Binding site characteristics in structure-based virtual screening: evaluation of current docking tools

Identification of non-peptide malignant brain tumor (MBT) repeat antagonists by virtual screening of commercially available compounds

The malignant brain tumor (MBT) repeat is an important epigenetic-code "reader" and is functionally associated with differentiation, gene silencing, and tumor suppression. (1-3) Small molecule probes of MBT domains should enable a systematic study of MBT-containing proteins and potentially reveal novel druggable targets. We designed and applied a virtual screening strategy that identified potential MBT antagonists in a large database of commercially available compounds. A small set of virtual hits was purchased and submitted to experimental testing. Nineteen of the purchased compounds showed a specific dose-dependent protein binding and will provide critical structure-activity information for subsequent lead generation and optimization.

Discovery of novel GSK-3β inhibitors with potent in vitro and in vivo activities and excellent brain permeability using combined ligand- and structure-based virtual screening

Dysregulation of glycogen synthase kinase (GSK-3β) is implicated in the pathophysiology of many diseases, including type-2 diabetes, stroke, Alzheimer's, and others. A multistage virtual screening strategy designed so as to overcome known caveats arising from the considerable flexibility of GSK-3β yielded, from among compounds in our in-house database and two commercial databases, new GSK-3β inhibitors with novel scaffold structures. The two most potent and selective validated hits, a 2-anilino-5-phenyl-1,3,4-oxadiazole (24) and a phenylmethylene hydantoin (28), both exhibited nanomolar affinity and selectivity over CDK2 and were potent enough for direct in vivo validation. Both were able to cause significant increases in liver glycogen accumulation in dose-dependent fashion. One also exhibited excellent blood-brain barrier permeability, the other adequate for a lead compound. Analogues of the oxadiazole 24 were synthesized to experimentally corroborate or rule out ligand-bound structures arising from docking studies. SAR results supported one docking study among a number of alternatives.

Synthesis and evaluation of azetidinone analogues of combretastatin A-4 as tubulin targeting agents

The synthesis and antiproliferative activity of a new series of rigid analogues of combretastatin A-4 are described which contain the 1,4-diaryl-2-azetidinone (β-lactam) ring system in place of the usual ethylene bridge present in the natural combretastatin stilbene products. These novel compounds are also substituted at position 3 of the β-lactam ring with an aryl ring. A number of analogues showed potent nanomolar activity in human MCF-7 and MDA-MB-231 breast cancer cell lines, displayed in vitro inhibition of tubulin polymerization, and did not cause significant cytotoxicity in normal murine breast epithelial cells. 4-(4-Methoxyaryl)-substituted compound 32, 4-(3-hydroxy-4-methoxyaryl)-substituted compounds 35 and 41, and the 3-(4-aminoaryl)-substituted compounds 46 and 47 displayed the most potent antiproliferative activity of the series. β-Lactam 41 in particular showed subnanomolar activity in MCF-7 breast cancer cells (IC₅₀= 0.8 nM) together with significant in vitro inhibition of tubulin polymerization and has been selected for further biochemical assessment. These novel β-lactam compounds are identified as potentially useful scaffolds for the further development of antitumor agents that target tubulin.

[Molecular docking: role of intermolecular contacts in formation of complexes of proteins with nucleotides and peptides]

Knowledge of 3D-structure of protein-ligand complex is a major prerequisite for understanding the functioning mechanism of cellular proteins and membrane receptors. This is also of a great help in rational drug design projects. In the present paper we briefly review the molecular docking approaches used to predict possible orientation of a ligand in the protein binding site. The recent trends to improve the accuracy and efficiency of docking algorithms are demonstrated with the results obtained in Laboratory of Biomolecular Modeling. Particular attention is paid to protein-ligand hydrophobic and stacking interactions responsible for molecular recognition of ligand fragments. Such type of interactions are not always adequately represented in scoring criteria of docking applications that leads to mismatch in 3D-structure complexes predictions. That is why further inquiry of methods to account for these interactions is now the area of active research.

