Investigation of acetyl-CoA carboxylase-inhibiting herbicides that exhibit soybean crop selectivity.

The sustainable control of weed populations, particularly resistant species, is a significant challenge in agriculture around the world. The α-aryl-keto-enol (aryl-KTE) class of acetyl-CoA carboxylase (ACCase)-inhibiting herbicides represent a possible solution for the control of resistant grasses even though achieving crop selectivity remains a challenge. Herein, we present some of our investigations into identifying the most promising structural features within the aryl-KTE class that give the highest chance of achieving soybean crop selectivity, whilst also maintaining strong and broad efficacy against problematic weed species.

Best of both worlds: An expansion of the state of the art pK model with data from three industrial partners.

In a unique collaboration between Simulations Plus and several industrial partners, we were able to develop a new version 11.0 of the previously published in silico pK model, S+pKa, with considerably improved prediction accuracy. The model's training set was vastly expanded by large amounts of experimental data obtained from F.

Optimized Method of 3D Scaffold Seeding, Cell Cultivation, and Monitoring Cell Status for Bone Tissue Engineering.

The cultivation of cells in 3D systems is commonly regarded to be more physiological than in 2D as it comes much closer to the natural situation in tissues in many different aspects. However, 3D cell culture is much more complex. Cells within the pores of a printed 3D scaffold face a special situation concerning cell-material interaction and cell adhesion, cell proliferation, and supply of medium and oxygen into the core of the scaffolds.

Protocol for Cell Colonization and Comprehensive Monitoring of Osteogenic Differentiation in 3D Scaffolds Using Biochemical Assays and Multiphoton Imaging.

The goal of bone tissue engineering is to build artificial bone tissue with properties that closely resemble human bone and thereby support the optimal integration of the constructs (biografts) into the body. The development of tissues in 3D scaffolds includes several complex steps that need to be optimized and monitored. In particular, cell-material interaction during seeding, cell proliferation and cell differentiation within the scaffold pores play a key role.

Pan-cancer image-based detection of clinically actionable genetic alterations.

Molecular alterations in cancer can cause phenotypic changes in tumor cells and their micro-environment. Routine histopathology tissue slides - which are ubiquitously available - can reflect such morphological changes. Here, we show that deep learning can consistently infer a wide range of genetic mutations, molecular tumor subtypes, gene expression signatures and standard pathology biomarkers directly from routine histology.

A Consistent Scheme for Gradient-Based Optimization of ProteinLigand Poses.

Scoring and numerical optimization of protein-ligand poses is an integral part of docking tools. Although many scoring functions exist, many of them are not continuously differentiable and they are rarely explicitly analyzed with respect to their numerical optimization behavior. Here, we present a consistent scheme for pose scoring and gradient-based pose optimization.

Conformator: A Novel Method for the Generation of Conformer Ensembles.

Computer-aided drug design methods such as docking, pharmacophore searching, 3D database searching, and the creation of 3D-QSAR models need conformational ensembles to handle the flexibility of small molecules. Here, we present Conformator, an accurate and effective knowledge-based algorithm for generating conformer ensembles. With 99.

NAOMInext - Synthetically feasible fragment growing in a structure-based design context.

Since decades de novo design of small molecules is intensively used and fragment-based drug discovery (FBDD) approaches still gain in popularity. Recent publications considering synthetically feasible de novo drug design underline the ongoing need for new methods. Continuous development of algorithms and tools are made, where a combination of intuitive usage, acceptable runtime, and a thoroughly evaluated workflow on large scale data sets is still a curiosity.

Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation.

Macrocycles play an increasing role in drug discovery, but their synthesis is often demanding. Computational tools that suggest macrocyclization based on a known binding mode and that estimate the binding affinity of these macrocycles could have a substantial impact on the medicinal chemistry design process. For both tasks, we established a workflow with high practical value.

NAOMInova: Interactive Geometric Analysis of Noncovalent Interactions in Macromolecular Structures.

Noncovalent interactions play an important role in macromolecular complexes. The assessment of molecular interactions is often based on knowledge derived from statistics on structural data. Within the last years, the available data in the Brookhaven Protein Data Bank has increased dramatically, quantitatively as well as qualitatively.

From cheminformatics to structure-based design: Web services and desktop applications based on the NAOMI library.

Nowadays, computational approaches are an integral part of life science research. Problems related to interpretation of experimental results, data analysis, or visualization tasks highly benefit from the achievements of the digital era. Simulation methods facilitate predictions of physicochemical properties and can assist in understanding macromolecular phenomena.

High-Quality Dataset of Protein-Bound Ligand Conformations and Its Application to Benchmarking Conformer Ensemble Generators.

We developed a cheminformatics pipeline for the fully automated selection and extraction of high-quality protein-bound ligand conformations from X-ray structural data. The pipeline evaluates the validity and accuracy of the 3D structures of small molecules according to multiple criteria, including their fit to the electron density and their physicochemical and structural properties. Using this approach, we compiled two high-quality datasets from the Protein Data Bank (PDB): a comprehensive dataset and a diversified subset of 4626 and 2912 structures, respectively.

UNICON: A Powerful and Easy-to-Use Compound Library Converter.

The accurate handling of different chemical file formats and the consistent conversion between them play important roles for calculations in complex cheminformatics workflows. Working with different cheminformatic tools often makes the conversion between file formats a mandatory step. Such a conversion might become a difficult task in cases where the information content substantially differs.

Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist.