SDOVS: A solvent dipole ordering‐based method for virtual screening

We previously reported that solvent dipole ordering (SDO) at the ligand binding site of a protein indicates an outline of the preferred shape and binding pose of the ligands. We suggested that SDO‐mimetic pseudo‐molecules that mimic the 3D shape of the SDO region could be used as molecular queries with a shape similarity matching method in virtual screening. In this work, a virtual screening method based on SDO, named SDOVS, was proposed. This method was applied to virtual screening of ligands for four typical drug target proteins and the performance compared with that of FRED (well‐known rigid docking method); the efficiency of SDOVS was demonstrated to be better than FRED. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from‐scratch construction of molecules is not limited to compounds in pre‐existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X‐ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug‐like compounds (generic libraries), and (3) application to a challenging protein‐protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.     

ReverseScreen3D: a structure-based ligand matching method to identify protein targets

Ligand promiscuity, which is now recognized as an extremely common phenomenon, is a major underlying cause of drug toxicity. We have developed a new reverse virtual screening (VS) method called ReverseScreen3D, which can be used to predict the potential protein targets of a query compound of interest. The method uses a 2D fingerprint-based method to select a ligand template from each unique binding site of each protein within a target database. The target database contains only the structurally determined bioactive conformations of known ligands. The 2D comparison is followed by a 3D structural comparison to the selected query ligand using a geometric matching method, in order to prioritize each target binding site in the database. We have evaluated the performance of the ReverseScreen2D and 3D methods using a diverse set of small molecule protein inhibitors known to have multiple targets, and have shown that they are able to provide a highly significant enrichment of true targets in the database. Furthermore, we have shown that the 3D structural comparison improves early enrichment when compared with the 2D method alone, and that the 3D method performs well even in the absence of 2D similarity to the template ligands. By carrying out further experimental screening on the prioritized list of targets, it may be possible to determine the potential targets of a new compound or determine the off-targets of an existing drug. The ReverseScreen3D method has been incorporated into a Web server, which is freely available at http://www.modelling.leeds.ac.uk/ReverseScreen3D .     

Approaches to solving the rigid receptor problem by identifying a minimal set of flexible residues during ligand docking

BACKGROUND: Using fixed receptor sites derived from high-resolution crystal structures in structure-based drug design does not properly account for ligand-induced enzyme conformational change and imparts a bias into the discovery and design of novel ligands. We sought to facilitate the design of improved drug leads by defining residues most likely to change conformation, and then defining a minimal manifold of possible conformations of a target site for drug design based on a small number of identified flexible residues. RESULTS: The crystal structure of thymidylate synthase from an important pathogenic target Pneumocystis carinii (PcTS) bound to its substrate and the inhibitor, BW1843U89, is reported here and reveals a new conformation with respect to the structure of PcTS bound to substrate and the more conventional antifolate inhibitor, CB3717. We developed an algorithm for determining which residues provide 'soft spots' in the protein, regions where conformational adaptation suggests possible modifications for a drug lead that may yield higher affinity. Remodeling the active site of thymidylate synthase with new conformations for only three residues that were identified with this algorithm yields scores for ligands that are compatible with experimental kinetic data. CONCLUSIONS: Based on the examination of many protein/ligand complexes, we develop an algorithm (SOFTSPOTS) for identifying regions of a protein target that are more likely to accommodate plastically to regions of a drug molecule. Using these indicators we develop a second algorithm (PLASTIC) that provides a minimal manifold of possible conformations of a protein target for drug design, reducing the bias in structure-based drug design imparted by structures of enzymes co-crystallized with inhibitors.     

Drug screening of pharmaceutical discovery compounds by micro-size exclusion chromatography/mass spectrometry.

Micro-size exclusion chromatography coupled with capillary liquid chromatography (capLC) and mass spectrometry (MS) provides a rapid and simple approach to the preliminary screening of active ligands toward a specific target macromolecule. In this study, the effectiveness of this technique is demonstrated by a number of small molecule ligands with known binding affinities towards the protein target. All ligands were incubated together with a target protein under native conditions. Separation was then achieved by microcentrifugation where the high molecular weight (MW) compounds were selectively passed through the size-exclusion material. The retained low MW compounds were then recovered and analyzed by capLC/MS. The absence of the ligand indicated strong affinity towards the target, while ligand detection indicated inactivity. This assay demonstrated the drugs that were acting as strong inhibitors of Co-PDF from those showing to be comparatively inactive. The relative binding rank order of the drugs towards Co-PDF was also determined. The results were validated by a corresponding set of control experiments in which the target molecules were excluded from the process. In principle, high-throughput micro-size exclusion chromatography, coupled with capLC/MS, offers a powerful technique as a preliminary screen in determining both the strong binding affinity and the relative affinity rank ordering of ligands towards a specific target macromolecule, and is complementary with other analytical drug screening techniques.     

