A standard system phantom for magnetic resonance imaging.

PURPOSE: A standard MRI system phantom has been designed and fabricated to assess scanner performance, stability, comparability and assess the accuracy of quantitative relaxation time imaging. The phantom is unique in having traceability to the International System of Units, a high level of precision, and monitoring by a national metrology institute. Here, we describe the phantom design, construction, imaging protocols, and measurement of geometric distortion, resolution, slice profile, signal-to-noise ratio (SNR), proton-spin relaxation times, image uniformity and proton density. METHODS: The system phantom, designed by the International Society of Magnetic Resonance in Medicine ad hoc committee on Standards for Quantitative MR, is a 200 mm spherical structure that contains a 57-element fiducial array; two relaxation time arrays; a proton density/SNR array; resolution and slice-profile insets. Standard imaging protocols are presented, which provide rapid assessment of geometric distortion, image uniformity, T1 and T2 mapping, image resolution, slice profile, and SNR. RESULTS: Fiducial array analysis gives assessment of intrinsic geometric distortions, which can vary considerably between scanners and correction techniques. This analysis also measures scanner/coil image uniformity, spatial calibration accuracy, and local volume distortion. An advanced resolution analysis gives both scanner and protocol contributions. SNR analysis gives both temporal and spatial contributions. CONCLUSIONS: A standard system phantom is useful for characterization of scanner performance, monitoring a scanner over time, and to compare different scanners. This type of calibration structure is useful for quality assurance, benchmarking quantitative MRI protocols, and to transition MRI from a qualitative imaging technique to a precise metrology with documented accuracy and uncertainty.

Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening.

We present Ligity, a hybrid ligand-structure-based, non-superpositional method for virtual screening of large databases of small molecules. Ligity uses the relative spatial distribution of pharmacophoric interaction points (PIPs) derived from the conformations of small molecules. These are compared with the PIPs derived from key interaction features found in protein-ligand complexes and are used to prioritize likely binders. We investigated the effect of generating PIPs using the single lowest energy conformer versus an ensemble of conformers for each screened ligand, using different bin sizes for the distance between two features, utilizing triangular sets of pharmacophoric features (3-PIPs) versus chiral tetrahedral sets (4-PIPs), fusing data for targets with multiple protein-ligand complex structures, and applying different similarity measures. Ligity was benchmarked using the Directory of Useful Decoys-Enhanced (DUD-E). Optimal results were obtained using the tetrahedral PIPs derived from an ensemble of bound ligand conformers and a bin size of 1.5 Å, which are used as the default settings for Ligity. The high-throughput screening mode of Ligity, using only the lowest-energy conformer of each ligand, was used for benchmarking against the whole of the DUD-E, and a more resource-intensive, "information-rich" mode of Ligity, using a conformational ensemble of each ligand, were used for a representative subset of 10 targets. Against the full DUD-E database, mean area under the receiver operating characteristic curve (AUC) values ranged from 0.44 to 0.99, while for the representative subset they ranged from 0.61 to 0.86. Data fusion further improved Ligity's performance, with mean AUC values ranging from 0.64 to 0.95. Ligity is very efficient compared to a protein-ligand docking method such as AutoDock Vina: if the time taken for the precalculation of Ligity descriptors is included in the comparason, then Ligity is about 20 times faster than docking. A direct comparison of the virtual screening steps shows Ligity to be over 5000 times faster. Ligity highly ranks the lowest-energy conformers of DUD-E actives, in a statistically significant manner, behavior that is not observed for DUD-E decoys. Thus, our results suggest that active compounds tend to bind in relatively low-energy conformations compared to decoys. This may be because actives-and thus their lowest-energy conformations-have been optimized for conformational complementarity with their cognate binding sites.

Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom.

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi-institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application-specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48-61, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Structure-guided selection of specificity determining positions in the human Kinome.