Lead identification of conformationally restricted β-lactam type combretastatin analogues: synthesis, antiproliferative activity and tubulin targeting effects

The synthesis and study of the structure-activity relationships of a series of rigid analogues of combretastatin A-4 are described which contain the 1,4-diaryl-2-azetidinone (β-lactam) ring system in place of the usual ethylene bridge present in the natural combretastatin stilbene products. The 1,4-diaryl-2-azetidinones are unsubstituted at C-3, or contain methyl substituent(s) at C-3. The most potent compounds 12d and 12e display antiproliferative activity at nanomolar concentrations when evaluated against the MCF-7 and MDA-MB-231 human breast carcinoma cell lines. 12d exerts antimitotic effects through an inhibition of tubulin polymerisation and subsequent G2/M arrest of the cell cycle in human MDA-MB-231 breast cancer cells, with similar activity to that of CA-4. These novel β-lactam compounds are identified as potentially useful scaffolds for the further development of antitumour agents which target tubulin.

HPPD: ligand- and target-based virtual screening on a herbicide target

Hydroxyphenylpyruvate dioxygenase (HPPD) has proven to be a very successful target for the development of herbicides with bleaching properties, and today HPPD inhibitors are well established in the agrochemical market. Syngenta has a long history of HPPD-inhibitor research, and HPPD was chosen as a case study for the validation of diverse ligand- and target-based virtual screening approaches to identify compounds with inhibitory properties. Two-dimensional extended connectivity fingerprints, three-dimensional shape-based tools (ROCS, EON, and Phase-shape) and a pharmacophore approach (Phase) were used as ligand-based methods; Glide and Gold were used as target-based. Both the virtual screening utility and the scaffold-hopping ability of the screening tools were assessed. Particular emphasis was put on the specific pitfalls to take into account for the design of a virtual screening campaign in an agrochemical context, as compared to a pharmaceutical environment.

Druggable pockets and binding site centric chemical space: a paradigm shift in drug discovery

Detection, comparison and analyses of binding pockets are pivotal to structure-based drug design endeavors, from hit identification, screening of exosites and de-orphanization of protein functions to the anticipation of specific and non-specific binding to off- and anti-targets. Here, we analyze protein-ligand complexes and discuss methods that assist binding site identification, prediction of druggability and binding site comparison. The full potential of pockets is yet to be harnessed, and we envision that better understanding of the pocket space will have far-reaching implications in the field of drug discovery, such as the design of pocket-specific compound libraries and scoring functions.

DynaDock: A new molecular dynamics-based algorithm for protein-peptide docking including receptor flexibility

Molecular docking programs play an important role in drug development and many well-established methods exist. However, there are two situations for which the performance of most approaches is still not satisfactory, namely inclusion of receptor flexibility and docking of large, flexible ligands like peptides. In this publication a new approach is presented for docking peptides into flexible receptors. For this purpose a two step procedure was developed: first, the protein-peptide conformational space is scanned and approximate ligand poses are identified and second, the identified ligand poses are refined by a new molecular dynamics-based method, optimized potential molecular dynamics (OPMD). The OPMD approach uses soft-core potentials for the protein-peptide interactions and applies a new optimization scheme to the soft-core potential. Comparison with refinement results obtained by conventional molecular dynamics and a soft-core scaling approach shows significant improvements in the sampling capability for the OPMD method. Thus, the number of starting poses needed for successful refinement is much lower than for the other methods. The algorithm was evaluated on 15 protein-peptide complexes with 2-16mer peptides. Docking poses with peptide RMSD values <2.10 A from the equilibrated experimental structures were obtained in all cases. For four systems docking into the unbound receptor structures was performed, leading to peptide RMSD values <2.12 A. Using a specifically fitted scoring function in 11 of 15 cases the best scoring poses featured a peptide RMSD < or = 2.10 A.

Troubleshooting computational methods in drug discovery

Computational approaches for drug discovery such as ligand-based and structure-based methods, are increasingly seen as an efficient approach for lead discovery as well as providing insights on absorption, distribution, metabolism, excretion and toxicity (ADME/Tox). What is perhaps less well known and widely described are the limitations of the different technologies. We have therefore presented a troubleshooting approach to QSAR, homology modeling, docking as well as hybrid methods. If such computational or cheminformatics methods are to become more widely used by non-experts it is critical that such limitations are brought to the user's attention and addressed during their workflows. This could improve the quality of the models and results that are obtained.

