Automated docking of ligands to an artificial active site: augmenting crystallographic analysis with computer modeling

Synthesis of Four Steroidal Carbamates with Antitumor Activity against Mouse Colon Carcinoma CT26WT Cells: In Vitro and In Silico Evidence

Colorectal cancer (CRC) is one of the most lethal cancers worldwide. If detected on time, surgery can expand life expectations of patients up to five more years. However, if metastasis has grown deliberately, the use of chemotherapy can play a crucial role in CRC control. Moreover, the lack of selectivity of current anticancer drugs, plus mutations that occur in cancerous cells, demands the development of new chemotherapeutic agents. Several steroids have shown their potentiality as anticancer agents, while some other compounds, such as Taxol and its derivatives bearing a carbamate functionality, have reached the market. In this article, the synthesis, characterization, and antiproliferative activity of four steroidal carbamates on mouse colon carcinoma CT26WT cells are described. Carbamate synthesis occurred via direct reaction between diosgenin, its B-ring modified derivative, and testosterone with phenyl isocyanate under a Brønsted acid catalysis. All obtained compounds were characterized by ¹H and ¹³C Nuclear Magnetic Resonance (NMR), High Resolution Mass Spectroscopy (HRMS); their melting points are also reported. Results obtained from antiproliferative activity assays indicated that carbamates compounds have inhibitory effects on the growth of this colon cancer cell line. A molecular docking study carried out on Human Prostaglandin E Receptor (EP4) showed a high affinity between carbamates and protein, thus providing a valuable theoretical explanation of the in vitro results.

Anti-ageing and Anti-lung Carcinoma Effects of Vulpinic Acid and Usnic Acid Compounds and Biological Investigations with Molecular Modeling Study

Disorganization and breakdown of extracellular matrix proteins like fibronectin, collagen, and elastin are key characteristics of skin aging due to the increased activation of important proteolytic enzymes like elastases and collagenase enzymes. Also, inhibition of their enzymatic activities by natural molecules might be a promising factor to prevent extrinsic skin aging. All chemicals were obtained from Sigma-Aldrich unless otherwise stated. The assay employed was based on spectrophotometric methods reported in the literature. The collagenase and elastase inhibition assays of some phenolic compounds were performed according to the previous studies. These compounds showed excellent to good inhibitory activities of vulpinic acid against studied these enzymes with IC50 values of 195.36 µM for collagenase and 25.24 µM for elastase. The molecular docking calculations were conducted to investigate the chemical and biological activity of vulpinic acid and usnic acid against collagenase and elastase. The results indicated that these two compounds can interact with the essential residues of the enzymes and affect their activities. The calculations of binding free energies were also performed to obtain more details about the characteristics and free energies of the ligand-enzyme complexes. Additionally, both compounds exhibited the most potent inhibition in the three lung cancer cells, with an IC50 value of 21-68 µM, indicating that vulpinic acid is more potent than Doxorubicin, which exhibited an IC50 value of 21-29 µM.

Cosolvent and Dynamic Effects in Binding Pocket Search by Docking Simulations

The lack of conformational sampling in virtual screening projects can lead to inefficient results because many of the potential drugs may not be able to bind to the target protein during the static docking simulations. Here, we performed ensemble docking for around 2000 United States Food and Drug Administration (FDA)-approved drugs with the RNA-dependent RNA polymerase (RdRp) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a target. The representative protein structures were generated by clustering classical molecular dynamics trajectories, which were evolved using three solvent scenarios, namely, pure water, benzene/water and phenol/water mixtures. The introduction of dynamic effects in the theoretical model showed improvement in docking results in terms of the number of strong binders and binding sites in the protein. Some of the discovered pockets were found only for the cosolvent simulations, where the nonpolar probes induced local conformational changes in the protein that lead to the opening of transient pockets. In addition, the selection of the ligands based on a combination of the binding free energy and binding free energy gap between the best two poses for each ligand provided more suitable binders than the selection of ligands based solely on one of the criteria. The application of cosolvent molecular dynamics to enhance the sampling of the configurational space is expected to improve the efficacy of virtual screening campaigns of future drug discovery projects.

Searching for Potential Novel BCR-ABL Tyrosine Kinase Inhibitors Through G-QSAR and Docking Studies of Some Novel 2-Phenazinamine Derivatives

BACKGROUND

The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity and selectivity over specific BCR-ABL Tyrosine kinase.

METHODS

This has been achieved through G-QSAR and molecular docking studies. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2. 2D and structures of ligands were drawn by using Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using semi-empirical method called MOPAC. The protein structure was downloaded as PDB file from RCSC protein data bank. PYMOL was used for studying the binding interactions. The G-QSAR models generated were found to possess training (r2=0.8074), cross-validation (q2=0.6521), and external validation (pred_r2=0.5892) which proved their statistical significance. Accordingly, the newly designed series of 2-phenazinamines viz., 3-chloro-4-aryl-1-(phenazin-7-yl) azetidin-2-ones (4a-4e) were subjected to wet lab synthesis. Alternatively, docking studies were also conducted which showed binding interactions of some derivatives with > 30% higher binding energy values than the standard anticancer drug imatinib. The lower energy values obtained for these derivatives indicate energetically favorable interaction with protein binding site as compared to standard imatinib.

RESULTS

G-QSAR and molecular docking studies predicted better anticancer activity for the synthesized azitidine derivatives of 2-phenazinamines (4a-4e) as compared to standard drug.

CONCLUSION

It is therefore surmised that the molecular manipulations at appropriate sites of these derivatives suggested by structure activity relationship data will prove to be beneficial in raising anticancer potential.

Identification of novel thiadiazin derivatives as potentially selective inhibitors towards trypanothione reductase from Trypanosoma cruzi by molecular docking using the numerical index poses ratio Pr and the binding mode analysis

Abstract

Chagas disease is a serious health problem in Central and South America for which effective treatment is not currently available. This illness is caused by the protozoa Trypanosoma cruzi, a species that relies on a thiol-based metabolism to regulate oxidative stress. Trypanothione reductase enzyme plays a central role in the metabolic pathway of the parasite. In this work, a virtual screening of a library of novel thiadiazine derivatives against trypanothione reductase using molecular docking was performed. Four different series of hybrid ligands having in the structure one or two peptoid moieties (series I and II) or the tetrazole ring (series III and IV) were considered. An ad hoc numerical index called poses ratio was introduced to interpret the results of the docking analysis and to establish relevant structure-interaction relationships. In addition, six binding modes were found for the ligands with the highest populated conformational clusters after applying contact-based analysis. The most regular and relevant were binding modes I and II, found mainly for ligands from series I. A subsequent molecular docking on human glutathione reductase enzyme allowed to assess the possible cytotoxicity of the ligands towards human cells. A selective binding profile was found for ligands with interactions in the Hydrophobic cleft, the spermidine and the Z subsites inside the active site of trypanothione reductase. At the end of the study, new thiadiazine-based compounds were identified as plausible candidates to selectively inhibit the parasitic enzyme.

Graphic abstract

LC-MS-based multivariate statistical analysis for the screening of potential thrombin/factor Xa inhibitors from Radix Salvia Miltiorrhiza

Background

The dry root and rhizome of Salvia miltiorrhiza Bunge, or Danshen, is a well-known traditional Chinese medicine with anticoagulant activity. Taking into account that thrombin (THR) and factor Xa (FXa) play crucial roles in the coagulation cascade, it is reasonable and meaningful to screening THR and/or FXa inhibitors from Danshen.

Methods

Four extracts [butanol (BA), ethyl acetate (EA) and remained extract (RE) from 75% ethanol extract, and water extract (WE)] of Danshen were prepared, and their THR/FXa inhibitory activities were assessed in vitro. Then, the active EA extract was further separated by silica-gel column chromatography (SC), and its fractions (SC1–SC5) were analyzed by LC–MS. The principal component analysis (PCA) and orthogonal partial least squares discriminate analysis (OPLS-DA) were employed for predicting the specific marker compounds. The chemical structures of targeted compounds were identified by LC–MS/MS and their interactions with THR/FXa were analyzed by the molecular docking analysis.

Results

Danshen EA extract showed strong activity against THR and FXa, and its fractions (SC1–SC5) exhibited obvious difference in inhibitory activity against these two enzymes. Furthermore, four marker compounds with potential THR/FXa inhibitory activity were screened by PCA and OPLS-DA, and were identified as cryptotanshinone, tanshinone I, dihydrotanshinone I and tanshinone IIA. The molecular docking study showed that all these four tanshinones can interact with some key amino acid residues of the THR/FXa active cavities, such as HIS57 and SER195, which were considered to be promising candidates targeting THR and/or FXa with low binding energy (< − 7 kcal mol⁻¹).

Conclusions

LC–MS combined with multivariate statistical analysis can effectively screen potential THR/FXa inhibitory components in Danshen.

In silico identification of new potentially active brassinosteroid analogues

Brassinosteroids (BRs) are hormones found in a wide range of plant species, they are synthesized at low concentrations and are essential for normal growth and development. These phytohormones are recognized by the Leucine-rich-repeat ectodomain of the receptor-like-kinase BRI1 which leads to subsequent downstream signaling mediating plant growth/development. In spite of the advantages that BRs offer, their extraction from natural sources is highly expensive, which constitutes one of its major limitations. Thus, the design and synthesis of structural and/or functional analogues of BRs with higher activity and lower cost has a great practical significance in world agriculture. In this matter, in silico methods, such as molecular docking, are valuable tools for the prediction and design of new compounds with improved activity. In this work we performed molecular docking simulations of 20 synthetic steroids in order to identify active compounds. Contact based analysis, level of exposure of polar groups to the solvent and binding affinity were the parameters used to consider if a synthetic steroid was active. Our results suggested that 17 out of a total of 20 of the analyzed steroids can potentially activate BRI1 receptor.

Plasmodium falciparum dihydroorotate dehydrogenase: a drug target against malaria

Malaria remains one of the most lethal infectious diseases worldwide, and the most severe form is caused by Plasmodium falciparum. In recent decades, the major challenge to treatment of this disease has been the ability of the protozoan parasite to develop resistance to the drugs that are currently in use. Among P. falciparum enzymes, P. falciparum dihydroorotate dehydrogenase has been identified as an important target in drug discovery. Interference with the activity of this enzyme inhibits de novo pyrimidine biosynthesis and consequently prevents malarial infection. Organic synthesis, x-ray crystallography, high-throughput screening and molecular modeling methods such as molecular docking, quantitative structure-activity relationships, structure-based pharmacophore mapping and molecular dynamics simulations have been applied to the discovery of new inhibitors of P. falciparum dihydroorotate dehydrogenase.

