Prediction of Optimal Conditions of Hydrogenation Reaction Using the Likelihood Ranking Approach.

The selection of experimental conditions leading to a reasonable yield is an important and essential element for the automated development of a synthesis plan and the subsequent synthesis of the target compound. The classical QSPR approach, requiring one-to-one correspondence between chemical structure and a target property, can be used for optimal reaction conditions prediction only on a limited scale when only one condition component (e.g., catalyst or solvent) is considered. However, a particular reaction can proceed under several different conditions. In this paper, we describe the Likelihood Ranking Model representing an artificial neural network that outputs a list of different conditions ranked according to their suitability to a given chemical transformation. Benchmarking calculations demonstrated that our model outperformed some popular approaches to the theoretical assessment of reaction conditions, such as k Nearest Neighbors, and a recurrent artificial neural network performance prediction of condition components (reagents, solvents, catalysts, and temperature). The ability of the Likelihood Ranking model trained on a hydrogenation reactions dataset, (~42,000 reactions) from Reaxys® database, to propose conditions that led to the desired product was validated experimentally on a set of three reactions with rich selectivity issues.

Computational Approaches to the Rational Design of Tubulin-Targeting Agents.

Microtubules are highly dynamic polymers of α,ß-tubulin dimers which play an essential role in numerous cellular processes such as cell proliferation and intracellular transport, making them an attractive target for cancer and neurodegeneration research. To date, a large number of known tubulin binders were derived from natural products, while only one was developed by rational structure-based drug design. Several of these tubulin binders show promising in vitro profiles while presenting unacceptable off-target effects when tested in patients. Therefore, there is a continuing demand for the discovery of safer and more efficient tubulin-targeting agents. Since tubulin structural data is readily available, the employment of computer-aided design techniques can be a key element to focus on the relevant chemical space and guide the design process. Due to the high diversity and quantity of structural data available, we compiled here a guide to the accessible tubulin-ligand structures. Furthermore, we review different ligand and structure-based methods recently used for the successful selection and design of new tubulin-targeting agents.

Doxorubicin aqueous systems at low concentrations: Interconnection between self-organization, fluorescent and physicochemical properties, and action on hydrobionts.

Doxorubicin (Dox) is a highly effective cytostatic antibiotic that exhibits activity against a wide range of malignant neoplasms and is often used as the basis of various anti-tumor compositions. However, the use of Dox in therapeutic doses is associated with high systemic toxicity, which makes it urgent to find ways to reduce therapeutic concentrations, which is necessary primarily to minimize the side effects on the patient's body, as well as to reduce the harmful effects on aquatic ecosystems, commonly polluted by toxic pharmaceuticals. Studying the self-organization, physicochemical and spectral patterns, and their relation to bioeffects of Dox solutions in the range of low concentrations can reveal useful insights into the unknown effects of Dox as a cytostatic and potential pollutant of ecosystems. The self-organization in solutions and on substrates, physicochemical and spectral properties, and action of Dox solutions on hydrobionts were studied in the range of calculated concentrations from 1·10-20 to 1·10-4 M by methods of dynamic and electrophoretic light scattering (DLS and ELS), scanning electron microscopy (SEM), scanning probe microscopy (SPM), fluorescence spectroscopy, UV absorption spectroscopy, conductometry, tensiometry, pH-metry. Certified techniques for monitoring the toxicity of natural water and wastewater were used to establish the interconnection between these phenomena. It was shown that aqueous solutions of Dox are dispersed systems which rearrange their dispersed phase measuring hundreds of nm in size (nanoassociates) at dilution, followed by concerted changes in nanoassociates' parameters (size and ζ-potential) and properties of systems, as well as their bioassay results. SPM and SEM results confirm and complement the DLS and ELS data indicating the existence of nanoassociates in dilute Dox solutions.