Improving virtual screening performance against conformational variations of receptors by shape matching with ligand binding pocket

In this report, we present a novel virtual high-throughput screening methodology to assist in computer-aided drug discovery. Our method, designated as SLIM, involves ligand-free shape and chemical feature matching. The procedure takes advantage of a negative image of a binding pocket in a target receptor. The negative image is a set of virtual atoms representing the inner shape and chemical features of the binding pocket. Using this image, SLIM implements a shape-based similarity search based on molecular volume superposition for the ensemble of conformers of each molecule. The superposed structures, prioritized by shape similarity, are subjected to comparison of chemical feature similarities. To validate the merits of the SLIM method, we compared its performance with those of three distinct widely used tools ROCS, GLIDE, and GOLD. ROCS was selected as a representative of the ligand-centric methods, and docking programs GLIDE and GOLD as representatives of the receptor-centric methods. Our data suggest that SLIM has overall hit ranking ability that is comparable to that of the docking method, retaining the high computational speed of the ligand-centric method. It is notable that the SLIM method offers consistently reliable screening quality against conformational variations of receptors, whereas the docking methods have limited screening performance.

New 2-aryloxy-3-phenyl-propanoic acids as peroxisome proliferator-activated receptors alpha/gamma dual agonists with improved potency and reduced adverse effects on skeletal muscle function

The preparation of a new series of 2-aryloxy-3-phenyl-propanoic acids, resulting from the introduction of a linker into the diphenyl system of the previously reported PPARalpha/gamma dual agonist 1, allowed the identification of new ligands with improved potency on PPARalpha and unchanged activity on PPARgamma. For the most interesting stereoisomers S-2 and S-4, X-ray studies in PPARgamma and docking experiments in PPARalpha provided a molecular explanation for their different behavior as full and partial agonists of PPARalpha and PPARgamma, respectively. Due to the adverse effects provoked by hypolipidemic drugs on skeletal muscle function, we also investigated the blocking activity of S-2 and S-4 on skeletal muscle membrane chloride channel conductance and found that these ligands have a pharmacological profile more beneficial compared to fibrates currently used in therapy.

Comparison of several molecular docking programs: pose prediction and virtual screening accuracy

Molecular docking programs are widely used modeling tools for predicting ligand binding modes and structure based virtual screening. In this study, six molecular docking programs (DOCK, FlexX, GLIDE, ICM, PhDOCK, and Surflex) were evaluated using metrics intended to assess docking pose and virtual screening accuracy. Cognate ligand docking to 68 diverse, high-resolution X-ray complexes revealed that ICM, GLIDE, and Surflex generated ligand poses close to the X-ray conformation more often than the other docking programs. GLIDE and Surflex also outperformed the other docking programs when used for virtual screening, based on mean ROC AUC and ROC enrichment values obtained for the 40 protein targets in the Directory of Useful Decoys (DUD). Further analysis uncovered general trends in accuracy that are specific for particular protein families. Modifying basic parameters in the software was shown to have a significant effect on docking and virtual screening results, suggesting that expert knowledge is critical for optimizing the accuracy of these methods.

Validation of molecular docking programs for virtual screening against dihydropteroate synthase

Dihydropteroate synthase (DHPS) is the target of the sulfonamide class of antibiotics and has been a validated antibacterial drug target for nearly 70 years. The sulfonamides target the p-aminobenzoic acid (pABA) binding site of DHPS and interfere with folate biosynthesis and ultimately prevent bacterial replication. However, widespread bacterial resistance to these drugs has severely limited their effectiveness. This study explores the second and more highly conserved pterin binding site of DHPS as an alternative approach to developing novel antibiotics that avoid resistance. In this study, five commonly used docking programs, FlexX, Surflex, Glide, GOLD, and DOCK, and nine scoring functions, were evaluated for their ability to rank-order potential lead compounds for an extensive virtual screening study of the pterin binding site of B. anthracis DHPS. Their performance in ligand docking and scoring was judged by their ability to reproduce a known inhibitor conformation and to efficiently detect known active compounds seeded into three separate decoy sets. Two other metrics were used to assess performance; enrichment at 1% and 2% and Receiver Operating Characteristic (ROC) curves. The effectiveness of postdocking relaxation prior to rescoring and consensus scoring were also evaluated. Finally, we have developed a straightforward statistical method of including the inhibition constants of the known active compounds when analyzing enrichment results to more accurately assess scoring performance, which we call the 'sum of the sum of log rank' or SSLR. Of the docking and scoring functions evaluated, Surflex with Surflex-Score and Glide with GlideScore were the best overall performers for use in virtual screening against the DHPS target, with neither combination showing statistically significant superiority over the other in enrichment studies or pose selection. Postdocking ligand relaxation and consensus scoring did not improve overall enrichment.

