Successful drug discovery projects require control and optimization of compound properties related to pharmacokinetics, pharmacodynamics, and safety. While volume and chemotype coverage of public and ...corporate ADME-Tox (absorption, distribution, excretion, metabolism, and toxicity) databases are constantly growing, deep neural nets (DNN) emerged as transformative artificial intelligence technology to analyze those challenging data. Relevant features are automatically identified, while appropriate data can also be combined to multitask networks to evaluate hidden trends among multiple ADME-Tox parameters for implicitly correlated data sets. Here we describe a novel, fully industrialized approach to parametrize and optimize the setup, training, application, and visual interpretation of DNNs to model ADME-Tox data. Investigated properties include microsomal lability in different species, passive permeability in Caco-2/TC7 cells, and logD. Statistical models are developed using up to 50 000 compounds from public or corporate databases. Both the choice of DNN hyperparameters and the type and quantity of molecular descriptors were found to be important for successful DNN modeling. Alternate learning of multiple ADME-Tox properties, resulting in a multitask approach, performs statistically superior on most studied data sets in comparison to DNN single-task models and also provides a scalable method to predict ADME-Tox properties from heterogeneous data. For example, predictive quality using external validation sets was improved from R 2 of 0.6 to 0.7 comparing single-task and multitask DNN networks from human metabolic lability data. Besides statistical evaluation, a new visualization approach is introduced to interpret DNN models termed “response map”, which is useful to detect local property gradients based on structure fragmentation and derivatization. This method is successfully applied to visualize fragmental contributions to guide further design in drug discovery programs, as illustrated by CRCX3 antagonists and renin inhibitors, respectively.
The discovery of Streptomyces-produced streptomycin founded the age of tuberculosis therapy. Despite the subsequent development of a curative regimen for this disease, tuberculosis remains a ...worldwide problem, and the emergence of multidrug-resistant Mycobacterium tuberculosis has prioritized the need for new drugs. Here we show that new optimized derivatives from Streptomyces-derived griselimycin are highly active against M. tuberculosis, both in vitro and in vivo, by inhibiting the DNA polymerase sliding clamp DnaN. We discovered that resistance to griselimycins, occurring at very low frequency, is associated with amplification of a chromosomal segment containing dnaN, as well as the ori site. Our results demonstrate that griselimycins have high translational potential for tuberculosis treatment, validate DnaN as an antimicrobial target, and capture the process of antibiotic pressure-induced gene amplification.
The identification and optimization of promising lead molecules is essential for drug discovery. Recently, artificial intelligence (AI) based generative methods provided complementary approaches for ...generating molecules under specific design constraints of relevance in drug design. The goal of our study is to incorporate protein 3D information directly into generative design by flexible docking plus an adapted protein-ligand scoring function, thereby moving towards automated structure-based design. First, the protein-ligand scoring function RFXscore integrating individual scoring terms, ligand descriptors, and combined terms was derived using the PDBbind database and internal data. Next, design results for different workflows are compared to solely ligand-based reward schemes. Our newly proposed, optimal workflow for structure-based generative design is shown to produce promising results, especially for those exploration scenarios, where diverse structures fitting to a protein binding site are requested. Best results are obtained using docking followed by RFXscore, while, depending on the exact application scenario, it was also found useful to combine this approach with other metrics that bias structure generation into “drug-like” chemical space, such as target-activity machine learning models, respectively.
Human glucose transporters (GLUTs) are responsible for cellular uptake of hexoses. Elevated expression of GLUTs, particularly GLUT1 and GLUT3, is required to fuel the hyperproliferation of cancer ...cells, making GLUT inhibitors potential anticancer therapeutics. Meanwhile, GLUT inhibitor-conjugated insulin is being explored to mitigate the hypoglycemia side effect of insulin therapy in type 1 diabetes. Reasoning that exofacial inhibitors of GLUT1/3 may be favored for therapeutic applications, we report here the engineering of a GLUT3 variant, designated GLUT3exo, that can be probed for screening and validating exofacial inhibitors. We identify an exofacial GLUT3 inhibitor SA47 and elucidate its mode of action by a 2.3 Å resolution crystal structure of SA47-bound GLUT3. Our studies serve as a framework for the discovery of GLUTs exofacial inhibitors for therapeutic development.
The efficiency of the drug discovery process can be significantly improved using design techniques to maximize the diversity of structure databases or combinatorial libraries. Here, several ...physicochemical descriptors were investigated to quantify molecular diversity. Based on the 2D or 3D topological similarity of molecules, the relationship between physicochemical metrics and biological activity was studied to find valid descriptors. Several compounds were selected using those descriptors from a database containing diverse templates and 55 biological classes. It was evaluated whether the obtained subsets represent all biological properties and structural variations of the original database. In addition, hierarchical cluster analyses were used to group molecules from the parent database, which should have similar biological properties. Using various sets of structurally similar molecules, it was possible to derive quantitative measures for compound similarities in relation to biological properties. A similarity radius for 2D fingerprints and molecular steric fields was estimated; compounds within this radius of another molecule were shown to have comparable biological properties. This study demonstrates that 2D fingerprints alone or in combination with other metrics as the primary descriptor allow to handle global diversity. In addition, standard atom-pair descriptors or molecular steric fields can be used to correlate structural diversity with biological activity. Hence, the latter two descriptors can be classified as secondary descriptors useful for analog library design, while 2D fingerprints are applicable to design a general library for lead discovery. Based on these findings, an optimally diverse subset containing only 38% of the entire IC93 database was generated using 2D fingerprints. Here no structure is more similar than 0.85 to any other (Tanimoto coefficient), but all biological classes were selected. This reduction of redundancy led to a child database with the same physicochemical diversity space, which contains the same information as the original database.