BACKGROUND: The human kinome contains many important drug targets. It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. The increased availability of protein 3D structures has provided much information on the structural variation within a given protein family. However, the relationship between structural variations and binding specificity is complex and incompletely understood. We have developed a structural bioinformatics approach which provides an analysis of key determinants of binding selectivity as a tool to enhance the rational design of drugs with a specific selectivity profile. RESULTS: We propose a greedy algorithm that computes a subset of residue positions in a multiple sequence alignment such that structural and chemical variation in those positions helps explain known binding affinities. By providing this information, the main purpose of the algorithm is to provide experimentalists with possible insights into how the selectivity profile of certain inhibitors is achieved, which is useful for lead optimization. In addition, the algorithm can also be used to predict binding affinities for structures whose affinity for a given inhibitor is unknown. The algorithm's performance is demonstrated using an extensive dataset for the human kinome. CONCLUSION: We show that the binding affinity of 38 different kinase inhibitors can be explained with consistently high precision and accuracy using the variation of at most six residue positions in the kinome binding site. We show for several inhibitors that we are able to identify residues that are known to be functionally important.

Carbocyclic Amino Ketones by Bredt's Rule-Arrested Kulinkovich-de Meijere Reaction.

The Ti(II) -mediated formation of cyclopropylamines from alkenes and amides, the Kulinkovich-de Meijere reaction, involves two carbon-carbon bond-forming steps. Strategic use of a tricyclic intermediate can arrest the process if the second step requires formation of a bridgehead double bond. Use of this Bredt's rule constraint results in the production of carbocyclic amino ketones, key alkaloid building blocks.

Combinatorial clustering of residue position subsets predicts inhibitor affinity across the human kinome.

The protein kinases are a large family of enzymes that play fundamental roles in propagating signals within the cell. Because of the high degree of binding site similarity shared among protein kinases, designing drug compounds with high specificity among the kinases has proven difficult. However, computational approaches to comparing the 3-dimensional geometry and physicochemical properties of key binding site residue positions have been shown to be informative of inhibitor selectivity. The Combinatorial Clustering Of Residue Position Subsets (ccorps) method, introduced here, provides a semi-supervised learning approach for identifying structural features that are correlated with a given set of annotation labels. Here, ccorps is applied to the problem of identifying structural features of the kinase atp binding site that are informative of inhibitor binding. ccorps is demonstrated to make perfect or near-perfect predictions for the binding affinity profile of 8 of the 38 kinase inhibitors studied, while only having overall poor predictive ability for 1 of the 38 compounds. Additionally, ccorps is shown to identify shared structural features across phylogenetically diverse groups of kinases that are correlated with binding affinity for particular inhibitors; such instances of structural similarity among phylogenetically diverse kinases are also shown to not be rare among kinases. Finally, these function-specific structural features may serve as potential starting points for the development of highly specific kinase inhibitors.

Substrate derived peptidic α-ketoamides as inhibitors of the malarial protease PfSUB1.

Peptidic α-ketoamides have been developed as inhibitors of the malarial protease PfSUB1. The design of inhibitors was based on the best known endogenous PfSUB1 substrate sequence, leading to compounds with low micromolar to submicromolar inhibitory activity. SAR studies were performed indicating the requirement of an aspartate mimicking the P1' substituent and optimal P1-P4 length of the non-prime part. The importance of each of the P1-P4 amino acid side chains was investigated, revealing crucial interactions and size limitations.

Exploration of piperidinols as potential antitubercular agents.

Novel drugs to treat tuberculosis are required and the identification of potential targets is important. Piperidinols have been identified as potential antimycobacterial agents (MIC < 5 µg/mL), which also inhibit mycobacterial arylamine N-acetyltransferase (NAT), an enzyme essential for mycobacterial survival inside macrophages. The NAT inhibition involves a prodrug-like mechanism in which activation leads to the formation of bioactive phenyl vinyl ketone (PVK). The PVK fragment selectively forms an adduct with the cysteine residue in the active site. Time dependent inhibition of the NAT enzyme from Mycobacterium marinum (M. marinum) demonstrates a covalent binding mechanism for all inhibitory piperidinol analogues. The structure activity relationship highlights the importance of halide substitution on the piperidinol benzene ring. The structures of the NAT enzymes from M. marinum and M. tuberculosis, although 74% identical, have different residues in their active site clefts and allow the effects of amino acid substitutions to be assessed in understanding inhibitory potency. In addition, we have used the piperidinol 3-dimensional shape and electrostatic properties to identify two additional distinct chemical scaffolds as inhibitors of NAT. While one of the scaffolds has anti-tubercular activity, both inhibit NAT but through a non-covalent mechanism.

