Quantized surface complementarity diversity (QSCD): a model based on small molecule-target complementarity

New compounds identified through in silico approaches reduce the α-synuclein expression by inhibiting prolyl oligopeptidase in vitro

Prolyl oligopeptidase (POP) is a serine protease that is responsible for the maturation and degradation of short neuropeptides and peptide hormones. The inhibition of POP has been demonstrated in the treatment of α-synucleinopathies and several neurological conditions. Therefore, ligand-based and structure-based pharmacophore models were generated and validated in order to identify potent POP inhibitors. Pharmacophore-based and docking-based virtual screening of a drug-like database resulted in 20 compounds. The in vitro POP assays indicated that the top scoring compounds obtained from virtual screening, Hit 1 and Hit 2 inhibit POP activity at a wide range of concentrations from 0.1 to 10 µM. Moreover, treatment of the hit compounds significantly reduced the α-synuclein expression in SH-SY5Y human neuroblastoma cells, that is implicated in Parkinson’s disease. Binding modes of Hit 1 and Hit 2 compounds were explored through molecular dynamics simulations. A detailed investigation of the binding interactions revealed that the hit compounds exhibited hydrogen bond interactions with important active site residues and greater electrostatic and hydrophobic interactions compared to those of the reference inhibitors. Finally, our findings indicated the potential of the identified compounds for the treatment of synucleinopathies and CNS related disorders.

The evolving role of infectomics in drug discovery

Signatures of infectomes, which are encoded by both host and microbial genomes, and mirror the interplay between pathogens and their hosts, provide invaluable knowledge in the search for novel antimicrobial drugs. Infectomics is the study of infectomes by using systems biology and high-throughput omic approaches. There are three types of infectomic approaches that can be used for drug discovery: ecological infectomics, immunoinfectomics and chemical infectomics. Ecological infectomics, which is the ecological study of infectomes, explores symbiotic solutions to microbial infections. Research on drug discovery using infectomic signatures and immunomic approaches falls within the field of immunoinfectomics. Advances in chemical infectomics will lead to the development of a new generation of chemical drugs for therapeutics for microbial infections.

Concepts and challenges in quantitative pharmacology and model-based drug development

Model-based drug development (MBDD) has been recognized as a concept to improve the efficiency of drug development. The acceptance of MBDD from regulatory agencies, industry, and academia has been growing, yet today's drug development practice is still distinctly distant from MBDD. This manuscript is aimed at clarifying the concept of MBDD and proposing practical approaches for implementing MBDD in the pharmaceutical industry. The following concepts are defined and distinguished: PK-PD modeling, exposure-response modeling, pharmacometrics, quantitative pharmacology, and MBDD. MBDD is viewed as a paradigm and a mindset in which models constitute the instruments and aims of drug development efforts. MBDD covers the whole spectrum of the drug development process instead of being limited to a certain type of modeling technique or application area. The implementation of MBDD requires pharmaceutical companies to foster innovation and make changes at three levels: (1) to establish mindsets that are willing to get acquainted with MBDD, (2) to align processes that are adaptive to the requirements of MBDD, and (3) to create a closely collaborating organization in which all members play a role in MBDD. Pharmaceutical companies that are able to embrace the changes MBDD poses will likely be able to improve their success rate in drug development, and the beneficiaries will ultimately be the patients in need.

High-Throughput Lead Finding and Optimisation for GPCR Targets

Driven by past successes and the detailed knowledge of signalling cascades and physiological processes, G-protein-coupled receptors are taking a prominent place in the portfolios of many pharmaceutical companies. To successfully address this target class, scientists need not only a good understanding of the specific receptor under investigation, but also the right tools from assay technology, reagent production to a hit-to-lead process that acknowledges the importance of parameters beyond potency and embraces the gain in knowledge of the last decade. This manuscripts attempts to summarise some of the changes and progress made across the pharmaceutical industry to design an efficient and effective strategy for finding and optimising small molecules modulating the activity of GPCRs.