An effective docking strategy for virtual screening based on multi-objective optimization algorithm

Background

Development of a fast and accurate scoring function in virtual screening remains a hot issue in current computer-aided drug research. Different scoring functions focus on diverse aspects of ligand binding, and no single scoring can satisfy the peculiarities of each target system. Therefore, the idea of a consensus score strategy was put forward. Integrating several scoring functions, consensus score re-assesses the docked conformations using a primary scoring function. However, it is not really robust and efficient from the perspective of optimization. Furthermore, to date, the majority of available methods are still based on single objective optimization design.

Results

In this paper, two multi-objective optimization methods, called MOSFOM, were developed for virtual screening, which simultaneously consider both the energy score and the contact score. Results suggest that MOSFOM can effectively enhance enrichment and performance compared with a single score. For three different kinds of binding sites, MOSFOM displays an excellent ability to differentiate active compounds through energy and shape complementarity. EFMOGA performed particularly well in the top 2% of database for all three cases, whereas MOEA_Nrg and MOEA_Cnt performed better than the corresponding individual scoring functions if the appropriate type of binding site was selected.

Conclusion

The multi-objective optimization method was successfully applied in virtual screening with two different scoring functions that can yield reasonable binding poses and can furthermore, be ranked with the potentially compromised conformations of each compound, abandoning those conformations that can not satisfy overall objective functions.

Mechanism of binding of fluoroquinolones to the quinolone resistance-determining region of DNA gyrase: towards an understanding of the molecular basis of quinolone resistance

We have studied the bacterial resistance to fluoroquinolones that arises as a result of mutations in the DNA gyrase target protein. Although it is known that DNA gyrase is a target of quinolone antibacterial agents, the molecular details of the quinolone-gyrase interaction remain unclear. The mode of binding of ciprofloxacin, levofloxacin, and moxifloxacin to DNA gyrase was analyzed by means of docking calculations over the surface of the QRDR of GyrA. The analysis of these binding models allows study of the resistance mechanism associated with gyrA mutations more commonly found in E. coli fluoroquinolone-resistant strains at the atomic level. Asp87 was found to be critical in the binding of these fluoroquinolones because it interacts with the positively charged nitrogens in these bactericidal drugs. The role of the other most common mutations at amino acid codon Ser83 can be explained through the contacts that the side chain of this residue establishes with fluoroquinolone molecules. Finally, our results strongly suggest that, although Arg121 has never been found to be associated with fluoroquinolone resistance, this residue makes a pivotal contribution to the binding of the antibiotic to GyrA and to defining its position in the QRDR of the enzyme.

Docking, virtual high throughput screening and in silico fragment-based drug design

The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high-throughput screening and fragment-based ligand design.

Lead Discovery Using Virtual Screening

The practice of virtual screening (VS) to identify chemical leads to known or novel targets is becoming a core function of the computational chemist within industry. By employing a range of techniques, when attempting to identify compounds with activity against a biological target, a small focused subset of a larger collection of compounds can be identified and tested, often with results much better than selecting a similar number of compounds at random. We will review the key methods available, their relative success, and provide practical insights into best practices and key gaps. We will also argue that the capability of VS methods has grown to a point where fuller integration with experimental methods, including HTS, could increase the effectiveness of both.

