Weak affinity chromatography as a new approach for fragment screening in drug discovery

Fragment-based drug design (FBDD) is currently being implemented in drug discovery, creating a demand for developing efficient techniques for fragment screening. Due to the intrinsic weak or transient binding of fragments (mM–μM in dissociation constant (K_D)) to targets, methods must be sensitive enough to accurately detect and quantify an interaction. This study presents weak affinity chromatography (WAC) as an alternative tool for screening of small fragments. The technology was demonstrated by screening of a selected 23-compound fragment collection of documented binders, mostly amidines, using trypsin and thrombin as model target protease proteins. WAC was proven to be a sensitive, robust, and reproducible technique that also provides information about affinity of a fragment in the range of 1 mM–10 μM. Furthermore, it has potential for high throughput as was evidenced by analyzing mixtures in the range of 10 substances by WAC–MS. The accessibility and flexibility of the technology were shown as fragment screening can be performed on standard HPLC equipment. The technology can further be miniaturized and adapted to the requirements of affinity ranges of the fragment library. All these features of WAC make it a potential method in drug discovery for fragment screening.     

A new strategy for improved secondary screening and lead optimization using high-resolution SPR characterization of compound-target interactions

Biophysical label-free assays such as those based on SPR are essential tools in generating high-quality data on affinity, kinetic, mechanistic and thermodynamic aspects of interactions between target proteins and potential drug candidates. Here we show examples of the integration of SPR with bioinformatic approaches and mutation studies in the early drug discovery process. We call this combination 'structure-based biophysical analysis'. Binding sites are identified on target proteins using information that is either extracted from three-dimensional structural analysis (X-ray crystallography or NMR), or derived from a pharmacore model based on known binders. The binding site information is used for in silico screening of a large substance library (e.g. available chemical directory), providing virtual hits. The three-dimensional structure is also used for the design of mutants where the binding site has been impaired. The wild-type target and the impaired mutant are then immobilized on different spots of the sensor chip and the interactions of compounds with the wild-type and mutant are compared in order to identify selective binders for the binding site of the target protein. This method can be used as a cost-effective alternative to high-throughput screening methods in cases when detailed binding site information is available. Here, we present three examples of how this technique can be applied to provide invaluable data during different phases of the drug discovery process.     

The ribosomal A-site as an inspiration for the design of RNA binders

The specific binding of aminoglycoside antibiotics to the bacterial ribosomal decoding site (A-site) has inspired the study of RNA-small molecules interactions and the search for novel RNA binders. Among the numerous RNA targets studied so far, the A-site holds a unique place. It is among the few truly validated RNA targets for which naturally occurring ligands have been discovered as "cognate" binders. In addition, due to its encapsulating architecture, the A-site is a more discriminating RNA target when compared to other RNA sequences. Previous observations and current challenges for the designers of potent and specific RNA binders are discussed.     

Discovery of selective small-molecule CD80 inhibitors

Protein-protein interactions are widely found in biological systems controlling diverse cellular events. Because these interactions are implicated in many diseases such as autoimmunity and cancer, regulation of protein-protein interactions provides ideal targets for drug intervention. The CD80-CD28 costimulatory pathway plays a critical role in regulation of the immune response and thus constitutes an attractive target for therapeutic manipulation of autoimmune diseases. The objective of this study is to identify small compounds disrupting these pivotal protein-protein interactions. Compounds that specifically blocked binding of CD80 to CD28 were identified using a strategy involving a cell-based scintillation proximity assay as the initial step. Secondary screening (e.g., by analyzing the direct binding of these compounds to the target immobilized on a biosensor surface) revealed that these compounds are highly selective CD80 binders. Screening of structurally related derivatives led to the identification of the chemical features required for inhibition of the CD80-CD28 interaction. In addition, the optimization process led to a 10-fold increase in binding affinity of the CD80 inhibitors. Using this approach, the authors identify low-molecular-weight compounds that specifically and with high potency inhibit the interaction between CD80 and CD28. These compounds serve as promising starting points for further development of CD80 inhibitors as potential immunomodulatory drugs.     

