insights into computational strategies useful for the identification of potential GSK-3beta inhibitors.     

New scoring functions for virtual screening from molecular dynamics simulations with a quantum-refined force-field (QRFF-MD). Application to cyclin-dependent kinase 2

A recently introduced new methodology based on ultrashort (50-100 ps) molecular dynamics simulations with a quantum-refined force-field (QRFF-MD) is here evaluated in its ability both to predict protein-ligand binding affinities and to discriminate active compounds from inactive ones. Physically based scoring functions are derived from this approach, and their performance is compared to that of several standard knowledge-based scoring functions. About 40 inhibitors of cyclin-dependent kinase 2 (CDK2) representing a broad chemical diversity were considered. The QRFF-MD method achieves a correlation coefficient, R(2), of 0.55, which is significantly better than that obtained by a number of traditional approaches in virtual screening but only slightly better than that obtained by consensus scoring (R(2) = 0.50). Compounds from the Available Chemical Directory, along with the known active compounds, were docked into the ATP binding site of CDK2 using the program Glide, and the 650 ligands from the top scored poses were considered for a QRFF-MD analysis. Combined with structural information extracted from the simulations, the QRFF-MD methodology results in similar enrichment of known actives compared to consensus scoring. Moreover, a new scoring function is introduced that combines a QRFF-MD based scoring function with consensus scoring, which results in substantial improvement on the enrichment profile.     

A pseudo-ligand approach to virtual screening

A virtual screening method is presented that is grounded on a receptor-derived pharmacophore model termed "virtual ligand" or "pseudo-ligand". The model represents an idealized constellation of potential ligand sites that interact with residues of the binding pocket. For rapid virtual screening of compound libraries the potential pharmacophore points of the virtual ligand are encoded as an alignment-free correlation vector, avoiding spatial alignment of pharmacophore features between the pharmacophore query (i.e., the virtual ligand) and the candidate molecule. The method was successfully applied to retrieving factor Xa inhibitors from a Ugi three-component combinatorial library, and yielded high enrichment of actives in a retrospective search for cyclooxygenase-2 (COX-2) inhibitors. The approach provides a concept for "de-orphanizing" potential drug targets and identifying ligands for hitherto unexplored or allosteric binding pockets.     

Module assembly for protein-surface recognition: geranylgeranyltransferase I bivalent inhibitors for simultaneous targeting of interior and exterior protein surfaces

Synthetic chemical probes designed to simultaneously targeting multiple sites of protein surfaces are of interest owing to their potential application as site specific modulators of protein-protein interactions. A new approach toward bivalent inhibitors of mammalian type I geranylgeranyltransferase (GGTase I) based on module assembly for simultaneous recognition of both interior and exterior protein surfaces is reported. The inhibitors synthesized in this study consist of two modules linked by an alkyl spacer; one is the tetrapeptide CVIL module for binding to the interior protein surface (active pocket) and the other is a 3,4,5-alkoxy substituted benzoyl motif that contains three aminoalkyl groups designed to bind to the negatively charged protein exterior surface near the active site. The compounds were screened by two distinct enzyme inhibition assays based on fluorescence spectroscopy and incorporation of a [(3)H]-labeled prenyl group onto a protein substrate. The bivalent inhibitors block GGTase I enzymatic activity with K(i) values in the submicromolar range and are approximately one order of magnitude and more than 150 times more effective than the tetrapeptide CVIL and the methyl benzoate derivatives, respectively. The bivalent compounds 6 and 8 were shown to be competitive inhibitors, suggesting that the CVIL module anchors the whole molecule to the GGTase I active site and delivers the other module to the targeting protein surface. Thus, our module-assembly approach resulted in simultaneous multiple-site recognition, and as a consequence, synergetic inhibition of GGTase I activity, thereby providing a new approach in designing protein-surface-directed inhibitors for targeting protein-protein interactions.     