Mechanism of action of and resistance to quinolones

Fluoroquinolones are an important class of wide-spectrum antibacterial agents. The first quinolone described was nalidixic acid, which showed a narrow spectrum of activity. The evolution of quinolones to more potent molecules was based on changes at positions 1, 6, 7 and 8 of the chemical structure of nalidixic acid. Quinolones inhibit DNA gyrase and topoisomerase IV activities, two enzymes essential for bacteria viability. The acquisition of quinolone resistance is frequently related to (i) chromosomal mutations such as those in the genes encoding the A and B subunits of the protein targets (gyrA, gyrB, parC and parE), or mutations causing reduced drug accumulation, either by a decreased uptake or by an increased efflux, and (ii) quinolone resistance genes associated with plasmids have been also described, i.e. the qnr gene that encodes a pentapeptide, which blocks the action of quinolones on the DNA gyrase and topoisomerase IV; the aac(6')-Ib-cr gene that encodes an acetylase that modifies the amino group of the piperazin ring of the fluoroquinolones and efflux pump encoded by the qepA gene that decreases intracellular drug levels. These plasmid-mediated mechanisms of resistance confer low levels of resistance but provide a favourable background in which selection of additional chromosomally encoded quinolone resistance mechanisms can occur.

The basic concepts of molecular modeling

Molecular modeling techniques have made significant advances in recent years and are becoming essential components of many chemical, physical and biological studies. Here we present three widely used techniques used in the simulation of biomolecular systems: structural and homology modeling, molecular dynamics and molecular docking. For each of these topics we present a brief discussion of the underlying scientific basis of the technique, some simple examples of how the method is commonly applied, and some discussion of the limitations and caveats of which the user should be aware. References for further reading as well as an extensive list of software resources are provided.

Phylogenetic analysis, homology modelling, molecular dynamics and docking studies of caffeoyl-CoA-O- methyl transferase (CCoAOMT 1 and 2) isoforms isolated from subabul (Leucaena leucocephala)

Caffeoyl coenzyme A O-methyltransferase (CCoAOMT) is an important enzyme that participates in lignin biosynthesis especially in the formation of cell wall ferulic esters of plants. It plays a pivotal role in the methylation of the 3-hydroxyl group of caffeoyl CoA. Two cDNA clones that code CCoAOMT were isolated earlier from subabul and in the present study; 3D models of CCoAOMT1 and CCoAOMT2 enzymes were built using the MODELLER7v7 software to find out the substrate binding sites. These two proteins differed only in two amino acids and may have little or no functional redundancy. Refined models of the proteins were obtained after energy minimization and molecular dynamics in a solvated water layer. The models were further assessed by PROCHECK, WHATCHECK, Verify_3D and ERRAT programs and the results indicated that these models are reliable for further active site and docking analysis. The refined models showed that the two proteins have 9 and 10 alpha-helices, 6 and 7 beta-sheets respectively. The models were used for docking the substrates CoA, SAM, SAH, caffeoyl CoA, feruloyl CoA, 5-hydroxy feruloyl CoA and sinapyl CoA which showed that CoA and caffeoyl CoA are binding with high affinity with the enzymes in the presence and absence of SAM. It appears therefore that caffeoyl CoA is the substrate for both the isoenzymes. The results also indicated that CoA and caffeoyl CoA are binding with higher affinity to CCoAOMT2 than CCoAOMT1. Therefore, CCoAOMT2 conformation is thought to be the active form that exists in subabul. Docking studies indicated that conserved active site residues Met58, Thr60, Val63, Glu82, Gly84, Ser90, Asp160, Asp162, Thr169, Asn191 and Arg203 in CCoAOMT1 and CCoAOMT2 enzymes create the positive charge to balance the negatively charged caffeoyl CoA and play an important role in maintaining a functional conformation and are directly involved in donor-substrate binding.

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.

Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go

Accelerating the drug discovery process requires predictive computational protocols capable of reducing or simplifying the synthetic and/or combinatorial challenge. Docking-based virtual screening methods have been developed and successfully applied to a number of pharmaceutical targets. In this review, we first present the current status of docking and scoring methods, with exhaustive lists of these. We next discuss reported comparative studies, outlining criteria for their interpretation. In the final section, we describe some of the remaining developments that would potentially lead to a universally applicable docking/scoring method.