Suppression of the NF‑κB signaling pathway in colon cancer cells by the natural compound Riccardin D from Dumortierahirsute

Colorectal cancer (CRC) is a major cause of mortality and morbidity. Chronic inflammation is closely associated with the development, progression and prognosis of the majority of intestinal malignancies. In recent years, targeting the nuclear factor (NF)‑κB signaling pathway for CRC therapy has become an attractive strategy. Riccardin D, a novel macrocyclicbis (bibenzyl) compound, was isolated from the Chinese liverwort plant. Previous studies have suggested that Riccardin D exerted chemo‑preventative effects against the intestinal malignancy formation. In the present study, cell counting kit‑8, Hochest 33258 staining, mitochondria membrane permeability assay, western blotting analysis, reverse transcription‑polymerase chain reaction, luciferase reporter gene assay and molecular modeling analysis were performed to detect the effect and mechanisms of Riccardin D on human colon cancer cells. The results demonstrated that Riccardin D significantly inhibited the growth of HT‑29 cells. In addition, the cDNA expression of cyclooxygenase‑2, and the protein expression and activity of NF‑κB and tumor necrosis factor‑α were downregulated; however, the protein expression of cleaved caspase‑3 and ‑9, and cleaved poly (adenosine diphosphate‑ribose) polymerase, and the B‑cell lymphoma (Bcl)‑2: Bcl‑2‑associated X protein ratio were upregulated. Furthermore, Auto Dock analysis identified binding sites between Riccardin D and NF‑κB. These results indicated that Riccardin D may inhibit cell proliferation and induce apoptosis in HT‑29 cells, which may be associated with the blocking of the NF‑κB signaling pathway. Thus, Riccardin D should be investigated as an NF‑κB inhibitor in cancer therapy.

Computational enzymology for degradation of chemical warfare agents: promising technologies for remediation processes

Chemical weapons are a major worldwide problem, since they are inexpensive, easy to produce on a large scale and difficult to detect and control. Among the chemical warfare agents, we can highlight the organophosphorus compounds (OP), which contain the phosphorus element and that have a large number of applications. They affect the central nervous system and can lead to death, so there are a lot of works in order to design new effective antidotes for the intoxication caused by them. The standard treatment includes the use of an anticholinergic combined to a central nervous system depressor and an oxime. Oximes are compounds that reactivate Acetylcholinesterase (AChE), a regulatory enzyme responsible for the transmission of nerve impulses, which is one of the molecular targets most vulnerable to neurotoxic agents. Increasingly, enzymatic treatment becomes a promising alternative; therefore, other enzymes have been studied for the OP degradation function, such as phosphotriesterase (PTE) from bacteria, human serum paraoxonase 1 (HssPON1) and diisopropyl fluorophosphatase (DFPase) that showed significant performances in OP detoxification. The understanding of mechanisms by which enzymes act is of extreme importance for the projection of antidotes for warfare agents, and computational chemistry comes to aid and reduce the time and costs of the process. Molecular Docking, Molecular Dynamics and QM/MM (quantum-mechanics/molecular-mechanics) are techniques used to investigate the molecular interactions between ligands and proteins.

Computational protein-ligand docking and virtual drug screening with the AutoDock suite

Computational docking can be used to predict bound conformations and free energies of binding for small-molecule ligands to macromolecular targets. Docking is widely used for the study of biomolecular interactions and mechanisms, and it is applied to structure-based drug design. The methods are fast enough to allow virtual screening of ligand libraries containing tens of thousands of compounds. This protocol covers the docking and virtual screening methods provided by the AutoDock suite of programs, including a basic docking of a drug molecule with an anticancer target, a virtual screen of this target with a small ligand library, docking with selective receptor flexibility, active site prediction and docking with explicit hydration. The entire protocol will require ∼5 h.

Screening of direct thrombin inhibitors from Radix Salviae Miltiorrhizae by a peak fractionation approach

Thrombin plays a significant role in thromboembolic disease. In this work, a peak fractionation approach combined with an activity assay method was used to screen direct thrombin inhibitors from Radix Salviae Miltiorrhizae (RSM), a famous herbal remedy for the treatment of cardiovascular diseases in China. A total of 91 fractions were collected from the RSM extract, and 19 fractions out of them showed thrombin inhibitory effects with dose-effect relationship. Among them, three compounds were unambiguously identified as 15, 16-dihydrotanshinone I, cryptotanshinone and tanshinone IIA with IC50 values of 29.39, 81.11 and 66.60μM, respectively. The three compounds were reported with direct thrombin inhibition activities for the first time and their ligand-thrombin interactions were explored by a molecular docking research. These results may contribute to explain the medical benefit of RSM for the prevention and treatment of cardiovascular diseases.

Validation of a computational docking methodology to identify the non-covalent binding site of ligands to DNA

Despite the biomedical consequences of carcinogen-DNA interactions and the potential of DNA as a drug target in medicinal chemistry, only a small number of studies have validated or used docking methods for the prediction of the physical binding of small molecules to DNA. Knowledge of the DNA-physically-bound ligand geometry can lead to the elucidation of the molecular-level mechanism of drugs as well as predicting the subsequent chemical interactions that lead to DNA damage from carcinogens. We sought to validate AutoDock 4.2, a docking method that includes a physics-based free energy function and a Lamarckian Genetic Algorithm, for the prediction of ligand geometries upon physical binding to DNA. We performed simulations by systematically changing the length of the search process for a comprehensive set of 32 ligand-DNA molecular systems with different physico-chemical properties, and we used a free-energy-based convergence criterion to terminate our simulations. For 11 out of 28 molecular systems for which convergence was achieved, the lowest binding free energy geometries were within 2 Å of the experimentally determined geometry. Considering all predicted sites with free energy changes within 20% of the lowest binding free energy site, we found a site within 2 Å of the experimentally determined geometry for 24 out of the 28 systems. However, the predicted hydrogen bonding interactions were different for most molecular systems compared to the same interactions in the experimentally determined geometry. We discuss reasons for the successes and failures, implications, and the importance of ensuring an adequate search in docking calculations. Overall, we concluded that AutoDock 4.2 can be used to predict the non-covalent binding geometry of a small molecule to DNA with some limitations.

Interactions of non-natural halogenated substrates with D-specific dehalogenase (DehD) mutants using in silico studies

The D-2-haloacid dehalogenase of D-specific dehalogenase (DehD) from Rhizobium sp. RC1 catalyses the hydrolytic dehalogenation of D-haloalkanoic acids, inverting the substrate-product configuration and thereby forming the corresponding L-hydroxyalkanoic acids. Our investigations were focused on DehD mutants: R134A and Y135A. We examined the possible interactions between these mutants with haloalkanoic acids and characterized the key catalytic residues in the wild-type dehalogenase, to design dehalogenase enzyme(s) with improved potential for dehalogenation of a wider range of substrates. Three natural substrates of wild-type DehD, specifically, monochloroacetate, monobromoacetate and D,L-2,3-dichloropropionate, and eight other non-natural haloalkanoic acids substrates of DehD, namely, L-2-chloropropionate; L-2-bromopropionate; 2,2-dichloropropionate; dichloroacetate; dibromoacetate; trichloroacetate; tribromoacetate; and 3-chloropropionate, were docked into the active site of the DehD mutants R134A and Y135A, which produced altered catalytic functions. The mutants interacted strongly with substrates that wild-type DehD does not interact with or degrade. The interaction was particularly enhanced with 3-chloropropionate, in addition to monobromoacetate, monochloroacetate and D,L-2,3-dichloropropionate. In summary, DehD variants R134A and Y135A demonstrated increased propensity for binding haloalkanoic acid and were non-stereospecific towards halogenated substrates. The improved characteristics in these mutants suggest that their functionality could be further exploited and harnessed in bioremediations and biotechnological applications.

A shortcut organic dye-based staining method for the detection of DNA both in agarose and polyacrylamide gel electrophoresis

In this study, we describe a brief, sensitive and safe organic dye-based staining method for the visualization of DNA both in agarose and polyacrylamide gels by using Victoria Pure Blue BO (VPBBO). Down to 0.8-1.6 ng of λ DNA/HindIII markers in agarose gels and 0.4-0.8 ng of pUC18 DNA/Mspl markers in polyacrylamide gels can be successfully detected within 15 and 10 min by the new developed technique, respectively. Moreover, the mechanism of the VPBBO staining was investigated and further confirmed by electrospray ionization mass spectrometry (ESI-MS) and molecular docking. The results indicated that the interaction between VPBBO and DNA is mainly due to groove binding.

6-Shogaol induces apoptosis in human leukemia cells through a process involving caspase-mediated cleavage of eIF2α

Background

6-Shogaol is a promising antitumor agent isolated from dietary ginger (Zingiber officinale). However, little is known about the efficacy of 6-shogaol on leukemia cells. Here we investigated the underlying mechanism of 6-shogaol induced apoptosis in human leukemia cells in vitro and in vivo.

Methods

Three leukemia cell lines and primary leukemia cells were used to investigate the apoptosis effect of 6-shogaol. A shotgun approach based on label-free proteome with LC-CHIP Q-TOF MS/MS was employed to identify the cellular targets of 6-shogaol and the differentially expressed proteins were analyzed by bioinformatics protocols.

Results

The present study indicated that 6-shogaol selectively induced apoptosis in transformed and primary leukemia cells but not in normal cells. Eukaryotic translation initiation factor 2 alpha (eIF2α), a key regulator in apoptosis signaling pathway, was significantly affected in both Jurkat and U937 proteome profiles. The docking results suggested that 6-shogaol might bind well to eIF2α at Ser51 of the N-terminal domain. Immunoblotting data indicated that 6-shogaol induced apoptosis through a process involving dephosphorylation of eIF2α and caspase activation–dependent cleavage of eIF2α. Furthermore, 6-shogaol markedly inhibited tumor growth and induced apoptosis in U937 xenograft mouse model.

Conclusion

The potent anti-leukemia activity of 6-shogaol found both in vitro and in vivo in our study make this compound a potential anti-tumor agent for hematologic malignancies.

Fluorescent staining of protein in sodium dodecyl sulfate polyacrylamide gels by salicylaldehyde azine

As a non-covalent fluorescence probe, in this study, salicylaldehyde azine (SA) was introduced as a sensitive fluorescence-based dye for detecting proteins both in 1-D and 2-D polyacrylamide electrophoresis gels. Down to 0.2 ng of single protein band could be detected within 1 h, which similars to that of glutaraldehyde (GA)-silver stain, but approximately four times higher than that of SYPRO Ruby fluorescent stain. Furthermore, comparative analysis of the MS compatibility of SA stain with SYPRO Ruby stain indicated that SA stain is compatible with the downstream of protein identification by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Additionally, the probable mechanism of the SA stain was investigated by molecular docking. The results demonstrated that the interaction between SA and protein was mainly contributed by hydrogen bonding and hydrophobic forces.

Catalytic transitions in the human MDR1 P-glycoprotein drug binding sites

Multidrug resistance proteins that belong to the ATP-binding cassette family like the human P-glycoprotein (ABCB1 or Pgp) are responsible for many failed cancer and antiviral chemotherapies because these membrane transporters remove the chemotherapeutics from the targeted cells. Understanding the details of the catalytic mechanism of Pgp is therefore critical to the development of inhibitors that might overcome these resistances. In this work, targeted molecular dynamics techniques were used to elucidate catalytically relevant structures of Pgp. Crystal structures of homologues in four different conformations were used as intermediate targets in the dynamics simulations. Transitions from conformations that were wide open to the cytoplasm to transition state conformations that were wide open to the extracellular space were studied. Twenty-six nonredundant transitional protein structures were identified from these targeted molecular dynamics simulations using evolutionary structure analyses. Coupled movement of nucleotide binding domains (NBDs) and transmembrane domains (TMDs) that form the drug binding cavities were observed. Pronounced twisting of the NBDs as they approached each other as well as the quantification of a dramatic opening of the TMDs to the extracellular space as the ATP hydrolysis transition state was reached were observed. Docking interactions of 21 known transport ligands or inhibitors were analyzed with each of the 26 transitional structures. Many of the docking results obtained here were validated by previously published biochemical determinations. As the ATP hydrolysis transition state was approached, drug docking in the extracellular half of the transmembrane domains seemed to be destabilized as transport ligand exit gates opened to the extracellular space.

Application of consensus scoring and principal component analysis for virtual screening against β-secretase (BACE-1)

Background

In order to identify novel chemical classes of β-secretase (BACE-1) inhibitors, an alternative scoring protocol, Principal Component Analysis (PCA), was proposed to summarize most of the information from the original scoring functions and re-rank the results from the virtual screening against BACE-1.

Method

Given a training set (50 BACE-1 inhibitors and 9950 inactive diverse compounds), three rank-based virtual screening methods, individual scoring, conventional consensus scoring and PCA, were judged by the hit number in the top 1% of the ranked list. The docking poses were generated by Surflex, five scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, and PMF_Score) were used for pose extraction. For each pose group, twelve scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, PMF_Score, LigScore1, LigScore2, PLP1, PLP2, jain, Ludi_1, and Ludi_2) were used for the pose rank. For a test set, 113,228 chemical compounds (Sigma-Aldrich® corporate chemical directory) were docked by Surflex, then ranked by the same three ranking methods motioned above to select the potential active compounds for experimental test.

Results

For the training set, the PCA approach yielded consistently superior rankings compared to conventional consensus scoring and single scoring. For the test set, the top 20 compounds according to conventional consensus scoring were experimentally tested, no inhibitor was found. Then, we relied on PCA scoring protocol to test another different top 20 compounds and two low micromolar inhibitors (S450588 and 276065) were emerged through the BACE-1 fluorescence resonance energy transfer (FRET) assay.

Conclusion

The PCA method extends the conventional consensus scoring in a quantitative statistical manner and would appear to have considerable potential for chemical screening applications.

Binding site and affinity prediction of general anesthetics to protein targets using docking

BACKGROUND

The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool.

METHODS

High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics.

RESULTS

All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC.

CONCLUSION

We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.

Molecular docking studies of protein-nucleotide complexes using MOLSDOCK (mutually orthogonal Latin squares DOCK)

Understanding the principles of protein receptor recognition, interaction, and association with molecular substrates and inhibitors is of principal importance in the drug discovery process. MOLSDOCK is a molecular docking method that we have recently developed. It uses mutually orthogonal Latin square sampling (together with a variant of the mean field technique) to identify the optimal docking conformation and pose of a small molecule ligand in the appropriate receptor site. Here we report the application of this method to simultaneously identify both the low energy conformation and the one with the best pose in the case of 62 protein-bound nucleotide ligands. The experimental structures of all these complexes are known. We have compared our results with those obtained from two other well-known molecular docking software, viz. AutoDock 4.2.3 and GOLD 5.1. The results show that the MOLSDOCK method was able to sample a wide range of binding modes for these ligands and also scores them well.

Solution structure and function of YndB, an AHSA1 protein from Bacillus subtilis

The solution structure of the Bacillus subtilis protein YndB has been solved using NMR to investigate proposed biological functions. The YndB structure exhibits the helix-grip fold, which consists of a β-sheet with two small and one long α-helix, forming a hydrophobic cavity that preferentially binds lipid-like molecules. Sequence and structure comparisons with proteins from eukaryotes, prokaryotes, and archaea suggest that YndB is very similar to the eukaryote protein Aha1, which binds to the middle domain of Hsp90 and induces ATPase activity. On the basis of these similarities, YndB has been classified as a member of the activator of Hsp90 ATPase homolog 1-like protein (AHSA1) family with a function that appears to be related to stress response. An in silico screen of a compound library of ∼ 18,500 lipids was used to identify classes of lipids that preferentially bind YndB. The in silico screen identified, in order of affinity, the chalcone/hydroxychalcone, flavanone, and flavone/flavonol classes of lipids, which was further verified by 2D (1) H-(15) N HSQC NMR titration experiments with trans-chalcone, flavanone, flavone, and flavonol. All of these compounds are typically found in plants as precursors to various flavonoid antibiotics and signaling molecules. The sum of the data suggests an involvement of YndB with the stress response of B. subtilis to chalcone-like flavonoids released by plants due to a pathogen infection. The observed binding of chalcone-like molecules by YndB is likely related to the symbiotic relationship between B. subtilis and plants.

Quantum mechanics/molecular mechanics strategies for docking pose refinement: distinguishing between binders and decoys in cytochrome C peroxidase

We investigate the effect of systematically applying molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) to docked poses in an attempt to improve the correspondence between theoretical prediction and experimental observation. The proposed scheme involves running a short time scale MD simulation on a docked ligand pose (and any known structurally important crystal structure waters in the active site), followed by QM/MM minimization. Both of these steps are relatively fast for moderately sized ligands; longer time scale MD involving the protein is not found to improve the results. The final binding energy is given in terms of the QM/MM total energy, a van der Waals correction, and a term to account for desolvation effects. This methodology is first tested with a trypsin inhibitor, for which we establish the importance of running MD before reoptimizing with QM/MM. The method is then applied to cytochrome c peroxidase using a set of binders and decoys. In this example, the proposed methodology affords much better discrimination between binders and decoys than the traditional docking approach used. For both systems presented, application of this protocol results in a significantly better energetic ranking and a smaller root mean squared deviation from known crystallographic ligand poses. This work highlights the importance of including polarization effects through QM/MM and of sampling with MD to refine a set of initial docked poses.

