Discovery of novel methionine adenosyltransferase 2A (MAT2A) allosteric inhibitors by structure-based virtual screening.

Methionine adenosyltransferase 2A (MAT2A) has been indicated as a drug target for oncology indications. Clinical trials with MAT2A inhibitors are currently on-going. Here, a structure-based virtual screening campaign was performed on the commercially available chemical space which yielded two novel MAT2A-inhibitor chemical series. The binding modes of the compounds were confirmed with X-ray crystallography. Both series have acceptable physicochemical properties and show nanomolar activity in the biochemical MAT2A inhibition assay and single-digit micromolar activity in the proliferation assay (MTAP -/- cell line). The identified compounds and the relating structural data could be helpful in related drug discovery projects.

Machine Learning-Boosted Docking Enables the Efficient Structure-Based Virtual Screening of Giga-Scale Enumerated Chemical Libraries.

The emergence of ultra-large screening libraries, filled to the brim with billions of readily available compounds, poses a growing challenge for docking-based virtual screening. Machine learning (ML)-boosted strategies like the tool HASTEN combine rapid ML prediction with the brute-force docking of small fractions of such libraries to increase screening throughput and take on giga-scale libraries. In our case study of an anti-bacterial chaperone and an anti-viral kinase, we first generated a brute-force docking baseline for 1.56 billion compounds in the Enamine REAL lead-like library with the fast Glide high-throughput virtual screening protocol. With HASTEN, we observed robust recall of 90% of the true 1000 top-scoring virtual hits in both targets when docking only 1% of the entire library. This reduction of the required docking experiments by 99% significantly shortens the screening time. In the kinase target, the employment of a hydrogen bonding constraint resulted in a major proportion of unsuccessful docking attempts and hampered ML predictions. We demonstrate the optimization potential in the treatment of failed compounds when performing ML-boosted screening and benchmark and showcase HASTEN as a fast and robust tool in a growing arsenal of approaches to unlock the chemical space covered by giga-scale screening libraries for everyday drug discovery campaigns.

Extending the range of applicability of the semi-empirical ecosystem flux model PRELES for varying forest types and climate.

Applications of ecosystem flux models on large geographical scales are often limited by model complexity and data availability. Here we calibrated and evaluated a semi-empirical ecosystem flux model, PREdict Light-use efficiency, Evapotranspiration and Soil water (PRELES), for various forest types and climate conditions, based on eddy covariance data from 55 sites. A Bayesian approach was adopted for model calibration and uncertainty quantification. We applied the site-specific calibrations and multisite calibrations to nine plant functional types (PFTs) to obtain the site-specific and PFT-specific parameter vectors for PRELES. A systematically designed cross-validation was implemented to evaluate calibration strategies and the risks in extrapolation. The combination of plant physiological traits and climate patterns generated significant variation in vegetation responses and model parameters across but not within PFTs, implying that applying the model without PFT-specific parameters is risky. But within PFT, the multisite calibrations performed as accurately as the site-specific calibrations in predicting gross primary production (GPP) and evapotranspiration (ET). Moreover, the variations among sites within one PFT could be effectively simulated by simply adjusting the parameter of potential light-use efficiency (LUE), implying significant convergence of simulated vegetation processes within PFT. The hierarchical modelling of PRELES provides a compromise between satellite-driven LUE and physiologically oriented approaches for extrapolating the geographical variation of ecosystem productivity. Although measurement errors of eddy covariance and remotely sensed data propagated a substantial proportion of uncertainty or potential biases, the results illustrated that PRELES could reliably capture daily variations of GPP and ET for contrasting forest types on large geographical scales if PFT-specific parameterizations were applied.

Discovery of sulfonamides and 9-oxo-2,8-diazaspiro[5,5]undecane-2-carboxamides as human kynurenine aminotransferase 2 (KAT2) inhibitors.