Identification of Novel β3-Adrenoceptor Agonists Using Energetic Analysis, Structure Based Pharmacophores and Virtual Screening

β3 Adrenergic receptor (β3-AR), is a potential therapeutic target for the treatment of type II diabetes and obesity. We report the identification of novel compounds as β3-AR agonists by integrating different approaches of energetic analysis, structure based pharmacophore designing and virtual screening. In a step wise filtering protocol, structure based virtual screening of 2,33,450 compounds was done. These molecules were docked into the active site of the receptor utilizing three levels of accuracy; ligands passing the HTVS (high throughput virtual screening) step were subsequently analyzed in Glide SP (Standard Precision) and finally in Glide XP (Extra Precision) to estimate the receptor ligand binding affinities. In the second step a total of 300 pharmacophore hypotheses were generated from a set of known and diverse β3-AR agonists. The best hypothesis showed six features: three hydrogen bond acceptors, one positively charged group, and two aromatic rings. To cross validate, pharmacophore filtering was done on the set of shortlisted compounds from structure based VS (virtual screening). The different screening techniques employed were validated using enrichment factor calculations. The energetic based Pharmacophore performed fairly well at distinguishing active from the inactive compounds and yielded a greater diversity of active molecules whereas the number of actives retrieved in the case of structure based screening was the highest.     

Improving database enrichment through ensemble docking

While it may seem intuitive that using an ensemble of multiple conformations of a receptor in structure-based virtual screening experiments would necessarily yield improved enrichment of actives relative to using just a single receptor, it turns out that at least in the p38 MAP kinase model system studied here, a very large majority of all possible ensembles do not yield improved enrichment of actives. However, there are combinations of receptor structures that do lead to improved enrichment results. We present here a method to select the ensembles that produce the best enrichments that does not rely on knowledge of active compounds or sophisticated analyses of the 3D receptor structures. In the system studied here, the small fraction of ensembles of up to 3 receptors that do yield good enrichments of actives were identified by selecting ensembles that have the best mean GlideScore for the top 1% of the docked ligands in a database screen of actives and drug-like "decoy" ligands. Ensembles of two receptors identified using this mean GlideScore metric generally outperform single receptors, while ensembles of three receptors identified using this metric consistently give optimal enrichment factors in which, for example, 40% of the known actives outrank all the other ligands in the database.     

Virtual screening using a conformationally flexible target protein: models for ligand binding to p38α MAPK

We have used virtual screening to develop models for the binding of aryl substituted heterocycles to p38α MAPK. Virtual screening was conducted on a number of p38α MAPK crystal structures using a library of 46 known p38α MAPK inhibitors containing a heterocyclic core substituted by pyridine and fluorophenyl rings (structurally related to SB203580) and a set of decoy compounds. Multiple protonation states and tautomers of active and decoy compounds were considered. Each docking model was evaluated using receiver operating characteristic (ROC) curves and enrichment factors. The two best performing single crystal structures were found to be 1BL7 and 2EWA, with enrichment factors of 14.1 and 13.0 at 2 % of the virtual screen respectively. Ensembles of up to four receptors of similar conformations were generated, generally giving good or very good performances with high ROC AUCs and good enrichment. The 1BL7-2EWA ensemble was able to outperform each of its constituent receptors and gave high enrichment factors of 17.3, 12.0, 8.0 at 2, 5 and 10 % respectively, of the virtual screen. A ROC AUC of 0.94 was obtained for this ensemble. This method may be applied to other proteins where there are a large number of inhibitor classes with different binding site conformations.     

In situ selection of lead compounds by click chemistry: target-guided optimization of acetylcholinesterase inhibitors

The target-guided, in situ click chemistry approach to lead discovery has been successfully employed for discovering acetylcholinesterase (AChE) inhibitors by incubating a selected enzyme/tacrine azide combination with a variety of acetylene reagents that were not previously known to interact with the enzyme's peripheral binding site. The triazole products, formed by the enzyme, were identified by HPLC-mass spectrometry analysis of the crude reaction mixtures. The target-guided lead discovery search was also successful when performed with reagent mixtures containing up to 10 components. From 23 acetylene reagents, the enzyme selected two phenyltetrahydroisoquinoline (PIQ) building blocks that combined with the tacrine azide within the active center gorge to form multivalent inhibitors that simultaneously associate with the active and peripheral binding sites. These new inhibitors are up to 3 times as potent as our previous phenylphenanthridinium-derived compounds, and with dissociation constants as low as 33 femtomolar, they are the most potent noncovalent AChE inhibitors known. In addition, the new compounds lack a permanent positive charge and aniline groups and possess fewer fused aromatic rings. Remarkably, despite the high binding affinity, the enzyme displayed a surprisingly low preference for one PIQ enantiomer over the other.     