Computational approaches for protein function prediction: a combined strategy from multiple sequence alignment to molecular docking-based virtual screening

The functional characterization of proteins represents a daily challenge for biochemical, medical and computational sciences. Although finally proved on the bench, the function of a protein can be successfully predicted by computational approaches that drive the further experimental assays. Current methods for comparative modeling allow the construction of accurate 3D models for proteins of unknown structure, provided that a crystal structure of a homologous protein is available. Binding regions can be proposed by using binding site predictors, data inferred from homologous crystal structures, and data provided from a careful interpretation of the multiple sequence alignment of the investigated protein and its homologs. Once the location of a binding site has been proposed, chemical ligands that have a high likelihood of binding can be identified by using ligand docking and structure-based virtual screening of chemical libraries. Most docking algorithms allow building a list sorted by energy of the lowest energy docking configuration for each ligand of the library. In this review the state-of-the-art of computational approaches in 3D protein comparative modeling and in the study of protein-ligand interactions is provided. Furthermore a possible combined/concerted multistep strategy for protein function prediction, based on multiple sequence alignment, comparative modeling, binding region prediction, and structure-based virtual screening of chemical libraries, is described by using suitable examples. As practical examples, Abl-kinase molecular modeling studies, HPV-E6 protein multiple sequence alignment analysis, and some other model docking-based characterization reports are briefly described to highlight the importance of computational approaches in protein function prediction.

Virtual Screening with AutoDock: Theory and Practice

IMPORTANCE TO THE FIELD: Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. AREAS COVERED IN THIS REVIEW: We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. WHAT THE READER WILL GAIN: A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. TAKE HOME MESSAGE: Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening.

Discovery of fragment molecules that bind the human peroxiredoxin 5 active site

The search for protein ligands is a crucial step in the inhibitor design process. Fragment screening represents an interesting method to rapidly find lead molecules, as it enables the exploration of a larger portion of the chemical space with a smaller number of compounds as compared to screening based on drug-sized molecules. Moreover, fragment screening usually leads to hit molecules that form few but optimal interactions with the target, thus displaying high ligand efficiencies. Here we report the screening of a homemade library composed of 200 highly diverse fragments against the human Peroxiredoxin 5 protein. Peroxiredoxins compose a family of peroxidases that share the ability to reduce peroxides through a conserved cysteine. The three-dimensional structures of these enzymes ubiquitously found throughout evolution have been extensively studied, however, their biological functions are still not well understood and to date few inhibitors have been discovered against these enzymes. Six fragments from the library were shown to bind to the Peroxiredoxin 5 active site and ligand-induced chemical shift changes were used to drive the docking of these small molecules into the protein structure. The orientation of the fragments in the binding pocket was confirmed by the study of fragment homologues, highlighting the role of hydroxyl functions that hang the ligands to the Peroxiredoxin 5 protein. Among the hit fragments, the small catechol molecule was shown to significantly inhibit Peroxiredoxin 5 activity in a thioredoxin peroxidase assay. This study reports novel data about the ligand-Peroxiredoxin interactions that will help considerably the development of potential Peroxiredoxin inhibitors.

Design, synthesis, and evaluation of indole compounds as novel inhibitors targeting Gp41

A series of indole ring containing compounds were designed based on the structure of the gp41 complex in the region of the hydrophobic pocket. These compounds were synthesized using a Suzuki Coupling reaction, and evaluated using a fluorescence binding assay and cell-cell fusion assay. The observed inhibition constant of compound 7 was 2.1microM, and the IC(50) for cell-cell fusion inhibition was 1.1microM. Assay data indicated that 7 is a promising lead compound for optimization into an effective low molecular weight fusion inhibitor.

Protein-ligand docking using mutually orthogonal Latin squares (MOLSDOCK)

The theoretical prediction of the association of a flexible ligand with a protein receptor requires efficient sampling of the conformational space of the ligand. Several docking methodologies are currently available. We have proposed a docking technique that performs well at low computational cost. The method uses mutually orthogonal Latin squares to efficiently sample the docking space. A variant of the mean field technique is used to analyze this sample to arrive at the optimum. The method has been previously applied to search through both the conformational space of a peptide as well its docking space. Here we extend this method to simultaneously identify both the low energy conformation as well as a high scoring docking mode for the small organic ligand molecules. Application of the method to 45 protein-ligand complexes, in which the number of rotatable torsions varies from 2 to 19, and comparisons with AutoDock 4.0, showed that the method works well.