Evaluating docking programs: keeping the playing field level

Over recent years many enrichment studies have been published which purport to rigorously compare the performance of two or more docking protocols. It has become clear however that such studies often have flaws within their methodologies, which cast doubt on the rigour of the conclusions. Setting up such comparisons is fraught with difficulties and no best mode of practice is available to guide the experimenter. Careful choice of structural models and ligands appropriate to those models is important. The protein structure should be representative for the target. In addition the set of active ligands selected should be appropriate to the structure in cases where different forms of the protein bind different classes of ligand. Binding site definition is also an area in which errors arise. Particular care is needed in deciding which crystallographic waters to retain and again this may be predicated by knowledge of the likely binding modes of the ligands making up the active ligand list. Geometric integrity of the ligand structures used is clearly important yet it is apparent that published sets of actives + decoys may contain sometimes high proportions of incorrect structures. Choice of protocol for docking and analysis needs careful consideration as many programs can be tweaked for optimum performance. Should studies be run using 'black box' protocols supplied by the software provider? Lastly, the correct method of analysis of enrichment studies is a much discussed topic at the moment. However currently promoted approaches do not consider a crucial aspect of a successful virtual screen, namely that a good structural diversity of hits be returned. Overall there is much to consider in the experimental design of enrichment studies. Hopefully this study will be of benefit in helping others plan such experiments.

Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection--what can we learn from earlier mistakes?

Within the last few years a considerable amount of evaluative studies has been published that investigate the performance of 3D virtual screening approaches. Thereby, in particular assessments of protein-ligand docking are facing remarkable interest in the scientific community. However, comparing virtual screening approaches is a non-trivial task. Several publications, especially in the field of molecular docking, suffer from shortcomings that are likely to affect the significance of the results considerably. These quality issues often arise from poor study design, biasing, by using improper or inexpressive enrichment descriptors, and from errors in interpretation of the data output. In this review we analyze recent literature evaluating 3D virtual screening methods, with focus on molecular docking. We highlight problematic issues and provide guidelines on how to improve the quality of computational studies. Since 3D virtual screening protocols are in general assessed by their ability to discriminate between active and inactive compounds, we summarize the impact of the composition and preparation of test sets on the outcome of evaluations. Moreover, we investigate the significance of both classic enrichment parameters and advanced descriptors for the performance of 3D virtual screening methods. Furthermore, we review the significance and suitability of RMSD as a measure for the accuracy of protein-ligand docking algorithms and of conformational space sub sampling algorithms.

Enantiomeric separation of 2-aryloxyalkyl- and 2-arylalkyl-2-aryloxyacetic acids on a Penicillin G Acylase-based chiral stationary phase: Influence of the chemical structure on retention and enantioselectivity

The chiral recognition mechanism of Penicillin G Acylase (PGA) was investigated with a set of 18 new chiral acidic compounds. A series of 2-aryloxyalkyl- and 2-arylalkyl-2-aryloxyacetic acids in which the absolute configuration has been reported to exert a strong influence on pharmacological activity, were synthesized and analysed on PGA-based chiral stationary phase (CSP) and 11 racemates were completely resolved with a mobile phase composed of 50 mM phosphate buffer (pH 7.0). The influence of structural variations of analytes on retention and enantioselectivity was investigated by application of molecular modelling studies. Docking experiments were also carried out to rationalize the observed enantioselective behaviour. The computation approach revealed to be helpful in elucidating the molecular basis of the enantioselectivity observed on PGA-CSP.