Molecular similarity and diversity in chemoinformatics: from theory to applications

This review is dedicated to a survey on molecular similarity and diversity. Key findings reported in recent investigations are selectively highlighted and summarized. Even if this overview is mainly centered in chemoinformatics, applications in other areas (pharmaceutical and medical chemistry, combinatorial chemistry, chemical databases management, etc.) are also introduced. The approaches used to define and describe the concepts of molecular similarity and diversity in the context of chemoinformatics are discussed in the first part of this review. We introduce, in the second and third parts, the descriptions and analyses of different methods and techniques. Finally, current applications and problems are enumerated and discussed in the last part.

MolDIA: XML based system of molecular diversity analysis towards virtual screening and QSPR

In this paper a new chemoinformatics tool for Molecular Diversity Analysis (MolDIA) is introduced. The objective of this system is the analysis of molecular similarity and diversity through the treatment of structural and physicochemical information. Current needs for chemical databases include the analysis, the management and the retrieval of chemical information. The implementation of eXtended Markup Languages (XML) is proposed as a basis for representing and structuring the chemical information contained in data structures and databases. The adequate descriptor vector and related physicochemical properties have been defined and constructed. The benefits of XML in chemoinformatics are discussed, as well as, the applications of this system in a virtual screening environment.

Measuring molecular similarity and diversity: total pharmacophore diversity

A novel method, total pharmacophore diversity (ToPD), based on known pharmacophore features for numerically defining molecular similarity or diversity is described. The method captures the 3D shape and functionality of molecules by the analysis of relevant intramolecular distances to generate a short and descriptive pharmacophoric fingerprint for each molecule. The ToPD fingerprints can then be used in diversity analysis, clustering, or database searching. Conformational sampling is carried out when needed by the means of molecular dynamics. Our results show that ToPD outperforms a traditional 2D fingerprint technique in all test cases.

Drug-like properties and the causes of poor solubility and poor permeability

There are currently about 10000 drug-like compounds. These are sparsely, rather than uniformly, distributed through chemistry space. True diversity does not exist in experimental combinatorial chemistry screening libraries. Absorption, distribution, metabolism, and excretion (ADME) and chemical reactivity-related toxicity is low, while biological receptor activity is higher dimensional in chemistry space, and this is partly explainable by evolutionary pressures on ADME to deal with endobiotics and exobiotics. ADME is hard to predict for large data sets because current ADME experimental screens are multi-mechanisms, and predictions get worse as more data accumulates. Currently, screening for biological receptor activity precedes or is concurrent with screening for properties related to "drugability." In the future, "drugability" screening may precede biological receptor activity screening. The level of permeability or solubility needed for oral absorption is related to potency. The relative importance of poor solubility and poor permeability towards the problem of poor oral absorption depends on the research approach used for lead generation. A "rational drug design" approach as exemplified by Merck advanced clinical candidates leads to time-dependent higher molecular weight, higher H-bonding properties, unchanged lipophilicity, and, hence, poorer permeability. A high throughput screening (HTS)-based approach as exemplified by unpublished data on Pfizer (Groton, CT) early candidates leads to higher molecular weight, unchanged H-bonding properties, higher lipophilicity, and, hence, poorer aqueous solubility.

Chemical ligands, genomics and drug discovery

The sequencing of the human genome and numerous pathogen genomes has resulted in an explosion of potential drug targets. These targets represent both an unprecedented opportunity and a technological challenge for the pharmaceutical industry. A new strategy is required to initiate small-molecule drug discovery with sets of incompletely characterized, disease-associated proteins. One such strategy is the early application of combinatorial chemistry and other technologies to the discovery of bioactive small-molecule ligands that act on candidate drug targets. Therapeutically active ligands serve to concurrently validate a target and provide lead structures for downstream drug development, thereby accelerating the drug discovery process.