NMR-Fragment Based Virtual Screening: A Brief Overview.
Ontology highlight
ABSTRACT:
SUBMITTER: Singh M
PROVIDER: S-EPMC6017141 | biostudies-literature | 2018 Jan
REPOSITORIES: biostudies-literature
Publications
NMR-Fragment Based Virtual Screening: A Brief Overview.
Singh Meenakshi M Tam Benjamin B Akabayov Barak B
Molecules (Basel, Switzerland) 20180125 2
Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the com ...[more]
Similar Datasets
Project description:Cadherins promote cell-cell adhesion by forming homophilic interactions via their N-terminal extracellular domains. Hence, they have broad-ranging physiological effects on tissue organization and homeostasis. When dysregulated, cadherins contribute to different aspects of cancer progression and metastasis; therefore, targeting the cadherin adhesive interface with small-molecule antagonists is expected to have potential therapeutic and diagnostic value. Here, we used molecular docking simulations to evaluate the propensity of three different libraries of commercially available drug-like fragments (nearly 18,000 compounds) to accommodate into the Trp2 binding pocket of E-cadherin, a crucial site for the orchestration of the protein's dimerization mechanism. Top-ranked fragments featuring five different aromatic chemotypes were expanded by means of a similarity search on the PubChem database (Tanimoto index >90%). Of this set, seven fragments containing an aromatic scaffold linked to an aliphatic chain bearing at least one amine group were finally selected for further analysis. Ligand-based NMR data (Saturation Transfer Difference, STD) and molecular dynamics simulations suggest that these fragments can bind E-cadherin mostly through their aromatic moiety, while their aliphatic portions may also diversely engage with the mobile regions of the binding site. A tetrahydro-β-carboline scaffold functionalized with an ethylamine emerged as the most promising fragment.
| S-EPMC9437437 | biostudies-literature
Project description:To reduce time and cost, virtual ligand screening (VLS) often precedes experimental ligand screening in modern drug discovery. Traditionally, high-resolution structure-based docking approaches rely on experimental structures, while ligand-based approaches need known binders to the target protein and only explore their nearby chemical space. In contrast, our structure-based FINDSITEcomb2.0 approach takes advantage of predicted, low-resolution structures and information from ligands that bind distantly related proteins whose binding sites are similar to the target protein. Using a boosted tree regression machine learning framework, we significantly improved FINDSITEcomb2.0 by integrating ligand fragment scores as encoded by molecular fingerprints with the global ligand similarity scores of FINDSITEcomb2.0. The new approach, FRAGSITE, exploits our observation that ligand fragments, e.g., rings, tend to interact with stereochemically conserved protein subpockets that also occur in evolutionarily unrelated proteins. FRAGSITE was benchmarked on the 102 protein DUD-E set, where any template protein whose sequence identify >30% to the target was excluded. Within the top 100 ranked molecules, FRAGSITE improves VLS precision and recall by 14.3 and 18.5%, respectively, relative to FINDSITEcomb2.0. Moreover, the mean top 1% enrichment factor increases from 25.2 to 30.2. On average, both outperform state-of-the-art deep learning-based methods such as AtomNet. On the more challenging unbiased set LIT-PCBA, FRAGSITE also shows better performance than ligand similarity-based and docking approaches such as two-dimensional ECFP4 and Surflex-Dock v.3066. On a subset of 23 targets from DEKOIS 2.0, FRAGSITE shows much better performance than the boosted tree regression-based, vScreenML scoring function. Experimental testing of FRAGSITE's predictions shows that it has more hits and covers a more diverse region of chemical space than FINDSITEcomb2.0. For the two proteins that were experimentally tested, DHFR, a well-studied protein that catalyzes the conversion of dihydrofolate to tetrahydrofolate, and the kinase ACVR1, FRAGSITE identified new small-molecule nanomolar binders. Interestingly, one new binder of DHFR is a kinase inhibitor predicted to bind in a new subpocket. For ACVR1, FRAGSITE identified new molecules that have diverse scaffolds and estimated nanomolar to micromolar affinities. Thus, FRAGSITE shows significant improvement over prior state-of-the-art ligand virtual screening approaches. A web server is freely available for academic users at http:/sites.gatech.edu/cssb/FRAGSITE.