Human kynurenine aminotransferase 2 (KAT2) inhibitors could be potentially used to treat the cognitive deficits associated with bipolar disease and schizophrenia. Although, there has been active drug research activity by several industrial and academic groups in developing KAT2 inhibitors over the years, no such compound has proceeded to the clinics. Here, we report two different chemical series of reversible KAT2 inhibitors with sub-micromolar activities. The first series was identified by a high-throughput screening of a diverse random library and the second one by structure-based virtual screening. Two novel crystal structures of KAT2 complexed with different reversible inhibitors were also deposited to the Protein databank which could be useful for future drug discovery efforts.

Realisation of small molecule libraries based on frameworks distantly related to natural products.

The availability of high-quality screening compounds is of paramount importance for the discovery of innovative new medicines. Natural product (NP) frameworks can inspire the design of productive compound libraries. Here, we describe the design and synthesis of four compound libraries based on scaffolds that have broad NP-like features, but that are only distantly related to specific NPs. The optimisation of syntheses of the scaffolds using [5 + 2] cycloaddition chemistry is detailed, together with methods to yield exemplar decorated screening compounds. In each case, a library was nominated for production, leading to a total of >2900 screening compounds that augmented the Joint European Compound Library of the European Lead Factory.

Design, synthesis and decoration of molecular scaffolds for exploitation in the production of alkaloid-like libraries.

The design, synthesis and decoration of six small molecule libraries is described. Each library was inspired by structures embedded in the framework of specific alkaloid natural products. The development of optimised syntheses of the required molecular scaffolds is described, in which reactions including Pd-catalysed aminoarylation and diplolar cycloadditions have been exploited as key steps. The synthesis of selected exemplar screening compounds is also described. In five cases, libraries were subsequently nominated for production on the basis of the scope and limitations of the validation work, as well as predicted molecular properties. In total, the research has led to the successful synthesis of >2500 novel alkaloid-like compounds for addition to the screening collection (the Joint European Compound Library, JECL) of the European Lead Factory.

Aminomethylhydroxylation of alkenes: Exploitation in the synthesis of scaffolds for small molecule libraries.

The application of [4+2] cycloadditions between alkenes and an N-benzoyl iminium species, generated in situ under acidic conditions, is described in the synthesis of diverse molecular scaffolds. The key reaction led to the formation of cyclic imidates in good yield and with high regioselectivity. It was demonstrated that the cyclic imidates may be readily converted into 1,3-amino alcohols. Incorporation of orthogonally-reactive functionality, such as aryl and alkyl bromides, into the cycloaddition substrates enabled the synthesis of additional scaffolds. For one scaffold, the synthesis of exemplar screening compounds was undertaken to demonstrate potential value in small molecule library production.

Subpocket analysis method for fragment-based drug discovery.

Although two binding sites might be dissimilar overall, they might still bind the same fragments if they share suitable subpockets. Information about shared subpockets can be therefore used in fragment-based drug design to suggest new fragments or to replace existing fragments within an already known compound. A novel computational method called SubCav is described which allows the similarity searching and alignment of subpockets from a PDB-wide database against a user-defined query. The method is based on pharmacophoric fingerprints combined with a subpocket alignment algorithm. SubCav was shown to be effective in producing reasonable alignments for subpockets with low sequence similarity and be able to retrieve relevant subpockets from a large database of structures including those with different folds. It can also be used to analyze subpockets inside a protein family to facilitate drug design and to rationalize compound selectivity.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