Structure-based virtual ligand screening with LigandFit: pose prediction and enrichment of compound collections

Virtual ligand screening methods based on the structure of the receptor are extensively used to facilitate the discovery of lead compounds. In the present study, we investigated the LigandFit package on four different proteins (coagulation factor VIIa, estrogen receptor, thymidine kinase, and neuraminidase), a relatively large compound collection of 65,560 unique "drug-like" molecules and four focused libraries (1950 molecules each). We performed virtual screening experiments with the large database and evaluated six scoring functions available in the package (DockScore, LigScore1, LigScore2, PLP1, PLP2, and PMF). The results showed that LigandFit is an efficient program, especially when used with LigScore1. Similar computations were carried out using focused libraries. In this situation the LigScore1 scoring function outperformed the other ones on three out of the four proteins tested. Even for the difficult neuraminidase case, the LigandFit/LigScore1 combination was still reasonably successful. Assessment of docking accuracy was also performed and again, we found that LigandFit (with DockScore and the CFF parameters) was performing well. On the basis of these results and observed increased enrichments after LigandFit/Ligscore1 screening on focused libraries, we suggest that using this program as a final step of a hierarchical protocol can be very beneficial to assist lead finding.

Supervised Scoring Models with Docked Ligand Conformations for Structure-Based Virtual Screening

Protein-ligand docking programs have been used to efficiently discover novel ligands for target proteins from large-scale compound databases. However, better scoring methods are needed. Generally, scoring functions are optimized by means of various techniques that affect their fitness for reproducing X-ray structures and protein-ligand binding affinities. However, these scoring functions do not always work well for all target proteins. A scoring function should be optimized for a target protein to enhance enrichment for structure-based virtual screening. To address this problem, we propose the supervised scoring model (SSM), which takes into account the protein-ligand binding process using docked ligand conformations with supervised learning for optimizing scoring functions against a target protein. SSM employs a rough linear correlation between binding free energy and the root mean square deviation of a native ligand for predicting binding energy. We applied SSM to the FlexX scoring function, that is, F-Score, with five different target proteins: thymidine kinase (TK), estrogen receptor (ER), acetylcholine esterase (AChE), phosphodiesterase 5 (PDE5), and peroxisome proliferator-activated receptor gamma (PPARgamma). For these five proteins, SSM always enhanced enrichment better than F-Score, exhibiting superior performance that was particularly remarkable for TK, AChE, and PPARgamma. We also demonstrated that SSM is especially good at enhancing enrichments of the top ranks of screened compounds, which is useful in practical drug screening.

Virtual ligand screening: strategies, perspectives and limitations

In contrast to high-throughput screening, in virtual ligand screening (VS), compounds are selected using computer programs to predict their binding to a target receptor. A key prerequisite is knowledge about the spatial and energetic criteria responsible for protein–ligand binding. The concepts and prerequisites to perform VS are summarized here, and explanations are sought for the enduring limitations of the technology. Target selection, analysis and preparation are discussed, as well as considerations about the compilation of candidate ligand libraries. The tools and strategies of a VS campaign, and the accuracy of scoring and ranking of the results, are also considered.

Comparison of Topological, Shape, and Docking Methods in Virtual Screening

Virtual screening benchmarking studies were carried out on 11 targets to evaluate the performance of three commonly used approaches: 2D ligand similarity (Daylight, TOPOSIM), 3D ligand similarity (SQW, ROCS), and protein structure-based docking (FLOG, FRED, Glide). Active and decoy compound sets were assembled from both the MDDR and the Merck compound databases. Averaged over multiple targets, ligand-based methods outperformed docking algorithms. This was true for 3D ligand-based methods only when chemical typing was included. Using mean enrichment factor as a performance metric, Glide appears to be the best docking method among the three with FRED a close second. Results for all virtual screening methods are database dependent and can vary greatly for particular targets.

A Multivariate Approach to Investigate Docking Parameters' Effects on Docking Performance

Increasingly powerful docking programs for analyzing and estimating the strength of protein-ligand interactions have been developed in recent decades, and they are now valuable tools in drug discovery. Software used to perform dockings relies on a number of parameters that affect various steps in the docking procedure. However, identifying the best choices of the settings for these parameters is often challenging. Therefore, the settings of the parameters are quite often left at their default values, even though scientists with long experience with a specific docking tool know that modifying certain parameters can improve the results. In the study presented here, we have used statistical experimental design and subsequent regression based on root-mean-square deviation values using partial least-square projections to latent structures (PLS) to scrutinize the effects of different parameters on the docking performance of two software packages: FRED and GOLD. Protein-ligand complexes with a high level of ligand diversity were selected from the PDBbind database for the study, using principal component analysis based on 1D and 2D descriptors, and space-filling design. The PLS models showed quantitative relationships between the docking parameters and the ability of the programs to reproduce the ligand crystallographic conformation. The PLS models also revealed which of the parameters and what parameter settings were important for the docking performance of the two programs. Furthermore, the variation in docking results obtained with specific parameter settings for different protein-ligand complexes in the diverse set examined indicates that there is great potential for optimizing the parameter settings for selected sets of proteins.