Limiting the Number of Potential Binding Modes by Introducing Symmetry into Ligands: Structure‐Based Design of Inhibitors for Trypsin‐Like Serine Proteases

In the absence of X‐ray data, the exploration of compound binding modes continues to be a challenging task. For structure‐based design, specific features of active sites in different targets play a major role in rationalizing ligand binding characteristics. For example, dibasic compounds have been reported as potent inhibitors of various trypsin‐like serine proteases, the active sites of which contain several binding pockets that can be targeted by cationic moieties. This results in several possible orientations within the active site, complicating the binding mode prediction of such compounds by docking tools. Therefore, we introduced symmetry in bi‐ and tribasic compounds to reduce conformational space in docking calculations and to simplify binding mode selection by limiting the number of possible pocket occupations. Asymmetric bisbenzamidines were used as starting points for a multistage and structure‐guided optimization. A series of 24 final compounds with either two or three benzamidine substructures was ultimately synthesized and evaluated as inhibitors of five serine proteases, leading to potent symmetric inhibitors for the pharmaceutical drug targets matriptase, matriptase‐2, thrombin and factor Xa. This study underlines the relevance of ligand symmetry for chemical biology.     

Discovery and Characterization of a Cryptic Secondary Binding Site in the Molecular Chaperone HSP70

Heat Shock Protein 70s (HSP70s) are key molecular chaperones that are overexpressed in many cancers and often associated with metastasis and poor prognosis. It has proven difficult to develop ATP-competitive, drug-like small molecule inhibitors of HSP70s due to the flexible and hydrophilic nature of the HSP70 ATP-binding site and its high affinity for endogenous nucleotides. The aim of this study was to explore the potential for the inhibition of HSP70 through alternative binding sites using fragment-based approaches. A surface plasmon resonance (SPR) fragment screen designed to detect secondary binding sites in HSP70 led to the identification by X-ray crystallography of a cryptic binding site in the nucleotide-binding domain (NBD) of HSP70 adjacent to the ATP-binding site. Fragment binding was confirmed and characterized as ATP-competitive using SPR and ligand-observed NMR methods. Molecular dynamics simulations were applied to understand the interactions with the protein upon ligand binding, and local secondary structure changes consistent with interconversion between the observed crystal structures with and without the cryptic pocket were detected. A virtual high-throughput screen (vHTS) against the cryptic pocket was conducted, and five compounds with diverse chemical scaffolds were confirmed to bind to HSP70 with micromolar affinity by SPR. These results identified and characterized a new targetable site on HSP70. While targeting HSP70 remains challenging, the new site may provide opportunities to develop allosteric ATP-competitive inhibitors with differentiated physicochemical properties from current series.     

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.     

Molecular docking and competitive binding study discovered different binding modes of microsomal prostaglandin E synthase-1 inhibitors

Microsomal prostaglandin E synthase-1 (mPGES-1) is a newly recognized therapeutic target for the treatment of inflammation, pain, cancer, atherosclerosis, and stroke. Many mPGES-1 inhibitors have been discovered. However, as the structure of the binding site is not well-characterized, none of these inhibitors was designed based on the mPGES-1 structure, and their inhibition mechanism remains to be fully disclosed. Recently, we built a new structural model of mPGES-1 which was well supported by experimental data. Based on this model, molecular docking and competition experiments were used to investigate the binding modes of four representive mPGES-1 inhibitors. As the inhibitor binding sites predicted by docking overlapped with both the substrate and the cofactor binding sites, mPGES-1 inhibitors might act as dual-site inhibitors. This inhibitory mechanism was further verified by inhibitor-cofactor and inhibitor-substrate competition experiments. To investigate the potency-binding site relationships of mPGES-1 inhibitors, we also carried out molecular docking studies for another series of compounds. The docking results correlated well with the different inhibitory effects observed experimentally. Our data revealed that mPGES-1 inhibitors could bind to the substrate and the cofactor binding sites simultaneously, and this dual-site binding mode improved their potency. Future rational design and optimization of mPGES-1 inhibitors can be carried out based on this binding mechanism.     

Structure-based discovery and in-parallel optimization of novel competitive inhibitors of thymidylate synthase.

