New machine learning and physics-based scoring functions for drug discovery.

Scoring functions are essential for modern in silico drug discovery. However, the accurate prediction of binding affinity by scoring functions remains a challenging task. The performance of scoring functions is very heterogeneous across different target classes. Scoring functions based on precise physics-based descriptors better representing protein-ligand recognition process are strongly needed. We developed a set of new empirical scoring functions, named DockTScore, by explicitly accounting for physics-based terms combined with machine learning. Target-specific scoring functions were developed for two important drug targets, proteases and protein-protein interactions, representing an original class of molecules for drug discovery. Multiple linear regression (MLR), support vector machine and random forest algorithms were employed to derive general and target-specific scoring functions involving optimized MMFF94S force-field terms, solvation and lipophilic interactions terms, and an improved term accounting for ligand torsional entropy contribution to ligand binding. DockTScore scoring functions demonstrated to be competitive with the current best-evaluated scoring functions in terms of binding energy prediction and ranking on four DUD-E datasets and will be useful for in silico drug design for diverse proteins as well as for specific targets such as proteases and protein-protein interactions. Currently, the MLR DockTScore is available at www.dockthor.lncc.br .

Investigational treatments for Type 2 diabetes mellitus: exenatide and liraglutide.

Although a number of compounds are currently used to treat Type 2 diabetes mellitus, achieving a sustained glycaemic control over time is often not possible using oral antidiabetics. Endogenous incretins exhibit beneficial effects that could be useful for Type 2 diabetes mellitus treatment, such as stimulating insulin secretion during hyperglycaemia, improving beta-cell mass and function, reducing glucagon secretion, delaying gastric emptying, reducing postprandial hyperglycaemia and diminishing body weight; however, their short half-life makes them unsuitable for treatment. Incretin mimetics such as liraglutide and exenatide were developed to overcome this limitation. This review discusses the effects of these compounds and their potential as a new class of antidiabetic agents.

Angiotensin-(1-7) and its receptor as a potential targets for new cardiovascular drugs.

The identification of novel biochemical components of the renin-angiotensin system (RAS) has added a further layer of complexity to the classical concept of this cardiovascular regulatory system. It is now clear that there is a counter-regulatory arm within the RAS that is mainly formed by the angiotensin-converting enzyme 2-angiotensin (1-7)-receptor Mas axis. The functions of this axis are often opposite to those attributed to the major component of the RAS, angiotensin II. This review will highlight the current knowledge concerning the cardiovascular effects of angiotensin-(1-7) through a direct interaction with its receptor Mas or through an indirect interplay with the kallikrein-kinin system. In addition, there will be a discussion of its role in the beneficial effects of angiotensin-converting enzyme inhibitors and angio-tensin receptor type 1 (AT1) antagonists, and the potential of this peptide and its receptor as a novel targets for new cardiovascular drugs.