The pregnane X receptor (PXR), a member of the nuclear hormone superfamily, regulates the expression of several enzymes and transporters involved in metabolically relevant processes. The significant ...induction of CYP450 enzymes by PXR, in particular CYP3A4, might significantly alter the metabolism of prescribed drugs. In order to early identify molecules in drug discovery with a potential to activate PXR as antitarget, we developed fast and reliable in silico filters by ligand-based QSAR techniques. Two classification models were established on a diverse dataset of 434 drug-like molecules. A second augmented set allowed focusing on interesting regions in chemical space. These classifiers are based on decision trees combined with a genetic algorithm based variable selection to arrive at predictive models. The classifier for the first dataset on 29 descriptors showed good performance on a test set with a correct classification of both 100% for PXR activators and non-activators plus 87% for activators and 83% for non-activators in an external dataset. The second classifier then correctly predicts 97% activators and 91% non-activators in a test set and 94% for activators and 64% non-activators in an external set of 50 molecules, which still qualifies for application as a filter focusing on PXR activators. Finally a quantitative model for PXR activation for a subset of these molecules was derived using a regression-tree approach combined with GA variable selection. This final model shows a predictive r2 of 0.774 for the test set and 0.452 for an external set of 33 molecules. Thus, the combination of these filters consistently provide guidelines for lowering PXR activation in novel candidate molecules.
Renin-Inhibitor (IC
50
=
0.002
μM).
Selective inhibition of the aspartyl protease renin has gained attraction as an interesting approach to control hypertension and associated cardiovascular risk ...factors given its unique position in the renin–angiotensin system. Using a combination of high-throughput screening, parallel synthesis, X-ray crystallography and structure-based design, we identified and optimized a novel series of potent and non-chiral indole-3-carboxamides with remarkable potency for renin. The most potent compound
5k displays an IC
50 value of 2
nM.
Effect of Storage Temperature on Allograft Bone Fölsch, Christian; Mittelmeier, Wolfram; Bilderbeek, Uwe ...
Transfusion medicine and hemotherapy,
02/2012, Letnik:
39, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Background: The recommendations for storage temperature of allogeneic bone are varying between –20 °C and –70 °C and down to –80 °C. The necessary temperature of storage is not exactly defined by ...scientific data, and the effect of different storage temperatures onto the biomechanical and the biological behavior is discussed controversially. Methods: The historical development of storage temperature of bone banks is described. A survey on literature concerning the biomechanical and biological properties of allograft bone depending on the procurement and storage temperature is given as well as on national and international regulations on storage conditions of bone banks (European Council, American Association of Tissue Banks (AATB), European Association of Tissue Banks (EATB)). Results: Short-term storage up to 6 months is recommended with –20 °C and –40 °C for a longer period (AATB), and EATB recommends storage at –40 °C and even –80 °C while the regulations of the German German Medical Association (Bundesärztekammer) from 2001 recommend storage at –70 °C. Duration of storage at –20 °C can be maintained at least for 2 years. The potential risk of proteolysis with higher storage temperatures remains, but a definite impairment of bone ingrowth due to a storage at –20 °C was not shown in clinical use, and no adverse biomechanical effects of storage at –20 °C could be proven. Conclusion: Biomechanical studies showed no clinically relevant impairment of biomechanical properties of cancellous bone due to different storage temperatures. Sterilization procedures bear the advantage of inactivating enzymatic activity though reducing the risk of proteolysis. In those cases a storage temperature of –20 °C can be recommended for at least a period of 2 years, and the risk of undesired effects seems to be low for native unprocessed bone.
Structure−activity relationships within a series of highly potent 2-carboxyindole-based factor Xa inhibitors incorporating a neutral P1 ligand are described with particular emphasis on the structural ...requirements for addressing subpockets of the factor Xa enzyme. Interactions with the subpockets were probed by systematic substitution of the 2-carboxyindole scaffold, in combination with privileged P1 and P4 substituents. Combining the most favorable substituents at the indole nucleus led to the discovery of a remarkably potent factor Xa inhibitor displaying a K i value of 0.07 nM. X-ray crystallography of inhibitors bound to factor Xa revealed substituent-dependent switching of the inhibitor binding mode and provided a rationale for the SAR obtained. These results underscore the key role played by the P1 ligand not only in determining the binding affinity of the inhibitor by direct interaction but also in modifying the binding mode of the whole scaffold, resulting in a nonlinear SAR.
Thermodisinfection of human femoral heads from living donors harvested during hip joint replacement is an established processing procedure. This study was designed to examine the influence of heat ...sterilization on pull out strength of cancellous bone and storage at different temperatures up to 2 years since we had previously studied the storage of unprocessed cancellous bone. Porcine cancellous bone resembling human bone structure was obtained from 140 proximal humerus of 6–8 months old piglets. Pull out strength of screws after thermodisinfection was compared with unprocessed cancellous bone and tested immediately and after 6, 12 and 24 months of storage at −20 and −80 °C. A three-way ANOVA was performed and significance level was 5 %. The thermodisinfected bone showed a pull out force of 2729 N (1657–3568 N). The reduction of pull out strength compared with unprocessed bone over all periods of storage was 276 N on average with 95 % confidence interval ranging from 166 N to 389 N (
p
< 0.0001). Different freezing temperatures did not influence this mechanic property within 24 months storage and showed no difference compared with fresh frozen bone. Thermodisinfection of cancellous bone preserves tensile strength necessary for clinical purposes. The storage at −20 °C for at least 2 years did not show relevant decrease of pull out strength compared with −80 °C without difference between thermodisinfected and fresh frozen bone. The increase of the storage temperature to −20 °C for at least 2 years should be considered.
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