The binding affinities of proteins interacting with the PDZ domain of PICK1

Protein interacting with C kinase (PICK1) is well conserved throughout evolution and plays a critical role in synaptic plasticity by regulating the trafficking and posttranslational modification of its interacting proteins. PICK1 contains a single PSD95/DlgA/Zo-1 (PDZ) protein-protein interaction domain, which is promiscuous and shown to interact with over 60 proteins, most of which play roles in neuronal function. Several reports have suggested the role of PICK1 in disorders such as epilepsy, pain, brain trauma and stroke, drug abuse and dependence, schizophrenia and psychosis. Importantly, lead compounds that block PICK1 interactions are also now becoming available. Here, a new modeling approach was developed to investigate binding affinities of PDZ interactions. Using these methods, the binding affinities of all major PICK1 interacting proteins are reported and the effects of PICK1 mutations on these interactions are described. These modeling methods have important implications in defining the binding properties of proteins interacting with PICK1 as well as the general structural requirements of PDZ interactions. The study also provides modeling methods to support in the drug design of ligands for PDZ domains, which may further aid in development of the family of PDZ domains as a drug target.     

Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity

Isothermal titration calorimetry (ITC) is a useful tool for understanding the complete thermodynamic picture of a binding reaction. In biological sciences, macromolecular interactions are essential in understanding the machinery of the cell. Experimental conditions, such as buffer and temperature, can be tailored to the particular binding system being studied. However, careful planning is needed since certain ligand and macromolecule concentration ranges are necessary to obtain useful data. Concentrations of the macromolecule and ligand need to be accurately determined for reliable results. Care also needs to be taken when preparing the samples as impurities can significantly affect the experiment. When ITC experiments, along with controls, are performed properly, useful binding information, such as the stoichiometry, affinity and enthalpy, are obtained. By running additional experiments under different buffer or temperature conditions, more detailed information can be obtained about the system. A protocol for the basic setup of an ITC experiment is given.     

The use of peptides in Diogenesis: a novel approach to drug discovery and phenomics

The Diogenesis Process is an integrated drug discovery platform that allows target validation, partner identification, and the identification of small molecule drug candidates for protein:protein interactions. Diogenesis utilizes the well-established methods of peptide display, synthetic and recombinant peptide production, in vitro biochemical and cell-based testing to form a universal drug discovery engine with distinct advantages over competing protocols. The process creates a library of diverse peptides, and selects rare and unique binders that identify and simplify surface "hot spots" on protein targets through which target activity can be regulated. In many cases, these peptide "Surrogates" have the minimal sequence and structural information needed to induce a change in the biological activity of the target; in pharmacological terms, only after inducing agonism or antagonism. The use of Surrogates in hot spot identification also allows subdivision of rather large surface domains into smaller domains that alone, or in combination with another subdomain, offers sufficient territory for modification of target activity. These Surrogates, in turn, provide the necessary ligands to develop appropriate Site Directed Assays (SDAs) for each essential subdomain. The SDAs provide the screening mode for finding competitive small molecules by high throughput screening. The other arm of the Diogenesis system is an application in the new area of "Phenomics." This part of the discovery process is a form of phenotypic analysis of genomic information that has also been referred to as "functional" genomics. Phenomics, done via the Diogenesis system, uses peptide Surrogates as modifiers of the activity of, and identifiers of the partners of, gene products of known and unknown function. Actually, in many instances, the same Surrogate isolated for use in Phenomics will be used to create SDAs for discovery of small molecule drug candidates. In this simple fashion, the two applications of Diogenesis are integrated to provide savings in research time and money.     