Synthesis and screening of peptoid arrays on cellulose membranes

Rapid synthesis and screening of compound libraries enables the accelerated identification of novel protein ligands in order to support processes like analysis of protein interactions, drug target discovery or lead structure discovery. SPOT synthesis—a well established method for the rapid preparation of peptide arrays—has recently been extended to the field of nonpeptides. In this contribution we report on the systematic evaluation of the SPOT technique for the assembly of N-alkylglycine (peptoid) library arrays. In the course of this investigation bromoacetic acid 2,4-dinitrophenylester (1a) was identified to be the most suited agent for bromoacetylation in terms of yield and N-selectivity enabling straightforward submonomer synthesis on hydroxy-group rich cellulose membranes. The potential of this method for the rapid identification of novel nonpeptidic protein ligands was demonstrated by synthesis and screening of a library consisting of 8000 peptoids and peptomers (i.e. their hybrids with α-substituted amino acids) allowing the identification of micromolar ligands for the monoclonal antibody Tab-2.     

TINS, target immobilized NMR screening: an efficient and sensitive method for ligand discovery

We propose a ligand screening method, called TINS (target immobilized NMR screening), which reduces the amount of target required for the fragment-based approach to drug discovery. Binding is detected by comparing 1D NMR spectra of compound mixtures in the presence of a target immobilized on a solid support to a control sample. The method has been validated by the detection of a variety of ligands for protein and nucleic acid targets (K(D) from 60 to 5000 muM). The ligand binding capacity of a protein was undiminished after 2000 different compounds had been applied, indicating the potential to apply the assay for screening typical fragment libraries. TINS can be used in competition mode, allowing rapid characterization of the ligand binding site. TINS may allow screening of targets that are difficult to produce or that are insoluble, such as membrane proteins.     

Transplant-insert-constrain-relax-assemble (TICRA): protein-ligand complex structure modeling and application to kinases

We introduce TICRA (transplant-insert-constrain-relax-assemble), a method for modeling the structure of unknown protein-ligand complexes using the X-ray crystal structures of homologous proteins and ligands with known activity. We present results from modeling the structures of protein kinase-inhibitor complexes using p38 and Lck as examples. These examples show that the TICRA method may be used prospectively to create and refine models for protein kinase-inhibitor complexes with an overall backbone rmsd of less than 0.75 ? for the kinase domain, when compared to published X-ray crystal structures. Further refinement of the models of the kinase domains of p38 and Lck in complex with their cognate ligands from the published crystal structures was able to improve the rmsd's of the model complexes to below 0.5 ?. Our results show that TICRA is a useful approach to the problem of structure-based drug design in cases where little structural information is available for the target proteins and the binding mode of active compounds is unknown.     

A Combination of Spin Diffusion Methods for the Determination of Protein–Ligand Complex Structural Ensembles

Structure‐based drug design (SBDD) is a powerful and widely used approach to optimize affinity of drug candidates. With the recently introduced INPHARMA method, the binding mode of small molecules to their protein target can be characterized even if no spectroscopic information about the protein is known. Here, we show that the combination of the spin‐diffusion‐based NMR methods INPHARMA, trNOE, and STD results in an accurate scoring function for docking modes and therefore determination of protein–ligand complex structures. Applications are shown on the model system protein kinase A and the drug targets glycogen phosphorylase and soluble epoxide hydrolase (sEH). Multiplexing of several ligands improves the reliability of the scoring function further. The new score allows in the case of sEH detecting two binding modes of the ligand in its binding site, which was corroborated by X‐ray analysis.     

A general technique to rank protein-ligand binding affinities and determine allosteric versus direct binding site competition in compound mixtures

To realize the full potential of combinatorial chemistry-based drug discovery, generic and efficient tools must be developed that apply the strengths of diversity-oriented chemical synthesis to the identification and optimization of lead compounds for disease-associated protein targets. We report an affinity selection-mass spectrometry (AS-MS) method for protein-ligand affinity ranking and the classification of ligands by binding site. The method incorporates the following steps: (1) an affinity selection stage, where protein-binding compounds are selected from pools of ligands in the presence of varying concentrations of a competitor ligand, (2) a first chromatography stage to separate unbound ligands from protein-ligand complexes, and (3) a second chromatography stage to dissociate the ligands from the complexes for identification and quantification by MS. The ability of the competitor ligand to displace a target-bound library member, as measured by MS, reveals the binding site classification and affinity ranking of the mixture components. The technique requires no radiolabel incorporation or direct biochemical assay, no modification or immobilization of the compounds or target protein, and all reaction components, including any buffers or cofactors required for protein stability, are free in solution. We demonstrate the method for several compounds of wide structural variety against representatives of the most important protein classes in contemporary drug discovery, including novel ATP-competitive and allosteric inhibitors of the Akt-1 (PKB) and Zap-70 kinases, and previously undisclosed antagonists of the M(2) muscarinic acetylcholine receptor, a G-protein coupled receptor (GPCR). The theoretical basis of the technique is analyzed mathematically, allowing quantitative estimation of binding affinities and, in the case of allosteric interaction, absolute determination of binding cooperativity. The method is readily applicable to high-throughput screening hit triage, combinatorial library-based affinity optimization, and developing structure-activity relationships among multiple ligands to a given receptor.     