BACKGROUND: Detailed and systematic understanding of the biological effects of millions of available compounds on living cells is a significant challenge. As most compounds impact multiple targets and pathways, traditional methods for analyzing structure-function relationships are not comprehensive enough. Therefore more advanced integrative models are needed for predicting biological effects elicited by specific chemical features. As a step towards creating such computational links we developed a data-driven chemical systems biology approach to comprehensively study the relationship of 76 structural 3D-descriptors (VolSurf, chemical space) of 1159 drugs with the microarray gene expression responses (biological space) they elicited in three cancer cell lines. The analysis covering 11350 genes was based on data from the Connectivity Map. We decomposed the biological response profiles into components, each linked to a characteristic chemical descriptor profile. RESULTS: Integrated analysis of both the chemical and biological space was more informative than either dataset alone in predicting drug similarity as measured by shared protein targets. We identified ten major components that link distinct VolSurf chemical features across multiple compounds to specific cellular responses. For example, component 2 (hydrophobic properties) strongly linked to DNA damage response, while component 3 (hydrogen bonding) was associated with metabolic stress. Individual structural and biological features were often linked to one cell line only, such as leukemia cells (HL-60) specifically responding to cardiac glycosides. CONCLUSIONS: In summary, our approach identified several novel links between specific chemical structure properties and distinct biological responses in cells incubated with these drugs. Importantly, the analysis focused on chemical-biological properties that emerge across multiple drugs. The decoding of such systematic relationships is necessary to build better models of drug effects, including unanticipated types of molecular properties having strong biological effects.

Drug screen in iPSC-Neurons identifies nucleoside analogs as inhibitors of (G4C2)n expression in C9orf72 ALS/FTD.

An intronic (G4C2)n expansion in C9orf72 causes amyotrophic lateral sclerosis and frontotemporal dementia primarily through gain-of-function mechanisms: the accumulation of sense and antisense repeat RNA foci and dipeptide repeat (DPR) proteins (poly-GA/GP/GR/PA/PR) translated from repeat RNA. To therapeutically block this pathway, we screen a library of 1,430 approved drugs and known bioactive compounds in patient-derived induced pluripotent stem cell-derived neurons (iPSC-Neurons) for inhibitors of DPR expression. The clinically used guanosine/cytidine analogs decitabine, entecavir, and nelarabine reduce poly-GA/GP expression, with decitabine being the most potent. Hit compounds nearly abolish sense and antisense RNA foci and reduce expression of the repeat-containing nascent C9orf72 RNA transcript and its mature mRNA with minimal effects on global gene expression, suggesting that they specifically act on repeat transcription. Importantly, decitabine treatment reduces (G4C2)n foci and DPRs in C9orf72 BAC transgenic mice. Our findings suggest that nucleoside analogs are a promising compound class for therapeutic development in C9orf72 repeat-expansion-associated disorders.

Machine Learning Boosted Docking (HASTEN): An Open-source Tool To Accelerate Structure-based Virtual Screening Campaigns.

The software macHine leArning booSTEd dockiNg (HASTEN) was developed to accelerate structure-based virtual screening using machine learning models. It has been validated using datasets both from literature (12 datasets, each containing three million molecules docked with FRED) and in-house sources (one dataset of four million compounds docked with Glide). HASTEN showed reasonable performance by having the mean recall value of 0.78 of the top one percent scoring molecules after docking 10 % of the dataset for the literature data, whereas excellent recall value of 0.95 was achieved for the in-house data. The program can be used with any docking- and machine learning methodology, and is freely available from https://github.com/TuomoKalliokoski/HASTEN.

The effect of tree architecture on conduit diameter and frequency from small distal roots to branch tips in Betula pendula, Picea abies and Pinus sylvestris.

We studied the effect of tree architecture on xylem anatomy in three Betula pendula Roth., three Picea abies (L.) H. Karst. and three Pinus sylvestris (L.) trees (mean age 35 years). First, the analysis of conduit anatomy in different tree parts showed that conduits tapered and their frequency increased from roots (≥ 2 mm) to stem, from stem to branches and further to leaf petioles in B. pendula. Conduit anatomy in lateral and main roots, as well as lateral and main branches, significantly differed from each other in all the studied species. The increase in conduit diameter and decrease in frequency from the pith to the bark were clear aboveground, but variable patterns were observed belowground. In the leaf petioles of B. pendula, conduit diameter increased and conduit frequency decreased with increasing individual leaf area. Second, the results concerning the scaling of conduit diameter were compared with the predictions of the general vascular scaling model (WBE model) and Murray's law. The scaling parameter values at the tree level corresponded with the predictions of the WBE model in all the studied trees except for one tree of both conifer species. However, the scaling parameter values changed from one tree compartment to another rather than remaining uniform inside a tree, as assumed by the WBE model. The assumptions of the WBE model of a constant conductivity ratio, constant tapering and an unchanged total number of conduits were not fulfilled. When the conductivity ratio and relative tapering were plotted together, the results aboveground corresponded quite well with Murray's law: the conductivity ratio increased when relative tapering decreased. Our results support the theory that trees adjust both their macro- and microstructure to maximize their water transport efficiency, but also to prevent embolism and ensure mechanical safety.