Non‐interacting surface solvation and dynamics in protein–protein interactions

Protein–protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure‐based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein–protein binding, even for simple lock‐and‐key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein–protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein–protein surfaces. We compare properties of the interface, rim, and non‐interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non‐interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non‐interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein–protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein–protein complexes from unintended protein–protein interactions. Proteins 2015; 83:445–458. © 2014 Wiley Periodicals, Inc.     

Survey of phosphorylation near drug binding sites in the Protein Data Bank (PDB) and their effects

While it is currently estimated that 40 to 50% of eukaryotic proteins are phosphorylated, little is known about the frequency and local effects of phosphorylation near pharmaceutical inhibitor binding sites. In this study, we investigated how frequently phosphorylation may affect the binding of drug inhibitors to target proteins. We examined the 453 non‐redundant structures of soluble mammalian drug target proteins bound to inhibitors currently available in the Protein Data Bank (PDB). We cross‐referenced these structures with phosphorylation data available from the PhosphoSitePlus database. Three hundred twenty‐two of 453 (71%) of drug targets have evidence of phosphorylation that has been validated by multiple methods or labs. For 132 of 453 (29%) of those, the phosphorylation site is within 12 Å of the small molecule‐binding site, where it would likely alter small molecule binding affinity. We propose a framework for distinguishing between drug‐phosphorylation site interactions that are likely to alter the efficacy of drugs versus those that are not. In addition we highlight examples of well‐established drug targets, such as estrogen receptor alpha, for which phosphorylation may affect drug affinity and clinical efficacy. Our data suggest that phosphorylation may affect drug binding and efficacy for a significant fraction of drug target proteins. Proteins 2015; 83:25–36. © 2014 Wiley Periodicals, Inc.     

Predicting new molecular targets for rhein using network pharmacology

Background

Drugs can influence the whole biological system by targeting interaction reactions. The existence of interactions between drugs and network reactions suggests a potential way to discover targets. The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of drug-targets in current datasets are validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. Currently, network pharmacology has used in identifying potential drug targets to predicting the spread of drug activity and greatly contributed toward the analysis of biological systems on a much larger scale than ever before.

Methods

In this article, we present a computational method to predict targets for rhein by exploring drug-reaction interactions. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for drug-target interaction. We used Cytoscape software for prediction rhein-target interactions, to facilitate the drug discovery pipeline.

Results

Results showed that 3 differentially expressed genes confirmed by Cytoscape as the central nodes of the complicated interaction network (99 nodes, 153 edges). Of note, we further observed that the identified targets were found to encompass a variety of biological processes related to immunity, cellular apoptosis, transport, signal transduction, cell growth and proliferation and metabolism.

Conclusions

Our findings demonstrate that network pharmacology can not only speed the wide identification of drug targets but also find new applications for the existing drugs. It also implies the significant contribution of network pharmacology to predict drug targets.     

Encoded self-assembling chemical libraries

The isolation of molecules capable of high-affinity and specific binding to biological targets is a central problem in chemistry, biology and pharmaceutical sciences. Here we describe the use of encoded self-assembling chemical (ESAC) libraries for the facile identification of molecules that bind macromolecular targets. ESAC technology uses libraries of organic molecules linked to individual oligonucleotides that mediate the self-assembly of the library and provide a code associated with each organic molecule. After panning ESAC libraries on the biomolecular target of interest, the 'binding code' of the selected compounds can be 'decoded' by a number of experimental techniques (e.g., hybridization on oligonucleotide microarrays). The potential of this technology was demonstrated by the affinity maturation (>40-fold) of binding molecules to human serum albumin and bovine carbonic anhydrase, leading to binders with dissociation constants in the nanomolar range.     

