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Many transition metal complexes have unique physicochemical properties that can be efficiently exploited in medicinal chemistry for cancer treatment. Traditionally, double-stranded DNA has been assumed to be the main binding target; however, recent studies have shown that nucleosomal DNA as well as proteins can act as dominant molecular binding partners. This has raised new questions about the molecular determinants that govern DNA versus protein binding selectivity, and has offered new ways to rationalize their biological activity and possible side effects. To address these questions, molecular simulations at an atomistic level of detail have been used to complement, support, and rationalize experimental data. Herein we review some relevant studies-focused on platinum and ruthenium compounds-to illustrate the power of state-of-the-art molecular simulation techniques and to demonstrate how the interplay between molecular simulations and experiments can make important contributions to elucidating the target preferences of some promising transition metal anticancer agents. This contribution aims at providing relevant information that may help in the rational design of novel drug-discovery strategies.

We describe a protocol for the discovery of synergistic drug combinations for the treatment of disease. Synergistic drug combinations lead to the use of drugs at lower doses, which reduces side effects and can potentially lead to reduced drug resistance, while being clinically more effective than the individual drugs. To cope with the extremely large search space for these combinations, we developed an efficient combinatorial drug screening method called the Feedback System Control (FSC) technique. Starting with a broad selection of drugs, the method follows an iterative approach of experimental testing in a relevant bioassay and analysis of the results by FSC. First, the protocol uses a cell viability assay to generate broad dose-response curves to assess the efficacy of individual compounds. These curves are then used to guide the dosage input of each drug to be tested in combination. Data from applied drug combinations are input into the differential evolution (DE) algorithm, which predicts new combinations to be tested in vitro. This process identifies optimal drug-dose combinations, while saving orders of magnitude in experimental effort. The complete optimization process is estimated to take ∼4 weeks. FSC does not require insight into the disease mechanism, and it has therefore been applied to find combination therapies for many different pathologies, including cancer and infectious diseases, and it has also been used in organ transplantation.

A major key to improvement of cancer therapy is the combination of drugs. Mixing drugs that already exist on the market may offer an attractive alternative. Here we report on a new model-based streamlined feedback system control (s-FSC) method, based on a design of experiment approach, for rapidly finding optimal drug mixtures with minimal experimental effort. We tested combinations in an in vitro assay for the viability of a renal cell adenocarcinoma (RCC) cell line, 786-O. An iterative cycle of in vitro testing and s-FSC analysis was repeated a few times until an optimal low dose combination was reached. Starting with ten drugs that target parallel pathways known to play a role in the development and progression of RCC, we identified the best overall drug combination, being a mixture of four drugs (axitinib, erlotinib, dasatinib and AZD4547) at low doses, inhibiting 90% of cell viability. The removal of AZD4547 from the optimized drug combination resulted in 80% of cell viability inhibition, while still maintaining the synergistic interaction. These optimized drug combinations were significantly more potent than monotherapies of all individual drugs (p

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Solar fuels offer a promising approach to provide sustainable fuels by harnessing sunlight1,2. Following a decade of advancement, Cu2O photocathodes are capable of delivering a performance comparable to that of photoelectrodes with established photovoltaic materials3–5. However, considerable bulk charge carrier recombination that is poorly understood still limits further advances in performance6. Here we demonstrate performance of Cu2O photocathodes beyond the state-of-the-art by exploiting a new conceptual understanding of carrier recombination and transport in single-crystal Cu2O thin films. Using ambient liquid-phase epitaxy, we present a new method to grow single-crystal Cu2O samples with three crystal orientations. Broadband femtosecond transient reflection spectroscopy measurements were used to quantify anisotropic optoelectronic properties, through which the carrier mobility along the [111] direction was found to be an order of magnitude higher than those along other orientations. Driven by these findings, we developed a polycrystalline Cu2O photocathode with an extraordinarily pure (111) orientation and (111) terminating facets using a simple and low-cost method, which delivers 7 mA cm−2 current density (more than 70% improvement compared to that of state-of-the-art electrodeposited devices) at 0.5 V versus a reversible hydrogen electrode under air mass 1.5 G illumination, and stable operation over at least 120 h.A study introduces a novel method to grow single-crystal Cu2O thin films with selected crystal orientations, highlighting enhanced bulk carrier mobility and carrier diffusion length along the [111] direction that yields Cu2O photocathodes with improved performance. [ABSTRACT FROM AUTHOR]

In this work, a series of passivating salts for perovskite solar cells (PSCs) based on ortho-methylammonium iodide functional units are molecularly engineered to study the steric hindrance driven passivation effect. The incorporation of fluorine atoms into passivating agents has been found to be beneficial not only for maximized defect passivation effect, ensuring improved charge transport, but also for significantly enhanced hydrophobicity of the perovskite film, leading to enhanced device stability. The highest power conversion efficiency (PCE) of over 24% has been achieved for surficial passivated PSCs based on fluorinated cation PFPDMAI2. Importantly, long-term operational stability over 1500 h is demonstrated showing the great prospect of a simple passivation strategy forming a thin organic halide salt layer instead of a 2D perovskite layer on the surface. [ABSTRACT FROM AUTHOR]

Catalytic hydrogenation and oxidative dehydrogenation of N‐heterocycles to produce tetrahydroquinoline and quinoline derivatives are important reactions of particular importance in the agrochemical and pharmaceutical industries. Herein, we report earth‐abundant cobalt nanoparticles supported on hydroxyapatite (HAP) as an inexpensive and efficient catalyst for the hydrogenation and reverse oxidative dehydrogenation of N‐heterocycles. The optimal nanocatalyst exhibits excellent activity in both reactions for a wide range of substrates including (iso)quinolines, acridine, benzo[h]quinoline, quinoxaline and indole. Reactions proceed under relatively mild conditions without requiring any additives. [ABSTRACT FROM AUTHOR]