Repurposing Hsp90 inhibitors as antimicrobials targeting two-component systems identifies compounds leading to loss of bacterial membrane integrity.

The discovery of antimicrobials with novel mechanisms of action is crucial to tackle the foreseen global health crisis due to antimicrobial resistance. Bacterial two-component signaling systems (TCSs) are attractive targets for the discovery of novel antibacterial agents. TCS-encoding genes are found in all bacterial genomes and typically consist of a sensor histidine kinase (HK) and a response regulator. Due to the conserved Bergerat fold in the ATP-binding domain of the TCS HK and the human chaperone Hsp90, there has been much interest in repurposing inhibitors of Hsp90 as antibacterial compounds. In this study, we explore the chemical space of the known Hsp90 inhibitor scaffold 3,4-diphenylpyrazole (DPP), building on previous literature to further understand their potential for HK inhibition. Six DPP analogs inhibited HK autophosphorylation in vitro and had good antimicrobial activity against Gram-positive bacteria. However, mechanistic studies showed that their antimicrobial activity was related to damage of bacterial membranes. In addition, DPP analogs were cytotoxic to human embryonic kidney cell lines and induced the cell arrest phenotype shown for other Hsp90 inhibitors. We conclude that these DPP structures can be further optimized as specific disruptors of bacterial membranes providing binding to Hsp90 and cytotoxicity are lowered. Moreover, the X-ray crystal structure of resorcinol, a substructure of the DPP derivatives, bound to the HK CheA represents a promising starting point for the fragment-based design of novel HK inhibitors. IMPORTANCE: The discovery of novel antimicrobials is of paramount importance in tackling the imminent global health crisis of antimicrobial resistance. The discovery of novel antimicrobials with novel mechanisms of actions, e.g., targeting bacterial two-component signaling systems, is crucial to bypass existing resistance mechanisms and stimulate pharmaceutical innovations. Here, we explore the possible repurposing of compounds developed in cancer research as inhibitors of two-component systems and investigate their off-target effects such as bacterial membrane disruption and toxicity. These results highlight compounds that are promising for further development of novel bacterial membrane disruptors and two-component system inhibitors.

Molecular determinants of binding to the Plasmodium subtilisin-like protease 1.

PfSUB1, a subtilisin-like protease of the human malaria parasite Plasmodium falciparum, is known to play important roles during the life cycle of the parasite and has emerged as a promising antimalarial drug target. In order to provide a detailed understanding of the origin of binding determinants of PfSUB1 substrates, we performed molecular dynamics simulations in combination with MM-GBSA free energy calculations using a homology model of PfSUB1 in complex with different substrate peptides. Key interactions, as well as residues that potentially make a major contribution to the binding free energy, are identified at the prime and nonprime side of the scissile bond and comprise peptide residues P4 to P2'. This finding stresses the requirement for peptide substrates to interact with both prime and nonprime side residues of the PfSUB1 binding site. Analyzing the energetic contributions of individual amino acids within the peptide-PfSUB1 complexes indicated that van der Waals interactions and the nonpolar part of solvation energy dictate the binding strength of the peptides and that the most favorable interactions are formed by peptide residues P4 and P1. Hot spot residues identified in PfSUB1 are dispersed over the entire binding site, but clustered areas of hot spots also exist and suggest that either the S4-S2 or the S1-S2' binding site should be exploited in efforts to design small molecule inhibitors. The results are discussed with respect to which binding determinants are specific to PfSUB1 and, therefore, might allow binding selectivity to be obtained.

Advances in CRISPR therapeutics.