Design, synthesis, and biological evaluation of a novel series of quercetin diacylglucosides as potent anti-MRSA and anti-VRE agents

A series of novel quercetin diacylglucosides were designed and first synthesized by Steglich esterification on the basis of MRSA strains inhibiting natural compound A. The in vitro inhibition of different multi-drug resistant bacterial strains and Escherichia coli DNA gyrase B was investigated. In the series, compound 10h was up to 128-fold more potent against vancomycin-resistant enterococci and more effective than A, which represents a promising new candidate as a potent anti-MRSA and anti-VRE agent.

p38alpha MAP kinase C-terminal domain binding pocket characterized by crystallographic and computational analyses

The mitogen-activated protein (MAP) kinase protein family has a critical role in cellular signaling events, with MAP kinase p38alpha acting in inflammatory processes and being an important drug discovery target. MAP kinase drug design efforts have focused on small-molecule inhibitors of the ATP catalytic site, which exhibit dose-limiting adverse effects. Therefore, characterizing other potential sites that bind substrates, inhibitors, or allosteric effectors is of great interest. Here, we present the crystal structure of human p38alpha MAP kinase, which has a lead compound bound both in the active site and in the lipid-binding site of the C-terminal cap. This C-terminal cap is formed from an extension to the kinase fold, unique to the MAP kinase and cyclin-dependent kinase families and glycogen synthase kinase 3. Binding of this lead, 4-[3-(4-fluorophenyl)-1H-pyrazol-4-yl]pyridine, to wild-type p38alpha induces movement of the C-terminal cap region, creating a hydrophobic pocket centered around residue Trp197. Computational analysis of this C-terminal domain pocket indicates notable flexibility for potentially binding different-shaped compounds, including lipids, oxidized arachidonic acid species such as leukotrienes, and small-molecule effectors. Furthermore, our structural results defining the open p38alpha C-lobe pocket provide a detailed framework for the design of novel small molecules with affinities comparable to active-site binders: to bind and potentially modulate the shape and activity of p38alpha in predetermined ways. Moreover, these results and analyses of p38alpha suggest strategies for designing specific binding compounds applicable to other MAP kinases, as well as the cyclin-dependent kinase family and glycogen synthase kinase 3beta that also utilize the C-terminal insert in their interactions.

Evaluation of an inverse molecular design algorithm in a model binding site

Computational molecular design is a useful tool in modern drug discovery. Virtual screening is an approach that docks and then scores individual members of compound libraries. In contrast to this forward approach, inverse approaches construct compounds from fragments, such that the computed affinity, or a combination of relevant properties, is optimized. We have recently developed a new inverse approach to drug design based on the dead-end elimination and A* algorithms employing a physical potential function. This approach has been applied to combinatorially constructed libraries of small-molecule ligands to design high-affinity HIV-1 protease inhibitors (Altman et al., J Am Chem Soc 2008;130:6099-6013). Here we have evaluated the new method using the well-studied W191G mutant of cytochrome c peroxidase. This mutant possesses a charged binding pocket and has been used to evaluate other design approaches. The results show that overall the new inverse approach does an excellent job of separating binders from nonbinders. For a few individual cases, scoring inaccuracies led to false positives. The majority of these involve erroneous solvation energy estimation for charged amines, anilinium ions, and phenols, which has been observed previously for a variety of scoring algorithms. Interestingly, although inverse approaches are generally expected to identify some but not all binders in a library, due to limited conformational searching, these results show excellent coverage of the known binders while still showing strong discrimination of the nonbinders.

Hexosamine template. A platform for modulating gene expression and for sugar-based drug discovery

This study investigates the breadth of cellular responses engendered by short chain fatty acid (SCFA)-hexosamine hybrid molecules, a class of compounds long used in "metabolic glycoengineering" that are now emerging as drug candidates. First, a "mix and match" strategy showed that different SCFA (n-butyrate and acetate) appended to the same core sugar altered biological activity, complementing previous results [Campbell et al. J. Med. Chem. 2008, 51, 8135-8147] where a single type of SCFA elicited distinct responses. Microarray profiling then compared transcriptional responses engendered by regioisomerically modified ManNAc, GlcNAc, and GalNAc analogues in MDA-MB-231 cells. These data, which were validated by qRT-PCR or Western analysis for ID1, TP53, HPSE, NQO1, EGR1, and VEGFA, showed a two-pronged response where a core set of genes was coordinately regulated by all analogues while each analogue simultaneously uniquely regulated a larger number of genes. Finally, AutoDock modeling supported a mechanism where the analogues directly interact with elements of the NF-kappaB pathway. Together, these results establish the SCFA-hexosamine template as a versatile platform for modulating biological activity and developing new therapeutics.

Docking for fragment inhibitors of AmpC beta-lactamase

Fragment screens for new ligands have had wide success, notwithstanding their constraint to libraries of 1,000-10,000 molecules. Larger libraries would be addressable were molecular docking reliable for fragment screens, but this has not been widely accepted. To investigate docking's ability to prioritize fragments, a library of >137,000 such molecules were docked against the structure of beta-lactamase. Forty-eight fragments highly ranked by docking were acquired and tested; 23 had K(i) values ranging from 0.7 to 9.2 mM. X-ray crystal structures of the enzyme-bound complexes were determined for 8 of the fragments. For 4, the correspondence between the predicted and experimental structures was high (RMSD between 1.2 and 1.4 A), whereas for another 2, the fidelity was lower but retained most key interactions (RMSD 2.4-2.6 A). Two of the 8 fragments adopted very different poses in the active site owing to enzyme conformational changes. The 48% hit rate of the fragment docking compares very favorably with "lead-like" docking and high-throughput screening against the same enzyme. To understand this, we investigated the occurrence of the fragment scaffolds among larger, lead-like molecules. Approximately 1% of commercially available fragments contain these inhibitors whereas only 10(-7)% of lead-like molecules do. This suggests that many more chemotypes and combinations of chemotypes are present among fragments than are available among lead-like molecules, contributing to the higher hit rates. The ability of docking to prioritize these fragments suggests that the technique can be used to exploit the better chemotype coverage that exists at the fragment level.

