Engineering enzyme specificity using computational design of a defined-sequence library

Engineered biosynthetic pathways have the potential to produce high-value molecules from inexpensive feedstocks, but a key limitation is engineering enzymes with high activity and specificity for new reactions. Here, we developed a method for combining structure-based computational protein design with library-based enzyme screening, in which inter-residue correlations favored by the design are encoded into a defined-sequence library. We validated this approach by engineering a glucose 6-oxidase enzyme for use in a proposed pathway to convert D-glucose into D-glucaric acid. The most active variant, identified after only one round of diversification and screening of only 10,000 wells, is approximately 400-fold more active on glucose than is the wild-type enzyme. We anticipate that this strategy will be broadly applicable to the discovery of new enzymes for engineered biological pathways.     

Integrating pharmacophore mapping,virtual screening,density functional theory,molecular simulation towards the discovery of novel apolipoprotein (apoE ε4) inhibitors

AimAn integrated protocol of virtual screening involving molecular docking, pharmacophore probing, and simulations was established to identify small novel molecules targeting crucial residues involved in the variant apoE ε4 to mimic its behavior as apoE2 thereby eliminating the amyloid plaque accumulation and facilitating its clearance.Materials and MethodsAn excellent ligand-based and structure-based approach was made to identify common pharmacophoric features involving structure-based docking with respect to apoE ε4 leading to the development of apoE ε4 inhibitors possessing new scaffolds. An effort was made to design multiple-substituted triazine derivatives series bearing a novel scaffold. A structure-based pharmacophore mapping was developed to explore the binding sites of apoE ε4 which was taken into consideration. Subsequently, virtual screening, ADMET, DFT searches were at work to narrow down the proposed hits to be forwarded as a potential drug likes candidates. Further, the binding patterns of the best-proposed hits were studied and were forwarded for molecular dynamic simulations of 10 ns for its structural optimization.ResultsSelectivity profile for the most promising candidates was studied, revealing significantly C13 and C15 to be the most potent compounds. The proposed hits can be forwarded for further study against apoE ε4 involved in neurological disorder Alzheimer’s.     

Three-dimensional pharmacophore modeling of liver-X receptor agonists

High cholesterol levels contribute to hyperlipidemia. Liver X receptors (LXRs) are the drug targets. LXRs regulate the cholesterol absorption, biosynthesis, transportation, and metabolism. Novel agonists of LXR, especially LXRβ, are attractive solutions for treating hyperlipidemia. In order to discover novel LXRβ agonists, a three-dimensional pharmacophore model was built based upon known LXRβ agonists. The model was validated with a test set, a virtual screening experiment, and the FlexX docking approach. Results show that the model is capable of predicting a LXRβ agonist activity. Ligand-based virtual screening results can be refined by cross-linking by structure-based approaches. This is because two ligands that are mapped in the same way to the same pharmacophore model may have significantly different binding behaviors in the receptor's binding pocket. This paper reports our approach to identify reliable pharmacophore models through combining both ligand- and structure-based approaches.     

Ligand design by a combinatorial approach based on modeling and experiment: application to HLA-DR4

Combinatorial synthesis and large scale screening methods are being used increasingly in drug discovery, particularly for finding novel lead compounds. Although these "random" methods sample larger areas of chemical space than traditional synthetic approaches, only a relatively small percentage of all possible compounds are practically accessible. It is therefore helpful to select regions of chemical space that have greater likelihood of yielding useful leads. When three-dimensional structural data are available for the target molecule this can be achieved by applying structure-based computational design methods to focus the combinatorial library. This is advantageous over the standard usage of computational methods to design a small number of specific novel ligands, because here computation is employed as part of the combinatorial design process and so is required only to determine a propensity for binding of certain chemical moieties in regions of the target molecule. This paper describes the application of the Multiple Copy Simultaneous Search (MCSS) method, an active site mapping and de novo structure-based design tool, to design a focused combinatorial library for the class II MHC protein HLA-DR4. Methods for the synthesizing and screening the computationally designed library are presented; evidence is provided to show that binding was achieved. Although the structure of the protein-ligand complex could not be determined, experimental results including cross-exclusion of a known HLA-DR4 peptide ligand (HA) by a compound from the library. Computational model building suggest that at least one of the ligands designed and identified by the methods described binds in a mode similar to that of native peptides.     