Differential Role of CYP2E1 Binders and Isoniazid on CYP2E1 Protein Modification in NADPH-dependent Microsomal Oxidative Reactions: Free Radical Scavenging Ability of Isoniazid

We evaluated the effect of "weak" CYP2E1 binders (ethanol, acetone and glycerol) "tight" CYP2E1 binders (4-methylpyrazole, imidazole, isoniazid and pyridine) and CCl 4 (suicide substrate of CYP2E1) on the NADPH-dependent production of microsomal reactive oxygen species (ROS), lipid peroxidation (LPO), and subsequent modification of microsomal and CYP2E1 proteins. The oxidation of 2',7'-dichlorofluorescin diacetate (DCFHDA) was used as an index of formation of microsomal ROS and LPO-derived reactive species. Microsomal LPO was determined by malondialdehyde (MDA) HPLC measurement. Addition of NADPH to rat liver microsomes initiated DCFHDA oxidation and MDA formation, leading to further selective modification of microsomal proteins and proteases-independent degradation of CYP2E1 protein. Iron chelators prevented these processes whereas hydroxyl radical scavengers showed weak effects, suggesting an important role of LPO. Among the tested CYP2E1 binders, only isoniazid strongly inhibited NADPH-dependent DCFHDA oxidation, LPO and modification of microsomal proteins. Other CYP2E1 binders showed weak inhibitory effects of these processes. Concerning NADPH-dependent modification of CYP2E1 protein, all of the tested CYP2E1 binders, except glycerol, prevented this process with a different potency (isoniazid > 4-methylpyrazole=imidazole=pyridine &#100 acetone > ethanol). "Tight" binders were more effective than "weak" binders. The CCl 4 stimulated the DCFHDA oxidation, LPO and CYP2E1 protein modification. Among the tested CYP2E1 binders, only isoniazid effectively scavenged 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radicals. In microsomes isolated from CYP2E1 transfected HepG2 cells, isoniazid inhibited the CYP2E1-dependent DCFHDA oxidation whereas other CYP2E1 binders did not inhibit this reaction although these compounds strongly inhibited CYP2E1 activity. The present study demonstrates that CYP2E1 binders and isoniazid differentially inhibit LPO-catalyzed oxidative modification of CYP2E1 protein in NADPH-dependent microsomal reactions. It seems that CYP2E1 binders protect CYP2E1 from the oxidative modification mainly by binding to the active site of the enzyme, rather than by blocking the reactive species production. The strong protective effect of isoniazid can be attributed to its ability to scavenge free radicals. These effects of CYP2E1 binders are considered to contribute to the regulation of hepatic CYP2E1 protein levels via stabilization of the protein.     

蛋白质- 配体相互作用信息数据库研究进展

研究蛋白质和配体相互作用的结构和亲和力,不仅有助于了解蛋白质的功能,而且对药物研发以及药物作用机制的研究,也具有十 分重要的意义。目前,人们通过人工检索和半自动检索的方式,从文献和蛋白质数据库（Protein Data Bank,PDB）中获得了许多蛋白质- 配体亲和力信息和生物相关配体信息,并构建了许多蛋白质-配体相互作用的信息数据库。对3 个蛋白质-配体亲和力数据库和6 个蛋白质 晶体结构-配体生物相关性数据库进行介绍,并对其主要应用进行简述,希望能为实现高效准确地筛选和设计药物提供一定的帮助。     

Modulating protein-protein interactions with small molecules: the importance of binding hotspots

The modulation of protein-protein interactions (PPIs) by small drug-like molecules is a relatively new area of research and has opened up new opportunities in drug discovery. However, the progress made in this area is limited to a handful of known cases of small molecules that target specific diseases. With the increasing availability of protein structure complexes, it is highly important to devise strategies exploiting homologous structure space on a large scale for discovering putative PPIs that could be attractive drug targets. Here, we propose a scheme that allows performing large-scale screening of all protein complexes and finding putative small-molecule and/or peptide binding sites overlapping with protein-protein binding sites (so-called "multibinding sites"). We find more than 600 nonredundant proteins from 60 protein families with multibinding sites. Moreover, we show that the multibinding sites are mostly observed in transient complexes, largely overlap with the binding hotspots and are more evolutionarily conserved than other interface sites. We investigate possible mechanisms of how small molecules may modulate protein-protein binding and discuss examples of new candidates for drug design.     