Assessing the role of polarization in docking

We describe a strategy for including ligand and protein polarization in docking that is based on the conversion of induced dipoles to induced charges. Induced charges have a distinct advantage in that they are readily implemented into a number of different computer programs, including many docking programs and hybrid QM/MM programs; induced charges are also more readily interpreted. In this study, the ligand was treated quantum mechanically to avoid parametrization issues and was polarized by the target protein, which was treated as a set of point charges. The induced dipole at a given target atom, due to polarization by the ligand and neighboring residues, was reformulated as induced charges at the given atom and its bonded neighbors, and these were allowed to repolarize the ligand in an iterative manner. The final set of polarized charges was evaluated in docking using AutoDock 4.0 on 12 protein-ligand systems against the default empirical Gasteiger charges, and against nonpolarized and partially polarized potential-derived charges. One advantage of AutoDock is that the best rmsd structure can be identified not only from the lowest energy pose but also from the largest cluster of poses. Inclusion of polarization does not always lead to the lowest energy pose having a lower rmsd, because docking is designed by necessity to be rapid rather than accurate. However, whenever an improvement in methodology, corresponding to a more thorough treatment of polarization, resulted in an increased cluster size, then there was also a corresponding decrease in the rmsd. The options for implementing polarization within a purely classical docking framework are discussed.

Peculiar inhibition of human mitochondrial aspartyl-tRNA synthetase by adenylate analogs

Human mitochondrial aminoacyl-tRNA synthetases (mt-aaRSs), the enzymes which esterify tRNAs with the cognate specific amino acid, form mainly a different set of proteins than those involved in the cytosolic translation machinery. Many of the mt-aaRSs are of bacterial-type in regard of sequence and modular structural organization. However, the few enzymes investigated so far do have peculiar biochemical and enzymological properties such as decreased solubility, decreased specific activity and enlarged spectra of substrate tRNAs (of same specificity but from various organisms and kingdoms), as compared to bacterial aaRSs. Here the sensitivity of human mitochondrial aspartyl-tRNA synthetase (AspRS) to small substrate analogs (non-hydrolysable adenylates) known as inhibitors of Escherichia coli and Pseudomonas aeruginosa AspRSs is evaluated and compared to the sensitivity of eukaryal cytosolic human and bovine AspRSs. L-aspartol-adenylate (aspartol-AMP) is a competitive inhibitor of aspartylation by mitochondrial as well as cytosolic mammalian AspRSs, with K(i) values in the micromolar range (4-27 microM for human mt- and mammalian cyt-AspRSs). 5'-O-[N-(L-aspartyl)sulfamoyl]adenosine (Asp-AMS) is a 500-fold stronger competitive inhibitor of the mitochondrial enzyme than aspartol-AMP (10nM) and a 35-fold lower competitor of human and bovine cyt-AspRSs (300 nM). The higher sensitivity of human mt-AspRS for both inhibitors as compared to either bacterial or mammalian cytosolic enzymes, is not correlated with clear-cut structural features in the catalytic site as deduced from docking experiments, but may result from dynamic events. In the scope of new antibacterial strategies directed against aaRSs, possible side effects of such drugs on the mitochondrial human aaRSs should thus be considered.

Evaluation of different virtual screening programs for docking in a charged binding pocket

Virtual screening of small molecules against a protein target often identifies the correct pose, but the ranking in terms of binding energy remains a difficult problem, resulting in unacceptable numbers of false positives and negatives. To investigate this problem, the performance of three docking programs, FRED, QXP/FLO, and GLIDE, along with their five different scoring functions, was evaluated with the engineered cavity in cytochrome c peroxidase (CCP). This small cavity is negatively charged and completely buried from solvent. A test set of 60 molecules, experimentally identified as 43 "binders" and 17 "non-binders", were tested with the CCP binding site. The docking methods' performance is quantified by the ROC curve and their reproduction of crystal poses. The effects from generation of different ligand tautomers and inclusion of water molecule in the cavity are also discussed.

An improved relaxed complex scheme for receptor flexibility in computer-aided drug design

The interactions among associating (macro)molecules are dynamic, which adds to the complexity of molecular recognition. While ligand flexibility is well accounted for in computational drug design, the effective inclusion of receptor flexibility remains an important challenge. The relaxed complex scheme (RCS) is a promising computational methodology that combines the advantages of docking algorithms with dynamic structural information provided by molecular dynamics (MD) simulations, therefore explicitly accounting for the flexibility of both the receptor and the docked ligands. Here, we briefly review the RCS and discuss new extensions and improvements of this methodology in the context of ligand binding to two example targets: kinetoplastid RNA editing ligase 1 and the W191G cavity mutant of cytochrome c peroxidase. The RCS improvements include its extension to virtual screening, more rigorous characterization of local and global binding effects, and methods to improve its computational efficiency by reducing the receptor ensemble to a representative set of configurations. The choice of receptor ensemble, its influence on the predictive power of RCS, and the current limitations for an accurate treatment of the solvent contributions are also briefly discussed. Finally, we outline potential methodological improvements that we anticipate will assist future development.

Empirical entropic contributions in computational docking: evaluation in APS reductase complexes

The results from reiterated docking experiments may be used to evaluate an empirical vibrational entropy of binding in ligand-protein complexes. We have tested several methods for evaluating the vibrational contribution to binding of 22 nucleotide analogues to the enzyme APS reductase. These include two cluster size methods that measure the probability of finding a particular conformation, a method that estimates the extent of the local energetic well by looking at the scatter of conformations within clustered results, and an RMSD-based method that uses the overall scatter and clustering of all conformations. We have also directly characterized the local energy landscape by randomly sampling around docked conformations. The simple cluster size method shows the best performance, improving the identification of correct conformations in multiple docking experiments.