Structure-based pharmacophore design and virtual screening for novel angiotensin converting enzyme 2 inhibitors

The metallopeptidase Angiotensin Converting Enzyme (ACE) is an important drug target for the treatment of hypertension, heart, kidney, and lung disease. Recently, a close and unique human ACE homologue termed ACE2 has been identified and found to be an interesting new cardiorenal disease target. With the recently resolved inhibitor-bound ACE2 crystal structure available, we have attempted a structure-based approach to identify novel potent and selective inhibitors. Computational approaches focus on pharmacophore-based virtual screening of large compound databases. Selectivity was ensured by initial screening for ACE inhibitors within an internal database and the Derwent World Drug Index, which could be reduced to zero false positives and 0.1% hit rate, respectively. An average hit reduction of 0.44% was achieved with a five feature hypothesis, searching approximately 3.8 million compounds from various commercial databases. Seventeen compounds were selected based on high fit values as well as diverse structure and subjected to experimental validation in a bioassay. We show that all compounds displayed an inhibitory effect on ACE2 activity, the six most promising candidates exhibiting IC50 values in the range of 62-179 microM.     

Hot-spots-guided receptor-based pharmacophores (HS-Pharm): a knowledge-based approach to identify ligand-anchoring atoms in protein cavities and prioritize structure-based pharmacophores

The design of biologically active compounds from ligand-free protein structures using a structure-based approach is still a major challenge. In this paper, we present a fast knowledge-based approach (HS-Pharm) that allows the prioritization of cavity atoms that should be targeted for ligand binding, by training machine learning algorithms with atom-based fingerprints of known ligand-binding pockets. The knowledge of hot spots for ligand binding is here used for focusing structure-based pharmacophore models. Three targets of pharmacological interest (neuraminidase, beta2 adrenergic receptor, and cyclooxygenase-2) were used to test the evaluated methodology, and the derived structure-based pharmacophores were used in retrospective virtual screening studies. The current study shows that structure-based pharmacophore screening is a powerful technique for the fast identification of potential hits in a chemical library, and that it is a valid alternative to virtual screening by molecular docking.     

Thermodynamic Feasibility of Enzymatic Reduction of Carbon Dioxide to Methanol

Production of valuable chemicals from CO₂ is highly desired for the purpose of controlling CO₂ emission. Toward that, enzymatic reduction of CO₂ for the production of methanol appeared to be especially promising. That has been achieved by reversing the biological metabolic reaction pathways. However, hitherto, there has been little discussion on the thermodynamic feasibility of reversing such biological pathways. The reported yields of methanol have been generally very low under regular reaction conditions preferred by naturally evolved enzymes. The current work examines the sequential enzymatic conversion of CO₂ into methanol from a thermodynamic point of view with a focus on factors that control the reaction equilibrium. Our analysis showed that the enzymatic conversion of carbon dioxide is highly sensitive to the pH value of the reaction solution and, by conducting the reactions at low pHs (such as pH 6 or 5) and ionic strength, it is possible to shift the biological methanol metabolic reaction equilibrium constants significantly (by a factor of several orders of magnitude) to favor the synthesis of methanol.     

Acoustic deposition with NIMS as a high-throughput enzyme activity assay

Mass spectrometry (MS)-based enzyme assay has been shown to be a useful tool for screening enzymatic activities from environmental samples. Recently, reported approaches for high-specificity multiplexed characterization of enzymatic activities allow for providing detailed information on the range of enzymatic products and monitoring multiple enzymatic reactions. However, the throughput has been limited by the slow liquid-liquid handling and manual analysis. This rapid communication demonstrates the integration of acoustic sample deposition with nanostructure initiator mass spectrometry (NIMS) imaging to provide reproducible measurements of multiple enzymatic reactions at a throughput that is tenfold to 100-fold faster than conventional MS-based enzyme assay. It also provides a simple means for the visualization of multiple reactions and reaction pathways.     

Development of purely structure-based pharmacophores for the topoisomerase I-DNA-ligand binding pocket

Purely structure-based pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.     