Alternative to consensus scoring--a new approach toward the qualitative combination of docking algorithms

Since the development of the first docking algorithm in the early 1980s a variety of different docking approaches and tools has been created in order to solve the docking problem. Subsequent studies have shown that the docking performance of most tools strongly depends on the considered target. Thus it is hard to choose the best algorithm in the situation at hand. The docking tools FlexX and AutoDock are among the most popular programs for docking flexible ligands into target proteins. Their analysis, comparison, and combination are the topics of this study. In contrast to standard consensus scoring techniques which integrate different scoring algorithms usually only by their rank, we focus on a more general approach. Our new combined docking workflow-AutoxX-unifies the interaction models of AutoDock and FlexX rather than combining the scores afterward which allows interpretability of the results. The performance of FlexX, AutoDock, and the combined algorithm AutoxX was evaluated on the basis of a test set of 204 structures from the Protein Data Bank (PDB). AutoDock and FlexX show a highly diverse redocking accuracy at the different complexes which assures again the usefulness of taking several docking algorithms into account. With the combined docking the number of complexes reproduced below an rmsd of 2.5 A could be raised by 10. AutoxX had a strong positive effect on several targets. The highest performance increase could be found when redocking 20 protein-ligand complexes of alpha-thrombin, plasmepsin, neuraminidase, and d-xylose isomerase. A decrease was found for gamma-chymotrypsin. The results show that--applied to the right target-AutoxX can improve the docking performance compared to AutoDock and FlexX alone.

Interaction of carboxyl-terminal peptides of cytosolic-tail of apactin with PDZ domains of NHERF/EBP50 and PDZK-1/CAP70

The C-terminal PDZ-binding motifs are required for polarized apical/basolateral localization of many membrane proteins. Ezrin-radixin-moesin (ERM) proteins regulate the organization and function of specific cortical structures in polarized epithelial cells by connecting filamentous (F)-actin to plasma membrane proteins through EBP50. Previous work showed that the membrane phosphoprotein apactin (an 80-kDa type I membrane protein derived from pro-Muclin) is associated with the acinar cell apical actin cytoskeleton and that this association is modulated by changes in the phosphorylation state of the apactin cytosolic tail. The carboxyl-terminal amino acids of apactin (-STKL-COOH) are predicted to form a type I PDZ-binding domain, similar to that of CFTR (-DTRL-COOH). Pairwise sequence comparison between NHERF/EBP50 and PDZK1/CAP70 PDZ domains reveals significant identity among the 83 amino-acid residues (12-92) of EBP50 and CAP70 (241-323), which are involved in the interaction with the carboxyl-terminal peptides (STKL-COOH and phosphomimetics) of apactin. Hence, the specificity and affinity of interactions are identical between them, which is corroborated with the two hybrid results. Substitution of all the four-carboxyl-terminal amino acids in the wild type to Ala reduces the interaction. Only the carbonyl oxygen and amide nitrogen of Ala are found to be involved in hydrogen bonding. Further, truncation of the wild carboxyl-terminal peptide to RGQPP-COOH, showed very low affinity of interaction with PDZ1 domain. Only the atom O(epsilon1) of Gln-2 hydrogen bonds with N(epsilon2) of His72 of PDZ domain. Ser-3 amino acid in wild type apactin protein (STKL-COOH) is not involved in hydrogen bonding with PDZ1 domain. However, substitution of Ser-3 to Asp-3 in PDTKL-COOH peptide increases the affinity of interaction of PDTKL-COOH with PDZ1 domain. Thus, carboxyl-terminal Asp(D) -3, Thr(T) -2, Lys(K) -1 and Leu(L) 0 are involved in numerous interactions with PDZ1 domains of NHERF/EBP50 and PDZK1/CAP70.