The clustered regularly interspaced short palindromic repeats (CRISPR) renaissance was catalysed by the discovery that RNA-guided prokaryotic CRISPR-associated (Cas) proteins can create targeted double-strand breaks in mammalian genomes. This finding led to the development of CRISPR systems that harness natural DNA repair mechanisms to repair deficient genes more easily and precisely than ever before. CRISPR has been used to knock out harmful mutant genes and to fix errors in coding sequences to rescue disease phenotypes in preclinical studies and in several clinical trials. However, most genetic disorders result from combinations of mutations, deletions and duplications in the coding and non-coding regions of the genome and therefore require sophisticated genome engineering strategies beyond simple gene knockout. To overcome this limitation, the toolbox of natural and engineered CRISPR-Cas systems has been dramatically expanded to include diverse tools that function in human cells for precise genome editing and epigenome engineering. The application of CRISPR technology to edit the non-coding genome, modulate gene regulation, make precise genetic changes and target infectious diseases has the potential to lead to curative therapies for many previously untreatable diseases.

Drug-Mediated Control of Receptor Valency Enhances Immune Cell Potency.

Designer T cells offer a novel paradigm for treating diseases like cancer, yet they are often hindered by target recognition evasion and limited in vivo control. To overcome these challenges, we develop valency-controlled receptors (VCRs), a novel class of synthetic receptors engineered to enable precise modulation of immune cell activity. VCRs use custom-designed valency-control ligands (VCLs) to modulate T cell signaling via spatial molecular clustering. Using multivalent DNA origami as VCL, we first establish that valency is important for tuning the activity of CD3-mediated immune activation. We then generate multivalent formats of clinically relevant drugs as VCL and incorporate VCR into the architecture of chimeric antigen receptors (CARs). Our data demonstrate that VCL-mediated VCRs can significantly amplify CAR activities and improve suboptimal CARs. Finally, through medicinal chemistry, we synthesize programmable, bioavailable VCL drugs that potentiate targeted immune response against low-antigen tumors both in vitro and in vivo. Our findings establish receptor valency as a core mechanism for enhancing CAR functionality and offer a synthetic chemical biology platform for strengthening customizable, potent, and safer cell therapies.

On the ability of machine learning methods to discover novel scaffolds.

The recent advances in the application of machine learning to drug discovery have made it a 'hot topic' for research, with hundreds of academic groups and companies integrating machine learning into their drug discovery projects. Nevertheless, there remains great uncertainty regarding the most appropriate ways to evaluate the relative performance of these powerful methods against more traditional cheminformatics approaches, and many pitfalls remain for the unwary. In 2020, researchers at MIT (Stokes et al., Cell 180(4), 688-702, 2020) reported the discovery of a new compound with antibacterial activity, halicin, through the use of a neural network machine learning method. A robust ability to identify new active chemotypes through computational methods would be very useful. In this study, we have used the Stokes et al. dataset to compare the performance of this method to two other approaches, Mapping of Activity Through Dichotomic Scores (MADS) by Todeschini et al. (J Chemom 32(4):e2994, 2018) and Random Matrix Theory (RMT) by Lee et al. (Proc Natl Acad Sci 116(9):3373-3378, 2019). Our results demonstrate that all three methods are capable of predicting halicin as an active antibacterial compound, but that this result is dependent on the dataset composition, pre-processing and the molecular fingerprint used. We have further assessed overall performance as determined by several performance metrics. We also investigated the scaffold hopping potential of the methods by modifying the dataset by removal of the ß-lactam and fluoroquinolone chemotypes. MADS and RMT are able to identify actives in the test set that contained these substructures. This ability arises because of high scoring fragments of the withheld chemotypes that are in common with other active antibiotic classes. Interestingly, MADS is relatively better compared to the other two methods based on general predictive performance.

Improving the accuracy of ultrafast ligand-based screening: incorporating lipophilicity into ElectroShape as an extra dimension.

In a previous paper, we presented the ElectroShape method, which we used to achieve successful ligand-based virtual screening. It extended classical shape-based methods by applying them to the four-dimensional shape of the molecule where partial charge was used as the fourth dimension to capture electrostatic information. This paper extends the approach by using atomic lipophilicity (alogP) as an additional molecular property and validates it using the improved release 2 of the Directory of Useful Decoys (DUD). When alogP replaced partial charge, the enrichment results were slightly below those of ElectroShape, though still far better than purely shape-based methods. However, when alogP was added as a complement to partial charge, the resulting five-dimensional enrichments shows a clear improvement in performance. This demonstrates the utility of extending the ElectroShape virtual screening method by adding other atom-based descriptors.