Efficient mining of myxobacterial metabolite profiles enabled by liquid chromatography-electrospray ionisation-time-of-flight mass spectrometry and compound-based principal component analysis

Bacteria producing secondary metabolites are an important source of natural products with highly diverse structures and biological activities. Developing methods to efficiently mine procaryotic secondary metabolomes for the presence of potentially novel natural products is therefore of considerable interest. Modern mass spectrometry-coupled liquid chromatography can effectively capture microbial metabolic diversity with ever improving sensitivity and accuracy. In addition, computational and statistical tools increasingly enable the targeted analysis and exploration of information-rich LC-MS datasets.In this article, we describe the use of such techniques for the characterization of myxobacterial secondary metabolomes. Using accurate mass data from high-resolution ESI-TOF measurements, target screening has facilitated the rapid identification of known myxobacterial metabolites in extracts from nine Myxococcus species. Furthermore, principal component analysis (PCA), implementing an advanced compound-based bucketing approach, readily revealed the presence of further compounds which contribute to variation among the metabolite profiles under investigation. The generation of molecular formulae for putative novel compounds with high confidence due to evaluation of both exact mass position and isotopic pattern, is exemplified as an important key for de-replication and prioritization of candidates for further characterization.     

Rapid Identification of Potential Drug Candidates from Multi-Million Compounds’ Repositories. Combination of 2D Similarity Search with 3D Ligand/Structure Based Methods and In Vitro Screening

Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost-effective approach in early drug discovery. If structures of active compounds are available, rapid 2D similarity search can be performed on multimillion compounds’ databases. This approach can be combined with physico-chemical parameter and diversity filtering, bioisosteric replacements, and fragment-based approaches for performing a first round biological screening. Our objectives were to investigate the combination of 2D similarity search with various 3D ligand and structure-based methods for hit expansion and validation, in order to increase the hit rate and novelty. In the present account, six case studies are described and the efficiency of mixing is evaluated. While sequentially combined 2D/3D similarity approach increases the hit rate significantly, sequential combination of 2D similarity with pharmacophore model or 3D docking enriched the resulting focused library with novel chemotypes. Parallel integrated approaches allowed the comparison of the various 2D and 3D methods and revealed that 2D similarity-based and 3D ligand and structure-based techniques are often complementary, and their combinations represent a powerful synergy. Finally, the lessons we learnt including the advantages and pitfalls of the described approaches are discussed.     

Developing multiple high-throughput GLP methods for an investigational drug candidate in various matrices within a 96-well plate

In early pharmaceutical product development, an investigational drug candidate is typically dosed to various species for toxicological and pharmacokinetic studies. Most of these studies require multiple analytical methods that have to be validated with good laboratory practice (GLP) prior to the application in regulated studies. Usually, these analytical methods are developed in either a serial or parallel approach. For either approach, the development of multiple analytical methods takes tremendous work from scientists and instruments, and thus is not cost-effective. In this respect, a new strategy has been developed for simultaneous GLP method development using liquid chromatographic separation and tandem mass spectrometric detection. This high-throughput approach allows system suitability, carryover, calibration curve, accuracy, precision, matrix effect and selectivity to be evaluated in one 96-well plate. The strategy has been successfully implemented for multiple investigational drug candidates at Abbott Laboratories. The methods developed with this strategy are accurate, precise, selective, robust and matrix-independent. As an example, ABT-279 was used to demonstrate the feasibility of this strategy.     

Combining ligation reaction and capillary gel electrophoresis to obtain reliable long DNA probes

New DNA amplification methods are continuously developed for sensitive detection and quantification of specific DNA target sequences for, e.g. clinical, environmental or food applications. These new applications often require the use of long DNA oligonucleotides as probes for target sequences hybridization. Depending on the molecular technique, the length of DNA probes ranges from 40 to 450 nucleotides, solid-phase chemical synthesis being the strategy generally used for their production. However, the fidelity of chemical synthesis of DNA decreases for larger DNA probes. Defects in the oligonucleotide sequence result in the loss of hybridization efficiency, affecting the sensitivity and selectivity of the amplification method. In this work, an enzymatic procedure has been developed as an alternative to solid-phase chemical synthesis for the production of long oligonucleotides. The enzymatic procedure for probe production was based on ligation of short DNA sequences. Long DNA probes were obtained from smaller oligonucleotides together with a short sequence that acts as bridge stabilizing the molecular complex for DNA ligation. The ligation reactions were monitored by capillary gel electrophoresis with laser-induced fluorescence detection (CGE-LIF) using a bare fused-silica capillary. The capillary gel electrophoresis-LIF method demonstrated to be very useful and informative for the characterization of the ligation reaction, providing important information about the nature of some impurities, as well as for the fine optimization of the ligation conditions (i.e. ligation cycles, oligonucleotide and enzyme concentration). As a result, the yield and quality of the ligation product were highly improved. The in-lab prepared DNA probes were used in a novel multiplex ligation-dependent genome amplification (MLGA) method for the detection of genetically modified maize in samples. The great possibilities of the whole approach were demonstrated by the specific and sensitive detection of transgenic maize at percentages lower than 1%.     