| S-EPMC8243409 | biostudies-literature
Project description:The growing size of make-on-demand chemical libraries is posing new challenges to cheminformatics. These ultra-large chemical libraries became too large for exhaustive enumeration. Using a combinatorial approach instead, the resource requirement scales approximately with the number of synthons instead of the number of molecules. This gives access to billions or trillions of compounds as so-called chemical spaces with moderate hardware and in a reasonable time frame. While extremely performant ligand-based 2D methods exist in this context, 3D methods still largely rely on exhaustive enumeration and therefore fail to apply. Here, we present SpaceGrow: a novel shape-based 3D approach for ligand-based virtual screening of billions of compounds within hours on a single CPU. Compared to a conventional superposition tool, SpaceGrow shows comparable pose reproduction capacity based on RMSD and superior ranking performance while being orders of magnitude faster. Result assessment of two differently sized subsets of the eXplore space reveals a higher probability of finding superior results in larger spaces highlighting the potential of searching in ultra-large spaces. Furthermore, the application of SpaceGrow in a drug discovery workflow was investigated in four examples involving G protein-coupled receptors (GPCRs) with the aim to identify compounds with similar binding capabilities and molecular novelty.
| S-EPMC10944417 | biostudies-literature
Project description:A series of new oxadiazole sulfone derivatives containing an amide moiety was synthesized based on fragment virtual screening to screen high-efficiency antibacterial agents for rice bacterial diseases. All target compounds showed greater bactericidal activity than commercial bactericides. 3-(4-fluorophenyl)-N-((5-(methylsulfonyl)-1,3,4-oxadiazol-2-yl)methyl)acrylamide (10) showed excellent antibacterial activity against Xanthomonas oryzae pv. oryzae and Xanthomonas oryzae pv. oryzicola, with EC50 values of 0.36 and 0.53 mg/L, respectively, which were superior to thiodiazole copper (113.38 and 131.54 mg/L) and bismerthiazol (83.07 and 105.90 mg/L). The protective activity of compound 10 against rice bacterial leaf blight and rice bacterial leaf streak was 43.2% and 53.6%, respectively, which was superior to that of JHXJZ (34.1% and 26.4%) and thiodiazole copper (33.0% and 30.2%). The curative activity of compound 10 against rice bacterial leaf blight and rice bacterial leaf streak was 44.5% and 51.7%, respectively, which was superior to that of JHXJZ (32.6% and 24.4%) and thiodiazole copper (27.1% and 28.6%). Moreover, compound 10 might inhibit the growth of Xanthomonas oryzae pv. oryzae and Xanthomonas oryzae pv. oryzicola by affecting the extracellular polysaccharides, destroying cell membranes, and inhibiting the enzyme activity of dihydrolipoamide S-succinyltransferase.
| S-EPMC8657855 | biostudies-literature
Project description:The TDP-43 is originally a nuclear protein but translocates to the cytoplasm in the pathological condition. TDP-43, as an RNA-binding protein, consists of two RNA Recognition Motifs (RRM1 and RRM2). RRMs are known to involve both protein-nucleotide and protein-protein interactions and mediate the formation of stress granules. Thus, they assist the entire TDP-43 protein with participating in neurodegenerative and cancer diseases. Consequently, they are potential therapeutic targets. Protein-observed and ligand-observed nuclear magnetic resonance (NMR) spectroscopy were used to uncover the small molecule inhibitors against the tandem RRM of TDP-43. We identified three hits weakly binding the tandem RRMs using the ligand-observed NMR fragment-based screening. The binding topology of these hits is then depicted by chemical shift perturbations (CSP) of the 15N-labeled tandem RRM and RRM2, respectively, and modeled by the CSP-guided High Ambiguity Driven biomolecular DOCKing (HADDOCK). These hits mainly bind to the RRM2 domain, which suggests the druggability of the RRM2 domain of TDP-43. These hits also facilitate further studies regarding the hit-to-lead evolution against the TDP-43 RRM domain.
| S-EPMC6651732 | biostudies-literature
Project description:The accurate prediction of protein druggability (propensity to bind high-affinity drug-like small molecules) would greatly benefit the fields of chemical genomics and drug discovery. We have developed a novel approach to quantitatively assess protein druggability by computationally screening a fragment-like compound library. In analogy to NMR-based fragment screening, we dock approximately 11,000 fragments against a given binding site and compute a computational hit rate based on the fraction of molecules that exceed an empirically chosen score cutoff. We perform a large-scale evaluation of the approach on four datasets, totaling 152 binding sites. We demonstrate that computed hit rates correlate with hit rates measured experimentally in a previously published NMR-based screening method. Secondly, we show that the in silico fragment screening method can be used to distinguish known druggable and non-druggable targets, including both enzymes and protein-protein interaction sites. Finally, we explore the sensitivity of the results to different receptor conformations, including flexible protein-protein interaction sites. Besides its original aim to assess druggability of different protein targets, this method could be used to identifying druggable conformations of flexible binding site for lead discovery, and suggesting strategies for growing or joining initial fragment hits to obtain more potent inhibitors.
