The identification of small-molecule modulators of protein function, and the process of transforming these into high-content lead series, are key activities in modern drug discovery. The decisions taken during this process have far-reaching consequences for success later in lead optimization and even more crucially in clinical development. Recently, there has been an increased focus on these activities due to escalating downstream costs resulting from high clinical failure rates. In addition, the vast emerging opportunities from efforts in functional genomics and proteomics demands a departure from the linear process of identification, evaluation and refinement activities towards a more integrated parallel process. This calls for flexible, fast and cost-effective strategies to meet the demands of producing high-content lead series with improved prospects for clinical success.

Hit and lead generation: beyond high-throughput screening

A rational approach is needed to maximize the chances of finding new drugs, and to exploit the opportunities of potential new drug targets emerging from genomic and proteomic initiatives, and from the large libraries of small compounds now readily available through combinatorial chemistry. Despite a shaky early history, computer-aided drug design techniques can now be effective in reducing costs and speeding up drug discovery. This happy outcome results from development of more accurate and reliable algorithms, use of more thoughtfully planned strategies to apply them, and greatly increased computer power to allow studies with the necessary reliability to be performed. Our review focuses on applications and protocols, with the main emphasis on critical analysis of recent studies where docking calculations and molecular dynamics (MD) simulations were combined to dock small molecules into protein receptors. We highlight successes to demonstrate what is possible now, but also point out drawbacks and future directions. The review is structured to lead the reader from the simpler to more compute-intensive methods. Thus, while inexpensive and fast docking algorithms can be used to scan large compound libraries and reduce their size, more accurate but expensive MD simulations can be applied when a few selected ligand candidates remain. MD simulations can be used: during the preparation of the protein receptor before docking, to optimize its structure and account for protein flexibility; for the refinement of docked complexes, to include solvent effects and account for induced fit; to calculate binding free energies, to provide an accurate ranking of the potential ligands; and in the latest developments, during the docking process itself to find the binding site and correctly dock the ligand a priori.

Combining docking and molecular dynamic simulations in drug design.

Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of “deep learning”. Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks.

Deep Learning in Drug Discovery.

It has been known for more than 60 years, and suspected for over 100, that alveolar hypoxia causes pulmonary vasoconstriction by means of mechanisms local to the lung. For the last 20 years, it has been clear that the essential sensor, transduction, and effector mechanisms responsible for hypoxic pulmonary vasoconstriction (HPV) reside in the pulmonary arterial smooth muscle cell. The main focus of this review is the cellular and molecular work performed to clarify these intrinsic mechanisms and to determine how they are facilitated and inhibited by the extrinsic influences of other cells. Because the interaction of intrinsic and extrinsic mechanisms is likely to shape expression of HPV in vivo, we relate results obtained in cells to HPV in more intact preparations, such as intact and isolated lungs and isolated pulmonary vessels. Finally, we evaluate evidence regarding the contribution of HPV to the physiological and pathophysiological processes involved in the transition from fetal to neonatal life, pulmonary gas exchange, high-altitude pulmonary edema, and pulmonary hypertension. Although understanding of HPV has advanced significantly, major areas of ignorance and uncertainty await resolution.

Hypoxic pulmonary vasoconstriction.

Virtual screening and fast automated docking methods.

Virtual Screening for Bioactive Molecules by Evolutionary De Novo Design

Appetite suppressants have been associated with primary pulmonary hypertension (PPH), inhibition of voltage-gated potassium channels, membrane depolarization, and calcium entry in pulmonary artery smooth muscle cells. In cells taken from pulmonary arteries of primary pulmonary hypertensive patients, voltage-gated potassium channels appear to be dysfunctional and in particular, reduced hKv1.5 gene transcription and hKv1.5 mRNA instability have been shown. We have compared the effects of anorexinogen agents on hKv1.5 channels stably expressed in mammalian cell line. We found that aminorex, phentermine, dexfenfluramine, sibutramine, and fluoxetine cause a dose-dependent inhibition of hKv1.5 current. Aminorex, phentermine, and dexfenfluramine had a K D of inhibition greater than to 300 μM and are not potent inhibitors of hKv1.5. Sibutramine and fluoxetine inhibited hKv1.5 current with lower K D values of 41 and 21 μM, respectively. Block by both drugs increased rapidly between −20 and +10 mV, coincident with channel opening and suggested an open channel block mechanism. This was confirmed by a slower deactivation time course resulting in a “crossover” phenomenon when tail currents recorded under control conditions and in the presence of either drug were superimposed. Single channel experiments demonstrated that open probability and open duration of hKv1.5 were decreased by fluoxetine and sibutramine. These results indicate that among the anorexinogen agents tested, sibutramine and fluoxetine are the most potent toward hKv1.5 channel, which they preferentially block in the open state. Nevertheless, their inhibitory effects do not correlate with their ability to produce PPH neither with their previously reported therapeutic plasma concentrations.

Effects of anorexinogen agents on cloned voltage-gated K(+) channel hKv1.5.

Evolutionäres De‐novo‐Design bioaktiver Moleküle: ein Ansatz zum virtuellen Screening

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Virtual Screening for Bioactive Molecules by Evolutionary De Novo Design

Effects of anorexinogen agents on cloned voltage-gated K(+) channel hKv1.5.

Evolutionäres De‐novo‐Design bioaktiver Moleküle: ein Ansatz zum virtuellen Screening