Detection of small-molecule enzyme inhibitors with peptides isolated from phage-displayed combinatorial peptide libraries

BACKGROUND: The rapidly expanding list of pharmacologically important targets has highlighted the need for ways to discover new inhibitors that are independent of functional assays. We have utilized peptides to detect inhibitors of protein function. We hypothesized that most peptide ligands identified by phage display would bind to regions of biological interaction in target proteins and that these peptides could be used as sensitive probes for detecting low molecular weight inhibitors that bind to these sites. RESULTS: We selected a broad range of enzymes as targets for phage display and isolated a series of peptides that bound specifically to each target. Peptide ligands for each target contained similar amino acid sequences and competition analysis indicated that they bound one or two sites per target. Of 17 peptides tested, 13 were found to be specific inhibitors of enzyme function. Finally, we used two peptides specific for Haemophilus influenzae tyrosyl-tRNA synthetase to show that a simple binding assay can be used to detect small-molecule inhibitors with potencies in the micromolar to nanomolar range. CONCLUSIONS: Peptidic surrogate ligands identified using phage display are preferentially targeted to a limited number of sites that inhibit enzyme function. These peptides can be utilized in a binding assay as a rapid and sensitive method to detect small-molecule inhibitors of target protein function. The binding assay can be used with a variety of detection systems and is readily adaptable to automation, making this platform ideal for high-throughput screening of compound libraries for drug discovery.     

Structural e-bioinformatics and drug design

Nowadays the in silico scenario for drug design is totally dependent on structural biology and structural bioinformatics. A myriad of free bioinformatics applications and services have been posted on the web. This mini-review mentions web sites that are useful in structure-based drug design. The information is given in a logical manner, following the drug design process i.e. characterization of a protein target, modelling the protein using sequence homology, optimization of the protein structure and finally docking of small ligands into the active site.     

Site-Identification by Ligand Competitive Saturation (SILCS) assisted pharmacophore modeling

Database screening using receptor-based pharmacophores is a computer-aided drug design technique that uses the structure of the target molecule (i.e. protein) to identify novel ligands that may bind to the target. Typically receptor-based pharmacophore modeling methods only consider a single or limited number of receptor conformations and map out the favorable binding patterns in vacuum or with a limited representation of the aqueous solvent environment, such that they may suffer from neglect of protein flexibility and desolvation effects. Site-Identification by Ligand Competitive Saturation (SILCS) is an approach that takes into account these, as well as other, properties to determine 3-dimensional maps of the functional group-binding patterns on a target receptor (i.e. FragMaps). In this study, a method to use the FragMaps to automatically generate receptor-based pharmacophore models is presented. It converts the FragMaps into SILCS pharmacophore features including aromatic, aliphatic, hydrogen-bond donor and acceptor chemical functionalities. The method generates multiple pharmacophore hypotheses that are then quantitatively ranked using SILCS grid free energies. The pharmacophore model generation protocol is validated using three different protein targets, including using the resulting models in virtual screening. Improved performance and efficiency of the SILCS derived pharmacophore models as compared to published docking studies, as well as a recently developed receptor-based pharmacophore modeling method is shown, indicating the potential utility of the approach in rational drug design.     

Multiple ligand detection and affinity measurement by ultrafiltration and mass spectrometry analysis applied to fragment mixture screening

Binding affinity of a small molecule drug candidate to a therapeutically relevant biomolecular target is regarded the first determinant of the candidate's efficacy. Although the ultrafiltration-LC/MS (UF-LC/MS) assay enables efficient ligand discovery for a specific target from a mixed pool of compounds, most previous analysis allowed for relative affinity ranking of different ligands. Moreover, the reliability of affinity measurement for multiple ligands with UF-LC/MS has hardly been strictly evaluated. In this study, we examined the accuracy of K_d determination through UF-LC/MS by comparison with classical ITC measurement. A single-point K_d calculation method was found to be suitable for affinity measurement of multiple ligands bound to the same target when binding competition is minimized. A second workflow based on analysis of the unbound fraction of compounds was then developed, which simplified sample preparation as well as warranted reliable ligand discovery. The new workflow implemented in a fragment mixture screen afforded rapid and sensitive detection of low-affinity ligands selectively bound to the RNA polymerase NS5B of hepatitis C virus. More importantly, ligand identification and affinity measurement for mixture-based fragment screens by UF-LC/MS were in good accordance with single ligand evaluation by conventional SPR analysis. This new approach is expected to become a valuable addition to the arsenal of high-throughput screening techniques for fragment-based drug discovery.     