| S-EPMC2852417 | biostudies-literature
Project description:AimFragment-based lead discovery (FBLD) is a complementary approach in drug research and development. In this study, we established an NMR-based FBLD platform that was used to screen novel scaffolds targeting human bromodomain of BRD4, and investigated the binding interactions between hit compounds and the target protein.Methods1D NMR techniques were primarily used to generate the fragment library and to screen compounds. The inhibitory activity of hits on the first bromodomain of BRD4 [BRD4(I)] was examined using fluorescence anisotropy binding assay. 2D NMR and X-ray crystallography were applied to characterize the binding interactions between hit compounds and the target protein.ResultsAn NMR-based fragment library containing 539 compounds was established, which were clustered into 56 groups (8-10 compounds in each group). Eight hits with new scaffolds were found to inhibit BRD4(I). Four out of the 8 hits (compounds 1, 2, 8 and 9) had IC50 values of 100-260 μmol/L, demonstrating their potential for further BRD4-targeted hit-to-lead optimization. Analysis of the binding interactions revealed that compounds 1 and 2 shared a common quinazolin core structure and bound to BRD4(I) in a non-acetylated lysine mimetic mode.ConclusionAn NMR-based platform for FBLD was established and used in discovery of BRD4-targeted compounds. Four potential hit-to-lead optimization candidates have been found, two of them bound to BRD4(I) in a non-acetylated lysine mimetic mode, being selective BRD4(I) inhibitors.
| S-EPMC4933754 | biostudies-literature
Project description:Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power. To remedy this, the approach has been reformulated to automatically decompose compounds into fragments using ring systems as anchors, and to likewise partition the ray-trace in accordance with the fragment assignments. Subsequently, descriptors are generated that are fragment-based, and query and target molecules are compared by mapping query fragments onto target fragments in all ways consistent with the underlying chemical connectivity. This has proven to greatly extend the selective power of the method, while maintaining the ease of use and scaffold-hopping capabilities that characterized the original implementation. In this work, we provide a full conceptual description of the next generation Shape Signatures, and we underline the advantages of the method by discussing its practical applications to ligand-based virtual screening. The new approach can also be applied in receptor-based mode, where protein-binding sites (partitioned into subsites) can be matched against the new fragment-based Shape Signatures descriptors of library compounds.
| S-EPMC3880490 | biostudies-literature
Project description:The structural differences between bacterial and human primases render the former an excellent target for drug design. Here we describe a technique for selecting small molecule inhibitors of the activity of T7 DNA primase, an ideal model for bacterial primases due to their common structural and functional features. Using NMR screening, fragment molecules that bind T7 primase were identified and then exploited in virtual filtration to select larger molecules from the ZINC database. The molecules were docked to the primase active site using the available primase crystal structure and ranked based on their predicted binding energies to identify the best candidates for functional and structural investigations. Biochemical assays revealed that some of the molecules inhibit T7 primase-dependent DNA replication. The binding mechanism was delineated via NMR spectroscopy. Our approach, which combines fragment based and virtual screening, is rapid and cost effective and can be applied to other targets.
| S-EPMC5090872 | biostudies-literature
Project description:Despite extensive and intensive research efforts in recent decades, there is still no effective treatment for neurodegenerative diseases. On this background, the use of drugs inhibiting the enzyme acetylcholinesterase (AChE) remains an eternal evergreen in the symptomatic treatment of mild to moderate cognitive impairments. Even more, the cholinergic hypothesis, somewhat forgotten in recent years due to the shift in focus on amyloid cascade, is back to life, and the search for new, more effective AChE inhibitors continues. We generated a fragment-based library containing aromatic moieties and linkers originating from a set of novel AChE inhibitors. We used this library to design 1220 galantamine (GAL) derivatives following the model GAL (binding core) - linker (L) - aromatic fragment (Ar). The newly designed compounds were screened virtually for blood-brain barrier (BBB) permeability and binding to AChE. Among the top 10 best-scored compounds, a representative lead molecule was selected and tested for anti-AChE activity and neurotoxicity. It was found that the selected compound was a powerful non-toxic AChE inhibitor, 68 times more active than GAL, and could serve as a lead molecule for further optimization and development.
| S-EPMC8038331 | biostudies-literature