The effect of ligand-based tautomer and protomer prediction on structure-based virtual screening.

As tautomerism and ionization may significantly change the interaction possibilities between a ligand and a target protein, these phenomena could have an effect on structure-based virtual screening. Tautomeric- and protonation-state enumeration ensures that the state with optimal interaction possibilities is included in the screening process, as the predicted state may not always be the optimal binder. However, there is very little information published if tautomer and protomer enumeration actually improves the enrichment of active molecules compared to the alternative of using a predicted form of each molecule. In this study, a retrospective virtual screening was performed using AutoDock on 19 drug targets with a publicly available data set. It is proposed that tautomer and protomer prediction can significantly save computing resources and can yield similar results to enumeration.

Predicting pKa for Small Molecules on Public and In-house Datasets Using Fast Prediction Methods Combined with Data Fusion.

Data fusion approach was investigated in the context of pKa prediction for 391 small molecules derived from a public data source as well as for 681 compounds from an internal corporate database. Four different pKa prediction methods (Simulations Plus ADMET-Predictor S+pKa, ACD/Labs Percepta Classic, ACD/Labs Percepta GALAS and Epik) were used to predict the most acidic or basic pKa for each of the compounds. By using data fusion, the median absolute error for the internal compounds was reduced from the best performing single model's value of 0.69 down to 0.50. In addition to the improved accuracy, data fusion also enabled predictions for all of the compounds in the dataset as individual methods failed on some of the molecules.

Current-year shoot hydraulic structure in two boreal conifers-implications of growth habit on water potential.

Metabolic scaling theory allows us to link plant hydraulic structure with metabolic rates in a quantitative framework. In this theoretical framework, we considered the hydraulic structure of current-year shoots in Pinus sylvestris and Picea abies, focusing on two properties unaccounted for by metabolic scaling theories: conifer needles are attached to the entire length of shoots, and the shoot as a terminal element does not display invariant properties. We measured shoot length and diameter as well as conduit diameter and density in two locations of 14 current-year non-leader shoots of pine and spruce saplings, and calculated conductivities of shoots from measured conduit properties. We evaluated scaling exponents for the hydraulic structure of shoots at the end of the water transport pathway from the data and applied the results to simulate water potential of shoots in the crown. Shoot shape was intermediate between cylindrical and paraboloid. Contrary to previous findings, we found that conduit diameter scaled with relative, not absolute, distance from the apex and absolute under-bark shoot diameter independently of species within the first-year shoots. Shoot hydraulic conductivity scaled with shoot diameter and hydraulic diameter. Larger shoots had higher hydraulic conductance. We further demonstrate by novel model calculations that ignoring foliage distribution along the hydraulic pathway overestimates water potential loss in shoots and branches and therefore overestimates related water stress effects. Scaling of hydraulic properties with shoot size enhances apical dominance and may contribute to the decline of whole-tree conductance in large trees.

Early root growth and architecture of fast- and slow-growing Norway spruce (Picea abies) families differ-potential for functional adaptation.