Stalis: A Computational Method for Template-Based Ab Initio Ligand Design

Proteins interact with small molecules through specific molecular recognition, which is central to essential biological functions in living systems. Therefore, understanding such interactions is crucial for basic sciences and drug discovery. Here, we present S tructure t emplate-based a b initio li gand design s olution (Stalis), a knowledge-based approach that uses structure templates from the Protein Data Bank libraries of whole ligands and their fragments and generates a set of molecules (virtual ligands) whose structures represent the pocket shape and chemical features of a given target binding site. Our benchmark performance evaluation shows that ligand structure-based virtual screening using virtual ligands from Stalis outperforms a receptor structure-based virtual screening using AutoDock Vina, demonstrating reliable overall screening performance applicable to computational high-throughput screening. However, virtual ligands from Stalis are worse in recognizing active compounds at the small fraction of a rank-ordered list of screened library compounds than crystal ligands, due to the low resolution of the virtual ligand structures. In conclusion, Stalis can facilitate drug discovery research by designing virtual ligands that can be used for fast ligand structure-based virtual screening. Moreover, Stalis provides actual three-dimensional ligand structures that likely bind to a target protein, enabling to gain structural insight into potential ligands. Stalis can be an efficient computational platform for high-throughput ligand design for fundamental biological study and drug discovery research at the proteomic level. © 2019 Wiley Periodicals, Inc.     

Arylfluorosulfate‐Based Electrophiles for Covalent Protein Labeling: A New Addition to the Arsenal

Selective covalent modification of a targeted protein is a powerful tool in chemical biology and drug discovery, with applications ranging from identification and characterization of proteins and their functions to the development of targeted covalent inhibitors. Most covalent ligands contain an affinity motif and an electrophilic warhead that reacts with a nucleophilic residue of the targeted protein. Because the electrophilic warhead is prone to react and modify off‐target nucleophiles, its reactivity should be balanced carefully to maximize target selectivity. Arylfluorosulfates have recently emerged as latent electrophiles for selective labeling of context‐specific tyrosine and lysine residues in protein pockets. Here, we review the recent but intense introduction of arylfluorosulfates into the arsenal of available warheads for selective covalent modification of proteins. We highlight the untapped potential of this functional group for use in chemical biology and drug discovery.     

Electrospray ionization mass spectrometry as a tool for determination of drug binding sites to human serum albumin by noncovalent interaction

Most proteins in blood plasma bind ligands. Human serum albumin (HSA) is the main transport protein with a very high capacity for binding of endogenous and exogenous compounds in plasma. Many pharmacokinetic properties of a drug depend on the level of binding to plasma proteins. This work reports studies of noncovalent interactions by means of nanoelectrospray ionization mass spectrometry (nanoESI-MS) for determination of the specific binding of selected drug candidates to HSA. Warfarin, iopanoic acid and digitoxin were chosen as site-specific probes that bind to the main sites of HSA. Two drug candidates and two known binders to HSA were analyzed using a competitive approach. The drugs were incubated with the target protein followed by addition of site-specific probes, one at a time. The drug candidates showed predominant affinity to site I (warfarin site). Naproxen and glyburide showed affinity to both sites I and II. The advantages of nanoESI-MS for these studies are the sensitivity, the absence of labeled molecules and the short method development time.     

Improvement of Targeted Gene Delivery to Human Cancer Cells by a Novel Trifunctional Crosslinker

A facile method for the construction of an immunoconjugate which displays targeting ligands, such as antibody fragments, with a high density is reported. For this purpose, we synthesized a novel trifunctional crosslinking reagent. By the use of this reagent, ligands targeting the specific cell can be displayed on the surface of the drug carrier with a high density. In this study, we display HER2 (human epidermal growth‐factor receptor‐2) binding ligands on branched polyethylenimine (PEI), which can form polyplexes with plasmid DNA. Kinetic analysis of the binding to the extracellular domain of HER2 show the PEI displaying a high density of ligands binds to the target more strongly compared to the PEI displaying ligands at a low density. The increased density of HER2 ligands displayed on the gene carrier contributes to the improved transfection efficiency. This approach can be applied to other drug delivery systems, including liposome, micelle, and so on.