ElectroShape: fast molecular similarity calculations incorporating shape, chirality and electrostatics.

We present ElectroShape, a novel ligand-based virtual screening method, that combines shape and electrostatic information into a single, unified framework. Building on the ultra-fast shape recognition (USR) approach for fast non-superpositional shape-based virtual screening, it extends the method by representing partial charge information as a fourth dimension. It also incorporates the chiral shape recognition (CSR) method, which distinguishes enantiomers. It has been validated using release 2 of the Directory of useful decoys (DUD), and shows a near doubling in enrichment ratio at 1% over USR and CSR, and improvements as measured by Receiver Operating Characteristic curves. These improvements persisted even after taking into account the chemotype redundancy in the sets of active ligands in DUD. During the course of its development, ElectroShape revealed a difference in the charge allocation of the DUD ligand and decoy sets, leading to several new versions of DUD being generated as a result. ElectroShape provides a significant addition to the family of ultra-fast ligand-based virtual screening methods, and its higher-dimensional shape recognition approach has great potential for extension and generalisation.

Outcome of ankle arthrodesis using a transfibular approach.

Variable union rates in ankle arthrodesis using different surgical techniques have been reported in the biomedical literature. However, the advantages of a transfibular approach with sagittal splitting of the fibula have not been widely reported, even though the technique is well known and even described in surgical textbooks. We analyzed outcomes in our practice for all patients who underwent ankle arthrodesis. Over a 5-year period, 2 surgeons using the same transfibular approach performed 26 ankle arthrodeses in 25 patients. The medical records and radiographs of the patients were reviewed for duration of hospital admission, time to union, and complications. All (100%) of the ankle fusions progressed to solid union in a mean postoperative duration of 4.5 ± 1.8 months (range, 2-10 months), and the only clinically significant complication involved 1 patient with suspected complex regional pain syndrome, who responded to treatment and recovered fully.

Cheminformatics in the Identification of Drug Classes for the Treatment of Type 2 Diabetes.

Computer-Aided Drug Design has developed into a powerful suite of methods that complement experimental approaches to the identification of new pharmacologically active compounds. In particular, virtual screening has become a standard tool for lead identification. Diverse examples of the application of virtual screening applied to T2DM target proteins have been reported. While several of these indicate successful identification of new lead compounds from synthetic chemical and natural product databases, many of them have been performed on a small scale and with limited validation. Careful study design and collaboration with cheminformaticians and computational chemists will enable these approaches to fulfil their potential for T2DM.

Single position substitution of hairpin pyrrole-imidazole polyamides imparts distinct DNA-binding profiles across the human genome.

Pyrrole-imidazole (Py-Im) polyamides are synthetic molecules that can be rationally designed to target specific DNA sequences to both disrupt and recruit transcriptional machinery. While in vitro binding has been extensively studied, in vivo effects are often difficult to predict using current models of DNA binding. Determining the impact of genomic architecture and the local chromatin landscape on polyamide-DNA sequence specificity remains an unresolved question that impedes their effective deployment in vivo. In this report we identified polyamide-DNA interaction sites across the entire genome, by covalently crosslinking and capturing these events in the nuclei of human LNCaP cells. This technique confirms the ability of two eight ring hairpin-polyamides, with similar architectures but differing at a single ring position (Py to Im), to retain in vitro specificities and display distinct genome-wide binding profiles.

Nephrogenic systemic fibrosis versus contrast-induced nephropathy: risks and benefits of contrast-enhanced MR and CT in renally impaired patients.

Magnetic resonance imaging (MRI) and computed tomography (CT) have become essential to diagnostic evaluation of many, or most, important medically and surgically treated diseases. It is important to consider comprehensively the implications in making decisions when choosing one or the other cross-sectional imaging modality. Factors to consider include the relative risks of the contrast agent. Other factors include the relative procedural risks, including radiation risks and the relative expected diagnostic yield of the examination technique (12). In this review we describe both nephrogenic systemic fibrosis and contrast-induced nephropathy to compare the implications with regard to relative risks and benefits of contrast-enhanced MRI or CT in patients with impaired renal function. J. Magn. Reson. Imaging 2009;30:1350-1356. (c) 2009 Wiley-Liss, Inc.