AB‐Bind: Antibody binding mutational database for computational affinity predictions

Antibodies (Abs) are a crucial component of the immune system and are often used as diagnostic and therapeutic agents. The need for high‐affinity and high‐specificity antibodies in research and medicine is driving the development of computational tools for accelerating antibody design and discovery. We report a diverse set of antibody binding data with accompanying structures that can be used to evaluate methods for modeling antibody interactions. Our Antibody‐Bind (AB‐Bind) database includes 1101 mutants with experimentally determined changes in binding free energies (ΔΔG) across 32 complexes. Using the AB‐Bind data set, we evaluated the performance of protein scoring potentials in their ability to predict changes in binding free energies upon mutagenesis. Numerical correlations between computed and observed ΔΔG values were low (r = 0.16–0.45), but the potentials exhibited predictive power for classifying variants as improved vs weakened binders. Performance was evaluated using the area under the curve (AUC) for receiver operator characteristic (ROC) curves; the highest AUC values for 527 mutants with |ΔΔG| > 1.0 kcal/mol were 0.81, 0.87, and 0.88 using STATIUM, FoldX, and Discovery Studio scoring potentials, respectively. Some methods could also enrich for variants with improved binding affinity; FoldX and Discovery Studio were able to correctly rank 42% and 30%, respectively, of the 80 most improved binders (those with ΔΔG < −1.0 kcal/mol) in the top 5% of the database. This modest predictive performance has value but demonstrates the continuing need to develop and improve protein energy functions for affinity prediction.     

Advancing Aptamers as Molecular Probes for Cancer Theranostic Applications—The Role of Molecular Dynamics Simulation

Theranostics cover emerging technologies for cell biomarking for disease diagnosis and targeted introduction of drug ingredients to specific malignant sites. Theranostics development has become a significant biomedical research endeavor for effective diagnosis and treatment of diseases, especially cancer. An efficient biomarking and targeted delivery strategy for theranostic applications requires effective molecular coupling of binding ligands with high affinities to specific receptors on the cancer cell surface. Bioaffinity offers a unique mechanism to bind specific target and receptor molecules from a range of non‐targets. The binding efficacy depends on the specificity of the affinity ligand toward the target molecule even at low concentrations. Aptamers are fragments of genetic materials, peptides, or oligonucleotides which possess enhanced specificity in targeting desired cell surface receptor molecules. Aptamer–target binding results from several inter‐molecular interactions including hydrogen bond formation, aromatic stacking of flat moieties, hydrophobic interaction, electrostatic, and van der Waals interactions. Advancements in Systematic Evolution of Ligands by Exponential Enrichment (SELEX) assay has created the opportunity to artificially generate aptamers that specifically bind to desired cancer and tumor surface receptors with high affinities. This article discusses the potential application of molecular dynamics (MD) simulation to advance aptamer‐mediated receptor targeting in targeted cancer therapy. MD simulation offers real‐time analysis of the molecular drivers of the aptamer‐receptor binding and generate optimal receptor binding conditions for theranostic applications. The article also provides an overview of different cancer types with focus on receptor biomarking and targeted treatment approaches, conventional molecular probes, and aptamers that have been explored for cancer cells targeting.     

Optimized Hydrophobic Interactions and Hydrogen Bonding at the Target-Ligand Interface Leads the Pathways of Drug-Designing

Background

Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures. However, it is still poorly understood how the binding parameters associated with these interactions facilitate a drug-lead to recognize a specific target and improve drugs efficacy. To understand this, comprehensive analysis of hydrophobic interactions, hydrogen bonding and binding affinity have been analyzed at the interface of c-Src and c-Abl kinases and 4-amino substituted 1H-pyrazolo [3, 4-d] pyrimidine compounds.