BACKGROUND: The substrate sites of enzymes are attractive targets for structure-based inhibitor design. Two difficulties hinder efforts to discover and elaborate new (nonsubstrate-like) inhibitors for these sites. First, novel inhibitors often bind at nonsubstrate sites. Second, a novel scaffold introduces chemistry that is frequently unfamiliar, making synthetic elaboration challenging. RESULTS: In an effort to discover and elaborate a novel scaffold for a substrate site, we combined structure-based screening with in-parallel synthetic elaboration. These techniques were used to find new inhibitors that bound to the folate site of Lactobacillus casei thymidylate synthase (LcTS), an enzyme that is a potential target for proliferative diseases, and is highly studied. The available chemicals directory was screened, using a molecular-docking computer program, for molecules that complemented the three-dimensional structure of this site. Five high-ranking compounds were selected for testing. Activity and docking studies led to a derivative of one of these, dansyltyrosine (Ki 65 microM). Using solid-phase in-parallel techniques 33 derivatives of this lead were synthesized and tested. These analogs are dissimilar to the substrate but bind competitively with it. The most active analog had a Ki of 1.3 microM. The tighter binding inhibitors were also the most specific for LcTS versus related enzymes. CONCLUSIONS: TS can recognize inhibitors that are dissimilar to, but that bind competitively with, the folate substrate. Combining structure-based discovery with in-parallel synthetic techniques allowed the rapid elaboration of this series of compounds. More automated versions of this approach can be envisaged.     

Studies of the mechanism of selectivity of protein tyrosine phosphatase 1B (PTP1B) bidentate inhibitors using molecular dynamics simulations and free energy calculations

Bidentate inhibitors of protein tyrosine phosphatase 1B (PTP1B) are considered as a group of ideal inhibitors with high binding potential and high selectivity in treating type II diabetes. In this paper, the binding models of five bidentate inhibitors to PTP1B, TCPTP, and SHP-2 were investigated and compared by using molecular dynamics (MD) simulations and free energy calculations. The binding free energies were computed using the Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) methodology. The calculation results show that the predicted free energies of the complexes are well consistent with the experimental data. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition analysis indicates that the residues ARG24, ARG254, and GLN262 in the second binding site of PTP1B are essential for the high selectivity of inhibitors. Furthermore, the residue PHE182 close to the active site is also important for the selectivity and the binding affinity of the inhibitors. According to our analysis, it can be concluded that in most cases the polarity of the portion of the inhibitor that binds to the second binding site of the protein is positive to the affinity of the inhibitors while negative to the selectivity of the inhibitors. We expect that the information we obtained here can help to develop potential PTP1B inhibitors with more promising specificity.     

Validated ligand mapping of ACE active site

Crystal structures of angiotensin-converting enzyme (ACE) complexed with three inhibitors (lisinopril, captopril, enalapril) provided experimental data for testing the validity of a prior active site model predicting the bound conformation of the inhibitors. The ACE active site model - predicted over 18 years ago using a series of potent ACE inhibitors of diverse chemical structure - was recreated using published data and commercial software. Comparison between the predicted structures of the three inhibitors bound to the active site of ACE and those determined experimentally yielded root mean square deviation (RMSD) values of 0.43-0.81 A, among the distances defining the active site map. The bound conformations of the chemically relevant atoms were accurately deduced from the geometry of ligands, applying the assumption that the geometry of the active site groups responsible for binding and catalysis of amide hydrolysis was constrained. The mapping of bound inhibitors at the ACE active site was validated for known experimental compounds, so that the constrained conformational search methodology may be applied with confidence when no experimentally determined structure of the enzyme yet exists, but potent, diverse inhibitors are available.     

Comparative protein modeling of 1-deoxy-D-xylulose-5-phosphate reductoisomerase enzyme from Plasmodium falciparum: a potential target for antimalarial drug discovery

Plasmodium falciparum 1-deoxy-D-xylulose-5-phosphate reductoisomerase (Pf-DXR) is a potential target for antimalarial chemotherapy. The three-dimensional model (3D) of this enzyme was determined by means of comparative modeling through multiple alignment followed by intensive optimization, minimization, and validation. The resulting model demonstrates a reasonable topology as gauged from the Ramachandran plot and acceptable three-dimensional structure compatibility as assessed by the Profiles-3D score. The modeled monomeric subunit consists of three domains: (1) N-terminal NADPH binding domain, (2) connective or linker domain (with most of the active site residues located in this domain), and (3) a C-terminal domain. This structure proved to be consistent with known DXR crystal structures from other species. The predicted active site compared favorably with those of the templates and appears to have an active site with a highly conserved architecture. Additionally, the model explains several site-directed mutagenesis data. Besides using several protein structure-checking programs to validate the model, a set of known inhibitors of DXR were also docked into the active site of the modeled Pf-DXR. The docked scores correlated reasonably well with experimental pIC50 values with a regression coefficient (R2) equal to 0.84. Results of the current study should prove useful in the early design and development of inhibitors by either de novo drug design or virtual screening of large small-molecule databases leading to development of new antimalarial agents.