The relationship between the growth rate of aboveground parts of trees and fine root development is largely unknown. We investigated the early root development of fast- and slow-growing Norway spruce (Picea abies (L.) H. Karst.) families at a developmental stage when the difference in size is not yet observed. Seedling root architecture data, describing root branching, were collected with the WinRHIZO™ image analysis system, and mixed models were used to determine possible differences between the two growth phenotypes. A new approach was used to investigate the spatial extent of root properties along the whole sample root from the base of 1-year-old seedlings to the most distal part of a root. The root architecture of seedlings representing fast-growing phenotypes showed ~30% higher numbers of root branches and tips, which resulted in larger root extensions and potentially a better ability to acquire nutrients. Seedlings of fast-growing phenotypes oriented and allocated root tips and biomass further away from the base of the seedling than those growing slowly, a possible advantage in nutrient-limited and heterogeneous boreal forest soils. We conclude that a higher long-term growth rate of the aboveground parts in Norway spruce may relate to greater allocation of resources to explorative roots that confers a competitive edge during early growth phases in forest ecosystems.

Translation of innovative chemistry into screening libraries: an exemplar partnership from the European Lead Factory.

The identification of high-quality starting points for drug discovery is an enduring challenge in medicinal chemistry. Yet, the chemical space explored in discovery programmes tends be limited by the narrow toolkit of robust methods that are exploited in discovery workflows. The European Lead Factory (ELF) was established in 2013 to boost early-stage drug discovery within Europe. In this Feature, we describe an exemplar partnership that has led to the addition of 21119 distinctive screening compounds to the ELF Joint European Compound Library. The partnership could serve as a blueprint for the translation of innovative academic chemistry into discovery programmes.

Effects of timing of soil frost thawing on Scots pine.

Effects of the timing of soil thawing in the spring on Scots pine (Pinus sylvestris L.) were studied under controlled laboratory conditions. Sixteen 6-year-old saplings were lifted from the field, replanted in containers and placed in four treatments in controlled environment (CE) chambers with four replicate saplings per chamber. The saplings were held in the CE chambers during one simulated winter and one simulated growing season. The soil was frozen to -2 degrees C during a second simulated winter in the CE chambers, and the soil thawing treatments began at the end of the second simulated winter. Soil thawing began at various times before (no delay in thawing) and after (delay in thawing) chamber air conditions were changed from simulated winter to simulated summer. Delayed soil thawing subjected saplings to stress, with the severity of stress depending on the length of the delay in thawing. If there was no delay or only a short delay in soil thawing, stress was minor and reversible. A 2-week delay in soil thawing led to death of the saplings. Stress was apparent as decreases in the variable to maximal chlorophyll fluorescence ratio (Fv/Fm), chlorophyll a/b ratio and needle water potential. In needles of stressed saplings, apoplastic electrical resistance first decreased and then increased and there were anomalies in the electrical impedance spectra of the stems. Stress from the soil thawing treatments affected both root and shoot growth.

Price-Focused Analysis of Commercially Available Building Blocks for Combinatorial Library Synthesis.

Combinatorial libraries are synthesized by combining smaller reagents (building blocks), the price of which is an important component of the total costs associated with the synthetic exercise. A significant portion of commercially available reagents are too expensive for large scale work. In this study, 13 commonly used reagent classes in combinatorial library synthesis (primary and secondary amines, carboxylic acids, alcohols, ketones, aldehydes, boronic acids, acyl halides, sulfonyl chlorides, isocyanates, isothiocyanates, azides and chloroformates) were analyzed with respect to the cost, physicochemical properties (molecular weight and calculated logP), chemical diversity, and 3D-likeness using a large data set. The results define the chemical space accessible under a constraint of limited financial resources.

Expansion of chemical space for collaborative lead generation and drug discovery: the European Lead Factory Perspective.

High-throughput screening (HTS) represents a major cornerstone of drug discovery. The availability of an innovative, relevant and high-quality compound collection to be screened often dictates the final fate of a drug discovery campaign. Given that the chemical space to be sampled in research programs is practically infinite and sparsely populated, significant efforts and resources need to be invested in the generation and maintenance of a competitive compound collection. The European Lead Factory (ELF) project is addressing this challenge by leveraging the diverse experience and know-how of academic groups and small and medium enterprises (SMEs) engaged in synthetic and/or medicinal chemistry. Here, we describe the novelty, diversity, structural complexity, physicochemical characteristics and overall attractiveness of this first batch of ELF compounds for HTS purposes.