Methodology

In-silico docking studies were performed, using Discovery Studio software modules LigandFit, CDOCKER and ZDOCK, to investigate the role of ligand binding affinity at the hydrophobic pocket of c-Src and c-Abl kinase. Hydrophobic and hydrogen bonding interactions of docked molecules were compared using LigPlot program. Furthermore, 3D-QSAR and MFA calculations were scrutinized to quantify the role of weak interactions in binding affinity and drug efficacy.

Conclusions

The in-silico method has enabled us to reveal that a multi-targeted small molecule binds with low affinity to its respective targets. But its binding affinity can be altered by integrating the conformationally favored functional groups at the active site of the ligand-target interface. Docking studies of 4-amino-substituted molecules at the bioactive cascade of the c-Src and c-Abl have concluded that 3D structural folding at the protein-ligand groove is also a hallmark for molecular recognition of multi-targeted compounds and for predicting their biological activity. The results presented here demonstrate that hydrogen bonding and optimized hydrophobic interactions both stabilize the ligands at the target site, and help alter binding affinity and drug efficacy.     

Transient pockets on XIAP-BIR2: toward the characterization of putative binding sites of small-molecule XIAP inhibitors

Protein-protein interactions are abundant in signal transduction pathways and thus of crucial importance in the regulation of apoptosis. However, designing small-molecule inhibitors for these potential drug targets is very challenging as such proteins often lack well-defined binding pockets. An example for such an interaction is the binding of the anti-apoptotic BIR2 domain of XIAP to the pro-apoptotic caspase-3 that results in the survival of damaged cells. Although small-molecule inhibitors of this interaction have been identified, their exact binding sites on XIAP are not known as its crystal structures reveal no suitable pockets. Here, we apply our previously developed protocol for identifying transient binding pockets to XIAP-BIR2. Transient pockets were identified in snapshots taken during four different molecular dynamics simulations that started from the caspase-3:BIR2 complex or from the unbound BIR2 structure and used water or methanol as solvent. Clustering of these pockets revealed that surprisingly many pockets opened in the flexible linker region that is involved in caspase-3 binding. We docked three known inhibitors into these transient pockets and so determined five putative binding sites. In addition, by docking two inactive compounds of the same series, we show that this protocol is also able to distinguish between binders and nonbinders which was not possible when docking to the crystal structures. These findings represent a first step toward the understanding of the binding of small-molecule XIAP-BIR2 inhibitors on a molecular level and further highlight the importance of considering protein flexibility when designing small-molecule protein-protein interaction inhibitors.     

Structural and energetic insights into sequence-specific interaction in DNA–drug recognition: development of affinity predictor and analysis of binding selectivity

Although the molecular mechanism and thermodynamic profile of a wide variety of chemical agents have been examined intensively in the past decades in terms of specific recognition of their protein receptors, to date the physicochemical nature of DNA–drug recognition and association still remains largely unexplored. The present study focused on understanding the structural basis, energetic landscape, and biological implications underlying the binding of small-molecule ligands to their cognate or non-cognate DNA receptors. First, a new method to capture the structural features of DNA–drug complex architecture was proposed and then used to correlate the extracted features with binding affinity of the complexes. By employing this method, a statistical regression-based predictor was developed to quantitatively evaluate the interaction potency of drug compounds with DNA in a fast and reliable manner. Subsequently, we use the predictor to examine the binding behavior of a number of structure-available, affinity-known DNA–drug complexes as well as a large pool of randomly generated DNA decoys in complex with the same drugs. It was found that (1) as compared with protein–DNA recognition, small-molecule agents have relatively low specificity in selecting their cognate DNA targets from the background of numerous random decoys; (2) the abundance of A–T base pairs in the DNA core motif exhibits a significant positive correlation with the affinity of drug ligand binding to the DNA receptor; and (3) high affinity seems not to be closely related to high selectivity for a DNA-targeting drug, although high-affinity drug entities have a greater possibility of being ranked computationally as top binders. We hope that this work will provide a preliminary insight into the molecular origin of sequence-specific interactions in DNA–drug recognition.