L-type calcium channels expressed in the brain are heterogeneous. The predominant class of L-type calcium channels has a Ca_V1.2 pore-forming subunit. L-type calcium channels with a Ca_V1.3 pore-forming subunit are much less abundant, but have been implicated in the generation of mitochondrial oxidant stress underlying pathogenesis in Parkinson's disease. Thus, selectively antagonizing Ca_V1.3 L-type calcium channels could provide a means of diminishing cell loss in Parkinson's disease without producing side effects accompanying general antagonism of L-type calcium channels. However, there are no known selective antagonists of Ca_V1.3 L-type calcium channel. Here we report high-throughput screening of commercial and 'in-house' chemical libraries and modification of promising hits. Pyrimidine-2,4,6-triones were identified as a potential scaffold; structure-activity relationship-based modification of this scaffold led to 1-(3-chlorophenethyl)-3-cyclopentylpyrimidine-2,4,6-(1H,3H,5H)-trione (8), a potent and highly selective Ca_V1.3 L-type calcium channel antagonist. The biological relevance was confirmed by whole-cell patch-clamp electrophysiology. These studies describe the first highly selective Ca_V1.3 L-type calcium channel antagonist and point to a novel therapeutic strategy for Parkinson's disease.

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the “golden age for GPCR structural biology.” Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand– and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

Nitric oxide (NO) is an important signaling molecule in the human body, playing a crucial role in cell and neuronal communication, regulation of blood pressure, and in immune activation. However, overproduction of NO by the neuronal isoform of nitric oxide synthase (nNOS) is one of the fundamental causes underlying neurodegenerative disorders and neuropathic pain. Therefore, developing small molecules for selective inhibition of nNOS over related isoforms (eNOS and iNOS) is therapeutically desirable. The aims of this review focus on the regulation and dysregulation of NO signaling, the role of NO in neurodegeneration and pain, the structure and mechanism of nNOS, and the use of this information to design selective inhibitors of this enzyme. Structure-based drug design, the bioavailability and pharmacokinetics of these inhibitors, and extensive target validation through animal studies are addressed.

The advent of advanced molecular modeling software, big data analytics, and high-speed processing units has led to the exponential evolution of modern drug discovery and better insights into complex biological processes and disease networks. This has progressively steered current research interests to understanding protein-protein interaction (PPI) systems that are related to a number of relevant diseases, such as cancer, neurological illnesses, metabolic disorders, etc. However, targeting PPIs are challenging due to their “undruggable” binding interfaces. In this review, we focus on the current obstacles that impede PPI drug discovery, and how recent discoveries and advances in in silico approaches can alleviate these barriers to expedite the search for potential leads, as shown in several exemplary studies. We will also discuss about currently available information on PPI compounds and systems, along with their usefulness in molecular modeling. Finally, we conclude by presenting the limits of in silico application in drug discovery and offer a perspective in the field of computer-aided PPI drug discovery.

Polyglutamine diseases are a class of dominantly inherited neurodegenerative disorders for which there is no effective treatment. Here we provide evidence that activation of serotonergic signalling is beneficial in animal models of Machado-Joseph disease. We identified citalopram, a selective serotonin reuptake inhibitor, in a small molecule screen of FDA-approved drugs that rescued neuronal dysfunction and reduced aggregation using a Caenorhabditis elegans model of mutant ataxin 3-induced neurotoxicity. MOD-5, the C. elegans orthologue of the serotonin transporter and cellular target of citalopram, and the serotonin receptors SER-1 and SER-4 were strong genetic modifiers of ataxin 3 neurotoxicity and necessary for therapeutic efficacy. Moreover, chronic treatment of CMVMJD135 mice with citalopram significantly reduced ataxin 3 neuronal inclusions and astrogliosis, rescued diminished body weight and strikingly ameliorated motor symptoms. These results suggest that small molecule modulation of serotonergic signalling represents a promising therapeutic target for Machado-Joseph disease.