Recent Progress in Enzymatic Synthesis of Sugar Nucleotides

Glycosylation is one of the most important reactions in nature as it results in the formation of glycoconjugates with diverse biological functions. Sugar nucleotides serve as the natural donor molecules for the biosynthesis of such glycoconjugates and other carbohydrates. Furthermore, these donor molecules are also indispensable building blocks for the enzymatic synthesis of carbohydrates in vitro using Leloir-type glycosyltransferases. Given such importance, the biosynthetic pathways of sugar nucleotides have been exploited, enabling the development of both chemical and enzymatic approaches to produce these molecules. A survey of recent progress in enzymatic synthesis of common mammalian sugar nucleotides as well as their derivatives is thus presented. As a popular strategy, conjugation of sugar nucleotide synthesis with glycosyltransfer reactions and in vivo production of sugar nucleotides are also included.     

Structure-based design technology contour and its application to the design of Renin inhibitors

It is well-known that the structure-based design approach has had a measurable impact on the drug discovery process in identifying novel and efficacious therapeutic agents for a variety of disease targets. The de novo design approach has inherent potential to generate novel molecules that best fit into a protein binding site when compared to all of the computational methods applied to structure-based design. In its initial attempts, this approach did not achieve much success due to technical hurdles. More recently, the algorithmic advancements in the methodologies and clever strategies developed to design drug-like molecules have improved the success rate. We describe a state-of-the-art structure-based design technology called Contour and provide details of the algorithmic enhancements we have implemented. Contour was designed to create novel drug-like molecules by assembling synthetically viable fragments in the protein binding site using a high-resolution crystal structure of the protein. The technology consists of a sophisticated growth algorithm and a novel scoring function based on a directional model. The growth algorithm generates molecules by dynamically selecting only those fragments from the fragment library that are complementary to the binding site, and assembling them by sampling the conformational space for each attached fragment. The scoring function embodying the essential elements of the binding interactions aids in the rank ordering of grown molecules and helps identify those that have high probability of exhibiting activity against the protein target of interest. The application of Contour to identify inhibitors against human renin enzyme eventually leading to the clinical candidate VTP-27,999 will be discussed here.     

Novel approach to structure-based pharmacophore search using computational geometry and shape matching techniques

Computationally efficient structure-based virtual screening methods have recently been reported that seek to find effective means to utilize experimental structure information without employing detailed molecular docking calculations. These tools can be coupled with efficient experimental screening technologies to improve the probability of identifying hits and leads for drug discovery research. Commercial software ROCS (rapid overlay of chemical structures) from Open Eye Scientific is such an example, which is a shape-based virtual screening method using the 3D structure of a ligand, typically from a bound X-ray costructure, as the query. We report here the development of a new structure-based pharmacophore search method (called Shape4) for virtual screening. This method adopts a variant of the ROCS shape technology and expands its use to work with an empty crystal structure. It employs a rigorous computational geometry method and a deterministic geometric casting algorithm to derive the negative image (i.e., pseudoligand) of a target binding site. Once the negative image (or pseudoligand) is generated, an efficient shape comparison algorithm in the commercial OE SHAPE Toolkit is adopted to compare and match small organic molecules with the shape of the pseudoligand. We report the detailed computational protocol and its computational validation using known biologically active compounds extracted from the WOMBAT database. Models derived for five selected targets were used to perform the virtual screening experiments to obtain the enrichment data for various virtual screening methods. It was found that our approach afforded similar or better enrichment ratios than other related methods, often with better diversity among the top ranking computational hits.     

基于DNA链置换反应的新型固定化酶反应器制备及应用

建立了一种新型的酶固定化方法,采用DNA链置换反应成功地在单链DNA标记的磁性纳米粒子上实现了酶的链置换无损更替。该技术可实现目标酶的再利用,节约了生产成本。制备的固定化胰蛋白酶微反应器具有较好的重复利用性和高酶切效率,重复使用10次后仍可保持原酶活性的86%;利用链置换反应制备的MNPs@DNATrypsin酶切马心肌红蛋白5 min后,即可获得95%±0%(n=3)的氨基酸序列覆盖率,远超过相同条件下自由酶酶切12 h的结果。实验表明,发展的固定化酶技术具有高磁响应性,便于从反应体系中回收固定化酶和重复使用,同时此技术可显著提高酶活性,因此可用于固定各种重要的酶,同时可将其广泛应用于各种酶促反应中。